CN116151155B - Digital twinning-based urban combined overflow system flow monitoring method and system - Google Patents
Digital twinning-based urban combined overflow system flow monitoring method and system Download PDFInfo
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Abstract
The invention discloses a digital twinning-based urban combined overflow system flow monitoring method and system, comprising the following steps: a preset working condition table is planned; obtaining the structural size and hydraulic parameters of the target overflow device, and constructing a physical model and a numerical model; substituting the preset working condition into the model for testing to obtain flow data; placing the structural size, the hydraulic parameters, the flow data and the corresponding water level data into a hydrologic characteristic parameter data set; calculating coefficients under preset working conditions and representing physical quantities according to the data set; respectively summarizing coefficients and characterization physical quantities thereof under different outflow conditions, and fitting to obtain a coefficient fitting formula; substituting the fitting formula into a flow rate calculation formula to obtain an algorithm model; the system flow is calculated, so that the digital twin urban combined overflow system flow can be monitored with higher accuracy.
Description
Technical Field
The invention relates to the technical field of urban water environment treatment, in particular to a digital twin-based urban combined overflow system flow monitoring method and system.
Background
Along with the development of science and technology, the digital twin technology is used as a further leading edge technology following artificial intelligence and cloud computing, the implementation of the digital twin technology is based on the simulation prediction of a virtual space to a physical entity by a certain rule, the digital twin technology gradually extends from manufacturing industry to urban space, and the digital twin technology is closely connected with urban planning, construction and development to construct a digital twin city. The digital twin urban combined overflow (CSO) system bears the functions of collecting and discharging domestic sewage, industrial wastewater and rainwater; and when the water quantity transported in the rainy day exceeds the sewage receiving capacity of the pipe network, overflow occurs, and the ecological environment of the urban river and lake is affected.
China starts later in the aspect of CSO pollution research, and lacks basic monitoring data such as CSO overflow quantity, overflow frequency, overflow water quality and the like, so that a CSO pollution control target is difficult to determine. Currently, most people acquire CSO flow data through monitoring or simulation.
However, due to the influence of shortage of urban land resources, a large number of thin-wall weirs with special structures and overflow functions exist, due to the influence of urban land and engineering structures, conventional flow monitoring facilities are difficult to set, and cannot monitor the flow of a CSO system, so that CSO pollution control is more difficult, and a reliable and simple flow monitoring method is needed.
Disclosure of Invention
In view of the above, the embodiment of the invention provides a digital twinning-based urban combined overflow system flow monitoring method and system, which are used for solving the problem that the flow of the combined overflow system cannot be monitored because conventional flow monitoring facilities are difficult to set in the prior art.
The first aspect of the embodiment of the invention provides a digital twinning-based urban combined overflow system flow monitoring method, which comprises the following steps:
a preset working condition table is planned, wherein the preset working condition table comprises an upstream water head and a downstream water level;
obtaining the structural size and hydraulic parameters of a target overflow device, and constructing a physical model and a numerical model according to the structural size and the hydraulic parameters;
substituting an upstream water head and a downstream water level in a preset working condition table into a physical model and a numerical model to perform test and simulation to obtain flow data, and putting the structural size, the hydraulic parameters, the flow data and the corresponding upstream water head and downstream water level into a hydrologic characteristic parameter data set;
the method comprises the steps of acquiring data from a hydrological characteristic parameter data set, and calculating to obtain coefficients and characteristic physical quantities thereof under preset working conditions, wherein the coefficients comprise flow fitting coefficients under free outflow conditions, submerged fitting coefficients under submerged outflow conditions and reduction fitting coefficients under orifice outflow conditions; the characterization physical quantity comprises the inverse of Reynolds number, the inverse of Weber number, the difference between the upstream water head and the downstream water level, the difference between the upstream water head and the weir height, and the difference between the upstream water head and the upper edge elevation of the weir;
The coefficients and the characterization physical quantities thereof obtained by calculation under all preset working conditions under different outflow conditions are respectively summarized, and are subjected to function fitting by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, wherein the fitting formulas comprise a flow fitting coefficient fitting formula under the free outflow condition, a submerged fitting coefficient fitting formula under the submerged outflow condition and a reduction fitting coefficient fitting formula under the orifice outflow condition;
substituting coefficients under different outflow conditions into a flow calculation formula under the corresponding outflow conditions to obtain a flow algorithm model of the urban combined overflow system;
and inputting the downstream water data into a flow algorithm model of the urban combined overflow system, judging the outflow mode of the water flow passing through the weir according to the downstream water data, selecting a corresponding coefficient fitting formula according to different outflow modes, substituting the selected coefficient into a corresponding flow calculation formula, and calculating the flow of the urban combined overflow system.
It can be understood that the flow fitting coefficient fitting formula is a function of the flow fitting coefficient, namely the flow fitting coefficient for short; the fitting formula of the submerged fitting coefficient is a function of the submerged fitting coefficient, namely the submerged fitting coefficient is short for short; the formula of fitting the reduction fitting coefficient is a function of the reduction fitting coefficient, namely the reduction fitting coefficient for short.
As an improvement of the flow monitoring method of the urban combined overflow system based on digital twinning, the method further comprises the following steps:
the method comprises the steps of acquiring data from a hydrologic characteristic parameter data set, calculating to obtain a coefficient and a characteristic physical quantity thereof under a preset working condition, wherein the coefficient comprises a flow fitting coefficient under a free outflow condition, a submerged fitting coefficient under a submerged outflow condition, and a reduction fitting coefficient under an orifice outflow condition, and the steps of:
the method comprises the steps of (1) extracting structural data, hydraulic parameters and flow data of a physical model test and a numerical model simulation from hydrologic characteristic parameter data set, and corresponding upstream water head and downstream water level;
according to the fetched data, calculating to obtain a flow fitting coefficient under the free outflow condition, and inundating the fitting coefficient under the outflow condition, and reducing the fitting coefficient under the orifice outflow condition;
according to and />Obtaining a flow fitting coefficient characterization physical quantity;
according to and />Obtaining a submerged fitting coefficient representation physical quantity;
according to and />And obtaining the physical quantity of the reduced fitting coefficient representation.
wherein ,is the Reynolds number; />Is Weber number; />Is dynamic viscosity; />A water head is arranged on the weir; />Gravitational acceleration; Is surface tension; />Is the density; />The unit is rice; />Is the downstream water level, and the unit is meter; />The unit is rice; />The height of the upper edge of the weir crest is expressed in meters.
As an improvement of the flow monitoring method of the urban combined overflow system based on digital twinning, the method further comprises the following steps:
the method comprises the steps of respectively summarizing coefficients and characterization physical quantities thereof obtained by calculation under all preset working conditions under different outflow conditions, and performing function fitting on the coefficients by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, wherein the fitting formulas comprise flow fitting coefficient fitting formulas under free outflow conditions, submerged fitting coefficient fitting formulas under submerged outflow conditions, and the step of reducing fitting coefficient fitting formulas under orifice outflow conditions comprises the following steps:
summarizing coefficients obtained by calculation of the physical model and the numerical model under all preset working conditions under different outflow conditions and representing physical quantities thereof;
fitting coefficients corresponding to the three outflow conditions and the characterization physical quantity thereof respectively according to the different outflow conditions;
according to the coefficients and the characterization physical quantity thereof, randomly generating a series of function expressions related to the coefficients and the characterization physical quantity, taking the function expressions as the parents, sequencing the parents according to the fitness of the parents, wherein the fitness is a Nash efficiency coefficient, screening out a batch of parents by using a roulette algorithm, sequencing the parents again according to the fitness, and sequentially carrying out hybridization and mutation operations on the coefficients, the calculation functions and operators in each group of parents according to the sequencing result so as to output offspring after the current iterative operation;
Acquiring the fitness of the offspring output by the current iterative operation so as to judge whether the Nash efficiency coefficient of the offspring output by the current iterative operation is larger than 0.95;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is smaller than 0.95, defining the offspring output by the current iteration operation as a parent, and repeating the previous operation to perform the iteration operation;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is larger than 0.95, defining the offspring output by the current iteration operation as target offspring;
the obtained target daughter function is the selected flow fitting coefficient fitting formula, the submerged fitting coefficient fitting formula and the reduced fitting coefficient fitting formula.
As an improvement of the flow monitoring method of the urban combined overflow system based on digital twinning, the method further comprises the following steps: substituting the coefficient fitting formulas under different outflow conditions into the flow calculation formulas under different outflow conditions to obtain the urban combined overflow system flow algorithm model comprises the following steps:
substituting the fitted flow fitting coefficient, the inundation fitting coefficient and the reduction fitting coefficient into a flow calculation formula;
wherein ,flow for free outflow, +. >To drown out the flow of the outflow->The flow rate of the outlet flow is expressed in units of cubic meters per second; />The weir width is given in meters; />Fitting coefficients for the flow; />Fitting coefficients for inundation; />Fitting coefficients are reduced; />The height of the upper edge of the weir crest is in meters; />Gravitational acceleration; />The unit is meter for a water head on a weir; />The unit is square meter of box culvert cross section area; />Is the roughness rate; />The hydraulic radius is given in meters; />The water level difference is the upstream and downstream water level difference, and the unit is meter; />The length of the box culvert is in meters.
As an improvement of the flow monitoring method of the urban combined overflow system based on digital twinning, the method further comprises the following steps:
according to the formulaObtain->；
According to the formulaObtain->；
According to the formulaObtain->；
wherein ,simulating orifice outflow flow by using a numerical model; />For the thank you coefficient, the units are per meter per second.
As an improvement of the flow monitoring method of the urban combined overflow system based on digital twinning, the method further comprises the following steps:
the step of obtaining the structural size and the hydraulic parameter of the target overflow device and constructing a physical model and a numerical model according to the structural size and the hydraulic parameter comprises the following steps:
Measuring the length, width and height of a sewage disposal box culvert, key structure size, weir height of a thin-wall weir, weir width, weir thickness, weir corner angle, ground elevation data, box culvert bottom and top elevation data, thin-wall weir bottom elevation data, weir top edge elevation data and sluice chamber bottom and top elevation data;
the hydraulic parameters comprise dynamic viscosity, surface tension, roughness and water density;
building a physical model according to the geometric shrinkage of the structural size and the hydraulic parameters;
and inputting the structural size and hydraulic parameter data into CFD simulation software, and constructing a numerical model.
As an improvement of the flow monitoring method of the urban combined overflow system based on digital twinning, the method further comprises the following steps:
the method for obtaining the structural size and the hydraulic parameters of the target overflow device, and constructing a physical model and a numerical model according to the structural size and the hydraulic parameters further comprises the following steps:
and calibrating and verifying the numerical model by adjusting the hydraulic parameters in the numerical model.
The second aspect of the embodiment of the invention provides a digital twinning-based urban combined overflow system flow monitoring system, which comprises the following components:
the preset working condition module is used for planning a preset working condition table, and the preset working condition table comprises an upstream water head and a downstream water level;
The model building module is used for obtaining the structural size and the hydraulic parameter of the target overflow device and building a physical model and a numerical model according to the structural size and the hydraulic parameter;
the test and simulation module is used for substituting the upstream water head and the downstream water level in the preset working condition table into the physical model and the numerical model to perform test and simulation to obtain flow data, and putting the structural size, the hydraulic parameters, the flow data and the corresponding upstream water head and downstream water level into a hydrologic characteristic parameter data set;
the coefficient and the characteristic physical quantity acquisition module are used for acquiring data from the hydrological characteristic parameter data set, and calculating to obtain the coefficient and the characteristic physical quantity under a preset working condition, wherein the coefficient comprises a flow fitting coefficient under a free outflow condition, a submerged fitting coefficient under a submerged outflow condition and a reduced fitting coefficient under an orifice outflow condition;
the function fitting module is used for respectively summarizing the coefficients obtained by calculation under all preset working conditions under different outflow conditions and the characterization physical quantity thereof, and performing function fitting on the coefficients by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, wherein the fitting formulas comprise a flow fitting coefficient fitting formula under the free outflow condition, a submerged fitting coefficient fitting formula under the submerged outflow condition and a reduction fitting coefficient fitting formula under the orifice outflow condition;
The algorithm model building module is used for substituting the coefficient fitting formulas under different outflow conditions into the flow calculation formulas under different outflow conditions to obtain an urban combined overflow system flow algorithm model;
the algorithm model using module is used for inputting the downstream water data into the urban combined overflow system flow algorithm model, judging the outflow mode of the water flow passing through the weir according to the downstream water data, selecting the corresponding coefficient fitting formula according to different outflow modes, substituting the selected coefficient into the corresponding flow calculation formula, and calculating the urban combined overflow system flow.
A third aspect of the embodiment of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the terminal device, where the processor implements the steps of the digital twinning-based urban combined overflow system flow monitoring method provided in the first aspect when the processor executes the computer program.
A fourth aspect of the embodiments of the present invention provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the digital twin-based urban combined overflow system flow monitoring method provided by the first aspect.
The urban combined overflow system flow monitoring method and system based on digital twinning provided by the embodiment of the invention have the following beneficial effects: according to the method, the physical model and the numerical model are built according to the structural size and the hydraulic parameters of the actual overflow device through pre-planning working condition data, the preset working condition is tested and simulated through the two models, the coefficient is obtained according to the test and the simulation result of the two models, the algorithm model which can be used for monitoring the flow of the urban combined overflow system and has higher monitoring accuracy is further obtained, the conventional flow monitoring facilities are not required to be arranged, the problem that the flow of the combined overflow system cannot be monitored due to the fact that the conventional flow monitoring facilities are difficult to set in the conventional mode is solved, and monitoring with higher accuracy can be achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an implementation of a digital twinning-based urban combined overflow system flow monitoring method provided by an embodiment of the invention;
FIG. 2 is a fitted view of the free outflow of the urban combined overflow system flow monitoring method based on digital twinning provided by the embodiment of the invention;
FIG. 3 is a submerged outflow fitting chart of a digital twin-based urban combined overflow system flow monitoring method provided by the embodiment of the invention;
FIG. 4 is an orifice outflow fitting chart of a digital twinning-based urban combined overflow system flow monitoring method provided by an embodiment of the invention;
FIG. 5 is a block diagram of a flow monitoring system of an urban combined overflow system based on digital twinning, which is provided by the embodiment of the invention;
fig. 6 is a block diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is exemplary, with reference to the accompanying drawings, it being understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit the application.
The terms "first," second, "" third and the like in the description and in the claims and drawings are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprising," "including," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion. For example, a series of steps or elements may be included, or alternatively, steps or elements not listed or, alternatively, other steps or elements inherent to such process, method, article, or apparatus may be included.
Referring to fig. 1, fig. 1 shows a flowchart of an implementation of a flow monitoring method of an urban combined overflow system based on digital twinning according to an embodiment of the invention.
Step S10, a preset working condition table is drawn up, wherein the preset working condition table comprises an upstream water head and a downstream water level.
And S20, obtaining the structural size and the hydraulic parameters of the target overflow device, and constructing a physical model and a numerical model according to the structural size and the hydraulic parameters.
Specifically, the length, width and height of a sewage disposal box culvert, the critical structure size, the weir height of a thin-wall weir, the weir width, the weir thickness, the weir corner angle, ground elevation data, box culvert bottom and top elevation data, thin-wall weir bottom elevation data, weir top edge elevation data and sluice chamber bottom and top elevation data are measured.
The hydraulic parameters include dynamic viscosity, surface tension, roughness, and water density.
And building a physical model according to the geometric shrinkage and hydraulic parameters of the structural size of the target overflow device.
The structural size and hydraulic parameter data are input into CFD simulation software, a numerical model is built, the FLOW3D modeling software has a plurality of functions, and after the numerical model is built, the accuracy of the numerical model can be calibrated by adjusting parameters in the FLOW3D modeling software.
Specifically, after a physical model and a numerical model are built, a plurality of groups of experiments are carried out by using the physical model, experimental data are used as reference data for calibration, and parameters such as roughness, kinematic viscosity, surface tension and the like in the numerical model are adjusted to calibrate and verify the numerical model, so that the error of the physical model and the numerical model is less than 10%, and the calibration is successful.
By constructing the physical model and the numerical model, the method has the characteristics of intuitiveness of the physical model and high calculation accuracy of the numerical model.
And S30, substituting the upstream water head and the downstream water level in the preset working condition table into a physical model and a numerical model to perform test and simulation to obtain flow data, and putting the structural size, the hydraulic parameters, the flow data and the corresponding upstream water head and downstream water level into a hydrologic characteristic parameter data set.
Specifically, the upstream water head and the downstream water level in a preset working condition table are substituted into a physical model for experiment, and flow data in the physical model are measured.
And calculating to obtain an upstream water level difference and a downstream water level difference according to the upstream water head and the downstream water level, and obtaining flow data in a numerical model.
Step S40, data are called from the hydrologic characteristic parameter data set, and coefficients and the characteristic physical quantity thereof under preset working conditions are obtained through calculation, wherein the coefficients comprise flow fitting coefficients under free outflow conditions, submerged fitting coefficients under submerged outflow conditions and reduction fitting coefficients under orifice outflow conditions; the characterization physical quantity comprises the inverse of Reynolds number, the inverse of Weber number, the difference between the upstream water head and the downstream water level, the difference between the upstream water head and the height of the weir, and the difference between the upstream water head and the height of the upper edge of the weir.
Specifically, the upstream water head, the downstream water level, the flow data and the structural size are obtained from the hydrologic characteristic parameter data set in a calling mode, the coefficients under three outflow conditions are obtained through calculation, the upstream water head, the downstream water level, the flow data, the structural size and the hydraulic parameters are obtained from the hydrologic characteristic parameter data set in a calling mode, and the physical quantity representing the coefficients is obtained through calculation.
Wherein according to and />And obtaining the flow fitting coefficient characterization physical quantity.
According to and />Obtaining the characteristic physical quantity of the submerged fitting coefficient.
According to and />And obtaining the physical quantity of the reduced fitting coefficient representation.
The thin-wall weir with a special-shaped structure in the city is taken as a research object, and the obtained flow fitting coefficient and the characterization physical quantity under the free outflow condition are shown in the table 1:
the resulting submerged fitting coefficients and their characterization physical quantities under submerged outflow conditions are shown in table 2:
the resulting reduction fit coefficients and their characterization physical quantities under orifice outflow conditions are shown in table 3:
and S50, respectively summarizing the calculated coefficients and the characterization physical quantities thereof under all preset working conditions under different outflow conditions, and performing function fitting on the coefficients by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, wherein the fitting formulas comprise a flow fitting coefficient fitting formula under a free outflow condition, a submerged fitting coefficient fitting formula under a submerged outflow condition and a reduction fitting coefficient fitting formula under an orifice outflow condition.
It should be noted that, in the fitting of the present invention, a genetic algorithm is used to perform fitting, in the fitting of the genetic algorithm, a plurality of indexes can reflect the fitness, in the present invention, a nash efficiency coefficient is used to reflect the fitness, in the fitting, according to different outflow types, the coefficients corresponding to the three outflow types and their physical quantities are respectively fitted, and the specific process is as follows: summarizing coefficients obtained by calculation of the physical model and the numerical model under all preset working conditions under different outflow conditions and representing physical quantities thereof;
fitting coefficients corresponding to the three outflow conditions and the characterization physical quantity thereof respectively according to the different outflow conditions;
according to the coefficients and the characterization physical quantity thereof, randomly generating a series of function expressions related to the coefficients and the characterization physical quantity, taking the function expressions as the parents, sequencing the parents according to the fitness of the parents, wherein the fitness is a Nash efficiency coefficient, screening out a batch of parents by using a roulette algorithm, sequencing the parents again according to the fitness, and sequentially carrying out hybridization and mutation operations on the coefficients, the calculation functions and operators in each group of parents according to the sequencing result so as to output offspring after the current iterative operation;
acquiring the fitness of the offspring output by the current iterative operation so as to judge whether the Nash efficiency coefficient of the offspring output by the current iterative operation is larger than 0.95;
If the Nash efficiency coefficient of the offspring output by the current iteration operation is smaller than 0.95, defining the offspring output by the current iteration operation as a parent, and repeating the previous operation to perform the iteration operation;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is larger than 0.95, defining the offspring output by the current iteration operation as target offspring;
the obtained target daughter function is the selected flow fitting coefficient fitting formula, the submerged fitting coefficient fitting formula and the reduced fitting coefficient fitting formula.
Compared with the traditional optimization method (enumeration, heuristic and the like), the genetic algorithm takes biological evolution as a prototype, has good convergence, and has the advantages of less calculation time, high robustness and the like when the calculation precision is required.
The fitted images obtained from the contents of tables 1, 2 and 3 are shown in fig. 2, 3 and 4.
Referring to FIG. 2, the flow fitting coefficient fitting formula is about and />Expression of->，/>Is Reynolds number (Reynolds number)>Is dynamic viscosity>Is the water head on the weir, and (2)>，/>Is Weber number, & gt>Is surface tension>The density is that the scattered points are basically positioned on the fitting curved surface, the fitting effect is good, and the obtained flow fitting coefficient is as follows: ；
Wherein m is a flow fitting coefficient, 1/R e Is the inverse of Reynolds number, 1/W e Is the inverse of the weber number.
Referring to FIG. 3, the flooding fit coefficient fitting formula is about and />Expression of->Is an upstream water head, the unit is meter, < >>Is the downstream water level in meters, < >>For the weir height, the unit is meter, the scattered points can be seen to be basically positioned on the fitting curved surface, the fitting effect is good, and the obtained submerged fitting coefficient is as follows:the method comprises the steps of carrying out a first treatment on the surface of the Wherein, sigma s is a submerged fitting coefficient,reducing the downstream water level for the upstream water head, < > and>the upstream water head is reduced in weir height.
Referring to FIG. 4, the reduced fitting coefficient fitting formula is about and />Expression of->Is used as an upstream water head, and the water head is provided with a water inlet,the unit is meter (Japan fern)>Is the downstream water level in meters, < >>For the elevation of the upper edge of the weir crest, the unit is meter, the scattered points can be seen to be basically positioned on the fitting curved surface, the fitting effect is good, and the obtained reduction fitting coefficient is as follows:wherein phi is a reduced fitting coefficient, X 1 =h' -H is the upstream water level minus the downstream water level, X 2 =h' -e is the upstream water head relief slice upper edge elevation.
And S60, substituting coefficients under different outflow conditions into a flow calculation formula under the corresponding outflow conditions to obtain the urban combined overflow system flow algorithm model.
And substituting the fitted flow fitting coefficient fitting formula, the submerged fitting coefficient fitting formula and the reduction fitting coefficient fitting formula into a flow calculation formula to obtain the urban combined overflow system flow algorithm model.
The algorithm model is derived according to the following formula:
wherein ,flow for free outflow, +.>To drown out the flow of the outflow->The flow rate of the outlet flow is expressed in units of cubic meters per second; />Fitting coefficients for the flow; />Fitting coefficients for inundation; />To reduce the fitting coefficient.
Specifically, according to the formulaObtain->；
According to the formulaObtain->；
According to the formulaObtain->；
wherein ,using simulated orifice outflow in a numerical model; />For the thank you coefficient, the units are per meter per second.
Wherein the formula is and />Although the two calculation formulas are available, the orifice outflow flow actually measured through the physical model is combined in this way>In the same way, the orifice outflow flow in the ideal state with simulation in numerical model +.>The idea of the invention is a research feature of the invention, which is to obtain a reduction fitting coefficient reflecting the overcurrent flow of the nonstandard model.
And step S70, inputting the downstream water data into a flow algorithm model of the urban combined overflow system, judging the outflow mode of the water flow passing through the weir according to the downstream water data, selecting a corresponding coefficient fitting formula according to different outflow modes, substituting the selected coefficient into a corresponding flow calculation formula, and calculating the flow of the urban combined overflow system.
Specifically, when the flow of the digital twin city combined overflow system is to be monitored, the digital twin city combined overflow system data is input into an algorithm model, including the downstream water levelWeigao->Height of upper edge of weir>Fitting coefficient of flow->Width of weir->Acceleration of gravity->Water head on weir->Submerged fitting coefficient->Reducing fitting coefficient->Area of box culvert section->Roughness rate->Hydraulic radius->Difference of water level between upstream and downstream>Length of box culvert->Upstream water head->And the algorithm model can judge why the outflow condition is generated at the moment according to the input data, and substitutes the data into formulas corresponding to different outflow conditions to finally obtain corresponding flow under different outflow types, so that the calculation of the flow of the digital twin urban combined overflow system is realized.
Referring to fig. 5, fig. 5 is a block diagram of a flow monitoring system of an urban combined overflow system based on digital twinning according to an embodiment of the invention. In this embodiment, each module included in the digital twin-based urban combined overflow system flow monitoring system is used to execute each step in the embodiment corresponding to fig. 1. Refer specifically to fig. 1 and the description of the embodiment corresponding to fig. 1. For convenience of explanation, only a portion with the present embodiment is shown. Referring to fig. 5, the digital twin-based urban combined overflow system flow monitoring system comprises: a preset working condition module 10, a model building module 11, a test and simulation module 12, a coefficient and its characterization physical quantity acquisition module 13, a function fitting module 14, an algorithm model building module 15 and an algorithm model using module 16, wherein:
The preset working condition module 10 is used for planning a preset working condition table, and the preset working condition table comprises an upstream water head and a downstream water level.
The model building module 11 is used for obtaining the structural size and the hydraulic parameter of the target overflow device and building a physical model and a numerical model according to the structural size and the hydraulic parameter;
specifically, the length, width and height of a sewage disposal box culvert, the critical structure size, the weir height of a thin-wall weir, the weir width, the weir thickness, the weir corner angle, ground elevation data, box culvert bottom and top elevation data, thin-wall weir bottom elevation data, weir top edge elevation data and sluice chamber bottom and top elevation data are measured.
The hydraulic parameters include dynamic viscosity, surface tension, roughness, and water density.
And building a physical model according to the geometric shrinkage and hydraulic parameters of the structural size of the target overflow device.
The structural size and hydraulic parameter data are input into CFD simulation software, a numerical model is built, the FLOW3D modeling software has a plurality of functions, and after the numerical model is built, the accuracy of the numerical model can be calibrated by adjusting parameters in the FLOW3D modeling software.
Specifically, after a physical model and a numerical model are built, a plurality of groups of experiments are carried out by using the physical model, experimental data are used as reference data for calibration, and parameters such as roughness, kinematic viscosity, surface tension and the like in the numerical model are adjusted to calibrate and verify the numerical model, so that the error of the physical model and the numerical model is less than 10%, and the calibration is successful.
By constructing the physical model and the numerical model, the method has the characteristics of intuitiveness of the physical model and high calculation accuracy of the numerical model.
And the test and simulation module 12 is used for substituting the upstream water head and the downstream water level in the preset working condition table into the physical model and the numerical model to perform test and simulation to obtain flow data, and putting the structural size, the hydraulic parameters, the flow data and the corresponding upstream water head and downstream water level into a hydrologic characteristic parameter data set.
Specifically, the upstream water head and the downstream water level in a preset working condition table are substituted into a physical model for experiment, and flow data in the physical model are measured.
And calculating to obtain an upstream water level difference and a downstream water level difference according to the upstream water head and the downstream water level, and obtaining flow data in a numerical model.
The coefficient and its characteristic physical quantity obtaining module 13 is used for retrieving data from the hydrologic characteristic parameter data set, and calculating to obtain a coefficient under a preset working condition and its characteristic physical quantity, wherein the coefficient comprises a flow fitting coefficient under a free outflow condition, a submerged fitting coefficient under a submerged outflow condition, and a reduced fitting coefficient under an orifice outflow condition; the characterization physical quantity comprises the inverse of Reynolds number, the inverse of Weber number, the difference between the upstream water head and the downstream water level, the difference between the upstream water head and the height of the weir, and the difference between the upstream water head and the height of the upper edge of the weir.
Specifically, the upstream water head, the downstream water level, the flow data and the structural size are obtained from the hydrologic characteristic parameter data set in a calling mode, the coefficients under three outflow conditions are obtained through calculation, the upstream water head, the downstream water level, the flow data, the structural size and the hydraulic parameters are obtained from the hydrologic characteristic parameter data set in a calling mode, and the physical quantity representing the coefficients is obtained through calculation.
Wherein according to and />And obtaining the flow fitting coefficient characterization physical quantity.
According to and />Obtaining the characteristic physical quantity of the submerged fitting coefficient.
According to and />And obtaining the physical quantity of the reduced fitting coefficient representation.
The function fitting module 14 is configured to sum up the coefficients and the characterization physical quantities thereof calculated under all preset working conditions under different outflow conditions, and perform function fitting on the coefficients and the characterization physical quantities by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, where the fitting formulas include a flow fitting coefficient fitting formula under a free outflow condition, a submerged fitting coefficient fitting formula under a submerged outflow condition, and a reduced fitting coefficient fitting formula under an orifice outflow condition.
It should be noted that, in the fitting of the present invention, a genetic algorithm is used to perform fitting, in the fitting of the genetic algorithm, a plurality of indexes can reflect the fitness, in the present invention, a nash efficiency coefficient is used to reflect the fitness, in the fitting, according to different outflow types, the coefficients corresponding to the three outflow types and their physical quantities are respectively fitted, and the specific process is as follows: summarizing coefficients obtained by calculation of the physical model and the numerical model under all preset working conditions under different outflow conditions and representing physical quantities thereof;
Fitting coefficients corresponding to the three outflow conditions and the characterization physical quantity thereof respectively according to the different outflow conditions;
according to the coefficients and the characterization physical quantity thereof, randomly generating a series of function expressions related to the coefficients and the characterization physical quantity, taking the function expressions as the parents, sequencing the parents according to the fitness of the parents, wherein the fitness is a Nash efficiency coefficient, screening out a batch of parents by using a roulette algorithm, sequencing the parents again according to the fitness, and sequentially carrying out hybridization and mutation operations on the coefficients, the calculation functions and operators in each group of parents according to the sequencing result so as to output offspring after the current iterative operation;
acquiring the fitness of the offspring output by the current iterative operation so as to judge whether the Nash efficiency coefficient of the offspring output by the current iterative operation is larger than 0.95;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is smaller than 0.95, defining the offspring output by the current iteration operation as a parent, and repeating the previous operation to perform the iteration operation;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is larger than 0.95, defining the offspring output by the current iteration operation as target offspring;
the obtained target daughter function is the selected flow fitting coefficient fitting formula, the submerged fitting coefficient fitting formula and the reduced fitting coefficient fitting formula.
Compared with the traditional optimization method (enumeration, heuristic and the like), the genetic algorithm takes biological evolution as a prototype, has good convergence, and has the advantages of less calculation time, high robustness and the like when the calculation precision is required.
And the algorithm model building module 15 is used for substituting coefficients under different outflow conditions into flow calculation formulas under corresponding outflow conditions to obtain the urban combined overflow system flow algorithm model.
And substituting the fitted flow fitting coefficient fitting formula, the submerged fitting coefficient fitting formula and the reduction fitting coefficient fitting formula into a flow calculation formula to obtain the urban combined overflow system flow algorithm model.
The algorithm model is derived according to the following formula:
wherein ,flow for free outflow, +.>To drown out the flow of the outflow->The flow rate of the outlet flow is expressed in units of cubic meters per second; />Fitting coefficients for the flow; />Fitting coefficients for inundation; />To reduce the fitting coefficient.
Specifically, according to the formulaObtain->；
According to the formulaObtain->；
According to the formulaObtain->；
wherein ,using simulated orifice outflow in a numerical model; />For the thank you coefficient, the units are per meter per second.
Wherein the formula is and />Although the two calculation formulas are available, the orifice outflow flow actually measured through the physical model is combined in this way>In the same case, the simulated ideal state in the numerical model is usedLower orifice outflow flow->The idea of the invention is a research feature of the invention, which is to obtain a reduction fitting coefficient reflecting the overcurrent flow of the nonstandard model.
The algorithm model using module 16 is configured to input the downstream water data into the urban combined overflow system flow algorithm model, determine the outflow mode of the water flow passing through the weir according to the downstream water data, select a corresponding coefficient fitting formula according to different outflow modes, and substitute the selected coefficient into a corresponding flow calculation formula to calculate the urban combined overflow system flow.
Specifically, when the flow of the digital twin city combined overflow system is to be monitored, the digital twin city combined overflow system data is input into an algorithm model, including the downstream water levelWeigao->Height of upper edge of weir>Fitting coefficient of flow->Width of weir->Acceleration of gravity->Water head on weir->Submerged fitting coefficient->Reducing fitting coefficient- >Area of box culvert section->Roughness rate->Hydraulic radius->Difference of water level between upstream and downstream>Length of box culvert->Upstream water head->And the algorithm model can judge why the outflow condition is generated at the moment according to the input data, and substitutes the data into formulas corresponding to different outflow conditions to finally obtain corresponding flow under different outflow types, so that the calculation of the flow of the digital twin urban combined overflow system is realized.
Fig. 6 is a block diagram of a terminal device 6 according to another embodiment of the present invention. As shown in fig. 6, the terminal device 6 of this embodiment includes: a processor 60, a memory 61 and a computer program 62 stored in said memory 61 and executable on said processor 60, for example a program based on a digital twin urban combined overflow system flow monitoring method. The steps of the above-described embodiments of the digital twin-based urban combined overflow system flow monitoring method are implemented by the processor 60 when executing the computer program 62, for example, S10 to S70 shown in fig. 1.
Illustratively, the computer program 62 may be partitioned into one or more units that are stored in the memory 61 and executed by the processor 60 to complete the present invention. The one or more units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 62 in the terminal device 6. For example, the computer program 62 may be divided into a preset working condition module 10, a model building module 11, a test and simulation module 12, a coefficient and its characterization physical quantity obtaining module 13, a function fitting module 14, an algorithm model building module 15, and an algorithm model using module 16, where the specific functions of the modules are as described above.
The terminal device may include, but is not limited to, a processor 60, a memory 61. It will be appreciated by those skilled in the art that fig. 6 is merely an example of the terminal device 6 and does not constitute a limitation of the terminal device 6, and may include more or less components than illustrated, or may combine certain components, or different components, e.g., the terminal device may further include an input-output device, a network access device, a bus, etc.
The processor 60 may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 61 may be an internal storage unit of the terminal device 6, such as a hard disk or a memory of the terminal device 6. The memory 61 may be an external storage device of the terminal device 6, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 6. Further, the memory 61 may also include both an internal storage unit and an external storage device of the terminal device 6. The memory 61 is used for storing the computer program and other programs and data required by the terminal device. The memory 61 may also be used for temporarily storing data that has been output or is to be output.
Embodiments of the present invention also provide a computer readable storage medium storing a computer program which, when executed by a processor, is operable to:
a preset working condition table is planned, wherein the preset working condition table comprises an upstream water head and a downstream water level;
obtaining the structural size and hydraulic parameters of a target overflow device, and constructing a physical model and a numerical model according to the structural size and the hydraulic parameters;
substituting an upstream water head and a downstream water level in a preset working condition table into a physical model and a numerical model to perform test and simulation to obtain flow data, and putting the structural size, the hydraulic parameters, the flow data and the corresponding upstream water head and downstream water level into a hydrologic characteristic parameter data set;
the method comprises the steps of acquiring data from a hydrological characteristic parameter data set, and calculating to obtain coefficients and characteristic physical quantities thereof under preset working conditions, wherein the coefficients comprise flow fitting coefficients under free outflow conditions, submerged fitting coefficients under submerged outflow conditions and reduction fitting coefficients under orifice outflow conditions; the characterization physical quantity comprises the inverse of Reynolds number, the inverse of Weber number, the difference between the upstream water head and the downstream water level, the difference between the upstream water head and the height of the weir, and the difference between the upstream water head and the height of the upper edge of the weir.
The coefficients and the characterization physical quantities thereof obtained by calculation under all preset working conditions under different outflow conditions are respectively summarized, and are subjected to function fitting by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, wherein the fitting formulas comprise a flow fitting coefficient fitting formula under the free outflow condition, a submerged fitting coefficient fitting formula under the submerged outflow condition and a reduction fitting coefficient fitting formula under the orifice outflow condition;
substituting coefficients under different outflow conditions into a flow calculation formula under the corresponding outflow conditions to obtain a flow algorithm model of the urban combined overflow system;
and inputting the downstream water data into a flow algorithm model of the urban combined overflow system, judging the outflow mode of the water flow passing through the weir according to the downstream water data, selecting a corresponding coefficient fitting formula according to different outflow modes, substituting the selected coefficient into a corresponding flow calculation formula, and calculating the flow of the urban combined overflow system.
In the description of the present specification, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples.
It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application for the embodiment. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
Claims (7)
1. The utility model provides a city confluence system overflow system flow monitoring method based on digital twin, which is characterized in that the method includes:
A preset working condition table is planned, wherein the preset working condition table comprises an upstream water head and a downstream water level;
obtaining the structural size and hydraulic parameters of a target overflow device, and constructing a physical model and a numerical model according to the structural size and the hydraulic parameters;
substituting an upstream water head and a downstream water level in a preset working condition table into a physical model and a numerical model to perform test and simulation to obtain flow data, and putting the structural size, the hydraulic parameters, the flow data and the corresponding upstream water head and downstream water level into a hydrologic characteristic parameter data set;
the method comprises the steps of acquiring data from a hydrological characteristic parameter data set, and calculating to obtain coefficients and characteristic physical quantities under preset working conditions, wherein the coefficients comprise flow fitting coefficients under free outflow conditions, submerged fitting coefficients under submerged outflow conditions and reduction fitting coefficients under orifice outflow conditions; the characterization physical quantity comprises the inverse of Reynolds number, the inverse of Weber number, the difference between the upstream water head and the downstream water level, the difference between the upstream water head and the weir height, and the difference between the upstream water head and the upper edge elevation of the weir;
the method comprises the steps of (1) extracting structural data, hydraulic parameters and flow data of a physical model test and a numerical model simulation from hydrologic characteristic parameter data set, and corresponding upstream water head and downstream water level;
According to the fetched data, calculating to obtain a flow fitting coefficient under the free outflow condition, and inundating the fitting coefficient under the outflow condition, and reducing the fitting coefficient under the orifice outflow condition;
according to and />Obtaining a flow fitting coefficient characterization physical quantity;
according to and />Obtaining a submerged fitting coefficient representation physical quantity;
according to and />Obtaining a physical quantity representing the reduction fitting coefficient;
wherein ,is the Reynolds number; />Is Weber number; />Is dynamic viscosity; />A water head is arranged on the weir; />Gravitational acceleration; />Is surface tension; />Is the density; />The unit is rice; />Is the downstream water level, and the unit is meter; />The unit is rice; />The height of the upper edge of the weir crest is in meters;
the coefficients and the characterization physical quantities thereof obtained by calculation under all preset working conditions under different outflow conditions are respectively summarized, and are subjected to function fitting by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, wherein the fitting formulas comprise a flow fitting coefficient fitting formula under the free outflow condition, a submerged fitting coefficient fitting formula under the submerged outflow condition and a reduction fitting coefficient fitting formula under the orifice outflow condition;
summarizing coefficients obtained by calculation of the physical model and the numerical model under all preset working conditions under different outflow conditions and representing physical quantities thereof;
Fitting coefficients corresponding to the three outflow conditions and the characterization physical quantity thereof respectively according to the different outflow conditions;
according to the coefficients and the characterization physical quantity thereof, randomly generating a series of function expressions related to the coefficients and the characterization physical quantity, taking the function expressions as the parents, sequencing the parents according to the fitness of the parents, wherein the fitness is a Nash efficiency coefficient, screening out a batch of parents by using a roulette algorithm, sequencing the parents again according to the fitness, and sequentially carrying out hybridization and mutation operations on the coefficients, the calculation functions and operators in each group of parents according to the sequencing result so as to output offspring after the current iterative operation;
acquiring the fitness of the offspring output by the current iterative operation so as to judge whether the Nash efficiency coefficient of the offspring output by the current iterative operation is larger than 0.95;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is smaller than 0.95, defining the offspring output by the current iteration operation as a parent, and repeating the previous operation to perform the iteration operation;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is larger than 0.95, defining the offspring output by the current iteration operation as target offspring;
the obtained target daughter function is a selected flow fitting coefficient fitting formula, a submerged fitting coefficient fitting formula and a reduced fitting coefficient fitting formula;
Substituting coefficients under different outflow conditions into a flow calculation formula under the corresponding outflow conditions to obtain a flow algorithm model of the urban combined overflow system;
substituting the fitted flow fitting coefficient, the inundation fitting coefficient and the reduction fitting coefficient into a flow calculation formula;
wherein ,flow for free outflow, +.>To drown out the flow of the outflow->The flow rate of the outlet flow is expressed in units of cubic meters per second; />The weir width is given in meters; />Fitting coefficients for the flow; />Fitting coefficients for inundation; />Fitting coefficients are reduced;the height of the upper edge of the weir crest is in meters; />Gravitational acceleration; />The unit is meter for a water head on a weir; />The unit is square meter of box culvert cross section area; />Is the roughness rate; />The hydraulic radius is given in meters; />The water level difference is the upstream and downstream water level difference, and the unit is meter; />The length of the box culvert is in meters;
and inputting the downstream water data into a flow algorithm model of the urban combined overflow system, judging the outflow mode of the water flow passing through the weir according to the downstream water data, selecting a corresponding coefficient fitting formula according to different outflow modes, substituting the selected coefficient into a corresponding flow calculation formula, and calculating the flow of the urban combined overflow system.
2. The digital twinning-based urban combined overflow system flow monitoring method according to claim 1, further comprising:
according to the formulaObtain->；
According to the formulaObtain->；
According to the formulaObtain->；
wherein ,simulating orifice outflow flow by using a numerical model; />For the thank you coefficient, the units are per meter per second.
3. The method for monitoring the flow of the urban combined overflow system based on digital twinning according to claim 1, wherein the steps of obtaining the structural size and the hydraulic parameter of the target overflow device and constructing a physical model and a numerical model according to the structural size and the hydraulic parameter comprise:
measuring the length, width and height of a sewage disposal box culvert, key structure size, weir height of a thin-wall weir, weir width, weir thickness, weir corner angle, ground elevation data, box culvert bottom and top elevation data, thin-wall weir bottom elevation data, weir top edge elevation data and sluice chamber bottom and top elevation data;
the hydraulic parameters comprise dynamic viscosity, surface tension, roughness and water density;
building a physical model according to the geometric shrinkage of the structural size and the hydraulic parameters;
and inputting the structural size and hydraulic parameter data into CFD simulation software, and constructing a numerical model.
4. The method for monitoring the flow of the urban combined overflow system based on digital twinning according to claim 1, wherein the steps of obtaining the structural size and the hydraulic parameter of the target overflow device, constructing a physical model and a numerical model according to the structural size and the hydraulic parameter, and then:
and calibrating and verifying the numerical model by adjusting the hydraulic parameters in the numerical model.
5. Digital twinning-based urban combined overflow system flow monitoring system is characterized by comprising:
the preset working condition module is used for planning a preset working condition table, and the preset working condition table comprises an upstream water head and a downstream water level;
the model building module is used for obtaining the structural size and the hydraulic parameter of the target overflow device and building a physical model and a numerical model according to the structural size and the hydraulic parameter;
the test and simulation module is used for substituting the upstream water head and the downstream water level in the preset working condition table into the physical model and the numerical model to perform test and simulation to obtain flow data, and putting the structural size, the hydraulic parameters, the flow data and the corresponding upstream water head and downstream water level into a hydrologic characteristic parameter data set;
The coefficient and the characteristic physical quantity acquisition module are used for acquiring data from the hydrological characteristic parameter data set, and calculating to obtain the coefficient and the characteristic physical quantity under a preset working condition, wherein the coefficient comprises a flow fitting coefficient under a free outflow condition, a submerged fitting coefficient under a submerged outflow condition and a reduced fitting coefficient under an orifice outflow condition;
the method is particularly used for intensively extracting structural data, hydraulic parameters, flow data and corresponding upstream water head and downstream water level of a physical model test and a numerical model simulation from hydrologic characteristic parameter data;
according to the fetched data, calculating to obtain a flow fitting coefficient under the free outflow condition, and inundating the fitting coefficient under the outflow condition, and reducing the fitting coefficient under the orifice outflow condition;
according to and />Obtaining a flow fitting coefficient characterization physical quantity;
according to and />Obtaining a submerged fitting coefficient representation physical quantity;
according to and />Obtaining a physical quantity representing the reduction fitting coefficient;
wherein ,is the Reynolds number; />Is Weber number; />Is dynamic viscosity; />A water head is arranged on the weir; />Gravitational acceleration; />Is surface tension; />Is the density; />The unit is rice; />Is the downstream water level, and the unit is meter; / >The unit is rice; />The height of the upper edge of the weir crest is in meters;
the function fitting module is used for respectively summarizing the coefficients obtained by calculation under all preset working conditions under different outflow conditions and the characterization physical quantity thereof, and performing function fitting on the coefficients by using a genetic algorithm to obtain coefficient fitting formulas under different outflow conditions, wherein the fitting formulas comprise a flow fitting coefficient fitting formula under the free outflow condition, a submerged fitting coefficient fitting formula under the submerged outflow condition and a reduction fitting coefficient fitting formula under the orifice outflow condition;
the method is particularly used for summarizing coefficients obtained by calculation under all preset working conditions of a physical model and a numerical model under different outflow conditions and representing physical quantities;
fitting coefficients corresponding to the three outflow conditions and the characterization physical quantity thereof respectively according to the different outflow conditions;
according to the coefficients and the characterization physical quantity thereof, randomly generating a series of function expressions related to the coefficients and the characterization physical quantity, taking the function expressions as the parents, sequencing the parents according to the fitness of the parents, wherein the fitness is a Nash efficiency coefficient, screening out a batch of parents by using a roulette algorithm, sequencing the parents again according to the fitness, and sequentially carrying out hybridization and mutation operations on the coefficients, the calculation functions and operators in each group of parents according to the sequencing result so as to output offspring after the current iterative operation;
Acquiring the fitness of the offspring output by the current iterative operation so as to judge whether the Nash efficiency coefficient of the offspring output by the current iterative operation is larger than 0.95;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is smaller than 0.95, defining the offspring output by the current iteration operation as a parent, and repeating the previous operation to perform the iteration operation;
if the Nash efficiency coefficient of the offspring output by the current iteration operation is larger than 0.95, defining the offspring output by the current iteration operation as target offspring;
the obtained target daughter function is a selected flow fitting coefficient fitting formula, a submerged fitting coefficient fitting formula and a reduced fitting coefficient fitting formula;
the algorithm model building module is used for substituting the coefficient fitting formulas under different outflow conditions into the flow calculation formulas under different outflow conditions to obtain an urban combined overflow system flow algorithm model;
the flow fitting coefficient, the inundation fitting coefficient and the reduction fitting coefficient are substituted into a flow calculation formula;
wherein ,flow for free outflow, +.>To drown out the flow of the outflow->The flow rate of the outlet flow is expressed in units of cubic meters per second; />The weir width is given in meters; / >Fitting coefficients for the flow; />Fitting coefficients for inundation; />Fitting coefficients are reduced;the height of the upper edge of the weir crest is in meters; />Gravitational acceleration; />The unit is meter for a water head on a weir; />The unit is square meter of box culvert cross section area; />Is the roughness rate; />The hydraulic radius is given in meters; />The water level difference is the upstream and downstream water level difference, and the unit is meter; />The length of the box culvert is in meters;
the algorithm model using module is used for inputting the downstream water data into the urban combined overflow system flow algorithm model, judging the outflow mode of the water flow passing through the weir according to the downstream water data, selecting the corresponding coefficient fitting formula according to different outflow modes, substituting the selected coefficient into the corresponding flow calculation formula, and calculating the urban combined overflow system flow.
6. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 4 when the computer program is executed.
7. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 4.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210109B (en) * | 2019-05-29 | 2021-07-30 | 中国水利水电科学研究院 | Numerical simulation method and system for reverse water flow of weir gate engineering in river network |
| CN113283095A (en) * | 2021-05-31 | 2021-08-20 | 中国水利水电科学研究院 | Evolutionary digital twin watershed construction method |
| CN114996264A (en) * | 2022-04-20 | 2022-09-02 | 云控智行科技有限公司 | Data processing method, device and equipment for digital twins |
| CN115795856A (en) * | 2022-11-28 | 2023-03-14 | 广东省水利水电科学研究院 | Method for monitoring downstream flow of sluice |
| CN115907429A (en) * | 2022-12-28 | 2023-04-04 | 清华大学 | PSO algorithm-based combined overflow optimization control method and device |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112417619B (en) * | 2020-11-23 | 2021-10-08 | 江苏大学 | Pump unit optimal operation adjusting system and method based on digital twinning |
| US20220245462A1 (en) * | 2021-01-29 | 2022-08-04 | World Wide Technology Holding Co., LLC | Training a digital twin in artificial intelligence-defined networking |
| US20220263734A1 (en) * | 2021-02-14 | 2022-08-18 | Broadstone Technologies, Llc | System and method for telemetry analysis of a digital twin |
-
2023
- 2023-04-19 CN CN202310417222.2A patent/CN116151155B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210109B (en) * | 2019-05-29 | 2021-07-30 | 中国水利水电科学研究院 | Numerical simulation method and system for reverse water flow of weir gate engineering in river network |
| CN113283095A (en) * | 2021-05-31 | 2021-08-20 | 中国水利水电科学研究院 | Evolutionary digital twin watershed construction method |
| CN114996264A (en) * | 2022-04-20 | 2022-09-02 | 云控智行科技有限公司 | Data processing method, device and equipment for digital twins |
| CN115795856A (en) * | 2022-11-28 | 2023-03-14 | 广东省水利水电科学研究院 | Method for monitoring downstream flow of sluice |
| CN115907429A (en) * | 2022-12-28 | 2023-04-04 | 清华大学 | PSO algorithm-based combined overflow optimization control method and device |
Non-Patent Citations (1)
| Title |
|---|
| 基于关键参数耦合效应的城市排涝设计方法;唐明 等;《水资源保护》;第38卷(第02期);第17-24页 * |
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