CN116384165B - Ultra-relaxation processing method and device for enhancing computing efficiency and robustness - Google Patents
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Abstract
The application discloses a method and a device for processing ultra-relaxation for enhancing calculation efficiency and robustness, which aim at the problem that calculation is not converged due to large grid skewness in the flow field calculation process of the conventional SIMPLE algorithm, process at least part of items in a pressure correction equation to be determined, and process the pressure correction equation to be determined based on analysis of face vectors after that, so that the data processing effect is effectively improved.
Description
Technical Field
The application belongs to the field of simulation data processing research, and particularly relates to an ultra-relaxation processing method and device for enhancing calculation efficiency and robustness.
Background
In the related art, when a SIMPLE algorithm is adopted to solve low-speed flow in the process of processing simulation data, grid cells with large skewness are frequently encountered, and the grid cells can cause calculation to be unable to converge. To obtain a converged flow field, the grid cells with larger skewness must be subjected to secondary correction, which greatly increases the calculation time, reduces the calculation efficiency, and makes the data processing effect less ideal.
Disclosure of Invention
In order to solve the defects of the prior art, the application provides an ultra-relaxation processing method and device for enhancing the calculation efficiency and the robustness, and aims to solve the problem that the calculation is not converged due to large grid skewness in the flow field calculation process of the conventional SIMPLE algorithm, at least part of items in a pressure correction equation to be determined are processed, and then the pressure correction equation to be determined is processed based on the analysis of face vectors, so that the data processing effect is effectively improved.
The technical effects to be achieved by the application are realized by the following scheme:
in a first aspect, the present specification provides a method of ultra-relaxation processing for enhancing computational efficiency and robustness, the method comprising:
obtaining a model of a target body, wherein at least part of a flow field formed by the model is divided into a plurality of grid cells; one part of the grid cells is an inclined grid, and the other part is a non-inclined grid;
generating a calculation model of a target speed field for determining the actual speed of the fluid at all parts of the flow field based on a preset initial speed field and an initial pressure field;
establishing a pending pressure correction equation by adopting a calculation model of the target speed field; wherein the undetermined pressure correction equation represents a quantitative relationship between a diffusion term and the target velocity field; the diffusion term is used for representing the accumulated quantity of the pressure correction intermediate value along with the volume of the grid unit;
performing discrete processing on the diffusion term by adopting a divergence theorem to obtain an intermediate phase expressed by the surface of a grid unit;
decomposing the face vector to obtain a first target phase expressed by an edge vector of a grid unit;
substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation;
determining a target speed field and a target pressure field through a calculation result of the target pressure correction equation;
and carrying out data processing based on the target speed field and the target pressure field.
In an alternative embodiment of the present disclosure, substituting the first target phase into the pending pressure correction equation to obtain a target pressure correction equation includes:
performing relaxation treatment on the first target phase to obtain a second target phase;
substituting the second target phase into the undetermined pressure correction equation to obtain a target pressure correction equation.
In an alternative embodiment of the present description,
the undetermined pressure correction equation is:；
in the method, in the process of the application,representing the velocity field after momentum interpolation; />Representing a diffusion term; p' represents the pressure correction intermediate value.
In an alternative embodiment of the present description,
the intermediate phase is:；
wherein Γ is a constant coefficient, dV is a microcell volume, dA is a microcell area, f is each face of the grid unit,for the face vector, O is the current grid center point, and N is the adjacent cell center point.
In an alternative embodiment of the present description,
the first target phase is:；
in the method, in the process of the application,and->Respectively representing components of the face vector decomposed in different directions.
In an alternative embodiment of the present description,
the second target phase is:；
in the method, in the process of the application,representing the normal vector of the face.
In an alternative embodiment of the present specification, the target speed field and the target pressure field by calculating the target pressure correction equation include:
interpolation processing is carried out on the pressure correction intermediate value belonging to the outlet boundary surface, so as to obtain a pressure correction target value;
and obtaining a target speed field output by a calculation model of the target speed field based on the target pressure field obtained by correcting the target value according to the pressure.
In an alternative embodiment of the present description, generating a computational model of a target velocity field for determining an actual velocity of a fluid across a flow field based on a preset initial velocity field and an initial pressure field, comprises:
setting an initial velocity field and an initial pressure field;
and correcting the inclined grid as a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of the target velocity field expressed by the target pressure field.
In an alternative embodiment of the present specification, the target pressure field is calculated by the following formula:
wherein: p (P) * Is the target pressure field; p (P) *-1 Is the historical target pressure field obtained by the last iteration; p' is the pressure correction target value.
In an alternative embodiment of the present specification, the target velocity field is calculated by the following formula:
wherein: />Is the historical target speed field obtained in the last iteration; />Is a speed correction target value.
In an alternative embodiment of the present disclosure, determining the target velocity field and the target pressure field by calculating the target pressure correction equation includes:
taking a designated field obtained through the calculation result of the target pressure correction equation as an intermediate field; wherein the specified field is at least one of a pressure field and a velocity field;
judging whether the residual error of the intermediate field meets a preset residual error condition or not;
if yes, the intermediate field is used as a target pressure field or a target speed field; if not, continuing to execute the iteration processing for the intermediate field until the residual error of the intermediate field after the iteration processing meets the preset residual error condition.
In a second aspect, the present specification provides an apparatus for enhancing computational efficiency and robustness of a super relaxation process, for implementing the method in the first aspect, the apparatus comprising:
the model acquisition module is configured to: wherein at least part of the flow field formed by the model is divided into a plurality of grid cells; one part of the grid cells is an inclined grid, and the other part is a non-inclined grid;
a computational model generation module configured to: generating a calculation model of a target speed field for determining the actual speed of the fluid at all parts of the flow field based on a preset initial speed field and an initial pressure field;
the undetermined pressure correction equation establishment module is configured to: establishing a pending pressure correction equation by adopting a calculation model of the target speed field; wherein the undetermined pressure correction equation represents a quantitative relationship between a diffusion term and the target velocity field; the diffusion term is used for representing the accumulated quantity of the pressure correction intermediate value along with the volume of the grid unit;
an mesophase determination module configured to: performing discrete processing on the diffusion term by adopting a divergence theorem to obtain an intermediate phase expressed by the surface of a grid unit;
a first target phase determination module configured to: decomposing the face vector to obtain a first target phase expressed by an edge vector of a grid unit;
the target pressure correction equation determination module is configured to: substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation;
a target field determination module configured to: determining a target speed field and a target pressure field through a calculation result of the target pressure correction equation;
a data processing module configured to: and carrying out data processing based on the target speed field and the target pressure field.
In a third aspect, the present specification provides an electronic device comprising:
a processor; and
a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of the first aspect.
In a fourth aspect, the present description provides a computer-readable storage medium storing one or more programs, which when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method of the first aspect.
Drawings
In order to more clearly illustrate the embodiments of the application or the prior art solutions, the drawings which are used in the description of the embodiments or the prior art will be briefly described below, it being obvious that the drawings in the description below are only some of the embodiments described in the present application, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flowchart of a method for processing ultra-relaxation to enhance computing efficiency and robustness according to an embodiment of the present application;
FIG. 2 is a flow chart of a method of ultra-relaxation processing for enhancing computational efficiency and robustness in an alternative embodiment of the present application;
FIG. 3 is a schematic diagram of face-based decomposition in an embodiment of the present application;
FIG. 4 is a schematic diagram of an apparatus for enhancing computational efficiency and robustness of ultra-relaxation processing according to an embodiment of the present application;
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The application will be described in further detail below with reference to the drawings by means of specific embodiments. Wherein like elements in different embodiments are numbered alike in association. In the following embodiments, numerous specific details are set forth in order to provide a better understanding of the present application. However, one skilled in the art will readily recognize that some of the features may be omitted, or replaced by other elements, materials, or methods in different situations. In some instances, related operations of the present application have not been shown or described in the specification in order to avoid obscuring the core portions of the present application, and may be unnecessary to persons skilled in the art from a detailed description of the related operations, which may be presented in the description and general knowledge of one skilled in the art.
Furthermore, the described features, operations, or characteristics of the description may be combined in any suitable manner in various embodiments. Also, various steps or acts in the method descriptions may be interchanged or modified in a manner apparent to those of ordinary skill in the art. Thus, the various orders in the description and drawings are for clarity of description of only certain embodiments, and are not meant to be required orders unless otherwise indicated.
The numbering of the components itself, e.g. "first", "second", etc., is used herein merely to distinguish between the described objects and does not have any sequential or technical meaning. The term "coupled" as used herein includes both direct and indirect coupling (coupling), unless otherwise indicated.
The simulation data processing is based on a simulation theory, uses a computer system and physical effect equipment as tools, builds and runs a model according to a target body, and realizes and reforms a researched object, so that the simulation data processing is an information type selectable technology generated in the progress of an industrialized society to an informatization society.
Various non-limiting embodiments of the present application are described in detail below with reference to the attached drawing figures. A super relaxation processing method for enhancing the calculation efficiency and the robustness in the specification, as shown in fig. 1, comprises the following steps:
s100: a model of the target volume is acquired.
The model of the present specification shows the internal interface and the outlet boundary surface of the object. At least part of the flow field formed by the model is divided into a number of grid cells. One part of the grid cells is a tilted grid, and the other part is a non-tilted grid.
The model in this specification may be a CAD file, for example. The manner of acquisition in this step may be determined according to actual requirements. For example, the model may be obtained by file import, or may be obtained by modeling.
The object in this description is a component of which during operation there is an airflow through at least part of its structure. By way of example, the target may be an engine (e.g., an engine of an aircraft), a turbine, or the like. When the airflow passes through the target body, the space provided by the periphery and/or the interior of the target body for the airflow to flow is a flow field. The interface inside the flow field is an internal interface; the interface at which the gas flows out of the flow field is the outlet boundary surface.
The present specification does not limit the specific shape of the mesh unit, and the mesh unit may be tetrahedral, hexahedral, or the like, for example. In the same model, there may be grid cells of different shapes. It can be seen that a model divides a grid cell into a plurality of grid cells.
In an alternative embodiment of the present specification, the grid cells in the present specification are unstructured grids. Alternatively, a specific implementation of this step may be to import the grid cells that make up the model into a solver.
S102: based on the preset initial velocity field and initial pressure field, a computational model of a target velocity field is generated for determining the actual velocity of the fluid throughout the flow field.
In an alternative embodiment of the present description, the initial velocity field and/or the initial pressure field may be set upon triggering by a person; in another alternative embodiment of the present description, the initial velocity field and/or the initial pressure field is automatically set by the executing body of the present application.
Alternatively, the specific implementation manner of this step may be: setting an initial velocity field and an initial pressure field; and correcting the inclined grid as a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of the target velocity field expressed by the target pressure field.
The target pressure field in the specification is a pressure field actually adopted when data processing is performed, and the target pressure field has a certain difference compared with the initial pressure field. The target speed field in the present specification is a speed field actually used in data processing, and there is a certain difference between the target speed field and the initial speed field.
In this step, the target pressure field is not yet obtained, and the target pressure field may be characterized by a computational model of the target pressure field. The computational model in this specification can be characterized in terms of formulas. After the target pressure field is obtained in the subsequent step, the target velocity field can be further obtained based on the target pressure field.
In an alternative embodiment of the present disclosure, a SIMPLE algorithm may be used to calculate a momentum equation based on a given initial velocity field, initial pressure field, to obtain a computational model of the target velocity field.
In an alternative embodiment of the present description, the pre-processing of the grid cells is also performed before performing this step.
S104: and establishing a pending pressure correction equation by adopting a calculation model of the target speed field.
The undetermined pressure correction equation represents a quantitative relationship between a diffusion term and the target velocity field; the diffusion term is used to represent the cumulative amount of the pressure correction intermediate value P' with the volume of the grid cell.
From this step, the target pressure field needs to be obtained by calculation. The pending pressure correction equation in this step is used to output a pressure correction intermediate value.
S106: performing discrete processing on the diffusion term by adopting a divergence theorem to obtain an intermediate phase expressed by the surface of a grid unit;
s108: substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation.
S110: and determining a target speed field and a target pressure field through the calculation result of the target pressure correction equation.
In an alternative embodiment of the present disclosure, the pressure correction intermediate value associated with the outlet boundary surface is interpolated to obtain a pressure correction target value. And obtaining a target speed field output by a calculation model of the target speed field based on the target pressure field obtained by correcting the target value according to the pressure. Optionally, the pressure correction intermediate value is obtained by calculating the undetermined pressure correction equation. After the pressure correction intermediate value is obtained, it may be processed to obtain a pressure correction target value, and further a target pressure field is obtained based on the pressure correction target value. After the target pressure field is obtained, the calculation model of the target velocity field can be calculated based on the target pressure field, and the target velocity field can be obtained.
And carrying out discrete solution on the pressure correction equation to be determined according to the divergence theorem, so as to obtain a pressure correction intermediate value. And carrying out interpolation processing on the pressure correction intermediate value belonging to the outlet boundary surface to obtain a pressure correction target value. Based on the steps, the interpolation method on the outlet boundary is matched with the interpolation method of the internal interface in the momentum correction process, so that the values on the internal interface and the outlet boundary simultaneously consider the inclination correction of the grid, and the calculation accuracy is ensured.
S114: and carrying out data processing based on the target speed field and the target pressure field.
The data relating to the flow field can be processed by the method in the specification under the condition of permitting. By way of example, the data processed by the methods in this specification may be pneumatic data. In this specification, the process of generating the target velocity field and/or generating the target pressure field may also be regarded as a kind of data processing.
SIMPLE type algorithms solve for low flow, often encounter grid cells with large skewness, which can result in computation failure to converge. The main reason for the failure to converge is that interpolation is performed on the interface in the calculation process, and when the grid cells are inclined, the calculation error caused by the inclination of the grid cells is ignored by a general interpolation method.
According to the ultra-relaxation processing method for enhancing the calculation efficiency and the robustness, which is provided by the application, the interpolation method applied to the internal interface of the target body is matched with the interpolation method of the outlet boundary, so that the value on the internal interface and the value on the outlet boundary simultaneously consider the inclination correction of the grid, and the interpolated value is more fit. By adopting the method of the application, the data processing efficiency can be improved, the robustness can be improved, and the data processing effect can be further improved.
In addition, in some cases, especially at the position of the outlet boundary surface, interpolation is omitted, so that a large deviation exists between the interpolated value and the true value on the interface, and therefore, the flow field simulation cannot be converged. Since flow correction of the inlet and outlet is performed in the SIMPLE algorithm, the correction method mainly performs a specific process on the value of the outlet boundary surface, and thus the accuracy of the variable value on the outlet boundary surface is particularly important. In order to obtain a flow field with calculated convergence, it is necessary to perform tilt correction interpolation on grid cells with tilt, however, in general, tilt correction of interface interpolation is usually ignored, and even for values on the outlet boundary surface, values of the internal cells are duplicated without performing interface interpolation, so that abnormal values occur in numerical simulation.
At present, for the grid unit with inclination, interpolation at the outlet boundary surface is often ignored, so that the value of an internal interface and the value of the outlet boundary surface do not reach effective fit, the value after interpolation of the internal interface considers the inclination correction of the grid unit, but the value on the outlet boundary surface is not subjected to the inclination correction, the value deviation on the outlet boundary surface is larger in the flow correction process, the flow field calculation result is abnormal, the convergence cannot be well achieved, and the robustness is reduced.
According to the ultra-relaxation processing method for enhancing the calculation efficiency and the robustness, the interpolation method applied to the internal interface of the target body is matched with the interpolation method of the outlet boundary, so that the value on the internal interface and the value on the outlet boundary are simultaneously considered for grid inclination correction, and the interpolated value is more matched. By adopting the method of the application, the data processing efficiency can be improved, the robustness can be improved, and the data processing effect can be further improved.
To further increase robustness in the data processing process and improve the data processing effect, a further alternative embodiment of the present application will now be described, with an exemplary, at least partially alternative embodiment having a flow as shown in fig. 2.
Before describing alternative embodiments, several concepts are described.
SIMPLE algorithm: semi-Implicit Method for Pressure Linked Equations, a Semi-implicit algorithm that solves the pressure coupling equation.
SIMPLE type algorithm: based on the SIMPLE algorithm, and with corresponding improvement to the defects of the SIMPLE algorithm, a series of algorithms are generated, and the algorithms are collectively called as the SIMPLE algorithms.
Momentum equation: the SIMPLE algorithm solves the equation for the velocity field, which is derived from the principle of conservation of momentum of the fluid.
Pending pressure correction equation: the equation for solving the pressure correction value in the SIMPLE algorithm reflects the conservation of mass of the fluid.
Grid cell: because the partial differential equation set needs to be solved in calculating the flow field, the current method for solving the equation adopts a numerical solution, namely the whole calculation domain is discrete, and the continuous flow field is decomposed into a plurality of small units, namely grids.
Grid skewness: because the shape of the flow field in reality is irregular, grid cells with larger offset angles often appear when grids are divided, and the grid cells are scattered, so that the solving of the equation can be adversely affected, and the convergence of the equation is not facilitated. Such grid cells are also referred to as tilting grids.
Boundary conditions: the change rule of the solved variable or the derivative thereof along time and position on the boundary of the solving area is the precondition that the control equation has a definite solution. Region boundaries such as exit boundary surfaces.
Internal interface: refers to the law of variation of the solved variables or their derivatives over time and position over the non-boundaries of the solved area.
In an alternative embodiment, the above-described equation for the pending pressure correction is shown in equation (one) below.
Formula 1
The right end of equation (one) is the velocity field after momentum interpolation (i.e., the target velocity field). The left end of equation (one) is a diffusion term, which can be discretized according to the divergence theorem. The formulation of the intermediate phase obtained by the discrete processing in step S106 is as shown in the following formula (two).
Formula II
Wherein Γ is a constant coefficient, dV is a microcell volume, dA is a microcell area, f is each face of the grid unit,for the face vector, O is the current grid center point, and N is the adjacent cell center point. u is the velocity field after momentum interpolation, v is the gradient operator, and v is the divergence operator.
It should be noted that in some cases, the aforementioned target velocity field may be a known phase; in other cases, the target velocity field may need to be calculated to obtain the pending pressure correction equation. In the calculation process of the target speed field, speed interpolation on the unit surface is used, and if the interpolation is incorrect, the solving of the pressure value or the speed value can be caused to oscillate. Momentum interpolation of the updated velocity field can solve the problem of velocity interpolation.
As shown in FIG. 3, to improve the accuracy of the calculation, the face amounts of the grid cells can be decomposed, including. The formulation of the first target phase obtained through the discrete process in step S108 is as shown in the following formula (iii).
Formula (III)
The explicit discrete format (i.e., the first target phase) at the left end of equation (three) may be expressed as equation (four):
formula (IV)
Wherein P' is a pressure correction value, u is a velocity field after momentum interpolation, v is a gradient operator, v is a divergence operator, Γ is a constant coefficient, dV is a infinitesimal volume, dA is infinitesimal area, f is each face of a grid unit,for the face vector, O is the current grid center point, and N is the adjacent cell center point.
In order to avoid the problem of slow convergence of the calculation of the first target phase when the inclination of the grid cell is large, in a further alternative embodiment of the present disclosure, the first target phase shown in formula (four) is subjected to relaxation processing, and the obtained second target phase is shown in formula (five).
Formula (five)
In comparison with the first target phase, the second target phaseInstead of->This variation allows the dominant nature of the principal diagonal of the equation to be satisfied with a greater degree of tilting of the grid cells, and when the grid cells are not tilted, the equation is unchanged, and therefore the method solves the problem of poor robustness due to the grid cell tilting. Meanwhile, the calculated amount is not increased, and compared with the prior art, the method solves the problem and saves about half of calculation time.
In alternative embodiments of the present description, the process of determining the target pressure field and/or determining the target velocity field is an iterative calculation process.
The calculation formula of the target pressure field is shown as a formula (six):
wherein: p (P) * Is the target pressure field; p (P) *-1 Is the historical target pressure field obtained by the last iteration; p' is the pressure correction target value.
Alternatively, the pressure correction intermediate value belonging to the outlet boundary surface may be interpolated to obtain the pressure correction target value. And obtaining a target speed field output by a calculation model of the target speed field based on the target pressure field obtained by correcting the target value according to the pressure.
The calculation formula of the target speed field is shown as formula (seven):
formula (seven)
Wherein:is the historical target speed field obtained in the last iteration; />Is a speed correction target value.
Alternatively, the process of generating a computational model of the target velocity field may be: an initial velocity field and an initial pressure field are set. And correcting the inclined grid as a target, and performing momentum interpolation on the initial velocity field to obtain a calculation model of the target velocity field expressed by the target pressure field.
In an alternative embodiment, determining the target velocity field and the target pressure field from the calculation of the target pressure correction equation comprises: taking a designated field obtained through the calculation result of the target pressure correction equation as an intermediate field; wherein the specified field is at least one of a pressure field and a velocity field; judging whether the residual error of the intermediate field meets a preset residual error condition or not; if yes, the intermediate field is used as a target pressure field or a target speed field; if not, continuing to execute the iteration processing for the intermediate field until the residual error of the intermediate field after the iteration processing meets the preset residual error condition.
Based on the same concept, the embodiment of the present disclosure further provides a super relaxation processing apparatus for enhancing computing efficiency and robustness, which corresponds to a part of the process shown in fig. 1, as shown in fig. 4, and the apparatus includes:
the model acquisition module 400 is configured to: wherein at least part of the flow field formed by the model is divided into a plurality of grid cells; one part of the grid cells is an inclined grid, and the other part is a non-inclined grid;
a computational model generation module 402 configured to: generating a calculation model of a target speed field for determining the actual speed of the fluid at all parts of the flow field based on a preset initial speed field and an initial pressure field;
the pending pressure correction equation establishment module 404 is configured to: establishing a pending pressure correction equation by adopting a calculation model of the target speed field; wherein the undetermined pressure correction equation represents a quantitative relationship between a diffusion term and the target velocity field; the diffusion term is used for representing the accumulated quantity of the pressure correction intermediate value along with the volume of the grid unit;
the mesophase determination module 406 is configured to: performing discrete processing on the diffusion term by adopting a divergence theorem to obtain an intermediate phase expressed by the surface of a grid unit;
a first target phase determination module 408 configured to: decomposing the face vector to obtain a first target phase expressed by an edge vector of a grid unit;
the target pressure correction equation determination module 410 is configured to: substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation;
a target field determination module 412 configured to: determining a target speed field and a target pressure field through a calculation result of the target pressure correction equation;
a data processing module 414 configured to: and carrying out data processing based on the target speed field and the target pressure field.
In an alternative embodiment of the present disclosure, the target pressure correction equation determination module is specifically configured to: performing relaxation treatment on the first target phase to obtain a second target phase; substituting the second target phase into the undetermined pressure correction equation to obtain a target pressure correction equation.
In an alternative embodiment of the present specification, the undetermined pressure correction equation is:；
in the method, in the process of the application,representing the velocity field after momentum interpolation; />Representing a diffusion term; p' represents the pressure correction intermediate value.
In an alternative embodiment of the present specification, the mesophase is:；
wherein Γ is a constant coefficient, dV is a microcell volume, dA is a microcell area, f is each face of the grid unit,for the face vector, O is the current grid center point, and N is the adjacent cell center point.
In an alternative embodiment of the present specification, the first target phase is:；
in the method, in the process of the application,and->Respectively representing components of the face vector decomposed in different directions.
In the present descriptionIn an alternative embodiment of the disclosure, the second target phase is:；
in the method, in the process of the application,representing the normal vector of the face.
In an alternative embodiment of the present specification, the target pressure field is calculated by the following formula:
wherein: p (P) * Is the target pressure field; p (P) *-1 Is the historical target pressure field obtained by the last iteration; p' is the pressure correction target value.
In an alternative embodiment of the present specification, the target velocity field is calculated by the following formula:wherein: />Is the historical target speed field obtained in the last iteration; />Is a speed correction target value.
In an alternative embodiment of the present disclosure, the object field determination module is specifically configured to: taking a designated field obtained through the calculation result of the target pressure correction equation as an intermediate field; wherein the specified field is at least one of a pressure field and a velocity field; judging whether the residual error of the intermediate field meets a preset residual error condition or not; if yes, the intermediate field is used as a target pressure field or a target speed field; if not, continuing to execute the iteration processing for the intermediate field until the residual error of the intermediate field after the iteration processing meets the preset residual error condition.
One embodiment of the present application provides an electronic device. At the hardware level, the electronic device comprises a processor, optionally an internal bus, a network interface, a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, network interface, and memory may be interconnected by an internal bus, which may be an ISA (Industry Standard Architecture ) bus, a PCI (Peripheral ComponentInterconnect, peripheral component interconnect standard) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be classified as address buses, data buses, control buses, etc.
And the memory is used for storing programs. In particular, the program may include program code including computer-operating instructions. The memory may include memory and non-volatile storage and provide instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory to the memory and then runs the computer program, and a super relaxation processing method for enhancing the calculation efficiency and the robustness is formed on a logic level. The processor executes the program stored in the memory and is specifically used for executing any one of the above ultra-relaxation processing methods for enhancing the computing efficiency and the robustness.
The above-described ultra-relaxation processing method for enhancing the computing efficiency and the robustness disclosed in the embodiment of fig. 1 of the present application may be applied to a processor (i.e., a deletion control module in the present specification) or implemented by the processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (ApplicationSpecific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.
The electronic device may also execute a super relaxation processing method for enhancing the computing efficiency and robustness in fig. 1, and implement the functions of the embodiment shown in fig. 1, which is not described herein.
The embodiment of the application also provides a computer readable storage medium, which stores one or more programs, the one or more programs include instructions, which when executed by an electronic device including a plurality of application programs, enable the electronic device to execute a method for executing a super relaxation processing method for enhancing computational efficiency and robustness in the embodiment shown in fig. 1, and is specifically used for executing any one of the super relaxation processing methods for enhancing computational efficiency and robustness.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (7)
1. A method of ultra-relaxation processing for enhancing computational efficiency and robustness, the method comprising:
obtaining a model of a target body, wherein at least part of a flow field formed by the model is divided into a plurality of grid cells; one part of the grid cells is an inclined grid, and the other part is a non-inclined grid;
generating a calculation model of a target speed field for determining the actual speed of the fluid at all parts of the flow field based on a preset initial speed field and an initial pressure field;
establishing a pending pressure correction equation by adopting a calculation model of the target speed field; wherein the undetermined pressure correction equation represents a quantitative relationship between a diffusion term and the target velocity field; the diffusion term is used for representing the accumulated quantity of the pressure correction intermediate value along with the volume of the grid unit;
performing discrete processing on the diffusion term by adopting a divergence theorem to obtain an intermediate phase expressed by the surface of a grid unit;
decomposing the face vector to obtain a first target phase expressed by an edge vector of a grid unit;
substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation;
determining a target speed field and a target pressure field through a calculation result of the target pressure correction equation;
performing data processing based on the target speed field and the target pressure field;
substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation, wherein the method comprises the following steps: performing relaxation treatment on the first target phase to obtain a second target phase; substituting the second target phase into the undetermined pressure correction equation to obtain a target pressure correction equation;
the first target phase is:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->And->Respectively representing components obtained by decomposing the surface vector in different directions;
the second target phase is:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing a normal vector to the face; />Is a constant coefficient.
2. The method of claim 1, wherein,
the undetermined pressure correction equation is:；
in the method, in the process of the application,representing the velocity field after momentum interpolation; />Representing a diffusion term; p' represents the pressure correctionAnd (5) a value of the interval.
3. The method of claim 2, wherein,
the intermediate phase is:；
wherein dV is the infinitesimal volume, dA is the infinitesimal area, f is each face of the grid cell,for the face vector, O is the current grid center point, and N is the adjacent cell center point.
4. The method of claim 1, wherein the target pressure field is calculated by the following formula:
wherein: p (P) * Is the target pressure field; p (P) *-1 Is the historical target pressure field obtained by the last iteration; p' is the pressure correction target value.
5. The method of claim 4, wherein the target velocity field is calculated by the following formula:
wherein: />Is the historical target speed field obtained in the last iteration; />Is a speed correction target value.
6. The method of claim 5, wherein determining the target velocity field and the target pressure field from the calculation of the target pressure correction equation comprises:
taking a designated field obtained through the calculation result of the target pressure correction equation as an intermediate field; wherein the specified field is at least one of a pressure field and a velocity field;
judging whether the residual error of the intermediate field meets a preset residual error condition or not;
if yes, the intermediate field is used as a target pressure field or a target speed field; if not, continuing to execute the iteration processing for the intermediate field until the residual error of the intermediate field after the iteration processing meets the preset residual error condition.
7. An apparatus for ultra-relaxation processing for enhancing computational efficiency and robustness, said apparatus comprising:
the model acquisition module is configured to: wherein at least part of the flow field formed by the model is divided into a plurality of grid cells; one part of the grid cells is an inclined grid, and the other part is a non-inclined grid;
a computational model generation module configured to: generating a calculation model of a target speed field for determining the actual speed of the fluid at all parts of the flow field based on a preset initial speed field and an initial pressure field;
the undetermined pressure correction equation establishment module is configured to: establishing a pending pressure correction equation by adopting a calculation model of the target speed field; wherein the undetermined pressure correction equation represents a quantitative relationship between a diffusion term and the target velocity field; the diffusion term is used for representing the accumulated quantity of the pressure correction intermediate value along with the volume of the grid unit;
an mesophase determination module configured to: performing discrete processing on the diffusion term by adopting a divergence theorem to obtain an intermediate phase expressed by the surface of a grid unit;
a first target phase determination module configured to: decomposing the face vector to obtain a first target phase expressed by an edge vector of a grid unit;
the target pressure correction equation determination module is configured to: substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation;
a target field determination module configured to: determining a target speed field and a target pressure field through a calculation result of the target pressure correction equation;
a data processing module configured to: performing data processing based on the target speed field and the target pressure field;
substituting the first target phase into the undetermined pressure correction equation to obtain a target pressure correction equation, wherein the method comprises the following steps: performing relaxation treatment on the first target phase to obtain a second target phase; substituting the second target phase into the undetermined pressure correction equation to obtain a target pressure correction equation;
the first target phase is:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Andrespectively representing components obtained by decomposing the surface vector in different directions;
the second target phase is:the method comprises the steps of carrying out a first treatment on the surface of the In the method, in the process of the application,representing the normal vector of the face.
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