CN112799310A - Method for urban drainage system simulation control mixed model based on mechanism model, concept model and data model of C language - Google Patents
Method for urban drainage system simulation control mixed model based on mechanism model, concept model and data model of C language Download PDFInfo
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Abstract
A city drainage system simulation control mixed model based on a mechanism model, a concept model and a data model of C language comprises the following steps: determining the model range: determining a refined modeling range and a rough modeling range; constructing an online mechanism model; constructing a conceptual model; the online mechanism model is coupled with the concept model; correcting the model parameters; establishing a rainfall process; simulating the water quantity and water quality of a drainage system; performing simulation control on a drainage system; data model-assisted application: establishing a neural network model, establishing the relation between rainfall and runoff and between the flow and the depth of a pipe network by receiving characteristic data, and predicting the runoff and the depth of the pipe network after establishing the relation; and (5) analyzing and displaying a simulation result. The model integrates rich functions of an on-line mechanism model SWMM model, a concept model and a data model of C language, and realizes quick simulation, efficient simulation control and automatic strategy optimization of water quantity and water quality of the urban drainage system.
Description
Technical Field
The invention relates to the field of real-time control of urban drainage systems, in particular to a method for simulating and controlling a mixed model of an urban drainage system based on a mechanism model, a concept model and a data model of C language.
Background
With the rapid urbanization process and the increase in frequency and magnitude of extreme rainfall events caused by climate change, the load of the urban drainage system is increased, thereby increasing the risk of waterlogging and combined system pipe network overflow. Real-time control of urban drainage systems is a reliable means to improve the operational performance of drainage systems. The real-time control is to dynamically adjust the control strategy by using an online model according to important process variable data monitored online, and to intervene the operation of the drainage facility and the sewage treatment plant in real time through the control equipment.
In the simulation of the urban drainage system, an online mechanism model EPA-SWMM is the most common and widely applied model, and is a process-oriented model. The SWMM model mainly uses the Saint-Venn equation to simulate the conservation relation of water flow quality and energy in the pipeline, so that the hydraulic process in a municipal drainage pipe network and auxiliary facilities can be accurately described, but the computational complexity of the SWMM model causes longer simulation operation time and cannot meet the requirement of real-time control.
Conceptual models are a class of control-oriented models whose physical systems are represented by highly simplified "concepts", relying on simpler and fewer relationships, with reduced overall complexity and thus significantly reduced computational time. However, since the conceptual model only focuses on the dominant process, the generalization degree of the conceptual model affects the accuracy of the model simulation. The concept model based on the Masjing root method is described by the assumed linear relation between the water storage volume of the pipeline and the inflow and outflow of the pipeline, and is a model widely applied to simulation and control, and the method is simple and has applicability in the aspect of prediction.
A data model is an abstraction of real-world data features that describe the concept and definition of a set of data. The data model is a storage mode of data in the database. The neural network model in the data model is a machine learning technology which simulates the neural network of the human brain so as to realize artificial intelligence. Years of research show that compared with the traditional model, the rainfall-runoff simulation and prediction speed of the neural network is higher, and the simulation prediction accuracy is higher. In water quality monitoring and prediction, because water quality needs to be comprehensively considered by combining factors such as smell, appearance and chlorine concentration, various factors influence each other and decay along with time, a traditional model is difficult to accurately simulate and predict, and a neural network has advantages due to the accuracy and stability of results.
Based on the respective advantages and disadvantages of the models, the online mechanism model, the concept model and the data model are integrated to construct the mixed model in the same simulation system, the method is an advanced technology with complementary advantages, the operation speed can be greatly increased on the premise of ensuring certain precision, and efficient, global and multi-objective optimization control of the drainage system is realized.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for simulating and controlling a mixed model of an urban drainage system based on a mechanism model, a conceptual model and a data model of C language.
As conceived above, the technical scheme of the invention is as follows: a method for a simulation control mixed model of a municipal drainage system based on a mechanism model, a concept model and a data model of C language is characterized in that: the method comprises the following steps:
1) determining the model range: determining a refined modeling range and a rough modeling range;
2) constructing an online mechanism model: for a refined modeling range, establishing an operable file in an online mechanism model, wherein the file comprises various input parameters of a part of mechanism models to be used in the simulation of the drainage system, and after the establishment of the file is finished, generating an online mechanism model module in a simulation control mixed model and importing the online mechanism model module into the input file;
3) constructing a conceptual model: regarding the rough modeling range, generalizing the rest parts of the drainage system, reserving key nodes, pipelines and facilities, merging, simplifying or deleting, and generating corresponding concept model modules in a hybrid model simulation platform;
4) the online mechanism model is coupled with the concept model: comprehensively connecting the relationship nodes or pipelines corresponding to the inflow/outflow of the online mechanism model module and the outflow/inflow of the concept model module on a hybrid model simulation platform to transmit the water quantity, water level and water quality information of each relationship node and pipeline;
5) and (3) correcting model parameters: the method comprises the steps of correcting parameters of an online mechanism model and correcting parameters of a conceptual model;
6) establishing a rainfall process;
7) simulating the water quantity and water quality of a drainage system;
8) performing simulation control on a drainage system;
9) data model-assisted application: establishing a neural network model, establishing the relation between rainfall and runoff and between the flow and the depth of a pipe network by receiving characteristic data, and predicting the runoff and the depth of the pipe network after establishing the relation;
10) and (5) analyzing and displaying a simulation result.
Further, the conceptual model construction in the step 3) comprises a catchment area module, a sewage treatment plant module, a storage regulation pool module, a pump station module and a node module, wherein the catchment area module selects a Masjing linear method or a non-linear reservoir method to obtain a rainfall-runoff relation, the area, initial loss, permeability loss, a runoff coefficient, pollutant types and concentrations of the catchment area are set, the sewage treatment plant module comprises a design volume of the sewage treatment plant, the storage regulation pool module comprises a maximum depth and a depth-area curve of the storage regulation pool, the maximum depth and the depth-area curve are usually connected with the pump station module, the pump station module comprises the maximum power of a pump and the opening and closing liquid level of the pump, and the node module is used for connecting each facility and pipeline.
Further, the parameter correction of the online mechanism model in the step 5) obtains a correction parameter matched with the monitoring data by adjusting related parameters of a catchment area, a pipeline, a regulation and storage tank and a pump station; parameter correction of the conceptual model obtains parameters with the best model evaluation result by obtaining basic information of a catchment area, a pipeline, a regulation and storage pool and a pump station and realizing an automatic optimization function of Mas Jing parameters (subsection number N, transmission time K and weight coefficient X) in a hybrid simulation platform.
Further, the step 6) of establishing the rainfall process comprises calling an external rainfall file or a typical rainfall database, generating rainfall by a custom formula and manually inputting rainfall data.
Further, the step 7) comprises solving the Saint Venn kinetic equation of the online mechanism model, solving the MaskJing root groove storage and water quantity balance equation of the conceptual model to calculate the flow, passing through the pollutant accumulation model and the pollutant scouring model, and solving the pollutant transmission and conversion equation.
Further, the step 8) of selecting a rule-based simulation control module for the drainage system simulation control selects a controlled facility and a corresponding monitoring point according to the control rule of the rule control method or the fuzzy logic method, automatically generates a response relation between monitoring information (monitoring time, water quality, water level, flow rate and the like) and a control instruction, obtains a control value of the controlled facility by using the real-time monitoring value and the response relation during the simulation control, and controls the facility to stably reach the control value by using a PID control method.
Further, the step 8) is that the simulation control selection optimization strategy simulation control module of the drainage system selects the controlled facility and the monitoring point according to the control rule of the optimization algorithm (genetic algorithm, linear programming and nonlinear programming), generates monitoring time, water quality, water level and flow information, selects the optimization algorithm and sets algorithm parameters, calculates the optimal control value of the controlled facility in real time through the optimization algorithm in the simulation process according to the monitoring information and in combination with a system control target, and controls the facility to stably reach the control value by using a PID control method.
Further, the step 10) of analyzing and displaying the simulation result comprises recording and calling data of each node and each pipe section, calculating a universality index, performing custom calculation, generating a time-flow and other common data charts.
Further, the specific functions of the rule-based simulation control module in the step 8) include: controlled facilities are selected, control rules in the form of if-then-else are established, and control over controllable facilities of a weir, a gate, an orifice, a valve, an intercepting well and a pump station is realized based on information of running time, depth, a water head, inflow, outflow, accumulated water, water quality and working state (opening and working flow) of monitoring points.
Further, the step 8) of optimizing the specific functions of the policy simulation control module includes: selecting a controlled facility; inputting control variables, a system constraint equation and an objective function, performing weight distribution and summation on different control targets to form multiple objective functions, selecting different optimization algorithms (genetic algorithm, linear programming and nonlinear programming) compiled by C language, and automatically implementing strategy optimization control based on monitoring information and control target weight; the parameters of the optimization algorithm comprise the number of variables, the number of objective functions, the number of boundary conditions and unique parameters of different optimization algorithms.
The invention has the following advantages and positive effects:
1. the invention combines all functions of the online mechanism model and is assisted with the data model to carry out rapid prediction, thereby realizing the coupling of the three on the same simulation platform. And constructing a conceptual model in a region with simple facility connection relation, constructing an SWMM model for fine simulation in a region with complex facility connection relation and inaccurate simulation of the conceptual model, and constructing a data model for the nonlinear, multivariable and high-uncertainty drainage system to assist in prediction. Therefore, the hybrid model has the characteristics of fast calculation, accurate simulation and efficient prediction.
2. The invention selects a proper optimization method according to different control targets based on various optimization algorithms of C language, automatically realizes the calculation of the optimal control rule, and feeds back the optimization control strategy to the online mechanism model/concept model in real time. Meanwhile, the calculation time of an optimization algorithm can be saved according to the prediction result of the data model, so that the rapid and efficient water quantity and water quality simulation, real-time simulation control and strategy optimization are realized.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, the drawings in the following description are for illustration only, and for those skilled in the art, other drawings may be obtained according to the structures shown in the drawings without any creative effort.
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a simulation control mixing system of a municipal drainage system;
FIG. 3 is a schematic diagram of a model parameter correction module;
FIG. 4 is a schematic diagram of a strategic optimization control module;
FIG. 5 is a graph comparing the results of strategic optimization and non-strategic simulation under selected control objectives and methods.
Detailed Description
Referring to fig. 1 and 2, the present invention provides a method for a simulation control hybrid model of an urban drainage system based on a mechanism model, a conceptual model and a data model of C language, comprising the following steps:
1. determining the model range: determining a refined modeling range and a rough modeling range;
2. constructing an online mechanism model: for a refined modeling range, establishing an operable file in an online mechanism model, wherein the file comprises various input parameters of a part of mechanism models to be used in the simulation of the drainage system, and after the establishment of the file is finished, generating an online mechanism model module in a simulation control mixed model and importing the online mechanism model module into the input file;
2. constructing a concept model module: regarding the rough modeling range, generalizing the rest parts of the drainage system, reserving key nodes, pipelines and facilities, merging, simplifying or deleting, and generating corresponding concept model modules in a hybrid model simulation platform;
the method comprises the following steps that a conceptual model is constructed and comprises a catchment area module, a sewage treatment plant module, a regulation and storage pool module, a pump station module and a node module, wherein the catchment area module selects a Masjing linear method or a non-linear reservoir method to obtain a rainfall-runoff relation, the area, initial loss, seepage loss, a runoff coefficient, pollutant types and concentration of the catchment area are set, the sewage treatment plant module comprises the design volume of the sewage treatment plant, the regulation and storage pool module comprises the maximum depth and the depth-area curve of the regulation and storage pool, the regulation and storage pool module and the depth-area curve are generally connected with the pump station module, the pump station module comprises the maximum power of a pump and the opening and closing liquid level;
4. the online mechanism model is coupled with the concept model: comprehensively connecting the relationship nodes or pipelines corresponding to the inflow/outflow of the online mechanism model module and the outflow/inflow of the concept model module on a hybrid model simulation platform to transmit the water quantity, water level and water quality information of each relationship node and pipeline;
5. constructing a model parameter correction module: the method comprises the steps of correcting parameters of an online mechanism model and correcting parameters of a conceptual model; the parameters of the online mechanism model are manually corrected, and correction parameters matched with the monitoring data are obtained by adjusting related parameters of a catchment area, a pipeline, a regulation and storage tank and a pump station; the parameters of the conceptual model are automatically corrected, and the automatic optimization function of the Massjing root parameters (the number N of subsections, the transmission time K and the weight coefficient X) is realized in the hybrid simulation platform by acquiring the basic information of a catchment area, a pipeline, a regulation pool and a pump station, so that the parameters with the best model evaluation result are obtained;
6. the rainfall process is established: calling an external rainfall file or a typical rainfall database, generating rainfall by a user-defined formula and manually inputting rainfall data;
7. simulating water quantity and water quality of a drainage system: solving a Saint Vietnam kinetic equation of an online mechanism model, solving a Masjing root tank storage and water quantity balance equation of a conceptual model, calculating flow, simulating a water quantity transmission process, passing through a pollutant accumulation model and a pollutant scouring model, and solving a pollutant transmission conversion equation;
8. constructing a drainage system simulation control module: a rule-based simulation control module or an optimization strategy simulation control module can be selected;
the simulation control module based on the rule selects the controlled facility and the corresponding monitoring point according to the control rule of the rule control method or the fuzzy logic method, automatically generates the response relation between the monitoring information (monitoring time, water quality, water level, flow and the like) and the control instruction, obtains the control value of the controlled facility by using the real-time monitoring value and the response relation during the simulation control, and controls the facility to stably reach the control value by using the PI D control method. The specific functions include: selecting controlled facilities, establishing a control rule in an if-then-else form, and realizing the control of controllable facilities such as a weir, a gate, an orifice, a valve, an intercepting well, a pump station and the like based on the information of the running time, the depth, the water head, the inflow, the outflow, the accumulated water, the water quality and the working state (opening degree and working flow) of a monitoring point;
selecting an optimization strategy simulation control module, selecting controlled facilities and monitoring points according to the control rules of an optimization algorithm (genetic algorithm, linear programming and nonlinear programming), generating monitoring time, water quality, water level and flow information, selecting the optimization algorithm and setting algorithm parameters, calculating the optimal control value of the controlled facilities in real time through the optimization algorithm in the simulation process according to the monitoring information and combining a system control target, controlling the facilities to stably reach the control value by utilizing a PID control method,
the specific functions include: selecting controlled facilities, inputting control variables, a system constraint equation and an objective function, carrying out weight distribution and summation on different control targets to form multiple objective functions, selecting different optimization algorithms (genetic algorithm, linear programming and nonlinear programming) compiled by C language, and automatically implementing strategy optimization control based on monitoring information and control target weight; the parameters of the optimization algorithm comprise the number of variables, the number of target functions, the number of boundary conditions and unique parameters of different optimization algorithms;
9. constructing a data model module: the system comprises the function of a neural network, can accurately predict the quality of inlet water and timely investigate the running state of a pipe network; accurately predicting waterlogging, overflow amount and position under the condition of the known future rainfall; and predicting at the non-monitoring important node, and judging the corresponding pipeline state and the flow and depth of each important drainage facility. The prediction result can be fed back to the optimization algorithm, and efficient and quick optimization strategy adjustment is realized.
10. Constructing a simulation result analysis display module: the method comprises the steps of simulating water quantity and water quality under a user-defined time step length; real-time simulation control based on rules; selecting a strategy optimization simulation under a control target and a control method; recording and calling data of each node; calculating a universality index; calculating a self-defined formula; common data chart generation.
The invention is described in detail below by way of specific examples, the implementation process including:
1. constructing an online mechanism model module: in the present embodiment, the modeling area is divided into a mechanism model modeling area and a conceptual model modeling area according to the area importance degree, the data detail degree, and the like. In the mechanism model modeling area, the data of facilities such as a catch basin, an orifice, a regulation and storage tank, a pump, a weir, a sewage treatment plant and the like and connecting pipelines and the like in the area are processed, and an operational SWMM model is established. And generating an online mechanism model module in the simulation control mixed model, and importing the built external SWMM model file.
2. Constructing a concept model module: in the embodiment, the conceptual model modeling area is moderately generalized, key nodes and pipelines are reserved, the catchment area and the pipelines are reasonably combined and simplified, and corresponding catchment area, pipeline and node modules are generated in the simulation control mixed model system.
3. The online mechanism model is coupled with the concept model: in this embodiment, according to the logical relationship between the drainage system facilities, the connection relationship between the modules of the conceptual model and between the conceptual model module and the online mechanism model module is established in the simulation control hybrid model platform, so as to form a complete drainage system model. And inputting the information of nodes and pipelines connected with the mechanism model and the concept model in the SWMM model file so as to complete the information transmission of water quantity, water quality and the like of the mixed model in real-time simulation control.
4. Referring to fig. 3, model parameter correction: in the present embodiment, the parameter correction of the online mechanism model and the conceptual model is performed by the model parameter correction module using the on-site monitoring data. The online mechanism model can truly and accurately reflect the actual operation condition by adjusting the pipeline roughness, the orifice discharge coefficient, the pump power curve, the opening and closing liquid level and other parameters in the parameter correction.
And the conceptual model parameter correction obtains the optimal masjing root parameters K, X, N of each catchment area and pipeline by inputting information such as the area of each generalized catchment area, the water inlet and outlet relation of the generalized pipeline and the like and utilizing the parameter optimization function of the simulation control mixed model.
5. The rainfall process is established: in this embodiment, a local rainfall data file is called in the rainfall module.
6. Referring to fig. 4, the drainage system optimization strategy simulation control: in this embodiment, a policy optimization control module is used to establish boundary conditions of the system (e.g., maximum treatment capacity of a sewage treatment plant), select control targets of the system (e.g., minimum overflow amount, maximum treatment amount of the sewage treatment plant, water amount balance of a storage tank, and stable water intake of a facility), perform weight distribution on each control target (e.g., 1, 0.2, and 0.2, respectively), form a multi-objective function, and select an optimization algorithm (e.g., nonlinear programming) to set algorithm parameters, thereby forming a set of complete policy optimization schemes.
According to the control rule of the optimization algorithm, controlled facilities (such as a storage tank) and monitoring points (such as a front tank of the storage tank) are selected to generate information such as monitoring time, water quality, water level, flow and the like. And according to the monitoring information and a system control target, calculating the optimal control value of the controlled facility in real time through an optimization algorithm in the simulation process, and transmitting the optimal control value to an online mechanism model or a concept model to realize strategy optimization control.
7. Neural network data model-assisted application: the data of a large number of training samples (such as pipeline flow velocity, inflow rate, outflow rate and the like) are added to the input end of the neural network, and meanwhile, the corresponding expected output (such as pipeline depth) is compared with the output (such as pipeline depth) of the neural network to obtain an error signal, so that the adjustment of the connection strength of the weight is controlled, and the weight is converged to a determined weight after multiple times of training. The trained model may be used to predict new outputs (e.g., pipe depth). And feeding back the prediction result to an optimization algorithm, and implementing efficient optimization strategy dynamic adjustment.
8. Referring to fig. 5, the simulation results analysis shows: in this embodiment, the result display module is used to set the simulation time step to 5 minutes, display the strategy optimization simulation under the selected control objective and method, and generate the corresponding data chart.
It should be understood that the embodiments and examples discussed herein are illustrative only and that various modifications or changes in light thereof will be suggested to persons skilled in the art and are to be included within the spirit and purview of this application and scope of the appended claims.
Claims (10)
1. A method for a simulation control mixed model of a municipal drainage system based on a mechanism model, a concept model and a data model of C language is characterized in that: the method comprises the following steps:
1) determining the model range: determining a refined modeling range and a rough modeling range;
2) constructing an online mechanism model: for a refined modeling range, establishing an operable file in an online mechanism model, wherein the file comprises various input parameters of a part of mechanism models to be used in the simulation of the drainage system, and after the establishment of the file is finished, generating an online mechanism model module in a simulation control mixed model and importing the online mechanism model module into the input file;
3) constructing a conceptual model: regarding the rough modeling range, generalizing the rest parts of the drainage system, reserving key nodes, pipelines and facilities, merging, simplifying or deleting, and generating corresponding concept model modules in a hybrid model simulation platform;
4) the online mechanism model is coupled with the concept model: comprehensively connecting the relationship nodes or pipelines corresponding to the inflow/outflow of the online mechanism model module and the outflow/inflow of the concept model module on a hybrid model simulation platform to transmit the water quantity, water level and water quality information of each relationship node and pipeline;
5) and (3) correcting model parameters: the method comprises the steps of correcting parameters of an online mechanism model and correcting parameters of a conceptual model;
6) establishing a rainfall process;
7) simulating the water quantity and water quality of a drainage system;
8) performing simulation control on a drainage system;
9) data model-assisted application: establishing a neural network model, establishing the relation between rainfall and runoff and between the flow and the depth of a pipe network by receiving characteristic data, and predicting the runoff and the depth of the pipe network after establishing the relation;
10) and (5) analyzing and displaying a simulation result.
2. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 1, wherein the method comprises the following steps: the step 3) conceptual model construction comprises a catchment area module, a sewage treatment plant module, a storage regulation pool module, a pump station module and a node module, wherein the catchment area module selects a Masjing linear method or a non-linear reservoir method to obtain a rainfall-runoff relation, the area, initial loss, osmotic loss, a runoff coefficient, pollutant types and concentrations of the catchment area are set, the sewage treatment plant module comprises a designed volume of the sewage treatment plant, the storage regulation pool module comprises a maximum depth and a depth-area curve of the storage regulation pool, the maximum depth and the depth-area curve are usually connected with the pump station module, the pump station module comprises the maximum power of a pump and the opening and closing liquid level of the pump, and the node module is used for connecting each facility and pipeline.
3. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 1, wherein the method comprises the following steps: the parameter correction of the online mechanism model in the step 5) obtains a correction parameter matched with the monitoring data by adjusting related parameters of a catchment area, a pipeline, a regulation and storage tank and a pump station; parameter correction of the conceptual model obtains parameters with the best model evaluation result by obtaining basic information of a catchment area, a pipeline, a regulation and storage pool and a pump station and realizing an automatic optimization function of Mas Jing parameters (subsection number N, transmission time K and weight coefficient X) in a hybrid simulation platform.
4. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 1, wherein the method comprises the following steps: and 6) the establishment of the rainfall process comprises calling an external rainfall file or a typical rainfall database, generating rainfall by a custom formula and manually inputting rainfall data.
5. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 1, wherein the method comprises the following steps: the step 7) comprises solving the Saint Vietnam dynamic equation of the online mechanism model, solving the Mars' Jing root groove storage and water quantity balance equation calculation flow of the conceptual model, passing through the pollutant accumulation model and the pollutant scouring model, and solving the pollutant transmission and conversion equation.
6. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 1, wherein the method comprises the following steps: and 8) selecting a rule-based simulation control module in the simulation control of the drainage system, selecting the controlled facility and a corresponding monitoring point according to the control rule of a rule control method or a fuzzy logic method, automatically generating a response relation between monitoring information (monitoring time, water quality, water level, flow and the like) and a control instruction, obtaining a control value of the controlled facility by using a real-time monitoring value and the response relation during the simulation control, and controlling the facility to stably reach the control value by using a PID control method.
7. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 1, wherein the method comprises the following steps: and 8) selecting an optimization strategy simulation control module for the drainage system simulation control, selecting a controlled facility and a monitoring point according to a control rule of an optimization algorithm (genetic algorithm, linear programming and nonlinear programming), generating monitoring time, water quality, water level and flow information, selecting the optimization algorithm and setting algorithm parameters, calculating an optimal control value of the controlled facility in real time through the optimization algorithm in the simulation process according to the monitoring information and by combining a system control target, and controlling the facility to stably reach the control value by using a PID control method.
8. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 1, wherein the method comprises the following steps: and step 10), analyzing and displaying the simulation result, wherein the analysis and display comprise recording and calling data of each node and each pipe section, calculating a universality index, performing custom calculation, generating a time-flow common data chart and the like.
9. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 6, wherein the method comprises the following steps: the specific functions of the rule-based simulation control module in the step 8) comprise: controlled facilities are selected, control rules in the form of if-then-else are established, and control over controllable facilities of a weir, a gate, an orifice, a valve, an intercepting well and a pump station is realized based on information of running time, depth, a water head, inflow, outflow, accumulated water, water quality and working state (opening and working flow) of monitoring points.
10. The method for the urban drainage system simulation control mixed model based on the mechanism model, the concept model and the data model of the C language according to claim 7, wherein the method comprises the following steps: the step 8) of optimizing the specific functions of the strategy simulation control module comprises the following steps: selecting a controlled facility; inputting control variables, a system constraint equation and an objective function, performing weight distribution and summation on different control targets to form multiple objective functions, selecting different optimization algorithms (genetic algorithm, linear programming and nonlinear programming) compiled by C language, and automatically implementing strategy optimization control based on monitoring information and control target weight; the parameters of the optimization algorithm comprise the number of variables, the number of objective functions, the number of boundary conditions and unique parameters of different optimization algorithms.
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