CN111899794A - Oil refining device simulation method, device, system and storage medium based on B/S architecture - Google Patents
Oil refining device simulation method, device, system and storage medium based on B/S architecture Download PDFInfo
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Abstract
The invention provides a B/S architecture-based oil refining device simulation method, device, system and storage medium, wherein the method comprises the following steps: receiving an operation instruction corresponding to the oil refining device, which is input by a user, through a browser interface of a web client; sending the operation instruction to a web server through network communication so that the web server analyzes the operation instruction, inputting the analyzed operation instruction into a pre-trained model, acquiring an execution result output by the model and corresponding to the analyzed operation instruction, and sending the execution result to a web client; and displaying the execution result received by the web client on a browser interface. According to the invention, a user can directly log in an account on a browser interface without installing a client program, the data processing speed of the web server is high, a developer can conveniently maintain and manage the system, and the interactive experience effect of the user and the client is improved by the method.
Description
Technical Field
The invention relates to the technical field of petroleum processing, in particular to a B/S architecture-based oil refining device simulation method, device, system and storage medium.
Background
In the technical field of petroleum processing, most of the simulation calculation software of the device is a single machine version, and the software only can use limited local calculation resources. The network version simulation software can use more computing resources, is basically an interactive mode based on a C/S (client/server) framework, a user needs to connect a remote server in a mode of installing a program at a client, and after the connection is successful, a message is sent to the server to operate the data terminal.
The prior technical scheme has the following defects: the user needs to install the client program on the local computer, the operation is complicated, and moreover, the development cost of the client program is high, so that the program updating speed is slow, the storage space is occupied, and the system maintenance by developers is inconvenient.
Disclosure of Invention
The invention mainly aims to provide a B/S architecture-based oil refining device simulation method, device, system and storage medium, so as to solve the defects of the prior art.
Aiming at the technical problems, the invention solves the technical problems by the following technical scheme:
the invention provides a B/S architecture-based oil refining device simulation method, which comprises the following steps:
receiving an operation instruction corresponding to the oil refining device, which is input by a user, through a browser interface of a web client;
sending the operation instruction to a web server through network communication so that the web server analyzes the operation instruction, inputting the analyzed operation instruction into a pre-trained model, acquiring an execution result output by the model and corresponding to the analyzed operation instruction, and sending the execution result to the web client;
and displaying the execution result received by the web client on the browser interface.
Wherein the method preferably further comprises:
receiving a user name and a password input by a user through the browser interface;
and sending the user name and the password to the web server through network communication so as to enable the web server to carry out user identity authentication, and if the user identity authentication passes, executing the step of receiving an operation instruction which is input by a user and corresponds to the oil refining device through a browser interface of the web client.
Wherein the displaying the execution result received by the web client on the browser interface preferably includes:
and displaying the execution result in a table mode, or displaying the execution result in a graphic mode, or displaying the execution result in a reaction network generating mode in an output window of the browser interface.
Wherein, the displaying the execution result in the manner of generating the reaction network preferably includes:
and displaying the execution result in a mode of generating a two-dimensional reaction network.
Wherein, the displaying the execution result in the manner of generating the reaction network preferably includes:
and displaying the execution result in a mode of generating a three-dimensional reaction network.
Wherein, the displaying the execution result in the manner of generating the reaction network preferably includes:
displaying one or more of the molecular composition, the structure of each single molecule in the molecular composition, the content of each single molecule, the physical properties of each single molecule, or the content of each single molecule.
Wherein the method preferably further comprises:
and displaying selectable operation instructions and corresponding controls on an operation instruction input window of the browser interface for the user to select and use.
Wherein, the operation instruction preferably comprises an instruction type and an instruction content.
Wherein the command types preferably include, but are not limited to, button clicks, screen slides, auxiliary flips, rotation zoom, and text entry.
Preferably, the model includes a product prediction model, and the obtaining of the execution result output by the model and corresponding to the analyzed operation instruction includes:
querying a molecular composition database, and taking molecular composition data corresponding to the analyzed operation instruction in the molecular composition database as the execution result output by the product prediction model; wherein the molecular composition database comprises: obtaining a molecular composition of the crude oil of the refinery; according to the physical properties of each single molecule in the molecular composition of the crude oil, obtaining the molecular composition of different fractions obtained by distilling the crude oil; according to the preset raw material proportion, respectively inputting the corresponding fractions as oil refining raw materials into corresponding product prediction models of an oil refining device to obtain the molecular composition of the corresponding prediction products and the content of each single molecule in the prediction products; and blending each predicted product serving as a product blending raw material according to a preset rule set to obtain the molecular composition of a plurality of groups of mixtures and the content of each single molecule in the mixtures.
Wherein the step of training the product prediction model preferably comprises:
establishing a product prediction model; wherein the product prediction model comprises: a reaction rule set of a plurality of reaction rules and a reaction rate algorithm;
acquiring sample raw material information of sample raw materials;
training the reaction rule set by using the sample raw material information, and fixing the trained reaction rule set;
and training the reaction rate algorithm by using the sample raw material information, and fixing the trained reaction rate algorithm to obtain the trained product prediction model.
Wherein, the sample material information of the sample material preferably includes: the molecular composition of the sample raw material, the molecular content of each molecule in the sample raw material, the molecular composition of an actual product corresponding to the sample raw material and the actual content of each molecule in the actual product.
Wherein, using the sample material information to train the reaction rule set, preferably comprising:
processing the molecular composition of the sample raw material according to a preset reaction rule set to obtain a reaction path corresponding to each molecule in the molecular composition of the sample raw material;
obtaining a first molecular composition of a device product according to a reaction path corresponding to each molecule in the molecular composition of the sample raw material; in the device product, comprising: the sample feedstock, intermediate product, and predicted product;
calculating a first relative deviation from a first molecular composition of the device product and a second molecular composition of the actual product;
if the first relative deviation meets a preset condition, fixing the reaction rule set;
and if the first relative deviation does not accord with the preset condition, adjusting the reaction rule in the reaction rule set, and recalculating the first relative difference value according to the adjusted reaction rule set until the first relative deviation accords with the preset condition.
Wherein calculating a first relative deviation from a first molecular composition of the device product and a second molecular composition of the actual product preferably comprises:
acquiring the types of single molecules in the first molecular composition to form a first set;
acquiring the species of single molecules in the second molecular composition to form a second set;
determining whether the second set is a subset of the first set;
if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as the first relative deviation value;
if the second set is a subset of the first set, calculating a first relative deviation by:
determining a first relative deviation from a ratio of the number of portions of the predicted artifact that are not in the second set to the total number of predicted artifacts;
for example, the first relative deviation is calculated by the following calculation formula:
wherein x is1Is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the sample material, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
Wherein, using the sample material information to train the reaction rate algorithm preferably comprises:
respectively calculating the reaction rate of the reaction path corresponding to each molecule in the molecular composition of the sample raw material according to the reaction rate algorithm;
obtaining the predicted content of each molecule in the predicted product corresponding to the sample raw material according to the molecular content of each molecule in the sample raw material and the reaction rate corresponding to the reaction path of the molecule;
calculating a second relative deviation according to the predicted content of each molecule in the predicted product and the actual content of each molecule in the actual product;
if the second relative deviation meets a preset condition, fixing the reaction rate algorithm;
and if the second relative deviation does not accord with the preset condition, adjusting parameters in the reaction rate algorithm, and recalculating the second relative deviation according to the adjusted reaction rate algorithm until the second relative deviation accords with the preset condition.
Wherein, according to the reaction rate algorithm, the reaction rate of the reaction path corresponding to each molecule in the molecular composition of the sample raw material is respectively calculated, and preferably includes:
calculating the reaction rate of each reaction path according to the reaction rate constant in the reaction rate algorithm; wherein the content of the first and second substances,
the reaction rate constant is determined based on a transition state theoretical calculation method;
for example, the reaction rate constant is determined according to the following calculation formula:
wherein k is a reaction rate constant, kBBoltzmann constant, h is planckian constant, R is ideal gas constant, E is temperature value of environment where reaction path is located, exp is exponential function with natural constant as base, Δ S is entropy change before and after reaction corresponding to reaction rule corresponding to reaction path, Δ E is reaction energy barrier corresponding to reaction rule corresponding to reaction path,
and the catalyst activity factor, P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path.
Preferably, the model includes a physical property calculation model, and the obtaining of the execution result output by the model and corresponding to the analyzed operation instruction includes:
querying a physical property parameter database, and taking physical property data corresponding to the analyzed operation instruction in the physical property parameter database as an execution result output by the physical property calculation model; wherein the physical property parameter database comprises: physical properties of various single molecules in the molecular composition of the crude oil of the oil refinery; physical properties of the mixture.
Preferably, the method for calculating physical properties of the mixture includes:
calculating, for each single molecule in the mixture, physical properties of the single molecule from the number of groups of each group constituting the single molecule and a contribution value of the each group to the physical properties;
and calculating the physical properties of the mixture according to the physical properties of each single molecule in the mixture and the content of each single molecule in the mixture.
Before calculating the physical properties of the single molecule, the method preferably further comprises:
comparing the group number of each group forming the single molecule with the pre-stored molecular information of the template single molecule with known physical properties in a second database; wherein the molecular information comprises: the number of groups of each group constituting a single molecule of the template;
judging whether a template single molecule identical to the single molecule exists;
if a template monomolecular identical to the monomolecular exists, outputting the physical property of the template monomolecular as the physical property of the monomolecular;
and if the template single molecule identical to the single molecule does not exist, calculating the physical property of the single molecule.
Preferably, the method for calculating the physical property of the single molecule includes:
for each single molecule in the mixture, obtaining the number of groups of each group constituting the single molecule, and obtaining a contribution value of each of the groups to physical properties;
inputting the number of groups of each group forming the single molecule and the contribution value of each group to the physical property into a physical property calculation model trained in advance, and acquiring the physical property of the single molecule output by the physical property calculation model; wherein the content of the first and second substances,
and the physical property calculation model is used for calculating the physical property of the single molecule according to the number of groups of each group contained in the single molecule and the contribution value of each group to the physical property.
Preferably, the step of training the property calculation model includes:
constructing a physical property calculation model of a single molecule;
obtaining the number of groups of each group constituting a single molecule of the sample; the physical properties of the sample single molecules are known;
inputting the number of groups of each group contained in a single molecule of the sample into the physical property calculation model;
obtaining the predicted physical property of the sample single molecule output by the physical property calculation model;
if the deviation value between the predicted physical property and the known physical property is smaller than a preset deviation threshold value, determining that the physical property calculation model converges, acquiring a contribution value corresponding to each group in the converged physical property calculation model, and storing the contribution value as the contribution value of the group to the physical property;
if the deviation value between the predicted physical property and the known physical property is equal to or greater than the deviation threshold value, the contribution value corresponding to each group in the physical property calculation model is adjusted until the physical property calculation model converges.
Wherein, preferably, primary groups and multi-order groups are defined among all groups of the single molecule; wherein the content of the first and second substances,
all groups constituting a single molecule are taken as primary groups;
taking a plurality of groups which exist simultaneously and contribute to the coexistence of the same physical property as a multilevel group, and taking the number of the plurality of groups as the level of the multilevel group;
wherein, the multilevel group refers to a group of more than two levels;
the plural groups mean two or more groups.
The physical property calculation model determines the physical properties of single molecules according to the following modes:
obtaining a product of the number of groups of each group and a contribution value of each group to the physical property;
and obtaining the physical property of the single molecule according to the sum of the products corresponding to all the groups.
For example, the physical property calculation model is as follows:
wherein f is the physical property of the single molecule, and n isiNumber of groups of i-th group,. DELTA.fiThe value of contribution of the i-th group to the physical property, and a is a correlation constant.
Wherein, preferably, said obtaining the number of groups of each group constituting a single molecule of the sample comprises: defining primary and multi-order groups among all groups of said single molecule; wherein the content of the first and second substances,
all groups constituting a single molecule are taken as primary groups;
taking a plurality of groups which exist simultaneously and contribute to the coexistence of the same physical property as a multilevel group, and taking the number of the plurality of groups as the level of the multilevel group;
wherein, the multilevel group refers to a group of more than two levels;
the plural groups mean two or more groups.
Wherein the physical property calculation model determines the physical properties of the single molecule according to the following modes:
in each level of group, respectively obtaining the product of the number of the groups of various groups and the contribution value of each group to the physical property, and then obtaining the sum of the products corresponding to each group to be recorded as the contribution value of the level of group to the physical property;
and obtaining the physical properties of the single molecule according to the sum of the contribution values of all levels of groups to the physical properties.
For example, the physical property calculation model is as follows:
wherein f is the physical property of the single molecule, and m is1iIs the number of groups of the i-th group in the primary group,. DELTA.f1iM is the value of the contribution of the i-th group in the primary group to the physical properties2jIs the number of groups of the jth group in the secondary group,. DELTA.f2jIs the contribution value of the jth group in the secondary group to the physical property; m isNlIs the number of groups of the group I in the N-th group,. DELTA.fNlIs the contribution value of the first group in the N-grade groups to physical properties; a is a correlation constant; n is a positive integer greater than or equal to 2.
Wherein the physical properties of the single molecule include: the boiling point of a single molecule;
the calculating the physical properties of the single molecule comprises:
the boiling point of the single molecule was calculated according to the following physical property calculation model:
wherein T is the boiling point of the single molecule, SOL is the monomolecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP11GROUP is a first contribution vector converted according to the contribution of each primary GROUP of the single molecule to the boiling point12GROUP is a second contribution vector converted according to the contribution of each secondary GROUP of the single molecule to the boiling point1NThe N contribution value vector is obtained by converting the contribution value of each N-grade group of the single molecule to the boiling point; numh is the number of atoms in the single molecule except hydrogen atoms; b is a first preset constant, c is a second preset constant, and d is a third preset constant; and N is a positive integer greater than or equal to 2.
Among them, the physical properties of the single molecule preferably include: the density of the single molecule;
the physical property calculation model determines the density of the single molecule in the following manner:
a monomolecular vector converted according to the number of groups of each group constituting the monomolecular;
converting the contribution value vector of each grade of group to the density according to the contribution value of each grade of group;
obtaining products of the single molecular vectors and the contribution value vectors of all levels of groups respectively, and then obtaining the sum of the products of the single molecular vectors and the corresponding products of all levels of groups;
and obtaining the density of the single molecule according to the ratio of the product of the single molecule vector and the contribution value vector of the first-level group in the sum of the single molecule vector and the products corresponding to all levels of groups.
For example, the physical property calculation model is as follows:
wherein D is the density of the single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP21GROUP is the vector of N +1 contribution converted from the contribution of the primary GROUP to the density22GROUP is the vector of N +2 contribution converted from the contribution of secondary GROUPs to the density2NThe vector of the 2N contribution value is obtained by converting the contribution value of the N-grade group to the density, and e is a fourth preset constant; and N is a positive integer greater than or equal to 2.
Among them, the physical properties of the single molecule preferably include: the octane number of a single molecule;
the calculating the physical properties of the single molecule comprises:
the physical property calculation model determines the octane number of a single molecule according to the following modes:
a monomolecular vector converted according to the number of groups of each group constituting the monomolecular;
converting the contribution value vector of each grade group to the octane number according to the contribution value of the grade group;
obtaining the product of the single molecular vector and the contribution value vector of each level of group;
and obtaining the octane number of the single molecule according to the sum of the products of the single molecule vector and the corresponding radicals of each level.
For example, the physical property calculation model is as follows:
X＝SOL×GROUP31+SOL×GROUP32+......+SOL×GROUP3N+h；
wherein X is the octane number of the single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP31GROUP is the 2N +1 contribution vector obtained by converting the contribution of each primary GROUP of the single molecule to the octane number respectively32GROUP is the 2N +2 contribution vector obtained by converting the contribution of each secondary GROUP of the single molecule to the octane number respectively3NThe 3N contribution value vector is obtained by converting the contribution value of each N-grade group of the single molecule to the octane number; n is a positive integer greater than or equal to 2; h is a fifth predetermined constant.
Among them, the physical properties of the mixture preferably include: density, cloud point, pour point, aniline point, and octane number.
Wherein, when the physical property of the mixture is density, calculating the physical property of the mixture preferably comprises:
the density of the mixture was calculated by the following method:
obtaining the product of the density of each of said single molecules and the content of that single molecule;
the density of the mixture is obtained from the sum of the products corresponding to each of the single molecules.
For example, the density of the mixture is calculated by the following calculation formula:
density＝∑(Di×xi_volume)；
wherein density is the density of the mixture, DiDensity of the i-th single molecule, xi_volumeIs the volume content of the i-th single molecule.
Wherein, when the physical property of the mixture is a cloud point, calculating the physical property of the mixture preferably comprises:
calculating a cloud point contribution for each single molecule based on the density and boiling point of the single molecule;
calculating the cloud point of the mixture based on the cloud point contribution of each single molecule in the mixture and the amount of each single molecule in the mixture.
Wherein when the physical property of the mixture is pour point, the physical property of the mixture is calculated, preferably comprising:
calculating a pour point contribution value for each single molecule based on the density and molecular weight of the single molecule;
the pour point of the mixture is calculated based on the pour point contribution value of each single molecule in the mixture and the amount of each single molecule in the mixture.
Wherein when the physical property of the mixture is an aniline point, calculating the physical property of the mixture preferably comprises:
calculating the aniline point contribution value of each single molecule according to the density and boiling point of the single molecule;
and calculating the aniline point of the mixture according to the aniline point contribution value of each single molecule in the mixture and the content of each single molecule in the mixture.
Wherein, when the physical property of the mixture is octane number, calculating the physical property of the mixture preferably includes:
the octane number of the mixture is calculated by the following calculation formula:
wherein ON is the octane number of the mixture, HISQFG is a molecular set, H is a molecular set of normal paraffin, I is a molecular set of isoparaffin, S is a molecular set of cycloparaffin, Q is a molecular set of olefin, F is a molecular set of aromatic hydrocarbon, G is a molecular set of oxygen-containing compound, and upsilon isiIs the content of each molecule in the mixture; upsilon isH、υI、υS、υQ、υF、υGRespectively the total content of normal paraffin, the total content of isoparaffin, the total content of cyclane, the total content of olefin, the total content of aromatic hydrocarbon and the total content of oxygen-containing compound in the mixture; beta is aiA regression parameter for each molecule in the mixture; ONiAn octane number for each molecule in the mixture; cHRepresenting the interaction coefficient of the normal alkane with other molecules; cIRepresenting the interaction coefficient of the isoparaffin with other molecules; cSRepresenting the coefficient of interaction of cycloalkanes with other molecules; cQRepresenting the coefficient of interaction of the olefin with other molecules; cFRepresenting the interaction coefficient of the aromatic hydrocarbon with other molecules; cGRepresenting the interaction coefficient of the oxygen-containing compound and other molecules;
a first constant coefficient between the normal paraffin and the isoparaffin,
A first constant coefficient between n-alkane and cycloalkane,
A first constant coefficient between the normal paraffin and the olefin,
A first constant coefficient between n-alkane and aromatic hydrocarbon,
A first constant coefficient between the normal alkane and the oxygen-containing compound,
A first constant coefficient between isoparaffin and cycloalkane,
A first constant coefficient between the isoparaffin and the olefin,
A first constant coefficient between isoparaffin and aromatic hydrocarbon,
A first constant coefficient between the isoparaffin and the oxygen-containing compound,
A first constant coefficient between a cycloalkane and an olefin,
A first constant coefficient between a cycloalkane and an aromatic hydrocarbon,
A first constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A first constant coefficient between olefin and aromatic hydrocarbon,
A first constant coefficient between the olefin and the oxygen-containing compound,
A first constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound,
A second constant coefficient between the normal paraffin and the isoparaffin,
A second constant coefficient between n-alkane and cycloalkane,
A second constant coefficient between the normal paraffin and the olefin,
A second constant coefficient between the normal paraffin and the aromatic hydrocarbon,
A second constant coefficient between the normal alkane and the oxygen-containing compound,
A second constant coefficient between isoparaffin and cycloalkane,
A second constant coefficient between the isoparaffin and the olefin,
A second constant coefficient between isoparaffin and aromatic hydrocarbon,
A second constant coefficient between the isoparaffin and the oxygen-containing compound,
A second constant coefficient between cycloalkane and olefin,
A second constant coefficient between the cycloalkane and the aromatic hydrocarbon,
A second constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A second constant coefficient between olefin and aromatic hydrocarbon,
A second constant coefficient between the olefin and the oxygen-containing compound,
Represents a second constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound; wherein the octane number comprises: research octane number and motor octane number.
Wherein the types of browsers of the web client include:
IE. One or more of Chrome, Firefox, Safari or Opera.
Wherein the categories of the web server include:
apache, Nginx, Tomcat, or IIS.
Wherein, the oil refining device includes:
a single petroleum processing unit, a plurality of petroleum processing units, or a corresponding petroleum processing unit in a whole flow of oil refinery processing, the types of petroleum processing units including:
catalytic cracker, delayed coking unit, residue hydrogenation unit, hydrocracking unit, diesel oil hydrogenation modification unit, diesel oil hydrogenation refining unit, gasoline hydrogenation refining unit, catalytic reforming unit and alkylation unit; wherein each petroleum processing plant corresponds to a set of reaction rules.
In a second aspect, an embodiment of the present invention provides a B/S architecture-based oil refining device simulation apparatus, where the apparatus includes:
the receiving unit is used for receiving an operation instruction which is input by a user and corresponds to the oil refining device through a browser interface of the web client;
the first processing unit is used for sending the operation instruction to a web server through network communication so that the web server can analyze the operation instruction, input the analyzed operation instruction into a pre-trained model, obtain an execution result output by the model and corresponding to the analyzed operation instruction, and send the execution result to the web client;
and the second processing unit is used for displaying the execution result received by the web client on the browser interface.
Wherein the apparatus further comprises: a third processing unit;
the receiving unit is further used for receiving a user name and a password input by a user through the browser interface;
and the third processing unit is used for sending the user name and the password to the web server through network communication so as to enable the web server to perform user identity authentication, and if the user identity authentication passes, the third processing unit executes the step of receiving an operation instruction which is input by a user and corresponds to the oil refining device through a browser interface of the web client.
The second processing unit is specifically configured to display the execution result in a tabular manner, or display the execution result in a graphical manner, or display the execution result in a manner of generating a reaction network in an output window of the browser interface.
Wherein the model comprises a product prediction model;
the first processing unit is specifically configured to query a molecular composition database, and use molecular composition data corresponding to the analyzed operation instruction in the molecular composition database as the execution result output by the product prediction model; wherein the molecular composition database comprises: obtaining a molecular composition of the crude oil of the refinery; according to the physical properties of each single molecule in the molecular composition of the crude oil, obtaining the molecular composition of different fractions obtained by distilling the crude oil; according to the preset raw material proportion, respectively inputting the corresponding fractions as oil refining raw materials into corresponding product prediction models of an oil refining device to obtain the molecular composition of the corresponding prediction products and the content of each single molecule in the prediction products; and blending each predicted product serving as a product blending raw material according to a preset rule set to obtain the molecular composition of a plurality of groups of mixtures and the content of each single molecule in the mixtures.
Wherein the model comprises a physical property calculation model;
the first processing unit is specifically configured to query a physical property parameter database, and use physical property data corresponding to the analyzed operation instruction in the physical property parameter database as an execution result output by the physical property calculation model; wherein the physical property parameter database comprises: physical properties of various single molecules in the molecular composition of the crude oil of the oil refinery; physical properties of the mixture.
The invention also provides an oil refining device simulation system based on the B/S architecture, which comprises a processor and a memory; the processor is used for executing the B/S architecture-based oil refining device simulation program stored in the memory so as to realize the B/S architecture-based oil refining device simulation method.
The invention also provides a storage medium, which stores one or more programs, wherein the one or more programs can be executed by one or more processors to realize the oil refining device simulation method based on the B/S architecture.
The invention has the following beneficial effects:
the method comprises the steps of receiving an operation instruction corresponding to an oil refining device input by a user through a browser interface of a web client; sending the operation instruction to a web server through network communication so that the web server analyzes the operation instruction, inputting the analyzed operation instruction into a pre-trained model, acquiring an execution result output by the model and corresponding to the analyzed operation instruction, and sending the execution result to the web client; and displaying the execution result received by the web client on the browser interface. According to the method, the execution result corresponding to the operation instruction of the oil refining device is calculated by using the pre-trained model through data interaction between the browser interface of the web client and the server, a user can directly log in an account on the browser interface without installing a client program, the data processing speed of the web server is high, a developer can conveniently maintain and manage the system, and the interactive experience effect of the user and the client is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a flow chart of a B/S architecture based refinery apparatus simulation method according to an embodiment of the present invention;
fig. 2 is a block diagram of a simulation apparatus of a refinery apparatus based on a B/S architecture according to an embodiment of the present invention;
fig. 3 is a diagram illustrating an architecture of a simulation system of an oil refinery apparatus based on a B/S architecture according to an embodiment of the present invention;
fig. 4 is a block diagram of a simulation system of a refinery apparatus based on a B/S architecture according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.
According to the embodiment of the invention, a B/S architecture-based oil refining device simulation method is provided. Fig. 1 is a flow chart of a simulation method of a refinery device based on a B/S architecture according to an embodiment of the present invention.
And step S110, receiving an operation instruction corresponding to the oil refining device, which is input by a user, through a browser interface of the web client.
In this embodiment, the oil refining apparatus includes: a single petroleum processing facility, a plurality of petroleum processing facilities, or a corresponding petroleum processing facility in a refinery process flow, the types of petroleum processing facilities including, but not limited to: catalytic cracker, delayed coking unit, residue hydrogenation unit, hydrocracking unit, diesel oil hydrogenation modification unit, diesel oil hydrogenation refining unit, gasoline hydrogenation refining unit, catalytic reforming unit and alkylation unit; wherein each petroleum processing plant corresponds to a set of reaction rules.
In this embodiment, in the operation instruction input window of the browser interface, a selectable operation instruction and a corresponding control are displayed, so that a user can select the operation instruction conveniently. The operation instruction comprises an instruction type and instruction content, wherein the instruction type comprises but is not limited to button clicking, screen sliding, auxiliary screen turning, rotating zooming and inputting text.
In this embodiment, the types of the browser of the web client include: IE. One or more of Chrome, Firefox, Safari or Opera.
Step S120, the operation instruction is sent to a web server through network communication, so that the web server analyzes the operation instruction, inputs the analyzed operation instruction into a pre-trained model, obtains an execution result output by the model and corresponding to the analyzed operation instruction, and sends the execution result to the web client.
In this embodiment, the categories of the web server include: apache, Nginx, Tomcat, or IIS.
Step S130, displaying the execution result received by the web client on the browser interface.
According to the method, the execution result corresponding to the operation instruction of the oil refining device is calculated by using the pre-trained model through data interaction between the browser interface of the web client and the server, a user can directly log in an account on the browser interface without installing a client program, the data processing speed of the web server is high, a developer can conveniently maintain and manage the system, and the interactive experience effect of the user and the client is improved.
In this embodiment, the execution result is displayed in a tabular manner, or graphically, or in a manner of generating a reaction network in an output window of the browser interface. Wherein displaying the execution result in a manner of generating a reaction network comprises: displaying one or more of the molecular composition, the structure of each single molecule in the molecular composition, the content of each single molecule, the physical properties of each single molecule, or the content of each single molecule. Wherein the reaction network comprises a two-dimensional reaction network or a three-dimensional reaction network.
In another embodiment of the present invention, the method further comprises:
receiving a user name and a password input by a user through the browser interface;
and sending the user name and the password to the web server through network communication so as to enable the web server to perform user identity authentication, and if the user identity authentication is passed, executing the step S110 and receiving an operation instruction which is input by a user and corresponds to the oil refining device through a browser interface of a web client. The interactive security management is improved by carrying out identity authentication on the user.
In another embodiment of the present invention, the obtaining the execution result output by the model and corresponding to the parsed operation instruction includes:
querying a molecular composition database, and taking molecular composition data corresponding to the analyzed operation instruction in the molecular composition database as the execution result output by the product prediction model; wherein the molecular composition database comprises: obtaining a molecular composition of the crude oil of the refinery; according to the physical properties of each single molecule in the molecular composition of the crude oil, obtaining the molecular composition of different fractions obtained by distilling the crude oil; according to the preset raw material proportion, respectively inputting the corresponding fractions as oil refining raw materials into corresponding product prediction models of an oil refining device to obtain the molecular composition of the corresponding prediction products and the content of each single molecule in the prediction products; and blending each predicted product serving as a product blending raw material according to a preset rule set to obtain the molecular composition of a plurality of groups of mixtures and the content of each single molecule in the mixtures.
In this embodiment, a product prediction model is previously trained for each type of petroleum processing apparatus, and an execution result corresponding to an operation instruction is predicted by the corresponding product prediction model. The method has the advantages of high accuracy, short time and low cost. In this embodiment, the molecular composition of the crude oil of the refinery apparatus can be determined by one or more of comprehensive two-dimensional gas chromatography, quadrupole gas chromatography-mass spectrometer detection, gas chromatography/field ionization-time-of-flight mass spectrometry detection, gas chromatography, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, raman spectroscopy, fourier transform ion cyclotron resonance mass spectrometry, electrostatic field orbitrap mass spectrometry, and ion mobility mass spectrometry.
Of course, the molecular composition of the crude oil can also be determined in other ways. For example: the molecular composition of crude oil was determined by ASTM D2425, SH/T0606, ASTM D8144-18.
In this example, individual single molecules (molecules) in the molecular composition were characterized using a SOL-Oriented Lumping (Structure-Oriented Lumping) based molecular characterization method. Among them, the SOL-based molecular characterization method can characterize the architecture of hydrocarbon molecules using 24 groups.
Further, the SOL belongs to the lump on the molecular scale, the number of molecules in an actual system is reduced from millions to thousands, and the complexity of the oil refining device model is greatly reduced. The SOL-based molecular characterization method can represent not only alkanes, cycloalkanes, up to complex aromatic architectures containing 50-60 carbon atoms, but also alkenes or cycloalkenes as intermediate products or secondary reaction products, in addition to heteroatom compounds containing sulfur, nitrogen, oxygen, etc.
And the product prediction model is used for determining the yield of the product of the crude oil under different reaction conditions according to the molecular composition of the crude oil. Further, a product prediction model is used for determining the content of various product molecules of the crude oil under different reaction conditions according to the molecular composition of the crude oil.
The steps for training the product prediction model will be described later, and are not described herein.
In another embodiment of the present invention, the obtaining the execution result corresponding to the analyzed operation instruction output by the model includes:
querying a physical property parameter database, and taking physical property data corresponding to the analyzed operation instruction in the physical property parameter database as an execution result output by the physical property calculation model; wherein the physical property parameter database comprises: physical properties of various single molecules in the molecular composition of the crude oil of the oil refinery; physical properties of the mixture.
The procedure for training the physical property calculation model will be described later, and will not be described herein.
The steps for training the artifact prediction model are further described below. In an embodiment of the present invention, the step of training the product prediction model includes:
establishing a product prediction model; wherein the product prediction model comprises: a reaction rule set of a plurality of reaction rules and a reaction rate algorithm; establishing a product prediction model according to the type correspondence of the petroleum processing device; the product prediction model corresponding to the type of petroleum processing equipment includes: a set of reaction rules and a reaction rate algorithm corresponding to the category of petroleum processing equipment. Wherein the set of reaction rules includes: a plurality of reaction rules corresponding to the type of petroleum processing equipment;
acquiring sample raw material information of sample raw materials; sample material information of the sample material includes: the molecular composition of the sample raw material, the molecular content of each molecule in the sample raw material, the molecular composition of an actual product corresponding to the sample raw material and the actual content of each molecule in the actual product. The actual product is the product obtained after the sample raw material is processed by the petroleum processing device of the kind.
Training the reaction rule set by using the sample raw material information, and fixing the trained reaction rule set;
and training the reaction rate algorithm by using the sample raw material information, and fixing the trained reaction rate algorithm to obtain the trained product prediction model.
One way to train the reaction rule set is given below. It should be understood by those skilled in the art that the manner is only for illustrating the embodiment and is not limited to the embodiment.
Training the reaction rule set by using the sample raw material information, comprising:
processing the molecular composition of the sample raw material according to a preset reaction rule set to obtain a reaction path corresponding to each molecule in the molecular composition of the sample raw material; and when the reaction path is calculated for the first time, processing the molecular composition of the sample raw material according to a preset reaction rule set to obtain the reaction path corresponding to each molecule in the molecular composition of the sample raw material.
And (3) reacting each molecule in the sample raw material according to the reaction rule in the reaction rule set to obtain a reaction path corresponding to each molecule.
Obtaining a first molecular composition of a device product according to a reaction path corresponding to each molecule in the molecular composition of the sample raw material; in the device product, comprising: the sample feedstock, intermediate product, and predicted product;
calculating a first relative deviation from a first molecular composition of the device product and a second molecular composition of the actual product;
if the first relative deviation meets a preset condition, fixing the reaction rule set;
and if the first relative deviation does not accord with the preset condition, adjusting the reaction rule in the reaction rule set, and recalculating the first relative difference value according to the adjusted reaction rule set until the first relative deviation accords with the preset condition.
In an embodiment of the invention, calculating a first relative deviation from a first molecular composition of the device product and a second molecular composition of the actual product comprises: acquiring the types of single molecules in the first molecular composition to form a first set; acquiring the species of single molecules in the second molecular composition to form a second set; determining whether the second set is a subset of the first set; if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as the first relative deviation value; if the second set is a subset of the first set, calculating a first relative deviation by:
wherein x is1Is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the sample material, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set. The preset conditions comprise: relative deviation range. The two endpoints of the relative deviation range are empirical values or experimentally obtained values.
One way to train the reaction rate algorithm is given below. It should be understood by those skilled in the art that the manner is only for illustrating the embodiment and is not limited to the embodiment. Training the reaction rate algorithm by using the sample raw material information, comprising:
respectively calculating the reaction rate of the reaction path corresponding to each molecule in the molecular composition of the sample raw material according to the reaction rate algorithm;
obtaining the predicted content of each molecule in the predicted product corresponding to the sample raw material according to the molecular content of each molecule in the sample raw material and the reaction rate corresponding to the reaction path of the molecule; in this embodiment, the reaction rate corresponding to each reaction path is calculated by the reaction rate calculation method in the product prediction model, and in combination with the monomolecular content of each monomolecular in the raw material, namely, the predicted content of each single molecule in the predicted product can be calculated, for example, the single molecule A in the raw material is assumed to correspond to 3 reaction paths, and the reaction rate corresponding to 3 reaction paths is known, as the reaction proceeds, the concentration of the single molecule A decreases, the reaction rate corresponding to 3 reaction paths decreases according to the decreasing proportion of the concentration, therefore, the single molecule A will generate the product with the ratio of the reaction rate of 3 paths, according to the above steps, obtaining a product obtained by reacting each molecule, obtaining a predicted product, and obtaining the predicted content of each single molecule in the predicted product when the content of each single molecule in the catalytic reforming raw material is known;
calculating a second relative deviation according to the predicted content of each molecule in the predicted product and the actual content of each molecule in the actual product; the second relative deviation is calculated, for example, as:
second relative deviation (actual content-predicted content) ÷ actual content.
If the second relative deviation meets a preset condition, fixing the reaction rate algorithm;
and if the second relative deviation does not accord with the preset condition, adjusting parameters in the reaction rate algorithm, and recalculating the second relative deviation according to the adjusted reaction rate algorithm until the second relative deviation accords with the preset condition.
In the embodiment of the present invention, calculating the reaction rate of the reaction path corresponding to each molecule in the molecular composition of the sample raw material according to the reaction rate algorithm includes:
calculating the reaction rate of each reaction path according to the reaction rate constant in the reaction rate algorithm; wherein the reaction rate constant is determined according to the following calculation formula:
the dynamic parameters in the formula are stored in a dynamic parameter database and called through a pre-trained model, and the dynamic parameters are as follows: k is a reaction rate constant, kBBoltzmann constant, h is planckian constant, R is ideal gas constant, E is temperature value of environment where reaction path is located, exp is exponential function with natural constant as base, Δ S is entropy change before and after reaction corresponding to reaction rule corresponding to reaction path, Δ E is reaction energy barrier corresponding to reaction rule corresponding to reaction path,
and the catalyst activity factor, P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path.
Specifically, the reaction rate of the reaction path is obtained according to the reaction rate constant and the reaction concentration corresponding to the reaction path. For example: where a reaction rate constant has been determined, the greater the space velocity, the shorter the contact time of the feedstock with the catalyst, the shorter the reaction time of the feedstock, the higher the concentration of reactants in the feedstock, and the higher the reaction rate of the reaction path; conversely, the lower the space velocity, the longer the contact time between the feedstock and the catalyst, the longer the reaction time of the feedstock, the lower the concentration of reactants in the feedstock, and the lower the reaction rate of the reaction path.
A way to train the physical property calculation model method is given below. It should be understood by those skilled in the art that the manner is only for illustrating the embodiment and is not limited to the embodiment. In an embodiment of the present invention, the step of training the property calculation model includes:
constructing a physical property calculation model of a single molecule; the physical property calculation model includes: contribution of each group to physical properties. The contribution value is an adjustable value, and the contribution value is an initial value when training for the first time. Further, the physical property calculation model includes: contribution of each group to each physical property.
Obtaining the number of groups of each group constituting a single molecule of the sample; the physical properties of the sample single molecules are known;
inputting the number of groups of each group contained in a single molecule of the sample into the physical property calculation model;
obtaining the predicted physical property of the sample single molecule output by the physical property calculation model;
if the deviation value between the predicted physical property and the known physical property is smaller than a preset deviation threshold value, determining that the physical property calculation model converges, acquiring a contribution value corresponding to each group in the converged physical property calculation model, and storing the contribution value as the contribution value of the group to the physical property;
if the deviation value between the predicted physical property and the known physical property is equal to or greater than the deviation threshold value, the contribution value corresponding to each group in the physical property calculation model is adjusted until the physical property calculation model converges.
Two types of physical property calculation models that can be used for different physical properties are given below. It should be understood by those skilled in the art that the following two physical property calculation models are only illustrative of the present embodiment and are not intended to limit the present embodiment.
Model one: the following physical property calculation model is established:
wherein f is a monomolecular physical property, and niIs the number of groups of the i-th group in the single molecule,. DELTA.fiAnd a is a correlation constant, which is a contribution value of the ith group in the single molecule to the physical property.
Groups constituting a single molecule can be further classified into multi-stage groups. Further, defining a primary group and a multi-order group among all groups of the single molecule; wherein all groups constituting a single molecule are taken as primary groups; a plurality of groups which exist simultaneously and contribute to the common existence of the same physical property are used as a multi-stage group, and the number of the plurality of groups is used as the level of the multi-stage group.
For example: for boiling point, in the SOL-based molecular characterization method, 24 groups are all used as primary groups; of the 24 groups, the presence of one or more of N6, N5, N4, N3, me, AA, NN, RN, NO, RO, KO simultaneously contributes to boiling point. When dividing a single molecule of groups, all groups forming the single molecule are used as first-order groups, whether a plurality of groups which can contribute to the boiling point together exist in all the groups of the single molecule or not is checked, if the groups exist, a plurality of groups which can contribute to the boiling point together exist together and are used as multi-order groups, such as: both N6 and N4 are present in the single molecule, and the number of groups that contribute to boiling point co-presence when present is two, both N6 and N4 are considered secondary groups.
Model two: based on the divided multilevel groups, a physical property calculation model can be established as follows:
wherein f is a physical property of a single molecule, and m is1iIs the radical number of the ith radical in the primary radical of the said single molecule,. DELTA.f1iIs the contribution value of the ith group in the primary group of the single molecule to the physical property; m is2jIs the radical number of the jth radical in the secondary radical of the said single molecule,. DELTA.f2jIs the contribution value of the jth group in the secondary group of the single molecule to the physical property; m isNlIs the radical number of the I group in the N-th order of the said single molecule,. DELTA.fNlIs the contribution value of the I group in the N-grade groups of the single molecule to the physical property; n is a positive integer greater than or equal to 2; a is a correlation constant.
In an embodiment of the present invention, the obtaining the number of groups of each group constituting a single molecule of the sample includes:
determining a primary group, the group number of the multilevel group and the group number of the multilevel group in all groups of the single molecule of the sample; wherein the physical properties of the sample single molecule are known.
A training sample set is preset. A plurality of sample single molecule information is included in the training sample set. Sample single molecule information including, but not limited to: the number of groups of each group constituting a single molecule of the sample, and the physical properties of the single molecule of the sample.
All groups constituting a single molecule are taken as primary groups;
a plurality of groups which exist simultaneously and contribute to the common existence of the same physical property are used as a multi-stage group, and the number of the plurality of groups is used as the level of the multi-stage group.
Physical properties of single molecules, including but not limited to: density, boiling point, density, octane number. For example: the physical properties of the single molecule may further include: viscosity, solubility parameter, cetane number, unsaturation, and the like.
A group is a part of a molecule, and the group generally participates in a chemical reaction as a whole.
Determining the group contained in each single molecule based on the SOL molecular characterization method; the number of groups per group in each single molecule and the contribution value of each group in the single molecule to the physical properties are determined, respectively. Since the number of physical properties of a single molecule is large, it is necessary to determine the contribution value of each group in the single molecule to each physical property.
The physical properties of the calculated mixture are further described below.
Calculating, for each single molecule in the mixture, physical properties of the single molecule from the number of groups of each group constituting the single molecule and a contribution value of the each group to the physical properties;
and calculating the physical properties of the mixture according to the physical properties of each single molecule in the mixture and the content of each single molecule in the mixture.
In another embodiment of the present invention, before calculating the physical properties of the single molecule, the method further comprises:
comparing the group number of each group forming the single molecule with the pre-stored molecular information of the template single molecule with known physical properties in a second database; wherein the molecular information comprises: the number of groups of each group constituting a single molecule of the template;
judging whether a template single molecule identical to the single molecule exists;
if a template monomolecular identical to the monomolecular exists, outputting the physical property of the template monomolecular as the physical property of the monomolecular;
and if the template single molecule identical to the single molecule does not exist, calculating the physical property of the single molecule.
In an embodiment of the present invention, the physical properties of the mixture include: density, cloud point, pour point, aniline point, and octane number.
In an embodiment of the present invention, when the physical property of the mixture is density, calculating the physical property of the mixture includes:
the density of the mixture is calculated by the following calculation:
density＝∑(Di×xi_volume)；
wherein density is the density of the mixture, DiDensity of the i-th single molecule, xi_volumeThe content of the i-th single molecule.
In an embodiment of the present invention, calculating the physical property of the mixture when the physical property of the mixture is the cloud point comprises:
calculating a cloud point contribution for each single molecule based on the density and boiling point of the single molecule;
calculating the cloud point of the mixture based on the cloud point contribution of each single molecule in the mixture and the amount of each single molecule in the mixture.
In an embodiment of the invention, when the physical property of the mixture is pour point, calculating the physical property of the mixture comprises:
calculating a pour point contribution value for each single molecule based on the density and molecular weight of the single molecule;
the pour point of the mixture is calculated based on the pour point contribution value of each single molecule in the mixture and the amount of each single molecule in the mixture.
In an embodiment of the present invention, when the physical property of the mixture is an aniline point, calculating the physical property of the mixture comprises:
calculating the aniline point contribution value of each single molecule according to the density and boiling point of the single molecule;
and calculating the aniline point of the mixture according to the aniline point contribution value of each single molecule in the mixture and the content of each single molecule in the mixture.
In an embodiment of the present invention, when the physical property of the mixture is octane number, calculating the physical property of the mixture includes:
the octane number of the mixture is calculated by the following calculation formula:
wherein said ON is of said mixtureOctane number, HISQFG is a molecular set, H is a molecular set of normal paraffin, I is a molecular set of isoparaffin, S is a molecular set of cycloparaffin, Q is a molecular set of olefin, F is a molecular set of aromatic hydrocarbon, G is a molecular set of oxygen-containing compound, and upsilon isiIs the content of each molecule in the mixture; upsilon isH、υI、υS、υQ、υF、υGRespectively the total content of normal paraffin, the total content of isoparaffin, the total content of cyclane, the total content of olefin, the total content of aromatic hydrocarbon and the total content of oxygen-containing compound in the mixture; beta is aiA regression parameter for each molecule in the mixture; ONiAn octane number for each molecule in the mixture; cHRepresenting the interaction coefficient of the normal alkane with other molecules; cIRepresenting the interaction coefficient of the isoparaffin with other molecules; cSRepresenting the coefficient of interaction of cycloalkanes with other molecules; cQRepresenting the coefficient of interaction of the olefin with other molecules; cFRepresenting the interaction coefficient of the aromatic hydrocarbon with other molecules; cGRepresenting the interaction coefficient of the oxygen-containing compound and other molecules;
a first constant coefficient between the normal paraffin and the isoparaffin,
A first constant coefficient between n-alkane and cycloalkane,
A first constant coefficient between the normal paraffin and the olefin,
A first constant coefficient between n-alkane and aromatic hydrocarbon,
Denotes a first constant system between the normal alkane and the oxygen-containing compoundA plurality of,
A first constant coefficient between isoparaffin and cycloalkane,
A first constant coefficient between the isoparaffin and the olefin,
A first constant coefficient between isoparaffin and aromatic hydrocarbon,
A first constant coefficient between the isoparaffin and the oxygen-containing compound,
A first constant coefficient between a cycloalkane and an olefin,
A first constant coefficient between a cycloalkane and an aromatic hydrocarbon,
A first constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A first constant coefficient between olefin and aromatic hydrocarbon,
A first constant coefficient between the olefin and the oxygen-containing compound,
A first constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound,
Represents a normal alkaneA second constant coefficient between the hydrocarbon and the isoparaffin,
A second constant coefficient between n-alkane and cycloalkane,
A second constant coefficient between the normal paraffin and the olefin,
A second constant coefficient between the normal paraffin and the aromatic hydrocarbon,
A second constant coefficient between the normal alkane and the oxygen-containing compound,
A second constant coefficient between isoparaffin and cycloalkane,
A second constant coefficient between the isoparaffin and the olefin,
A second constant coefficient between isoparaffin and aromatic hydrocarbon,
A second constant coefficient between the isoparaffin and the oxygen-containing compound,
A second constant coefficient between cycloalkane and olefin,
A second constant coefficient between the cycloalkane and the aromatic hydrocarbon,
A second constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A second constant coefficient between olefin and aromatic hydrocarbon,
A second constant coefficient between the olefin and the oxygen-containing compound,
Represents a second constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound; wherein the octane number comprises: research octane number and motor octane number.
The calculation of the physical properties of the single molecules is further described below.
For each single molecule in the mixture, acquiring the number of groups of each group constituting the single molecule, and acquiring the contribution value of each group to the physical property;
further, the kind of the group contained in a single molecule is determined, the number of the group of each kind of the group is determined, and the contribution value of each kind of the group to each physical property of the target product is obtained.
Inputting the number of groups of each group constituting the single molecule and the contribution value of each group to the physical property into a physical property calculation model trained in advance, and acquiring the physical property of the single molecule output by the physical property calculation model.
In this example, a physical property calculation model for calculating a physical property of a single molecule based on the number of groups of each group contained in the single molecule and a value of contribution of each group to the physical property.
Further, the group number of each kind of group of a single molecule is obtained, the contribution value of each kind of group to each physical property of the target product is obtained, the contribution value is input into a physical property calculation model trained in advance, and a plurality of physical properties of the single molecule output by the physical property calculation model are obtained;
for each group, storing the contribution value of the group to each physical property, so that when the physical property of a single molecule is calculated later, the contribution value of each group in the single molecule to the physical property to be known can be obtained, and the number of groups of each group in the single molecule and the contribution value of each group to the physical property to be known are used as the input of a physical property calculation model, the physical property calculation model uses the number of groups of each group in the single molecule as a model variable, and uses the contribution value of each group to the physical property to be known as a model parameter (replacing the adjustable contribution value of each group in the physical property calculation model to the physical property), and the physical property to be known is calculated.
In addition to the general-purpose physical property calculation model described above, a physical property calculation model may be constructed for each physical property depending on the type of physical property.
For example: the boiling point of the single molecule was calculated according to the following physical property calculation model:
wherein T is the boiling point of a single molecule, SOL is the monomolecular vector converted according to the number of GROUPs of each GROUP constituting a single molecule, GROUP11GROUP, a first contribution vector derived from the conversion of the contribution of the primary GROUP to the boiling point12GROUP, a second contribution vector converted from the contribution of the secondary GROUP to the boiling point1NThe N contribution value vector is obtained by converting the contribution value of the N-level group to the boiling point, Numh is the number of atoms in a single molecule except for hydrogen atoms, and b, c and d are preset constants; n is a positive integer greater than or equal to 2.
A monomolecular vector converted according to the number of groups of each group constituting the monomolecular, comprising: taking the number of species of all groups constituting the single molecule as the dimension of the single molecule vector; the number of groups per said group is taken as the element value of the corresponding dimension in said single molecular vector.
The first contribution value vector obtained by converting the contribution value of each primary group of the single molecule to the boiling point comprises: taking the number of species of primary groups as the dimension of the first contribution vector; and taking the contribution value of each primary group as the element value of the corresponding dimension in the first contribution value vector. And converting a second contribution value vector according to the contribution values of each secondary group of the single molecule to the boiling point respectively, wherein the second contribution value vector comprises: taking the number of species of secondary groups as the dimension of the second contribution vector; and taking the contribution value of each secondary group as the element value of the corresponding dimension in the second contribution value vector. By analogy, the Nth contribution value vector obtained by converting the contribution values of each N-grade group of the single molecule to the boiling point respectively comprises the following components: taking the number of species of the N-th order group as the dimension of the Nth contribution value vector; and taking the contribution value of each N-grade group as the element value of the corresponding dimension in the Nth contribution value vector.
For another example: the density of the single molecules was calculated according to the following physical property calculation model:
wherein D is the density of a single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting a single molecule, GROUP21GROUP is the vector of N +1 contribution converted from the contribution of the primary GROUP to the density22GROUP, a vector of N +2 contribution values converted from the contribution values of the secondary GROUPs to the density2NThe vector of the 2N contribution value is obtained by converting the contribution value of the N-grade group to the density, and e is a preset constant; n is a positive integer greater than or equal to 2.
A monomolecular vector converted according to the number of groups of each group constituting the monomolecular, comprising: taking the number of species of all groups constituting the single molecule as the dimension of the single molecule vector; the number of groups per said group is taken as the element value of the corresponding dimension in said single molecular vector.
The N +1 th contribution value vector obtained by converting the contribution values of the primary groups of the single molecule to the density respectively comprises: taking the number of species of primary groups as the dimension of the N +1 th contribution vector; and taking the contribution value of each primary group as the element value of the corresponding dimension in the N +1 th contribution value vector. And (3) converting the N +2 contribution value vector obtained according to the contribution value of each secondary group of the single molecule to the density respectively, wherein the vector comprises: taking the number of species of secondary groups as the dimension of the N +2 contribution vector; and taking the contribution value of each secondary group as the element value of the corresponding dimension in the N +2 th contribution value vector. By analogy, the 2N contribution value vector obtained by converting the contribution values of each N-level group of the single molecule to the density respectively comprises: taking the number of species of the N-th order group as the dimensionality of the 2N contribution vector; and taking the contribution value of each N-grade group as the element value of the corresponding dimension in the 2N contribution value vector.
The following steps are repeated: the octane number of the single molecule was calculated according to the following physical property calculation model:
X＝SOL×GROUP31+SOL×GROUP32+......+SOL×GROUP3N+h；
wherein X is the octane number of a single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting a single molecule, GROUP31GROUP is a 2N +1 contribution vector converted from the contribution of the primary GROUP to the octane number32GROUP is a 2N +2 contribution vector converted from the contribution of the secondary GROUP to the octane number3NThe 3N contribution value vector is obtained by converting the contribution value of the N-grade group to the octane number; n is a positive integer greater than or equal to 2; h is a preset constant.
A monomolecular vector converted according to the number of groups of each group constituting the monomolecular, comprising: taking the number of species of all groups constituting the single molecule as the dimension of the single molecule vector; the number of groups per said group is taken as the element value of the corresponding dimension in said single molecular vector.
The 2N +1 th contribution value vector obtained by converting the contribution value of each primary group of the single molecule to the octane number respectively comprises the following components: taking the number of species of primary groups as the dimensionality of the 2N +1 contribution vector; and taking the contribution value of each primary group as the element value of the corresponding dimension in the 2N +1 th contribution value vector. The 2N +2 contribution value vector obtained by converting the contribution value of each secondary group of the single molecule to the octane number respectively comprises the following components: taking the number of species of secondary groups as the dimensionality of the 2N +2 contribution vector; and taking the contribution value of each secondary group as the element value of the corresponding dimension in the 2N +2 contribution value vector. By analogy, the 3N contribution value vector obtained by converting the contribution values of each N-grade group of the single molecule to the octane number respectively comprises the following steps: taking the number of species of the N-th order group as the dimension of the 3 Nth contribution vector; and taking the contribution value of each N-grade group as the element value of the corresponding dimension in the 3 Nth contribution value vector.
The implementation provides an oil refining device simulation device based on a B/S framework. As shown in fig. 2, the apparatus includes: a receiving unit 11, a first processing unit 12 and a second processing unit 13.
In this embodiment, the receiving unit 11 is configured to receive, through a browser interface of a web client, an operation instruction corresponding to the oil refining apparatus input by a user;
in this embodiment, the first processing unit 12 is configured to send the operation instruction to a web server through network communication, so that the web server analyzes the operation instruction, inputs the analyzed operation instruction into a pre-trained model, obtains an execution result output by the model and corresponding to the analyzed operation instruction, and sends the execution result to the web client;
in this embodiment, the second processing unit 13 is configured to display the execution result received by the web client on the browser interface.
In this embodiment, the receiving unit 11 is further configured to receive, through the browser interface, a user name and a password input by a user.
In this embodiment, the apparatus further comprises: and a third processing unit.
In this embodiment, the third processing unit is configured to send the user name and the password to the web server through network communication, so that the web server performs user authentication, and if the user authentication passes, the receiving unit 11 executes the step of receiving, through a browser interface of the web client, an operation instruction corresponding to the oil refining apparatus input by the user.
In this embodiment, the second processing unit 13 is specifically configured to display the execution result in a table manner, or display the execution result in a graphic manner, or display the execution result in a manner of generating a reaction network in an output window of the browser interface.
In this embodiment, the second processing unit 13 is specifically configured to display the execution result in a manner of generating a two-dimensional reaction network.
In this embodiment, the second processing unit 13 is specifically configured to display the execution result in a manner of generating a three-dimensional reaction network.
In this embodiment, the second processing unit 13 is specifically configured to display one or more of a molecular composition, a structure of each single molecule in the molecular composition, a content of each single molecule, a physical property of each single molecule, or a content of each single molecule.
In this embodiment, the apparatus further comprises: and the control unit is used for displaying the selectable operation instruction and the corresponding control in an operation instruction input window of the browser interface for the user to select and use.
In the present embodiment, the operation instruction includes an instruction type and an instruction content.
In this embodiment, the instruction types include button clicks, screen slides, auxiliary flips, rotation zoom, and text entry.
In this embodiment, the model comprises a product prediction model.
In this embodiment, the first processing unit 12 is specifically configured to query a molecule composition database, and use molecule composition data corresponding to the analyzed operation instruction in the molecule composition database as the execution result output by the product prediction model; wherein the molecular composition database comprises: obtaining a molecular composition of the crude oil of the refinery; according to the physical properties of each single molecule in the molecular composition of the crude oil, obtaining the molecular composition of different fractions obtained by distilling the crude oil; according to the preset raw material proportion, respectively inputting the corresponding fractions as oil refining raw materials into corresponding product prediction models of an oil refining device to obtain the molecular composition of the corresponding prediction products and the content of each single molecule in the prediction products; and blending each predicted product serving as a product blending raw material according to a preset rule set to obtain the molecular composition of a plurality of groups of mixtures and the content of each single molecule in the mixtures.
In this embodiment, the first processing unit 12 is specifically configured to establish a product prediction model; acquiring sample raw material information of sample raw materials; training the reaction rule set by using the sample raw material information, and fixing the trained reaction rule set; training the reaction rate algorithm by using the sample raw material information, and fixing the trained reaction rate algorithm to obtain the trained product prediction model, wherein the product prediction model comprises: a reaction rule set of a plurality of reaction rules and a reaction rate algorithm.
In this embodiment, the sample material information of the sample material includes: the molecular composition of the sample raw material, the molecular content of each molecule in the sample raw material, the molecular composition of an actual product corresponding to the sample raw material and the actual content of each molecule in the actual product.
In this embodiment, the first processing unit 12 is specifically configured to process the molecular composition of the sample raw material according to a preset reaction rule set, so as to obtain a reaction path corresponding to each molecule in the molecular composition of the sample raw material; obtaining a first molecular composition of a device product according to a reaction path corresponding to each molecule in the molecular composition of the sample raw material; in the device product, comprising: the sample feedstock, intermediate product, and predicted product; calculating a first relative deviation from a first molecular composition of the device product and a second molecular composition of the actual product; if the first relative deviation meets a preset condition, fixing the reaction rule set; and if the first relative deviation does not accord with the preset condition, adjusting the reaction rule in the reaction rule set, and recalculating the first relative difference value according to the adjusted reaction rule set until the first relative deviation accords with the preset condition.
In this embodiment, the first processing unit 12 is specifically configured to obtain a kind of a single molecule in the first molecular composition to form a first set; acquiring the species of single molecules in the second molecular composition to form a second set; determining whether the second set is a subset of the first set; if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as the first relative deviation value; if the second set is a subset of the first set, calculating a first relative deviation by:
wherein x is1Is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the sample material, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
In this embodiment, the first processing unit 12 is specifically configured to calculate, according to the reaction rate algorithm, the reaction rate of the reaction path corresponding to each molecule in the molecular composition of the sample raw material; obtaining the predicted content of each molecule in the predicted product corresponding to the sample raw material according to the molecular content of each molecule in the sample raw material and the reaction rate corresponding to the reaction path of the molecule; calculating a second relative deviation according to the predicted content of each molecule in the predicted product and the actual content of each molecule in the actual product; if the second relative deviation meets a preset condition, fixing the reaction rate algorithm; and if the second relative deviation does not accord with the preset condition, adjusting parameters in the reaction rate algorithm, and recalculating the second relative deviation according to the adjusted reaction rate algorithm until the second relative deviation accords with the preset condition.
In this embodiment, the first processing unit 12 is specifically configured to calculate a reaction rate of each reaction path according to a reaction rate constant in the reaction rate algorithm; wherein the content of the first and second substances,
determining the reaction rate constant according to the following calculation formula:
wherein k is a reaction rate constant, kBBoltzmann constant, h is planckian constant, R is ideal gas constant, E is temperature value of environment where reaction path is located, exp is exponential function with natural constant as base, Δ S is entropy change before and after reaction corresponding to reaction rule corresponding to reaction path, Δ E is reaction energy barrier corresponding to reaction rule corresponding to reaction path,
and the catalyst activity factor, P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path.
In this embodiment, the model includes: and (4) a physical property calculation model.
In this embodiment, the first processing unit 12 is configured to query a physical property parameter database, and use physical property data corresponding to the analyzed operation instruction in the physical property parameter database as an execution result output by the physical property calculation model; wherein the physical property parameter database comprises: physical properties of various single molecules in the molecular composition of the crude oil of the oil refinery; physical properties of the mixture.
In the present embodiment, the first processing unit 12 is configured to calculate, for each single molecule in the mixture, the physical property of the single molecule based on the number of groups of each group constituting the single molecule and a contribution value of each group to the physical property; and calculating the physical properties of the mixture according to the physical properties of each single molecule in the mixture and the content of each single molecule in the mixture.
In this embodiment, the apparatus further comprises: the template monomolecular physical property matching unit is used for comparing the group quantity of each group forming the monomolecular with the pre-stored molecular information of the template monomolecular with known physical properties in a second database; wherein the molecular information comprises: the number of groups of each group constituting a single molecule of the template; judging whether a template single molecule identical to the single molecule exists; if a template monomolecular identical to the monomolecular exists, outputting the physical property of the template monomolecular as the physical property of the monomolecular; and if the template single molecule identical to the single molecule does not exist, calculating the physical property of the single molecule.
In the present embodiment, the first processing unit 12 is specifically configured to obtain, for each single molecule in the mixture, the number of groups of each group constituting the single molecule, and obtain a contribution value of each group to the physical property; inputting the number of groups of each group forming the single molecule and the contribution value of each group to the physical property into a physical property calculation model trained in advance, and acquiring the physical property of the single molecule output by the physical property calculation model; wherein the physical property calculation model is used for calculating the physical property of the single molecule according to the number of groups of each group contained in the single molecule and the contribution value of each group to the physical property.
In this embodiment, the apparatus further comprises: a model training unit for acquiring, for each single molecule in the mixture, the number of groups of each group constituting the single molecule, and acquiring a contribution value of each group to a physical property; inputting the number of groups of each group forming the single molecule and the contribution value of each group to the physical property into a physical property calculation model trained in advance, and acquiring the physical property of the single molecule output by the physical property calculation model; wherein the physical property calculation model is used for calculating the physical property of the single molecule according to the number of groups of each group contained in the single molecule and the contribution value of each group to the physical property.
In this embodiment, the model training unit is specifically configured to establish a physical property calculation model as follows:
wherein f is the physical property of the single molecule, and n isiNumber of groups of i-th group,. DELTA.fiThe value of contribution of the i-th group to the physical property, and a is a correlation constant.
In this embodiment, the model training unit is specifically configured to use all groups constituting a single molecule as primary groups; a plurality of groups which exist simultaneously and contribute to the common existence of the same physical property are used as a multi-stage group, and the number of the plurality of groups is used as the level of the multi-stage group.
In this embodiment, the model training unit is specifically configured to establish a physical property calculation model as follows:
wherein f is a physical property of a single molecule, and m is1iIs the radical number of the ith radical in the primary radical of the said single molecule,. DELTA.f1iIs the contribution value of the ith group in the primary group of the single molecule to the physical property; m is2jIs the radical number of the jth radical in the secondary radical of the said single molecule,. DELTA.f2jIs the contribution value of the jth group in the secondary group of the single molecule to the physical property; m isNlIs the radical number of the I group in the N-th order of the said single molecule,. DELTA.fNlIs the contribution value of the I group in the N-grade groups of the single molecule to the physical property; n is a positive integer greater than or equal to 2; a is a correlation constant.
In this embodiment, the model training unit is specifically configured to use all groups constituting a single molecule as primary groups; a plurality of groups which exist simultaneously and contribute to the common existence of the same physical property are used as a multi-stage group, and the number of the plurality of groups is used as the level of the multi-stage group.
In this embodiment, the first processing unit 12 is specifically configured to calculate the boiling point of the single molecule according to the following physical property calculation model:
wherein T is the boiling point of the single molecule, SOL is the monomolecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP11GROUP is a first contribution vector converted according to the contribution of each primary GROUP of the single molecule to the boiling point12GROUP is a second contribution vector converted according to the contribution of each secondary GROUP of the single molecule to the boiling point1NThe N contribution value vector is obtained by converting the contribution value of each N-grade group of the single molecule to the boiling point; numh is the number of atoms in the single molecule except hydrogen atoms; b is a first preset constant, c is a second preset constant, and d is a third preset constant; and N is a positive integer greater than or equal to 2.
In this embodiment, the first processing unit 12 is specifically configured to calculate the density of the single molecule according to the following physical property calculation model:
wherein D is the density of the single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP21GROUP is the vector of N +1 contribution converted from the contribution of the primary GROUP to the density22GROUP is the vector of N +2 contribution converted from the contribution of secondary GROUPs to the density2NThe vector of the 2N contribution value is obtained by converting the contribution value of the N-grade group to the density, and e is a fourth preset constant; and N is a positive integer greater than or equal to 2.
In this embodiment, the first processing unit 12 is specifically configured to calculate the octane number of the single molecule according to the following physical property calculation model:
X＝SOL×GROUP31+SOL×GROUP32+……+SOL×GROUP3N+h；
wherein X is the octane number of the single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP31GROUP is the 2N +1 contribution vector obtained by converting the contribution of each primary GROUP of the single molecule to the octane number respectively32GROUP is the 2N +2 contribution vector obtained by converting the contribution of each secondary GROUP of the single molecule to the octane number respectively3NThe 3N contribution value vector is obtained by converting the contribution value of each N-grade group of the single molecule to the octane number; n is a positive integer greater than or equal to 2; h is a fifth predetermined constant.
Physical properties of the mixture include: density, cloud point, pour point, aniline point, and octane number.
In this embodiment, the first processing unit 12 is specifically configured to calculate the density of the mixture according to the following calculation formula:
density＝∑(Di×xi_volume)；
wherein density is the density of the mixture, DiDensity of the i-th single molecule, xi_volumeThe content of the i-th single molecule.
In this embodiment, the first processing unit 12 is specifically configured to calculate a cloud point contribution value of each single molecule according to the density and the boiling point of the single molecule; calculating the cloud point of the mixture based on the cloud point contribution of each single molecule in the mixture and the amount of each single molecule in the mixture.
In this embodiment, the first processing unit 12 is specifically configured to calculate a pour point contribution value of each single molecule according to the density and molecular weight of the single molecule; the pour point of the mixture is calculated based on the pour point contribution value of each single molecule in the mixture and the amount of each single molecule in the mixture.
In this embodiment, the first processing unit 12 is specifically configured to calculate an aniline point contribution value of each single molecule according to the density and boiling point of the single molecule; and calculating the aniline point of the mixture according to the aniline point contribution value of each single molecule in the mixture and the content of each single molecule in the mixture.
In this embodiment, the first processing unit 12 is specifically configured to calculate the octane number of the mixture according to the following calculation formula:
wherein ON is the octane number of the mixture, HISQFG is a molecular set, H is a molecular set of normal paraffin, I is a molecular set of isoparaffin, S is a molecular set of cycloparaffin, Q is a molecular set of olefin, F is a molecular set of aromatic hydrocarbon, G is a molecular set of oxygen-containing compound, and upsilon isiIs the content of each molecule in the mixture; upsilon isH、υI、υS、υQ、υF、υGRespectively the total content of normal paraffin, the total content of isoparaffin, the total content of cyclane, the total content of olefin, the total content of aromatic hydrocarbon and the total content of oxygen-containing compound in the mixture; beta is aiA regression parameter for each molecule in the mixture; ONiAn octane number for each molecule in the mixture; cHRepresenting the interaction coefficient of the normal alkane with other molecules; cIRepresenting the interaction coefficient of the isoparaffin with other molecules; cSRepresenting the coefficient of interaction of cycloalkanes with other molecules; cQRepresenting the coefficient of interaction of the olefin with other molecules; cFRepresenting the interaction coefficient of the aromatic hydrocarbon with other molecules; cGRepresenting the interaction coefficient of the oxygen-containing compound and other molecules;
a first constant coefficient between the normal paraffin and the isoparaffin,
A first constant coefficient between n-alkane and cycloalkane,
A first constant coefficient between the normal paraffin and the olefin,
A first constant coefficient between n-alkane and aromatic hydrocarbon,
A first constant coefficient between the normal alkane and the oxygen-containing compound,
A first constant coefficient between isoparaffin and cycloalkane,
Means for indicating differentA first constant coefficient between the constituent alkane and the alkene,
A first constant coefficient between isoparaffin and aromatic hydrocarbon,
A first constant coefficient between the isoparaffin and the oxygen-containing compound,
A first constant coefficient between a cycloalkane and an olefin,
A first constant coefficient between a cycloalkane and an aromatic hydrocarbon,
A first constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A first constant coefficient between olefin and aromatic hydrocarbon,
A first constant coefficient between the olefin and the oxygen-containing compound,
A first constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound,
A second constant coefficient between the normal paraffin and the isoparaffin,
A second constant coefficient between n-alkane and cycloalkane,
A second constant coefficient between the normal paraffin and the olefin,
A second constant coefficient between the normal paraffin and the aromatic hydrocarbon,
A second constant coefficient between the normal alkane and the oxygen-containing compound,
A second constant coefficient between isoparaffin and cycloalkane,
A second constant coefficient between the isoparaffin and the olefin,
A second constant coefficient between isoparaffin and aromatic hydrocarbon,
A second constant coefficient between the isoparaffin and the oxygen-containing compound,
A second constant coefficient between cycloalkane and olefin,
A second constant coefficient between the cycloalkane and the aromatic hydrocarbon,
A second constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A second constant coefficient between olefin and aromatic hydrocarbon,
A second constant coefficient between the olefin and the oxygen-containing compound,
Represents a second constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound; wherein the octane number comprises: research octane number and motor octane number.
In this embodiment, the types of browsers of the web client include: IE. One or more of Chrome, Firefox, Safari or Opera.
In this embodiment, the categories of the web server include: apache, Nginx, Tomcat, or IIS.
In this embodiment, the oil refining apparatus includes: a single petroleum processing unit, a plurality of petroleum processing units, or a corresponding petroleum processing unit in a whole flow of oil refinery processing, the types of petroleum processing units including: catalytic cracker, delayed coking unit, residue hydrogenation unit, hydrocracking unit, diesel oil hydrogenation modification unit, diesel oil hydrogenation refining unit, gasoline hydrogenation refining unit, catalytic reforming unit and alkylation unit; wherein each petroleum processing plant corresponds to a set of reaction rules.
The embodiment provides an oil refining device simulation system based on a B/S framework. Fig. 3 and 4 are schematic diagrams of a simulation system of an oil refining device based on a B/S architecture according to an embodiment of the present invention.
In this embodiment, the oil refining device simulation system based on the B/S architecture includes, but is not limited to: a processor 310, a memory 320.
The processor 310 is configured to execute the B/S architecture based refinery simulation program stored in the memory 320 to implement the B/S architecture based refinery simulation method described above.
Specifically, the processor 310 is configured to execute the B/S architecture-based refinery apparatus simulation program stored in the memory 320 to implement the following steps: receiving an operation instruction corresponding to the oil refining device, which is input by a user, through a browser interface of the web client 210; sending the operation instruction to the web server 211 through network communication, so that the web server 211 analyzes the operation instruction, inputs the analyzed operation instruction into a pre-trained model, obtains an execution result output by the model and corresponding to the analyzed operation instruction, and sends the execution result to the web client 210; displaying the execution result received by the web client 210 on the browser interface.
The embodiment of the invention also provides a storage medium. The storage medium herein stores one or more programs. Among others, the storage medium may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, a hard disk, or a solid state disk; the memory may also comprise a combination of memories of the kind described above.
When the one or more programs stored in the storage medium are executable by the one or more processors, the above-described B/S architecture-based refinery apparatus simulation method is implemented.
Specifically, the processor is used for executing a B/S architecture-based oil refining device simulation program stored in the memory so as to realize the following steps: receiving an operation instruction corresponding to the oil refining device, which is input by a user, through a browser interface of a web client; sending the operation instruction to a web server through network communication so that the web server analyzes the operation instruction, inputting the analyzed operation instruction into a pre-trained model, acquiring an execution result output by the model and corresponding to the analyzed operation instruction, and sending the execution result to the web client; and displaying the execution result received by the web client on the browser interface.
The above description is only an example of the present invention, and is not intended to limit the present invention, and it is obvious to those skilled in the art that various modifications and variations can be made in the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (44)
1. A B/S architecture-based oil refining device simulation method is characterized by comprising the following steps:
receiving an operation instruction corresponding to the oil refining device, which is input by a user, through a browser interface of a web client;
sending the operation instruction to a web server through network communication so that the web server analyzes the operation instruction, inputting the analyzed operation instruction into a pre-trained model, acquiring an execution result output by the model and corresponding to the analyzed operation instruction, and sending the execution result to the web client;
and displaying the execution result received by the web client on the browser interface.
2. The method of claim 1, further comprising:
receiving a user name and a password input by a user through the browser interface;
and sending the user name and the password to the web server through network communication so as to enable the web server to carry out user identity authentication, and if the user identity authentication passes, executing the step of receiving an operation instruction which is input by a user and corresponds to the oil refining device through a browser interface of the web client.
3. The method of claim 1, wherein displaying the execution results received by the web client on the browser interface comprises:
and displaying the execution result in a table mode, or displaying the execution result in a graphic mode, or displaying the execution result in a reaction network generating mode in an output window of the browser interface.
4. The method of claim 3, wherein displaying the execution result in a manner to generate a reaction network comprises:
and displaying the execution result in a mode of generating a two-dimensional reaction network.
5. The method of claim 3, wherein displaying the execution result in a manner to generate a reaction network comprises:
and displaying the execution result in a mode of generating a three-dimensional reaction network.
6. The method of claim 4 or 5, wherein displaying the execution result in a manner of generating a reaction network comprises:
displaying one or more of the molecular composition, the structure of each single molecule in the molecular composition, the content of each single molecule, the physical properties of each single molecule, or the content of each single molecule.
7. The method of claim 1, further comprising:
and displaying selectable operation instructions and corresponding controls on an operation instruction input window of the browser interface for the user to select and use.
8. The method of claim 1, wherein the operation instruction comprises an instruction type and an instruction content.
9. The method of claim 8, wherein the command types include button clicks, screen slides, assisted screen flips, rotation zoom, and text entry.
10. The method of claim 1, wherein the model comprises a product prediction model, and the obtaining of the execution result output by the model corresponding to the parsed operation instruction comprises:
querying a molecular composition database, and taking molecular composition data corresponding to the analyzed operation instruction in the molecular composition database as the execution result output by the product prediction model; wherein the molecular composition database comprises: obtaining a molecular composition of the crude oil of the refinery; according to the physical properties of each single molecule in the molecular composition of the crude oil, obtaining the molecular composition of different fractions obtained by distilling the crude oil; according to the preset raw material proportion, respectively inputting the corresponding fractions as oil refining raw materials into corresponding product prediction models of an oil refining device to obtain the molecular composition of the corresponding prediction products and the content of each single molecule in the prediction products; and blending each predicted product serving as a product blending raw material according to a preset rule set to obtain the molecular composition of a plurality of groups of mixtures and the content of each single molecule in the mixtures.
11. The method of claim 10, wherein the step of training the product prediction model comprises:
establishing a product prediction model; wherein the product prediction model comprises: a reaction rule set of a plurality of reaction rules and a reaction rate algorithm;
acquiring sample raw material information of sample raw materials;
training the reaction rule set by using the sample raw material information, and fixing the trained reaction rule set;
and training the reaction rate algorithm by using the sample raw material information, and fixing the trained reaction rate algorithm to obtain the trained product prediction model.
12. The method of claim 11,
sample material information of the sample material includes: the molecular composition of the sample raw material, the molecular content of each molecule in the sample raw material, the molecular composition of an actual product corresponding to the sample raw material and the actual content of each molecule in the actual product.
13. The method of claim 12, wherein training the set of reaction rules using the sample material information comprises:
processing the molecular composition of the sample raw material according to a preset reaction rule set to obtain a reaction path corresponding to each molecule in the molecular composition of the sample raw material;
obtaining a first molecular composition of a device product according to a reaction path corresponding to each molecule in the molecular composition of the sample raw material; in the device product, comprising: the sample feedstock, intermediate product, and predicted product;
calculating a first relative deviation from a first molecular composition of the device product and a second molecular composition of the actual product;
if the first relative deviation meets a preset condition, fixing the reaction rule set;
and if the first relative deviation does not accord with the preset condition, adjusting the reaction rule in the reaction rule set, and recalculating the first relative difference value according to the adjusted reaction rule set until the first relative deviation accords with the preset condition.
14. The method of claim 13, wherein calculating a first relative deviation from a first molecular composition of the device product and a second molecular composition of the actual product comprises:
acquiring the types of single molecules in the first molecular composition to form a first set;
acquiring the species of single molecules in the second molecular composition to form a second set;
determining whether the second set is a subset of the first set;
if the second set is not the subset of the first set, acquiring a pre-stored relative deviation value which does not meet a preset condition as the first relative deviation value;
if the second set is a subset of the first set, calculating a first relative deviation by:
wherein x is1Is the first relative deviation, M is the first set, M1Is a collection of species compositions of single molecules in the molecular composition of the sample material, M2Is a collection of species constituents of a single molecule in the molecular composition of the intermediate product, M3For the second set, card represents the number of elements in the set.
15. The method of claim 12, wherein training the reaction rate algorithm using the sample feedstock information comprises:
respectively calculating the reaction rate of the reaction path corresponding to each molecule in the molecular composition of the sample raw material according to the reaction rate algorithm;
obtaining the predicted content of each molecule in the predicted product corresponding to the sample raw material according to the molecular content of each molecule in the sample raw material and the reaction rate corresponding to the reaction path of the molecule;
calculating a second relative deviation according to the predicted content of each molecule in the predicted product and the actual content of each molecule in the actual product;
if the second relative deviation meets a preset condition, fixing the reaction rate algorithm;
and if the second relative deviation does not accord with the preset condition, adjusting parameters in the reaction rate algorithm, and recalculating the second relative deviation according to the adjusted reaction rate algorithm until the second relative deviation accords with the preset condition.
16. The method of claim 15, wherein separately calculating the reaction rate of the reaction pathway corresponding to each molecule in the molecular composition of the sample material according to the reaction rate algorithm comprises:
calculating the reaction rate of each reaction path according to the reaction rate constant in the reaction rate algorithm; wherein the content of the first and second substances,
determining the reaction rate constant according to the following calculation formula:
wherein k is a reaction rate constant, kBBoltzmann constant, h is planckian constant, R is ideal gas constant, E is temperature value of environment where reaction path is located, exp is exponential function with natural constant as base, Δ S is entropy change before and after reaction corresponding to reaction rule corresponding to reaction path, Δ E is reaction energy barrier corresponding to reaction rule corresponding to reaction path,
and the catalyst activity factor, P is the pressure value of the environment where the reaction path is located, and alpha is the pressure influence factor corresponding to the reaction rule corresponding to the reaction path.
17. The method according to claim 1, wherein the model includes a physical property calculation model, and the obtaining of the execution result output by the model and corresponding to the analyzed operation instruction includes:
querying a physical property parameter database, and taking physical property data corresponding to the analyzed operation instruction in the physical property parameter database as an execution result output by the physical property calculation model; wherein the physical property parameter database comprises: physical properties of various single molecules in the molecular composition of the crude oil of the oil refinery; physical properties of the mixture.
18. The method of claim 17, wherein the method of calculating the physical properties of the mixture comprises:
calculating, for each single molecule in the mixture, physical properties of the single molecule from the number of groups of each group constituting the single molecule and a contribution value of the each group to the physical properties;
and calculating the physical properties of the mixture according to the physical properties of each single molecule in the mixture and the content of each single molecule in the mixture.
19. The method of claim 18, further comprising, prior to calculating the physical properties of the single molecule:
comparing the group number of each group forming the single molecule with the pre-stored molecular information of the template single molecule with known physical properties in a second database; wherein the molecular information comprises: the number of groups of each group constituting a single molecule of the template;
judging whether a template single molecule identical to the single molecule exists;
if a template monomolecular identical to the monomolecular exists, outputting the physical property of the template monomolecular as the physical property of the monomolecular;
and if the template single molecule identical to the single molecule does not exist, calculating the physical property of the single molecule.
20. The method according to claim 18 or 19, wherein the method for calculating the physical properties of the single molecule comprises:
for each single molecule in the mixture, obtaining the number of groups of each group constituting the single molecule, and obtaining a contribution value of each of the groups to physical properties;
inputting the number of groups of each group forming the single molecule and the contribution value of each group to the physical property into a physical property calculation model trained in advance, and acquiring the physical property of the single molecule output by the physical property calculation model; wherein the content of the first and second substances,
and the physical property calculation model is used for calculating the physical property of the single molecule according to the number of groups of each group contained in the single molecule and the contribution value of each group to the physical property.
21. The method of claim 20, wherein the step of training the property calculation model comprises:
constructing a physical property calculation model of a single molecule;
obtaining the number of groups of each group constituting a single molecule of the sample; the physical properties of the sample single molecules are known;
inputting the number of groups of each group contained in a single molecule of the sample into the physical property calculation model;
obtaining the predicted physical property of the sample single molecule output by the physical property calculation model;
if the deviation value between the predicted physical property and the known physical property is smaller than a preset deviation threshold value, determining that the physical property calculation model converges, acquiring a contribution value corresponding to each group in the converged physical property calculation model, and storing the contribution value as the contribution value of the group to the physical property;
if the deviation value between the predicted physical property and the known physical property is equal to or greater than the deviation threshold value, the contribution value corresponding to each group in the physical property calculation model is adjusted until the physical property calculation model converges.
22. The method of claim 21, wherein constructing a single-molecule computational model of physical properties comprises:
the following physical property calculation model is established:
wherein f is the physical property of the single molecule, and n isiNumber of groups of i-th group,. DELTA.fiThe value of contribution of the i-th group to the physical property, and a is a correlation constant.
23. The method of claim 21, wherein a primary group and a multi-stage group are defined among all groups of the single molecule; wherein the content of the first and second substances,
all groups constituting a single molecule are taken as primary groups;
a plurality of groups which exist simultaneously and contribute to the common existence of the same physical property are used as a multi-stage group, and the number of the plurality of groups is used as the level of the multi-stage group.
24. The method of claim 23,
the following physical property calculation model is established:
wherein f is a physical property of a single molecule, and m is1iIs the radical number of the ith radical in the primary radical of the said single molecule,. DELTA.f1iIs the contribution value of the ith group in the primary group of the single molecule to the physical property; m is2jIs the radical number of the jth radical in the secondary radical of the said single molecule,. DELTA.f2jIs the contribution value of the jth group in the secondary group of the single molecule to the physical property; m isNlIs the radical number of the I group in the N-th order of the said single molecule,. DELTA.fNlIs the contribution value of the I group in the N-grade groups of the single molecule to the physical property; n is a positive integer greater than or equal to 2; a is a correlation constant.
25. The method of claim 20 or 21, wherein said obtaining the number of groups per group constituting a single molecule of the sample comprises: defining primary and multi-order groups among all groups of said single molecule; wherein the content of the first and second substances,
all groups constituting a single molecule are taken as primary groups;
a plurality of groups which exist simultaneously and contribute to the common existence of the same physical property are used as a multi-stage group, and the number of the plurality of groups is used as the level of the multi-stage group.
26. The method of claim 25,
the physical properties of the single molecule include: the boiling point of a single molecule;
the calculating the physical properties of the single molecule comprises:
the boiling point of the single molecule was calculated according to the following physical property calculation model:
wherein T is the boiling point of the single molecule, SOL is the monomolecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP11GROUP is a first contribution vector converted according to the contribution of each primary GROUP of the single molecule to the boiling point12GROUP is a second contribution vector converted according to the contribution of each secondary GROUP of the single molecule to the boiling point1NThe N contribution value vector is obtained by converting the contribution value of each N-grade group of the single molecule to the boiling point; numh is the number of atoms in the single molecule except hydrogen atoms; b is a first preset constant, c is a second preset constant, and d is a third preset constant; and N is a positive integer greater than or equal to 2.
27. The method of claim 25,
the physical properties of the single molecule include: the density of the single molecule;
the calculating the physical properties of the single molecule comprises:
the density of the single molecule was calculated according to the following physical property calculation model:
wherein D is the density of the single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP21GROUP is the vector of N +1 contribution converted from the contribution of the primary GROUP to the density22GROUP is the vector of N +2 contribution converted from the contribution of secondary GROUPs to the density2NThe vector of the 2N contribution value is obtained by converting the contribution value of the N-grade group to the density, and e is a fourth preset constant; and N is a positive integer greater than or equal to 2.
28. The method of claim 25,
the physical properties of the single molecule include: the octane number of a single molecule;
the calculating the physical properties of the single molecule comprises:
the octane number of the single molecule was calculated according to the following physical property calculation model:
X＝SOL×GROUP31+SOL×GROUP32+......+SOL×GROUP3N+h；
wherein X is the octane number of the single molecule, SOL is a single molecular vector converted according to the number of GROUPs of each GROUP constituting the single molecule, GROUP31GROUP is a 2N +1 contribution vector converted from the contribution of the primary GROUP to the octane number32GROUP is a 2N +2 contribution vector converted from the contribution of the secondary GROUP to the octane number3NThe 3N contribution value vector is obtained by converting the contribution value of the N-grade group to the octane number; n is a positive integer greater than or equal to 2; h is a fifth predetermined constant.
29. The method of claim 17,
physical properties of the mixture include: density, cloud point, pour point, aniline point, and octane number.
30. The method of claim 29, wherein calculating the physical property of the mixture when the physical property of the mixture is density comprises:
the density of the mixture is calculated by the following calculation:
density＝∑(Di×xi_volume)；
wherein density is the density of the mixture, DiDensity of the i-th single molecule, xi_volumeThe content of the i-th single molecule.
31. The method of claim 29, wherein calculating the physical property of the mixture when the physical property of the mixture is a cloud point comprises:
calculating a cloud point contribution for each single molecule based on the density and boiling point of the single molecule;
calculating the cloud point of the mixture based on the cloud point contribution of each single molecule in the mixture and the amount of each single molecule in the mixture.
32. The method of claim 29, wherein calculating the physical property of the mixture when the physical property of the mixture is pour point comprises:
calculating a pour point contribution value for each single molecule based on the density and molecular weight of the single molecule;
the pour point of the mixture is calculated based on the pour point contribution value of each single molecule in the mixture and the amount of each single molecule in the mixture.
33. The method of claim 29, wherein calculating the physical property of the mixture when the physical property of the mixture is an aniline point comprises:
calculating the aniline point contribution value of each single molecule according to the density and boiling point of the single molecule;
and calculating the aniline point of the mixture according to the aniline point contribution value of each single molecule in the mixture and the content of each single molecule in the mixture.
34. The method of claim 29, wherein calculating the physical property of the mixture when the physical property of the mixture is octane number comprises:
the octane number of the mixture is calculated by the following calculation formula:
wherein ON is the octane number of the mixture, HISQFG is a molecular set, H is a molecular set of normal paraffin, I is a molecular set of isoparaffin, S is a molecular set of cycloparaffin, Q is a molecular set of olefin, F is a molecular set of aromatic hydrocarbon, G is a molecular set of oxygen-containing compound, and upsilon isiIs the content of each molecule in the mixture; upsilon isH、υI、υS、υQ、υF、υGRespectively the total content of normal paraffin, the total content of isoparaffin, the total content of cyclane, the total content of olefin, the total content of aromatic hydrocarbon and the total content of oxygen-containing compound in the mixture; beta is aiA regression parameter for each molecule in the mixture; ONiAn octane number for each molecule in the mixture; cHRepresenting the interaction coefficient of the normal alkane with other molecules; cIRepresenting the interaction coefficient of the isoparaffin with other molecules; cSRepresenting the coefficient of interaction of cycloalkanes with other molecules; cQRepresenting the coefficient of interaction of the olefin with other molecules; cFRepresents an aromatic hydrocarbonCoefficient of interaction with other molecules; cGRepresenting the interaction coefficient of the oxygen-containing compound and other molecules;
a first constant coefficient between the normal paraffin and the isoparaffin,
A first constant coefficient between n-alkane and cycloalkane,
A first constant coefficient between the normal paraffin and the olefin,
A first constant coefficient between n-alkane and aromatic hydrocarbon,
A first constant coefficient between the normal alkane and the oxygen-containing compound,
A first constant coefficient between isoparaffin and cycloalkane,
A first constant coefficient between the isoparaffin and the olefin,
A first constant coefficient between isoparaffin and aromatic hydrocarbon,
A first constant coefficient between the isoparaffin and the oxygen-containing compound,
A first constant coefficient between a cycloalkane and an olefin,
A first constant coefficient between a cycloalkane and an aromatic hydrocarbon,
A first constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A first constant coefficient between olefin and aromatic hydrocarbon,
A first constant coefficient between the olefin and the oxygen-containing compound,
A first constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound,
A second constant coefficient between the normal paraffin and the isoparaffin,
A second constant coefficient between n-alkane and cycloalkane,
A second constant coefficient between the normal paraffin and the olefin,
A second constant coefficient between the normal paraffin and the aromatic hydrocarbon,
A second constant coefficient between the normal alkane and the oxygen-containing compound,
A second constant coefficient between isoparaffin and cycloalkane,
A second constant coefficient between the isoparaffin and the olefin,
A second constant coefficient between isoparaffin and aromatic hydrocarbon,
A second constant coefficient between the isoparaffin and the oxygen-containing compound,
A second constant coefficient between cycloalkane and olefin,
A second constant coefficient between the cycloalkane and the aromatic hydrocarbon,
A second constant coefficient representing the ratio between the cycloalkane and the oxygen-containing compound,
A second constant coefficient between olefin and aromatic hydrocarbon,
A second constant coefficient between the olefin and the oxygen-containing compound,
Represents a second constant coefficient between the aromatic hydrocarbon and the oxygen-containing compound; wherein the octane number comprises: research octane number and motor octane number.
35. The method of any of claims 1-34, wherein the category of the browser of the web client comprises:
IE. One or more of Chrome, Firefox, Safari or Opera.
36. The method of any of claims 1-34, wherein the category of the web server comprises:
apache, Nginx, Tomcat, or IIS.
37. The process of any one of claims 1 to 34, wherein the oil refinery comprises:
a single petroleum processing unit, a plurality of petroleum processing units, or a corresponding petroleum processing unit in a whole flow of oil refinery processing, the types of petroleum processing units including:
catalytic cracker, delayed coking unit, residue hydrogenation unit, hydrocracking unit, diesel oil hydrogenation modification unit, diesel oil hydrogenation refining unit, gasoline hydrogenation refining unit, catalytic reforming unit and alkylation unit; wherein each petroleum processing plant corresponds to a set of reaction rules.
38. A refinery device simulation device based on B/S architecture, the device comprising:
the receiving unit is used for receiving an operation instruction which is input by a user and corresponds to the oil refining device through a browser interface of the web client;
the first processing unit is used for sending the operation instruction to a web server through network communication so that the web server can analyze the operation instruction, input the analyzed operation instruction into a pre-trained model, obtain an execution result output by the model and corresponding to the analyzed operation instruction, and send the execution result to the web client;
and the second processing unit is used for displaying the execution result received by the web client on the browser interface.
39. The refinery apparatus simulation device of claim 38, further comprising: a third processing unit;
the receiving unit is further used for receiving a user name and a password input by a user through the browser interface;
and the third processing unit is used for sending the user name and the password to the web server through network communication so as to enable the web server to perform user identity authentication, and if the user identity authentication passes, the third processing unit executes the step of receiving an operation instruction which is input by a user and corresponds to the oil refining device through a browser interface of the web client.
40. The oil refinery apparatus simulation device of claim 38, wherein the second processing unit is specifically configured to display the execution result in a tabular manner, or display the execution result in a graphical manner, or display the execution result in a manner of generating a reaction network in an output window of the browser interface.
41. The refinery apparatus of claim 38, wherein the model comprises a product prediction model;
the first processing unit is specifically configured to query a molecular composition database, and use molecular composition data corresponding to the analyzed operation instruction in the molecular composition database as the execution result output by the product prediction model; wherein the molecular composition database comprises: obtaining a molecular composition of the crude oil of the refinery; according to the physical properties of each single molecule in the molecular composition of the crude oil, obtaining the molecular composition of different fractions obtained by distilling the crude oil; according to the preset raw material proportion, respectively inputting the corresponding fractions as oil refining raw materials into corresponding product prediction models of an oil refining device to obtain the molecular composition of the corresponding prediction products and the content of each single molecule in the prediction products; and blending each predicted product serving as a product blending raw material according to a preset rule set to obtain the molecular composition of a plurality of groups of mixtures and the content of each single molecule in the mixtures.
42. The refinery apparatus simulation of claim 38, wherein the model comprises a physical property calculation model;
the first processing unit is specifically configured to query a physical property parameter database, and use physical property data corresponding to the analyzed operation instruction in the physical property parameter database as an execution result output by the physical property calculation model; wherein the physical property parameter database comprises: physical properties of various single molecules in the molecular composition of the crude oil of the oil refinery; physical properties of the mixture.
43. The oil refining device simulation system based on the B/S architecture is characterized by comprising a processor and a memory; the processor is configured to execute a B/S architecture based refinery simulation program stored in the memory to implement the B/S architecture based refinery simulation method according to any one of claims 1-37.
44. A storage medium storing one or more programs executable by one or more processors to implement the B/S architecture based refinery apparatus simulation method according to any one of claims 1 to 37.
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