A model decision method and system for computational fluid dynamics analysis

Abstract

The present invention provides a model decision method and system for computational fluid dynamics analysis, the method comprising: step 1: obtaining the workflow of a cooling tower; step 2: constructing a workflow simulation model according to the workflow of the cooling tower; step 3: simulating the current workflow according to the workflow simulation model and outputting working parameters; step 4: analyzing the working parameters based on fluid dynamics calculations, outputting an evaluation result of the current workflow, and assisting in deciding the next execution process of the cooling tower according to the evaluation result; effectively improving the monitoring efficiency and accuracy of the cooling tower, and effectively improving the working efficiency of the cooling tower through auxiliary decision-making.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis and processing, and in particular to a model decision method and system applied to computational fluid dynamics analysis. Background Art

[0002] At present, cooling towers are a common industrial equipment, mainly used to reduce the heat and thermal energy generated in industrial production, and are usually used to cool substances or other media. Cooling towers transfer heat from hot media to cooling media by contacting and exchanging heat with hot media, thereby achieving a cooling effect;

[0003] When the cooling tower performs the cooling step, it usually includes: hot water or other cooling medium flows from the system into the tower body of the cooling tower, the cooling medium flows downward along the packing layer in the tower body, and the spray system sprays air or water mist onto the packing to increase the wetness of the packing surface, promote air convection, and accelerate the heat exchange rate. Through the large surface area of ​​the packing, effective heat exchange is achieved between the cooling medium and the air. When the hot water dissipates heat, part of the water evaporates into water vapor, taking away a large amount of heat, causing the temperature of the cooling medium to drop. The cooling medium gradually cools down in the tower body, and part of the water vapor condenses into droplets on the surface of the cooling medium, and then continues to flow downward or discharge out of the tower. After the cooled medium completes the heat exchange at the bottom of the cooling tower, it is transported to other parts of the system through pipes, or directly discharged into the sewage treatment system. The air is heated by the heat exchange between the cooling medium and the air, and the hot air is discharged through the fan at the top of the tower to promote air convection circulation. The whole process is continuously circulated until the stable operating temperature of the system is maintained to ensure the normal operation of the system;

[0004] However, nowadays, the monitoring and decision-making of the cooling tower workflow are often achieved manually, which leads to errors in the monitoring and decision-making of the cooling tower workflow and wastes a lot of manpower and material resources, which is not conducive to improving the working efficiency of the cooling tower, nor is it conducive to the smooth completion of the cooling tower work progress;

[0005] Therefore, in order to overcome the above technical problems, the present invention provides a model decision method and system for computational fluid dynamics analysis. Summary of the invention

[0006] The present invention provides a model decision method and system for computational fluid dynamics analysis, which are used to determine the workflow of a cooling tower, thereby effectively realizing the construction of a workflow simulation model, and then simulating the current workflow, accurately and efficiently obtaining the working parameters of the current workflow, and then analyzing the working parameters through fluid dynamics calculation, effectively outputting the evaluation results of the current workflow, and then assisting in deciding the next execution process of the cooling tower based on the evaluation results, effectively improving the monitoring efficiency and accuracy of the cooling tower, and effectively improving the working efficiency of the cooling tower through auxiliary decision-making.

[0007] A model decision method applied to computational fluid dynamics analysis, comprising:

[0008] Step 1: Get the working process of cooling tower;

[0009] Step 2: Construct a workflow simulation model based on the workflow of the cooling tower;

[0010] Step 3: Simulate the current workflow according to the workflow simulation model and output the working parameters;

[0011] Step 4: Analyze the working parameters based on fluid dynamics calculations, output the evaluation results of the current workflow, and assist in deciding the next execution process of the cooling tower based on the evaluation results.

[0012] Preferably, a model decision method applied to computational fluid dynamics analysis, in step 1, obtaining a workflow of a cooling tower, comprises:

[0013] Obtaining factory parameters of the cooling tower, wherein the factory parameters include the water treatment link of the cooling tower and the configuration parameters of each treatment link;

[0014] Analyze the factory parameters of the cooling tower to determine the logical relationship of the processing links and the link limiting conditions of the processing links;

[0015] Generate the workflow of the cooling tower based on logical relationships and link restriction conditions.

[0016] Preferably, a model decision method applied to computational fluid dynamics analysis analyzes factory parameters of a cooling tower, comprising:

[0017] Analyze the factory parameters of the cooling tower and determine the logical keywords and execution keywords of the processing links;

[0018] Sort multiple processing links based on execution keywords, and determine the execution logic corresponding to each two adjacent processing links after sorting based on logic keywords;

[0019] Determine the logical relationship between the processing links according to the sorting results and the execution logic corresponding to each two adjacent processing links;

[0020] The configuration parameters of each processing link in the factory parameters of the cooling tower are analyzed, the constraint standards of each processing link are determined, and the constraint standards of each processing link are used as link limiting conditions of the corresponding processing link.

[0021] Preferably, a model decision method applied to computational fluid dynamics analysis, in step 2, constructing a workflow simulation model according to the workflow of the cooling tower, comprising:

[0022] Analyze the workflow of the cooling tower and determine the execution steps of the workflow when cooling the cooling material in the cooling tower;

[0023] Read the key execution points of each execution step in the cooling tower;

[0024] Get the execution parameters of the key execution points;

[0025] According to the key execution points of each step in the cooling tower and the execution parameters of the key execution points, the basic framework corresponding to each execution step is constructed;

[0026] Obtain standard execution data for each execution step, and configure the basic framework of the execution step according to the execution data of each standard execution step;

[0027] Output the sub-execution model corresponding to each execution step according to the configuration results;

[0028] Read each execution step, determine the execution process of each execution step, and determine the execution flow chart between the execution steps according to the execution process of each execution step;

[0029] The sub-execution models are merged according to the execution process to generate a workflow simulation model corresponding to the cooling tower when executing the workflow.

[0030] Preferably, a model decision method applied to computational fluid dynamics analysis, after generating a workflow simulation model corresponding to a cooling tower when executing a workflow, further comprises:

[0031] Retrieve the model verification set and model validation set;

[0032] Input the model verification set into the workflow simulation model to perform process simulation, and output the execution result data corresponding to each execution step based on the workflow simulation model;

[0033] The execution result data is matched with the model verification set, and the qualified judgment result of the workflow simulation model is output.

[0034] Preferably, a model decision method applied to computational fluid dynamics analysis matches the execution result data with the model verification set, and outputs a qualified judgment result of the workflow simulation model, including:

[0035] Match the execution result data corresponding to each execution step with the model verification set to determine whether the workflow simulation model is qualified;

[0036] If the execution result data corresponding to all execution steps match the model verification set, the workflow simulation model is judged to be qualified;

[0037] Otherwise, the workflow simulation model is judged to be unqualified and the workflow simulation model is optimized.

[0038] Preferably, a model decision method applied to computational fluid dynamics analysis optimizes a workflow simulation model, comprising:

[0039] When the workflow simulation model is judged to be unqualified, the target execution steps corresponding to the mismatch between the execution result data and the model verification set are obtained;

[0040] Acquire the standard execution step corresponding to the target execution step, and at the same time, acquire first difference data between the target execution step and the standard execution step;

[0041] Obtain second difference data between the execution result data and the corresponding model verification set;

[0042] Read and analyze the first difference data and the second difference data, and output optimization data for the target execution step according to the reading and analysis results;

[0043] Optimize the optimization data in the target sub-execution model corresponding to the execution step, and output the target optimization sub-execution model corresponding to the optimization data according to the optimization result;

[0044] The target optimization sub-execution model is updated in the workflow simulation model to complete the optimization of the workflow simulation model.

[0045] Preferably, a model decision method applied to computational fluid dynamics analysis, in step 3, based on the fluid dynamics calculation analysis working parameters, outputs the evaluation result of the current workflow, and assists in deciding the next execution process of the cooling tower according to the evaluation result, including:

[0046] Retrieving a fluid dynamics calculation model and obtaining multiple calculation targets of the fluid dynamics calculation model;

[0047] Classifying the working parameters based on multiple calculation targets of the fluid dynamics calculation model and outputting multiple sub-working parameter sets;

[0048] Input each sub-operating parameter set into the fluid dynamics calculation model to perform calculations based on the corresponding calculation target, and output the calculation results corresponding to the calculation target;

[0049] Output the actual work progress corresponding to the current workflow based on the calculation target and the calculation result of the calculation target;

[0050] Based on the constraints of each calculation target and the actual work progress, the evaluation results of the current workflow are output, and the next execution process of the cooling tower is decided based on the evaluation results.

[0051] Preferably, a model decision method applied to computational fluid dynamics analysis outputs an evaluation result of the current workflow based on the limiting conditions and actual work progress of each calculation target, and assists in deciding the next execution process of the cooling tower according to the evaluation result, including:

[0052] Obtain the limiting conditions for each calculation target and match the limiting conditions with the actual work progress. Each calculation target corresponds to the completion status of the actual work progress.

[0053] When the completion status of each calculation target corresponding to the actual work progress reaches the specified condition, the next execution step corresponding to the current workflow is retrieved and used as the auxiliary decision result;

[0054] When the completion status of the actual work progress corresponding to the calculation target does not meet the limit conditions, the current workflow is used as the auxiliary decision result.

[0055] A model decision system for computational fluid dynamics analysis, comprising:

[0056] A process determination module is used to obtain the work flow of the cooling tower;

[0057] A model building module, used for building a workflow simulation model according to the workflow of the cooling tower;

[0058] A simulation module is used to simulate the current workflow according to the workflow simulation model and output the working parameters;

[0059] The auxiliary decision-making module is used to analyze the working parameters based on fluid dynamics calculations, output the evaluation results of the current working process, and assist in deciding the next execution process of the cooling tower based on the evaluation results.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] 1. By determining the workflow of the cooling tower, the construction of the workflow simulation model can be effectively realized, and then the current workflow can be simulated, and the working parameters of the current workflow can be accurately and efficiently obtained. Then, the working parameters can be analyzed through fluid dynamics calculations, and the evaluation results of the current workflow can be effectively output. Then, according to the evaluation results, the next execution process of the cooling tower can be assisted in decision-making, which effectively improves the monitoring efficiency and accuracy of the cooling tower. Through auxiliary decision-making, the working efficiency of the cooling tower can be effectively improved.

[0062] 2. By constructing the basic framework of the execution steps, the execution data can be configured for the basic framework of the execution steps, and then the sub-execution model of each execution step can be determined. By effectively merging the sub-execution models of the execution steps through the execution flowchart, the objectivity and accuracy of the workflow simulation model are guaranteed, and the working parameters corresponding to the workflow can be effectively measured, thereby effectively realizing the effective monitoring and judgment of the cooling process of the cooling tower.

[0063] 3. By determining the first difference data between the target execution step and the standard execution step, the difference point of the target execution step can be effectively determined. By determining the execution result data and the corresponding model verification set, the difference data of the result can be determined. By doubly determining the difference data, the optimization data can be effectively determined, which lays the foundation for optimizing the target sub-execution model, thereby ensuring the effective update of the target optimization sub-execution model and improving the accuracy of the optimization of the target sub-execution model.

[0064] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0065] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0067] Figure 1 A flow chart of a model decision method applied to computational fluid dynamics analysis in an embodiment of the present invention;

[0068] Figure 2 This is a flow chart of step 2 in a model decision method applied to computational fluid dynamics analysis in an embodiment of the present invention;

[0069] Figure 3 The figure is a structural diagram of a model decision system applied to computational fluid dynamics analysis in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0071] Embodiment 1:

[0072] This embodiment provides a model decision method applied to computational fluid dynamics analysis, including:

[0073] Step 1: Get the working process of cooling tower;

[0074] Step 2: Construct a workflow simulation model based on the workflow of the cooling tower;

[0075] Step 3: Simulate the current workflow according to the workflow simulation model and output the working parameters;

[0076] Step 4: Analyze the working parameters based on fluid dynamics calculations, output the evaluation results of the current workflow, and assist in deciding the next execution process of the cooling tower based on the evaluation results.

[0077] In this embodiment, the working process of the cooling tower includes: hot water or other cooling medium flows from the system into the tower body of the cooling tower, the cooling medium flows downward along the packing layer in the tower body, and the spray system sprays air or water mist onto the packing to increase the wetness of the packing surface, promote air convection, and accelerate the heat exchange rate. Through the large surface area of ​​the packing, effective heat exchange is achieved between the cooling medium and the air. When the hot water dissipates heat, part of the water evaporates into water vapor, taking away a large amount of heat, causing the temperature of the cooling medium to drop. The cooling medium gradually cools down in the tower body, and part of the water vapor condenses into droplets on the surface of the cooling medium, and then continues to flow downward or discharge out of the tower. After the cooled medium completes the heat exchange at the bottom of the cooling tower, it is transported to other parts of the system through a pipeline, or directly discharged into the sewage treatment system. Through the heat exchange between the cooling medium and the air, the air is heated, and the hot air is discharged through the fan at the top of the tower to promote air convection circulation. The whole process is continuously circulated until the stable operating temperature of the system is maintained to ensure the normal operation of the system.

[0078] In this embodiment, the workflow simulation model may be a model used to simulate the workflow, and the workflow simulation model may effectively output the work parameters corresponding to the current workflow.

[0079] In this embodiment, the working parameters may include parameters such as flow velocity, flow direction, flow field pressure, etc. of the corresponding fluid in the current working process.

[0080] In this embodiment, the working parameters are analyzed based on fluid dynamics calculations, and the working parameters can be calculated to simulate the mechanical properties, thermal characteristics and motion characteristics of the actual working process in the cooling tower, so as to determine the current work progress by the mechanical properties, thermal characteristics and motion characteristics of the cooling tower, and then assist in decision-making for the next execution process of the cooling tower.

[0081] The beneficial effect of the above technical solution is: by determining the workflow of the cooling tower, the construction of the workflow simulation model can be effectively realized, and then the current workflow can be simulated, and the working parameters of the current workflow can be accurately and efficiently obtained, and then the working parameters can be analyzed through fluid dynamics calculation, and the evaluation results of the current workflow can be effectively output, and then the next execution process of the cooling tower can be assisted in decision-making based on the evaluation results, effectively improving the monitoring efficiency and accuracy of the cooling tower, and the working efficiency of the cooling tower can be effectively improved through auxiliary decision-making.

[0082] Embodiment 2:

[0083] Based on Example 1, this example provides a model decision method for computational fluid dynamics analysis, such as Figure 2 As shown, in step 1, the workflow of the cooling tower is obtained, including:

[0084] S101: Obtaining factory parameters of a cooling tower, wherein the factory parameters include a water treatment link of the cooling tower and configuration parameters of each treatment link;

[0085] S102: Analyze the factory parameters of the cooling tower to determine the logical relationship of the processing links and the link limiting conditions of the processing links;

[0086] S103: Generate a cooling tower workflow based on logical relationships and link restriction conditions.

[0087] In this embodiment, the configuration parameters may be the processing requirements corresponding to each processing link, that is, the limiting conditions of each processing link (as a limitation on the completion of each processing link) are determined according to the configuration parameters.

[0088] The beneficial effect of the above technical solution is: by obtaining the factory parameters of the cooling tower, the logical relationship of processing counterattacks and the link limitation conditions of the processing links are effectively determined, thereby effectively realizing the construction of the workflow and ensuring the effectiveness, comprehensiveness and accuracy of the construction of the cooling tower workflow.

[0089] Embodiment 3:

[0090] Based on Example 2, this example provides a model decision method applied to computational fluid dynamics analysis, which analyzes the factory parameters of the cooling tower, including:

[0091] Analyze the factory parameters of the cooling tower and determine the logical keywords and execution keywords of the processing links;

[0092] Sort multiple processing links based on execution keywords, and determine the execution logic corresponding to each two adjacent processing links after sorting based on logic keywords;

[0093] Determine the logical relationship between the processing links according to the sorting results and the execution logic corresponding to each two adjacent processing links;

[0094] The configuration parameters of each processing link in the factory parameters of the cooling tower are analyzed, the constraint standards of each processing link are determined, and the constraint standards of each processing link are used as link limiting conditions of the corresponding processing link.

[0095] In this embodiment, the logic keywords include but are not limited to: and, or, not, etc., which are used to constrain the execution logic between processing links.

[0096] In this embodiment, the execution keyword may be used to implement a key description of the processing link. The processing links may be sorted by the execution keyword, thereby determining the sequence of the processing links.

[0097] The beneficial effects of the above technical solution are: by analyzing the factory parameters of the cooling tower, the logical relationship of the processing links can be effectively determined; by analyzing the configuration parameters of each processing link, the constraint standards of each processing link can be determined, and the link limitation conditions of the corresponding processing link can be effectively obtained, which effectively improves the accuracy of obtaining the logical relationship of the processing links and the link limitation conditions of the processing links.

[0098] Embodiment 4:

[0099] Based on Example 1, this example provides a model decision method for computational fluid dynamics analysis. In step 2, a workflow simulation model is constructed according to the workflow of a cooling tower, including:

[0100] Analyze the workflow of the cooling tower and determine the execution steps of the workflow when cooling the cooling material in the cooling tower;

[0101] Read the key execution points of each execution step in the cooling tower;

[0102] Get the execution parameters of the key execution points;

[0103] According to the key execution points of each step in the cooling tower and the execution parameters of the key execution points, the basic framework corresponding to each execution step is constructed;

[0104] Obtain standard execution data for each execution step, and configure the basic framework of the execution step according to the execution data of each standard execution step;

[0105] Output the sub-execution model corresponding to each execution step according to the configuration results;

[0106] Read each execution step, determine the execution process of each execution step, and determine the execution flow chart between the execution steps according to the execution process of each execution step;

[0107] The sub-execution models are merged according to the execution process to generate a workflow simulation model corresponding to the cooling tower when executing the workflow.

[0108] In this embodiment, the workflow may be the cooling process required to cool a cooling material (liquid, such as water, etc.) in a cooling tower. The workflow includes several execution steps to achieve the cooling operation of the cooling material in the cooling tower.

[0109] In this embodiment, the key execution point is the specific position of the cooling tower during the execution step when the cooling operation is performed.

[0110] In this embodiment, the execution parameters are information such as the position attribute structure of the specific position corresponding to the execution key point and the basic functions achieved by performing the cooling operation in the specific position.

[0111] In this embodiment, the standard execution data may be process data of specific execution steps and working parameters corresponding to the execution steps.

[0112] In this embodiment, the execution process is the operational flow of the execution steps. The association between the execution steps is determined by the operational flow between the execution steps. The execution flowchart between the execution steps is determined by the association between the execution steps. The sub-execution models are merged through the execution flowchart to determine the workflow simulation model.

[0113] The beneficial effect of the above technical solution is: by constructing a basic framework of the execution steps, the execution data can be configured for the basic framework of the execution steps, and then the sub-execution model of each execution step can be determined. By effectively merging the sub-execution models of the execution steps through the execution flowchart, the objectivity and accuracy of the workflow simulation model are guaranteed, and the working parameters corresponding to the workflow can be effectively measured, thereby effectively realizing the effective monitoring and judgment of the cooling process of the cooling tower.

[0114] Embodiment 5:

[0115] On the basis of Example 4, this embodiment provides a model decision method applied to computational fluid dynamics analysis, which, after generating a workflow simulation model corresponding to the cooling tower when executing the workflow, further includes:

[0116] Retrieve the model verification set and model validation set;

[0117] Input the model verification set into the workflow simulation model to perform process simulation, and output the execution result data corresponding to each execution step based on the workflow simulation model;

[0118] The execution result data is matched with the model verification set, and the qualified judgment result of the workflow simulation model is output.

[0119] In this embodiment, the model verification set may be a data set used to perform process simulation on the workflow simulation model, and each execution step is simulated through the workflow simulation model, thereby outputting each execution result data after simulation.

[0120] In this embodiment, the model verification set may be a data set used to implement accuracy verification of the workflow simulation model. The model verification set may be a standard execution result corresponding to each execution step after simulating the workflow through the workflow simulation model based on the model verification set.

[0121] In this embodiment, the execution result data is matched with the model verification set to output the qualification judgment result of the workflow simulation model, including: matching the execution result data corresponding to each execution step with the model verification set to determine whether the workflow simulation model is qualified; if the execution result data corresponding to all execution steps matches the model verification set, the workflow simulation model is determined to be qualified; otherwise, the workflow simulation model is determined to be unqualified, and the workflow simulation model is optimized.

[0122] The beneficial effects of the above technical solution are: effectively realizing the verification of the workflow simulation model, thereby avoiding errors in the workflow simulation model when it is working, and effectively ensuring the accuracy and qualification of the operation of the workflow simulation model.

[0123] Embodiment 6:

[0124] Based on Example 5, this embodiment provides a model decision method applied to computational fluid dynamics analysis, which optimizes the workflow simulation model, including:

[0125] When the workflow simulation model is judged to be unqualified, the target execution steps corresponding to the mismatch between the execution result data and the model verification set are obtained;

[0126] Acquire the standard execution step corresponding to the target execution step, and at the same time, acquire first difference data between the target execution step and the standard execution step;

[0127] Obtain second difference data between the execution result data and the corresponding model verification set;

[0128] Read and analyze the first difference data and the second difference data, and output optimization data for the target execution step according to the reading and analysis results;

[0129] Optimize the optimization data in the target sub-execution model corresponding to the execution step, and output the target optimization sub-execution model corresponding to the optimization data according to the optimization result;

[0130] The target optimization sub-execution model is updated in the workflow simulation model to complete the optimization of the workflow simulation model.

[0131] In this embodiment, the target execution step is the execution step with an error, and the execution step without an error corresponding to the target execution step is the standard execution step, which is set in advance.

[0132] In this embodiment, the first difference data is data corresponding to the difference between the target execution step and the standard execution step.

[0133] In this embodiment, the second difference data may be data of a different portion between the execution result data and the corresponding model verification set.

[0134] In this embodiment, the correction direction of the target execution step, that is, the optimization data, can be effectively determined by the first difference data and the second difference data.

[0135] The beneficial effects of the above technical solution are: by determining the first difference data between the target execution step and the standard execution step, the difference point of the target execution step can be effectively determined, and by determining the execution result data and the corresponding model verification set, the difference data of the result can be determined. By doubly determining the difference data, the optimization data can be effectively determined, which lays the foundation for optimizing the target sub-execution model, thereby ensuring the effective update of the target optimization sub-execution model and improving the accuracy of the optimization of the target sub-execution model.

[0136] Embodiment 7:

[0137] On the basis of Example 1, this embodiment provides a model decision method applied to computational fluid dynamics analysis. In step 3, based on the fluid dynamics calculation and analysis working parameters, an evaluation result of the current workflow is output, and the next execution process of the cooling tower is assisted in decision making according to the evaluation result, including:

[0138] Retrieving a fluid dynamics calculation model and obtaining multiple calculation targets of the fluid dynamics calculation model;

[0139] Classifying the working parameters based on multiple calculation targets of the fluid dynamics calculation model and outputting multiple sub-working parameter sets;

[0140] Input each sub-operating parameter set into the fluid dynamics calculation model to perform calculations based on the corresponding calculation target, and output the calculation results corresponding to the calculation target;

[0141] Output the actual work progress corresponding to the current workflow based on the calculation target and the calculation result of the calculation target;

[0142] Based on the constraints of each calculation target and the actual work progress, the evaluation results of the current workflow are output, and the next execution process of the cooling tower is decided based on the evaluation results.

[0143] In this embodiment, the calculation target may be an indicator for determining different types of operating states in the cooling tower through a fluid dynamics calculation model, such as heat transfer efficiency and medium distribution.

[0144] In this embodiment, the sub-working parameter set may be a parameter set of multiple categories obtained by classifying the working parameters according to the calculation objectives. For example, the heat transfer efficiency may correspond to a sub-working parameter set, and the medium distribution condition may correspond to a sub-working parameter set.

[0145] In this embodiment, the actual working progress may be the actual treatment of water at different stages in the cooling tower.

[0146] In this embodiment, the limiting conditions are set in advance.

[0147] The beneficial effects of the above technical solution are: by determining multiple calculation targets of the fluid dynamics calculation model, the items that need to be evaluated in the cooling tower are locked; secondly, the working parameters of the cooling tower are classified by the calculation targets, and the classification results are calculated by the fluid dynamics calculation model, so as to accurately and effectively determine the actual treatment of water in different links of the cooling tower; finally, by calculating the limiting conditions of the mother package and the actual work progress, the operation of the current work flow in the cooling tower is effectively evaluated, thereby providing a reliable reference basis for the next execution process and improving the execution accuracy and reliability of the cooling tower.

[0148] Embodiment 8:

[0149] On the basis of Example 7, this embodiment provides a model decision method applied to computational fluid dynamics analysis, which outputs the evaluation result of the current workflow based on the limiting conditions and actual work progress of each calculation target, and assists in deciding the next execution process of the cooling tower according to the evaluation result, including:

[0150] Obtain the limiting conditions for each calculation target and match the limiting conditions with the actual work progress. Each calculation target corresponds to the completion status of the actual work progress.

[0151] When the completion status of each calculation target corresponding to the actual work progress reaches the specified condition, the next execution step corresponding to the current workflow is retrieved and used as the auxiliary decision result;

[0152] When the completion status of the actual work progress corresponding to the calculation target does not meet the limit conditions, the current workflow is used as the auxiliary decision result.

[0153] The beneficial effect of the above technical solution is: by matching the limiting conditions of the calculation target with the actual work progress, the completion status of the calculation target corresponding to the actual work progress can be effectively determined, thereby effectively realizing the effective evaluation of the current workflow, providing auxiliary decision-making results for the current workflow in the subsequent execution process, and effectively improving the working efficiency of the cooling tower.

[0154] Embodiment 9:

[0155] This embodiment provides a model decision system for computational fluid dynamics analysis, such as Figure 3 As shown, including:

[0156] A process determination module is used to obtain the work flow of the cooling tower;

[0157] A model building module, used for building a workflow simulation model according to the workflow of the cooling tower;

[0158] A simulation module is used to simulate the current workflow according to the workflow simulation model and output the working parameters;

[0159] The auxiliary decision-making module is used to analyze the working parameters based on fluid dynamics calculations, output the evaluation results of the current working process, and assist in deciding the next execution process of the cooling tower based on the evaluation results.

[0160] The beneficial effect of the above technical solution is: by determining the workflow of the cooling tower, the construction of the workflow simulation model can be effectively realized, and then the current workflow can be simulated, and the working parameters of the current workflow can be accurately and efficiently obtained, and then the working parameters can be analyzed through fluid dynamics calculation, and the evaluation results of the current workflow can be effectively output, and then the next execution process of the cooling tower can be assisted in decision-making based on the evaluation results, effectively improving the monitoring efficiency and accuracy of the cooling tower, and the working efficiency of the cooling tower can be effectively improved through auxiliary decision-making.

[0161] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A model decision method for computational fluid dynamics analysis, characterized in that: include: Step 1: Get the working process of cooling tower; Step 2: Construct a workflow simulation model based on the workflow of the cooling tower; Step 3: Simulate the current workflow according to the workflow simulation model and output the working parameters; Step 4: Analyze the working parameters based on fluid dynamics calculations, output the evaluation results of the current working process, and assist in deciding the next execution process of the cooling tower based on the evaluation results; In step 1, the workflow of the cooling tower is obtained, including: Obtaining factory parameters of the cooling tower, wherein the factory parameters include the water treatment link of the cooling tower and the configuration parameters of each treatment link; Analyze the factory parameters of the cooling tower to determine the logical relationship of the processing links and the link limiting conditions of the processing links; Generate the cooling tower workflow based on logical relationships and link constraints; In step 2, a workflow simulation model is constructed according to the workflow of the cooling tower, including: Analyze the workflow of the cooling tower and determine the execution steps of the workflow when cooling the cooling material in the cooling tower; Read the key execution points of each execution step in the cooling tower; Get the execution parameters of the key execution points; According to the key execution points of each step in the cooling tower and the execution parameters of the key execution points, the basic framework corresponding to each execution step is constructed; Obtain standard execution data for each execution step, and configure the basic framework of the execution step according to the execution data of each standard execution step; Output the sub-execution model corresponding to each execution step according to the configuration results; Read each execution step, determine the execution process of each execution step, and determine the execution flow chart between the execution steps according to the execution process of each execution step; The sub-execution models are merged according to the execution process to generate a workflow simulation model corresponding to the cooling tower when executing the workflow; Based on the fluid dynamics calculation and analysis of working parameters, the working parameters can be calculated to simulate the mechanical characteristics, thermal characteristics and motion characteristics of the actual work process in the cooling tower, so as to determine the current work progress through the mechanical characteristics, thermal characteristics and motion characteristics of the cooling tower, and then realize the auxiliary decision-making of the next execution process of the cooling tower; In step 3, based on the fluid dynamics calculation and analysis of the working parameters, the evaluation results of the current working process are output, and the next execution process of the cooling tower is assisted in decision-making according to the evaluation results, including: Retrieving a fluid dynamics calculation model and obtaining multiple calculation targets of the fluid dynamics calculation model; Classifying the working parameters based on multiple calculation targets of the fluid dynamics calculation model and outputting multiple sub-working parameter sets; Input each sub-operating parameter set into the fluid dynamics calculation model to perform calculations based on the corresponding calculation target, and output the calculation results corresponding to the calculation target; Output the actual work progress corresponding to the current workflow based on the calculation target and the calculation result of the calculation target; Based on the constraints of each calculation target and the actual work progress, the evaluation results of the current workflow are output, and the next execution process of the cooling tower is decided based on the evaluation results.

2. A model decision method for computational fluid dynamics analysis according to claim 1, characterized in that: Analyze the factory parameters of the cooling tower, including: Analyze the factory parameters of the cooling tower and determine the logical keywords and execution keywords of the processing links; Sort multiple processing links based on execution keywords, and determine the execution logic corresponding to each two adjacent processing links after sorting based on logic keywords; Determine the logical relationship between the processing links according to the sorting results and the execution logic corresponding to each two adjacent processing links; The configuration parameters of each processing link in the factory parameters of the cooling tower are analyzed, the constraint standards of each processing link are determined, and the constraint standards of each processing link are used as link limiting conditions of the corresponding processing link.

3. A model decision method for computational fluid dynamics analysis according to claim 1, characterized in that: After generating the corresponding workflow simulation model of the cooling tower when executing the workflow, it also includes: Retrieve the model verification set and model validation set; Input the model verification set into the workflow simulation model to perform process simulation, and output the execution result data corresponding to each execution step based on the workflow simulation model; The execution result data is matched with the model verification set, and the qualified judgment result of the workflow simulation model is output.

4. A model decision method for computational fluid dynamics analysis according to claim 3, characterized in that: According to the matching of the execution result data with the model verification set, the qualified judgment results of the workflow simulation model are output, including: Match the execution result data corresponding to each execution step with the model verification set to determine whether the workflow simulation model is qualified; If the execution result data corresponding to all execution steps match the model verification set, the workflow simulation model is judged to be qualified; Otherwise, the workflow simulation model is judged to be unqualified and the workflow simulation model is optimized.

5. A model decision method for computational fluid dynamics analysis according to claim 4, characterized in that: Optimize the workflow simulation model, including: When the workflow simulation model is judged to be unqualified, the target execution steps corresponding to the mismatch between the execution result data and the model verification set are obtained; Acquire the standard execution step corresponding to the target execution step, and at the same time, acquire first difference data between the target execution step and the standard execution step; Obtain second difference data between the execution result data and the corresponding model verification set; Read and analyze the first difference data and the second difference data, and output optimization data for the target execution step according to the reading and analysis results; Optimize the optimization data in the target sub-execution model corresponding to the execution step, and output the target optimization sub-execution model corresponding to the optimization data according to the optimization result; The target optimization sub-execution model is updated in the workflow simulation model to complete the optimization of the workflow simulation model.

6. The model decision method for computational fluid dynamics analysis according to claim 1, characterized in that: Based on the constraints and actual work progress of each calculation target, the evaluation results of the current workflow are output, and the next execution process of the cooling tower is decided based on the evaluation results, including: Obtain the limiting conditions for each calculation target and match the limiting conditions with the actual work progress. Each calculation target corresponds to the completion status of the actual work progress. When the completion status of each calculation target corresponding to the actual work progress reaches the specified condition, the next execution step corresponding to the current workflow is retrieved and used as the auxiliary decision result; When the completion status of the actual work progress corresponding to the calculation target does not meet the limit conditions, the current workflow is used as the auxiliary decision result.

7. A model decision system for computational fluid dynamics analysis, characterized in that: include: A process determination module is used to obtain the work flow of the cooling tower; A model building module, used for building a workflow simulation model according to the workflow of the cooling tower; A simulation module is used to simulate the current workflow according to the workflow simulation model and output the working parameters; The auxiliary decision-making module is used to analyze the working parameters based on fluid dynamics calculation, output the evaluation results of the current working process, and assist in deciding the next execution process of the cooling tower according to the evaluation results; In the process determination module, the workflow of the cooling tower is obtained, including: Obtaining factory parameters of the cooling tower, wherein the factory parameters include the water treatment link of the cooling tower and the configuration parameters of each treatment link; Analyze the factory parameters of the cooling tower to determine the logical relationship of the processing links and the link limiting conditions of the processing links; Generate the cooling tower workflow based on logical relationships and link constraints; In the model building module, a workflow simulation model is built according to the workflow of the cooling tower, including: Analyze the workflow of the cooling tower and determine the execution steps of the workflow when cooling the cooling material in the cooling tower; Read the key execution points of each execution step in the cooling tower; Get the execution parameters of the key execution points; According to the key execution points of each step in the cooling tower and the execution parameters of the key execution points, the basic framework corresponding to each execution step is constructed; Obtain standard execution data for each execution step, and configure the basic framework of the execution step according to the execution data of each standard execution step; Output the sub-execution model corresponding to each execution step according to the configuration results; Read each execution step, determine the execution process of each execution step, and determine the execution flow chart between the execution steps according to the execution process of each execution step; The sub-execution models are merged according to the execution process to generate a workflow simulation model corresponding to the cooling tower when executing the workflow; Based on the fluid dynamics calculation and analysis of working parameters, the working parameters can be calculated to simulate the mechanical characteristics, thermal characteristics and motion characteristics of the actual work process in the cooling tower, so as to determine the current work progress through the mechanical characteristics, thermal characteristics and motion characteristics of the cooling tower, and then realize the auxiliary decision-making of the next execution process of the cooling tower; In the simulation module, the working parameters are analyzed based on fluid dynamics calculations, and the evaluation results of the current workflow are output. Based on the evaluation results, the next execution process of the cooling tower is decided, including: Retrieving a fluid dynamics calculation model and obtaining multiple calculation targets of the fluid dynamics calculation model; Classifying the working parameters based on multiple calculation targets of the fluid dynamics calculation model and outputting multiple sub-working parameter sets; Input each sub-operating parameter set into the fluid dynamics calculation model to perform calculations based on the corresponding calculation target, and output the calculation results corresponding to the calculation target; Output the actual work progress corresponding to the current workflow based on the calculation target and the calculation result of the calculation target; Based on the constraints of each calculation target and the actual work progress, the evaluation results of the current workflow are output, and the next execution process of the cooling tower is decided based on the evaluation results.

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