CN114491751A - Flow field analysis system, flow field analysis method, and computer-readable storage medium - Google Patents

Flow field analysis system, flow field analysis method, and computer-readable storage medium Download PDF

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Publication number
CN114491751A
CN114491751A CN202210064667.2A CN202210064667A CN114491751A CN 114491751 A CN114491751 A CN 114491751A CN 202210064667 A CN202210064667 A CN 202210064667A CN 114491751 A CN114491751 A CN 114491751A
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dust removal
flow field
tunnel
model
simulation
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项杰
郑洪路
高承兴
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Sany Heavy Equipment Co Ltd
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Sany Heavy Equipment Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G06T17/205—Re-meshing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/08—Fluids

Abstract

The invention provides a flow field analysis system, a flow field analysis method and a computer readable storage medium, wherein the flow field analysis system comprises: the parameter acquisition module is used for acquiring tunnel simulation parameters and fan configuration parameters; the tunnel model establishing module is used for establishing a tunnel model according to the tunnel simulation parameters; the meshing module is used for meshing the tunnel model; the flow field calculation and output module is used for carrying out dust removal simulation according to the fan configuration parameters and the tunnel model subjected to grid division and outputting a dust removal simulation result; and the flow field optimization and output module is used for carrying out dust removal simulation correction based on the preset dust removal target and the dust removal simulation result until corrected tunnel simulation parameters and corrected fan configuration parameters meeting the preset dust removal target are obtained and output. According to the method and the device, various parameters are input to establish a tunnel model and calculate the flow field in the tunnel, and the current flow field is optimized, so that the parameter configuration with the best dust removal effect is finally obtained.

Description

Flow field analysis system, flow field analysis method, and computer-readable storage medium
Technical Field
The invention relates to the technical field of dust removal, in particular to a flow field analysis system, a flow field analysis method and a computer readable storage medium.
Background
At present, dry dust collectors are widely applied to the fields of coal mines, tunnels, non-coal mines and the like, and in the prior art, the configuration of the dry dust collectors is mostly subjected to a plurality of experiments or is configured according to previous successful cases and experiences, so that each device needs to be debugged, rectified, debugged and rectified again after being manufactured, and the process is labor-consuming, time-consuming, labor-consuming, expensive, low in efficiency and long in debugging period.
Therefore, how to provide a scheme for configuring a dry dust collector quickly and efficiently becomes a problem to be solved urgently.
Disclosure of Invention
In order to solve the above technical problem, a first aspect of the present invention provides a flow field analysis system.
The second aspect of the invention also provides a flow field analysis method.
The third aspect of the present invention also proposes a computer-readable storage medium.
In view of the above, the first aspect of the present invention provides a flow field analysis system, including: the parameter acquisition module is used for acquiring tunnel simulation parameters and fan configuration parameters; the tunnel model establishing module is used for establishing a tunnel model according to the tunnel simulation parameters; the meshing module is used for meshing the tunnel model; the flow field calculation and output module is used for carrying out dust removal simulation according to the fan configuration parameters and the tunnel model subjected to grid division and outputting a dust removal simulation result; and the flow field optimization and output module is used for carrying out dust removal simulation correction based on the preset dust removal target and the dust removal simulation result until corrected fan configuration parameters meeting the preset dust removal target are obtained and output.
According to the present invention, there is provided a flow field analysis system comprising: the system comprises a parameter acquisition module, a tunnel model establishing module, a grid dividing module, a flow field calculation and output module and a flow field optimization and output module. After the parameter acquisition module acquires the tunnel simulation parameters, the tunnel model establishment module builds a model according to the tunnel simulation parameters, establishes a tunnel model in reality in an equal proportion to facilitate the subsequent simulation of the dust distribution in the tunnel, then performs grid division on the established tunnel model through the grid division module to determine the calculation precision related to the flow field during dust removal simulation, acquires the fan configuration parameters through the parameter acquisition module after performing grid division on the tunnel model, further performs dust removal simulation according to the fan configuration parameters and combining the tunnel model after performing grid division through the flow field calculation and output module, and particularly, calculates the flow field in the tunnel model according to the fan configuration parameters to obtain the pressure, the flow rate, the flow velocity, the dust content/non-dust content gas pressure and the dust content gas pressure in the tunnel, The flow direction, the dust concentration and the distribution state are used as dust removal simulation results, namely, the wind field distribution in the tunnel is determined, the obtained dust removal simulation results are corrected by adopting a flow field optimization and processing module based on a preset dust removal target (the preset dust removal target is a dust removal effect meeting dust removal requirements, and the dust removal effect in the tunnel can be improved after parameter correction compared with the dust removal effect in the tunnel before parameter correction), namely, the parameter configuration with the best dust removal effect is obtained through iterative calculation and is used as a corrected fan configuration parameter, so that the configuration parameter with the best dust removal effect in the tunnel is determined, namely, a ventilation dust removal mode in the tunnel is determined. The application provides a flow field analysis system, which establishes a tunnel model and calculates the flow field in the tunnel by inputting various parameters, and finally obtains the parameter configuration with the best dust removal effect by optimizing the current flow field, further, in practical application, the equipment in the tunnel can be configured according to the finally obtained optimal parameter configuration, so that the dust removal effect of the dust remover is optimal when the dust remover works, and the dust remover does not need to be used in practice like the prior art, repeated debugging and modification are needed, which is labor-consuming, time-consuming, labor-consuming, expensive, inefficient and long in debugging period, the method directly simulates the field situation through the flow field analysis system, obtains the configuration parameters with the best dust removal effect, in practical application, the dust remover is only required to be configured according to a result obtained by simulation, so that the configuration process of the dust remover is quick and efficient.
When the grids are divided, the value of the grid density is in the range of 0-1, the smaller the value is, the larger the representative grid density is, and the longer the calculation time is; the larger the value is, the more sparse the representative grid density is, the shorter the calculation time is, but the phenomenon of non-convergence possibly occurs due to too sparse, in the flow field analysis system of the invention, the grid density is determined according to multiple times of simulation and experiments and is written in a program without setting.
In addition, the flow field analysis system in the above technical solution provided by the present invention may further have the following additional technical features:
in the technical scheme, the tunnel simulation parameters comprise the shape and size of the tunnel, the position of a dust generating point and the dust generating amount; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet; the corrected fan configuration parameters are parameters obtained by correcting the size and the position of the air supply opening, the size and the position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet.
In the technical scheme, tunnel simulation parameters comprise the shape and the size of the tunnel, the position and the dust production amount of a dust production point, so that the interior of the tunnel is known, and an object is positioned according to different positions and sizes so as to establish a tunnel model; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet, so that an initial variable is provided for the air flow in the tunnel model, and the flow field calculation in the tunnel model is carried out; the corrected fan configuration parameters are the size and position of the air supply opening, the size and position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet, which are obtained after optimization and correction, namely, the flow field analysis system corrects the input fan configuration parameters to correct the parameter configuration with the original non-optimal dust removal effect into the parameter configuration with the optimal dust removal effect, and the actual configuration of the dust remover according to the corrected parameters can enable the dust removal effect of the dust remover to be optimal.
In the above technical solution, the parameter obtaining module is further configured to obtain a corrected fan configuration parameter; and the flow field calculation and output module is also used for carrying out dust removal simulation according to the corrected fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result.
In the technical scheme, after the corrected fan configuration parameters are obtained, the parameter input, model establishment, grid division and dust removal simulation steps in the technical scheme are repeatedly executed according to the corrected fan configuration parameters, so that the dust removal simulation result of the corrected parameters is observed through the flow field analysis system, the result can be compared with the unmodified simulation result, the change of the dust removal effect before and after correction is observed, and whether the dust removal effect is better due to the corrected parameter configuration can be verified.
In the technical scheme, a SIMPLEC algorithm is adopted when the flow field calculation and output module carries out dust removal simulation; the flow field optimization and output module carries out dust removal simulation correction based on a preset dust removal target and a dust removal simulation result, specifically, a real number coding technology, a variable precision crossover operator and a dynamic punishment are adopted to process, calculate and solve the fan configuration parameters to obtain corrected fan configuration parameters and output the corrected fan configuration parameters.
In the technical scheme, the adopted fluid model is an incompressible ideal fluid with viscosity neglected in a steady state, in the prior art, a discrete equation based on a finite volume method is mostly adopted for flow field calculation, and unstructured grid division is more suitable for three-dimensional flow field calculation, so that a SIMPLEC algorithm suitable for steady state calculation on an unstructured grid is adopted when the flow field is calculated; the real number coding technology is adopted during dust removal simulation correction, so that all genetic operations are directly carried out in a problem space, the defect of adopting binary coding in the existing genetic algorithm can be overcome, and the performance of the optimization algorithm is improved. The operator in the genetic algorithm that plays a core role is the crossover operator, which determines the search capability of the genetic algorithm. The variable precision principle is a two-stage search strategy which is provided aiming at the problem of long search time caused by large search space, when the algorithm is in a primary optimization stage, the algorithm searches in a large range, and is convenient to quickly approach to an optimal solution. When the algorithm is in the second-level optimization stage, fine search is carried out, and the optimal solution is conveniently found near the better solution. The dynamic penalty is used in conjunction with variable precision searches. Because the discrete degree of the search point in the solution space is larger during the primary optimization, the optimal solution is likely to be lost; in the second-level optimization, the discrete degree of the search point is small, the difference between the feasible solutions is not large, and the convergence is possibly slow. Aiming at the problems, in the primary optimization stage, the algorithm is expected to collect global information as much as possible in the value range of the design variable, so that less punishment is applied to the design point which violates the constraint condition; in the second-level optimization stage, it is desirable to obtain as fine a design result as possible with high computational efficiency, so that a large penalty is imposed on the design point against the constraint.
In any of the above technical solutions, the flow field analysis system further includes: and the human-computer interaction unit is used for selecting a display mode of the dedusting simulation result image, wherein the display mode of the flow field image comprises displaying a three-dimensional model, displaying an XZ plane cutting model and a model section, displaying a YZ plane cutting model and a model section, displaying an XY plane cutting model and a model section, and an XYZ coordinate system is arranged on a display interface, wherein the X axis is rightward, the Y axis is vertically inward, and the Z axis is upward.
In the technical scheme, the flow field analysis system further comprises a human-computer interaction unit, the three-dimensional image, the front view, the side view and the vertical view can be selectively observed, the position of the observation section can be randomly set, the view to be observed can be selected by setting the human-computer interaction unit, the result of dust removal simulation at multiple visual angles and multiple angles is observed, and the dust removal effect is conveniently judged.
In any of the above technical solutions, the outputted dust removal simulation result includes: and displaying an image of the dust removal simulation result, wherein the image comprises one or more of pressure, flow speed, flow direction, dust concentration and distribution state information of the dust-containing gas in the tunnel.
In the technical scheme, the dust removal simulation result is output to display the dust removal simulation image, and one or more information of pressure, flow velocity, flow direction, dust concentration and distribution state of dust-containing gas in the tunnel can be observed in the image, so that the flow field in the tunnel model can be better observed, the distribution of dust in the tunnel model can be known, the concentrations of dust at different positions can be known, and the dust removal effect of current parameter configuration can be better observed.
A second aspect of the present invention provides a flow field analysis method, comprising: acquiring tunnel simulation parameters; establishing a tunnel model according to the tunnel simulation parameters; carrying out mesh division on the tunnel model; acquiring fan configuration parameters; carrying out dust removal simulation according to the fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result; and carrying out dust removal simulation correction based on the preset dust removal target and the dust removal simulation result until a corrected fan configuration parameter meeting the preset dust removal target is obtained and output.
According to the flow field analysis method provided by the technical scheme of the invention, after tunnel simulation parameters are obtained, modeling is carried out according to the tunnel simulation parameters, a tunnel model is built in an actual tunnel model in an equal proportion mode so as to facilitate the subsequent simulation of the dust distribution in the tunnel, then the built tunnel model is subjected to grid division so as to determine the calculation precision related to the flow field during dust removal simulation, after the tunnel model is subjected to grid division, fan configuration parameters are obtained, then dust removal simulation is carried out according to the fan configuration parameters and in combination with the tunnel model subjected to grid division, specifically, the flow field in the tunnel model is calculated according to the fan configuration parameters to obtain the pressure, the flow rate, the flow direction, the dust concentration and the distribution state of dust-containing/non-dust-containing gas in the tunnel as the dust removal simulation result, namely, the wind field distribution in the tunnel is determined, and then correcting the obtained dust removal simulation result based on a preset dust removal target (the preset dust removal target is a dust removal effect meeting the dust removal requirement, and the dust removal effect in the tunnel can be improved after the parameter correction compared with the parameter before the parameter correction), namely obtaining the parameter configuration with the best dust removal effect through iterative calculation as a corrected fan configuration parameter, so as to determine the configuration parameter with the best dust removal effect in the tunnel, namely determine the ventilation dust removal mode in the tunnel. The application establishes a tunnel model and calculates the flow field in the tunnel by inputting various parameters by providing a flow field analysis method, and finally obtains the parameter configuration with the best dust removal effect by optimizing the current flow field, further, in practical application, the equipment in the tunnel can be configured according to the finally obtained optimal parameter configuration, so that the dust removal effect of the dust remover is optimal when the dust remover works, and the dust remover does not need to be used in practice like the prior art, repeated debugging and modification are needed, which is labor-consuming, time-consuming, labor-consuming, expensive, inefficient and long in debugging period, the application directly simulates the field situation through a flow field analysis method, obtains configuration parameters with the best dust removal effect, in practical application, the dust remover is only required to be configured according to a result obtained by simulation, so that the configuration process of the dust remover is quick and efficient.
When the grids are divided, the value of the grid density is in the range of 0-1, the smaller the value is, the larger the representative grid density is, and the longer the calculation time is; the larger the value is, the more sparse the representative grid density is, the shorter the calculation time is, but the phenomenon of non-convergence possibly occurs due to too sparse, in the flow field analysis system of the invention, the grid density is determined according to multiple times of simulation and experiments and is written in a program without setting.
In any of the above technical solutions, the tunnel simulation parameters include the shape and size of the tunnel, the position of the dust-producing point and the dust-producing amount; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet; the corrected fan configuration parameters are parameters obtained by correcting the size and position of the air supply opening, the size and position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet.
In the technical scheme, tunnel simulation parameters comprise the shape and the size of the tunnel, the position and the dust production amount of a dust production point, so that the interior of the tunnel is known, and an object is positioned according to different positions and sizes so as to establish a tunnel model; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet, so that an initial variable is provided for the air flow in the tunnel model, and the flow field calculation in the tunnel model is performed conveniently; the corrected fan configuration parameters are the size and position of the air supply opening, the size and position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet, which are obtained after optimization and correction, namely, the flow field analysis system corrects the input fan configuration parameters to correct the parameter configuration with the original non-optimal dust removal effect into the parameter configuration with the optimal dust removal effect, and the actual configuration of the dust remover according to the corrected parameters can enable the dust removal effect of the dust remover to be optimal.
In any of the above technical solutions, the flow field analysis method further includes: acquiring configuration parameters of a corrected fan; and carrying out dust removal simulation according to the corrected fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result.
In the technical scheme, after the corrected fan configuration parameters are obtained, the parameter input, model establishment, grid division and dust removal simulation steps in the technical scheme are repeatedly executed according to the corrected fan configuration parameters, so that the dust removal simulation result of the corrected parameters is observed through the flow field analysis system, the result can be compared with the uncorrected simulation result, the change of the dust removal effect before and after correction is observed, and whether the dust removal effect is better due to the corrected parameter configuration can be verified.
In any of the above technical solutions, a simple algorithm is adopted when dust removal simulation is performed; and the dust removal simulation correction is specifically carried out on the basis of the preset dust removal target and the dust removal simulation result by adopting a real number coding technology, a variable precision cross operator and a dynamic penalty to process, calculate and solve the configuration parameters of the fan to be corrected, and output the configuration parameters.
In the technical scheme, the adopted fluid model is an incompressible ideal fluid with viscosity neglected in a steady state, in the prior art, a discrete equation based on a finite volume method is mostly adopted for flow field calculation, and unstructured grid division is more suitable for three-dimensional flow field calculation, so that a SIMPLEC algorithm suitable for steady state calculation on an unstructured grid is adopted when the flow field is calculated; the real number coding technology is adopted during dust removal simulation correction, so that all genetic operations are directly carried out in a problem space, the defect of adopting binary coding in the existing genetic algorithm can be overcome, and the performance of the optimization algorithm is improved. The operator in the genetic algorithm that plays a core role is the crossover operator, which determines the search capability of the genetic algorithm. The variable precision principle is a two-stage search strategy which is provided aiming at the problem of long search time caused by large search space, when the algorithm is in a primary optimization stage, the algorithm searches in a large range, and is convenient to quickly approach to an optimal solution. When the algorithm is in the second-level optimization stage, fine search is carried out, and the optimal solution is conveniently found near the better solution. The dynamic penalty is used in conjunction with variable precision searches. Because the discrete degree of the search point in the solution space is larger during the primary optimization, the optimal solution is likely to be lost; in the second-level optimization, the discrete degree of the search points is small, the difference between the feasible solutions is small, and the convergence is possibly slow. Aiming at the problems, in the primary optimization stage, the algorithm is expected to collect global information as much as possible in the value range of the design variable, so that less punishment is applied to the design point which violates the constraint condition; in the second-level optimization stage, it is desirable to obtain design results as fine as possible with high computational efficiency, so that a large penalty is imposed on the design point violating the constraint.
In any of the above technical solutions, the flow field analysis method further includes: selecting a display mode of a dedusting simulation result image, wherein the display mode of the flow field image comprises displaying a three-dimensional model, displaying an XZ plane cutting model and a model section, displaying a model section on a YZ plane cutting model and a model section, and displaying an XY plane cutting model and a model section, and an XYZ coordinate system is arranged on a display interface, wherein the X axis is rightward, the Y axis is vertically inward, and the Z axis is upward.
In the technical scheme, the flow field analysis method further comprises the steps of selecting and observing a three-dimensional view, a front view, a side view and a vertical view, and optionally setting the position of an observation section, so that the observed view can be selected by arranging the man-machine interaction unit, the result of dust removal simulation at multiple visual angles and multiple angles is observed, and the dust removal effect is conveniently judged.
In any of the above technical solutions, the outputted dust removal simulation result includes: and displaying an image of the dust removal simulation result, wherein the image comprises one or more of pressure, flow speed, flow direction, dust concentration and distribution state information of the dust-containing gas in the tunnel.
In the technical scheme, the dust removal simulation result is output to display the dust removal simulation image, and one or more information of pressure, flow velocity, flow direction, dust concentration and distribution state of dust-containing gas in the tunnel can be observed in the image, so that the flow field in the tunnel model can be better observed, the distribution of dust in the tunnel model can be known, the concentrations of dust at different positions can be known, and the dust removal effect of current parameter configuration can be better observed.
A third aspect of the present invention provides a computer-readable storage medium, on which a program or instructions are stored, and the program or instructions, when executed by a processor, implement the steps of the flow field analysis method in any one of the above-mentioned technical solutions.
According to the computer-readable storage medium provided in the technical solution of the present invention, since the program or the instructions stored thereon can be executed by the processor to implement the steps of the flow field analysis method in any of the above technical solutions, all the beneficial technical effects of the flow field analysis method are achieved, and are not described herein again.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 shows a block diagram of a flow field analysis system of one embodiment of the present invention;
FIG. 2 shows a schematic flow diagram of a flow field analysis method of yet another embodiment of the present invention;
FIG. 3 shows a schematic view of a display interface of flow field analysis software according to one embodiment of the invention;
FIG. 4a is a schematic diagram showing the output image of the flow field analysis software according to one embodiment of the present invention;
FIG. 4b shows a schematic image of the output of the flow field analysis software according to one embodiment of the present invention;
FIG. 4c shows a graphical representation of the output of the flow field analysis software according to one embodiment of the present invention;
FIG. 4d shows a schematic image of the output of the flow field analysis software according to one embodiment of the present invention.
Wherein, the correspondence between the reference numbers and the component names in fig. 1 and 3 is:
100 flow field analysis system, 102 parameter acquisition module, 104 tunnel model establishment module, 106 grid division module, 108 flow field calculation and output module, 110 flow field optimization and output module, 302 human-computer interaction module, 304 parameter input module, 306 calculation control module, 308 display module, 310 main display interface, 312 function selection module.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
A flow field analysis system, flow field analysis software, and a computer-readable storage medium in some embodiments of the invention are described below with reference to fig. 1-4 d.
In view of this, an embodiment of the first aspect of the present invention provides a flow field analysis system 100, as shown in fig. 1, including: the parameter acquisition module 102 is used for acquiring tunnel simulation parameters and fan configuration parameters; a tunnel model establishing module 104, configured to establish a tunnel model according to the tunnel simulation parameters; a meshing module 106, configured to perform meshing on the tunnel model; the flow field calculation and output module 108 is used for carrying out dust removal simulation according to the fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result; and the flow field optimization and output module 110 performs dust removal simulation correction based on the preset dust removal target and the dust removal simulation result until the corrected fan configuration parameters meeting the preset dust removal target are obtained and output.
The flow field analysis system 100 provided according to the present invention includes: the system comprises a parameter acquisition module 102, a tunnel model establishment module 104, a mesh division module 106, a flow field calculation and output module 108 and a flow field optimization and output module 110. After the parameter obtaining module 102 obtains the tunnel simulation parameters, the tunnel model establishing module 104 builds a model according to the tunnel simulation parameters, establishes a tunnel model in reality in an equal proportion to facilitate subsequent simulation of dust distribution in the tunnel, then performs meshing on the established tunnel model through the meshing module 106 to determine the calculation precision related to the flow field when performing dust removal simulation, obtains the fan configuration parameters through the parameter obtaining module 102 after performing meshing on the tunnel model, further performs dust removal simulation according to the fan configuration parameters and combining with the tunnel model after performing meshing through the flow field calculation and output module 108, and specifically, the flow field calculation and output module 108 calculates the flow field in the tunnel model according to the fan configuration parameters to obtain the pressure of dust/non-dust-containing gas in the tunnel, The flow velocity, the flow direction, the dust concentration and the distribution state are used as dust removal simulation results, namely, the wind field distribution in the tunnel is determined, the obtained dust removal simulation results are corrected by adopting a flow field optimization and processing module based on a preset dust removal target (the preset dust removal target is a dust removal effect meeting dust removal requirements, and the dust removal effect in the tunnel can be improved after parameter correction compared with that before parameter correction), namely, the parameter configuration with the best dust removal effect is obtained through iterative calculation and is used as a corrected fan configuration parameter, so that the configuration parameter with the best dust removal effect in the tunnel is determined, namely, a ventilation dust removal mode in the tunnel is determined. The present application provides a flow field analysis system 100, which establishes a tunnel model and calculates a flow field in a tunnel by inputting various parameters, and finally obtains the parameter configuration with the best dust removal effect by optimizing the current flow field, further, in practical application, the equipment in the tunnel can be configured according to the finally obtained optimal parameter configuration, so that the dust removal effect of the dust remover is optimal when the dust remover works, and the dust remover does not need to be used in practice like the prior art, repeated debugging and modification are needed, which is labor-consuming, time-consuming, labor-consuming, expensive, inefficient and long in debugging period, the flow field analysis system 100 directly simulates the field situation, and obtains configuration parameters with the best dust removal effect, in practical application, the dust remover is only required to be configured according to a result obtained by simulation, so that the configuration process of the dust remover is quick and efficient.
When the grids are divided, the value of the grid density is in the range of 0-1, the smaller the value is, the larger the representative grid density is, and the longer the calculation time is; the larger the value is, the more sparse the representative grid density is, the shorter the calculation time is, but the too sparse phenomenon may occur the non-convergence phenomenon, in the flow field analysis system 100 of the present invention, the grid density has been determined according to multiple simulations and experiments and written in the program, and does not need to be set.
In the above embodiment, the tunnel simulation parameters include the tunnel shape and size, the dust generation point position and the dust generation amount; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet; the corrected fan configuration parameters are parameters obtained by correcting the size and the position of the air supply opening, the size and the position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet.
In the embodiment, the tunnel simulation parameters comprise the shape and the size of the tunnel, the position and the dust production amount of the dust production point, so that the inside of the tunnel is known, and the object is positioned according to different positions and sizes so as to establish a tunnel model; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet, so that an initial variable is provided for the air flow in the tunnel model, and the flow field calculation in the tunnel model is carried out; the corrected fan configuration parameters are the size and position of the air supply opening, the size and position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet, which are obtained after optimization and correction, that is, the flow field analysis system 100 corrects the input fan configuration parameters to correct the parameter configuration with the originally non-optimal dust removal effect into the parameter configuration with the optimal dust removal effect, and the configuration of the actual dust remover according to the corrected parameters can enable the dust removal effect of the dust remover to be optimal.
In the above embodiment, the parameter obtaining module 102 is further configured to obtain a corrected fan configuration parameter; the tunnel model building module 104, the flow field calculating and outputting module 108 is further configured to perform a dust removal simulation according to the corrected fan configuration parameters and the tunnel model after grid division, and output a dust removal simulation result.
In this embodiment, after the corrected fan configuration parameters are obtained, the parameter input, model establishment, mesh division, and dust removal simulation steps in the above technical scheme are repeatedly performed according to the corrected fan configuration parameters, so that the dust removal simulation result of the corrected parameters is observed through the flow field analysis system 100, the result can be compared with the unmodified simulation result, the change of the dust removal effect before and after correction is observed, and whether the dust removal effect is better due to the corrected parameter configuration can be verified.
In the above embodiment, the simple algorithm is adopted when the flow field calculation and output module 108 performs the dust removal simulation; the flow field optimization and output module 110 performs dust removal simulation correction based on the preset dust removal target and the dust removal simulation result, specifically, the real number encoding technology, the variable precision crossover operator and the dynamic penalty are adopted to process, calculate and solve the fan configuration parameters to obtain corrected fan configuration parameters, and the corrected fan configuration parameters are output.
In the embodiment, the adopted fluid model is an incompressible ideal fluid with viscosity neglected in a steady state, in the prior art, a discrete equation based on a finite volume method is mostly adopted for flow field calculation, and unstructured grid division is more suitable for three-dimensional flow field calculation, so that a SIMPLEC algorithm suitable for steady state calculation on unstructured grids is adopted when the flow field is calculated; the real number coding technology is adopted during dust removal simulation correction, so that all genetic operations are directly carried out in a problem space, the defect of adopting binary coding in the existing genetic algorithm can be overcome, and the performance of the optimization algorithm is improved. The operator in the genetic algorithm that plays a core role is the crossover operator, which determines the search capability of the genetic algorithm. The variable precision principle is a two-stage search strategy which is provided aiming at the problem of long search time caused by large search space, when the algorithm is in a primary optimization stage, the algorithm searches in a large range, and is convenient to quickly approach to an optimal solution. When the algorithm is in the second-level optimization stage, fine search is carried out, and the optimal solution is conveniently found near the better solution. The dynamic penalty is used in conjunction with a variable precision search. Because the discrete degree of the search point in the solution space is larger during the primary optimization, the optimal solution is likely to be lost; in the second-level optimization, the discrete degree of the search points is small, the difference between the feasible solutions is small, and the convergence is possibly slow. Aiming at the problems, in the primary optimization stage, the algorithm is expected to collect global information as much as possible in the value range of the design variable, so that less punishment is applied to the design point which violates the constraint condition; in the second-level optimization stage, it is desirable to obtain design results as fine as possible with high computational efficiency, so that a large penalty is imposed on the design point violating the constraint.
In any of the above embodiments, the flow field analysis system 100 further comprises: and the human-computer interaction unit is used for selecting a display mode of the dedusting simulation result image, wherein the display mode of the flow field image comprises displaying a three-dimensional model, displaying an XZ plane cutting model and a model section, displaying a YZ plane cutting model and a model section, displaying an XY plane cutting model and a model section, and an XYZ coordinate system is arranged on a display interface, wherein the X axis is rightward, the Y axis is vertically inward, and the Z axis is upward.
In this embodiment, the flow field analysis system 100 further includes a human-computer interaction unit, which can selectively observe the three-dimensional view, the front view, the side view, and the vertical view, and can arbitrarily set the position of the observation cross section, so that the observed view can be selected by setting the human-computer interaction unit, and the result of the dust removal simulation can be observed at multiple viewing angles and multiple angles, thereby facilitating the judgment of the dust removal effect.
In any of the above embodiments, the output dust removal simulation result includes: and displaying an image of the dust removal simulation result, wherein the image comprises one or more of pressure, flow speed, flow direction, dust concentration and distribution state information of the dust-containing gas in the tunnel.
In this embodiment, the output of the dust removal simulation result is to display an image of the dust removal simulation, and one or more of the pressure, the flow velocity, the flow direction, the dust concentration and the distribution state of the dust-containing gas in the tunnel can be observed in the image, so that the flow field in the tunnel model can be better observed, how the dust is distributed in the tunnel model can be known, and how the dust concentration of the dust at different positions can be better observed, so that the dust removal effect of the current parameter configuration can be better observed.
A second aspect embodiment of the present invention provides a flow field analysis method, as shown in fig. 2, including:
s202, acquiring tunnel simulation parameters;
s204, establishing a tunnel model according to the tunnel simulation parameters;
s206, carrying out mesh division on the tunnel model;
s208, acquiring fan configuration parameters;
s210, carrying out dust removal simulation according to the fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result;
and S212, performing dust removal simulation correction based on the preset dust removal target and the dust removal simulation result until corrected fan configuration parameters meeting the preset dust removal target are obtained and output.
According to the flow field analysis method provided by the embodiment of the invention, after tunnel simulation parameters are obtained, modeling is carried out according to the tunnel simulation parameters, a tunnel model is established in an equal proportion in the real tunnel model so as to facilitate the subsequent simulation of the dust distribution in the tunnel, then the established tunnel model is subjected to grid division so as to determine the calculation precision related to the flow field when dust removal simulation is carried out, after the tunnel model is subjected to grid division, fan configuration parameters are obtained, then dust removal simulation is carried out according to the fan configuration parameters and in combination with the tunnel model subjected to grid division, specifically, the flow field in the tunnel model is calculated according to the fan configuration parameters to obtain the pressure, the flow speed, the flow direction, the dust concentration and the distribution state of dust contained/non-dust-contained gas in the tunnel as the dust removal simulation result, namely the wind field distribution in the tunnel is determined, and then correcting the obtained dust removal simulation result based on a preset dust removal target (the preset dust removal target is a dust removal effect meeting the dust removal requirement, and the dust removal effect in the tunnel can be improved after the parameter correction compared with the parameter before the parameter correction), namely obtaining the parameter configuration with the best dust removal effect through iterative calculation as a corrected fan configuration parameter, so as to determine the configuration parameter with the best dust removal effect in the tunnel, namely determine the ventilation dust removal mode in the tunnel. The application establishes a tunnel model and calculates the flow field in the tunnel by inputting various parameters by providing a flow field analysis method, and finally obtains the parameter configuration with the best dust removal effect by optimizing the current flow field, further, in practical application, the equipment in the tunnel can be configured according to the finally obtained optimal parameter configuration, so that the dust removal effect of the dust remover is optimal when the dust remover works, and the dust remover does not need to be used in practice like the prior art, repeated debugging and modification are needed, which is labor-consuming, time-consuming, labor-consuming, expensive, inefficient and long in debugging period, the method directly simulates the field situation through a flow field analysis method, obtains configuration parameters with the best dust removal effect, in practical application, the dust remover is only required to be configured according to a result obtained by simulation, so that the configuration process of the dust remover is quick and efficient.
When the grids are divided, the value of the grid density is in the range of 0-1, the smaller the value is, the larger the representative grid density is, and the longer the calculation time is; the larger the value is, the more sparse the representative grid density is, the shorter the calculation time is, but the phenomenon of non-convergence possibly occurs due to too sparse, in the flow field analysis system of the invention, the grid density is determined according to multiple times of simulation and experiments and is written in a program without setting.
In any of the above embodiments, the tunnel simulation parameters include tunnel shape and size, dust point location and dust yield; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet; the corrected fan configuration parameters are parameters obtained by correcting the size and the position of the air supply opening, the size and the position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet.
In the embodiment, the tunnel simulation parameters comprise the shape and the size of the tunnel, the position and the dust production amount of the dust production point, so that the inside of the tunnel is known, and the object is positioned according to different positions and sizes so as to establish a tunnel model; the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet, so that an initial variable is provided for the air flow in the tunnel model, and the flow field calculation in the tunnel model is carried out; the corrected fan configuration parameters are the size and position of the air supply opening, the size and position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet, which are obtained after optimization and correction, namely, the flow field analysis system corrects the input fan configuration parameters to correct the parameter configuration with the original non-optimal dust removal effect into the parameter configuration with the optimal dust removal effect, and the actual configuration of the dust remover according to the corrected parameters can enable the dust removal effect of the dust remover to be optimal.
In any of the above embodiments, the flow field analysis method further comprises: acquiring configuration parameters of a corrected fan; and carrying out dust removal simulation according to the corrected fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result.
In this embodiment, after the corrected fan configuration parameters are obtained, the parameter input, model establishment, mesh division and dust removal simulation steps in the above technical scheme are repeatedly executed according to the corrected fan configuration parameters, so that the dust removal simulation result of the corrected parameters is observed through the flow field analysis system, the result can be compared with the unmodified simulation result, the change of the dust removal effect before and after correction is observed, and whether the dust removal effect is better due to the corrected parameter configuration can be verified.
In any of the above embodiments, the simple algorithm is used for the dust removal simulation; and the dust removal simulation correction is specifically carried out on the basis of the preset dust removal target and the dust removal simulation result by adopting a real number coding technology, a variable precision cross operator and a dynamic penalty to process, calculate and solve the configuration parameters of the fan to be corrected, and output the configuration parameters.
In the embodiment, the adopted fluid model is an incompressible ideal fluid with viscosity neglected in a steady state, in the prior art, a discrete equation based on a finite volume method is mostly adopted for flow field calculation, and unstructured grid division is more suitable for three-dimensional flow field calculation, so that a SIMPLEC algorithm suitable for steady state calculation on unstructured grids is adopted when the flow field is calculated; the real number coding technology is adopted during dust removal simulation correction, so that all genetic operations are directly carried out in a problem space, the defect of adopting binary coding in the existing genetic algorithm can be overcome, and the performance of the optimization algorithm is improved. The operator in the genetic algorithm that plays a core role is the crossover operator, which determines the search capability of the genetic algorithm. The variable precision principle is a two-stage search strategy which is provided aiming at the problem of long search time caused by large search space, when the algorithm is in a primary optimization stage, the algorithm searches in a large range, and is convenient to quickly approach to an optimal solution. When the algorithm is in the second-level optimization stage, fine search is carried out, and the optimal solution is conveniently found near the better solution. The dynamic penalty is used in conjunction with variable precision searches. Because the discrete degree of the search point in the solution space is larger during the primary optimization, the optimal solution is likely to be lost; in the second-level optimization, the discrete degree of the search points is small, the difference between the feasible solutions is small, and the convergence is possibly slow. Aiming at the problems, in the primary optimization stage, the algorithm is expected to collect global information as much as possible in the value range of the design variable, so that the design point which violates the constraint condition is given a smaller penalty; in the second-level optimization stage, it is desirable to obtain design results as fine as possible with high computational efficiency, so that a large penalty is imposed on the design point violating the constraint.
In any of the above embodiments, the flow field analysis method further comprises: and selecting a display mode of a dedusting simulation result image, wherein the display mode of the flow field image comprises displaying a three-dimensional model, displaying an XZ plane cutting model and displaying a model section, displaying a YZ plane cutting model and displaying a model section, and displaying an XY plane cutting model and a model section, wherein an X-axis is rightward, a Y-axis is vertically inward, and a Z-axis is upward on a display interface.
In this embodiment, the flow field analysis method further includes that the three-dimensional view, the front view, the side view and the vertical view can be selectively observed, and the position of the observation section can be set arbitrarily, so that the observed view can be selected by setting the human-computer interaction unit, the result of the dust removal simulation can be observed in multiple visual angles and multiple angles, and the dust removal effect can be judged conveniently.
In any of the above embodiments, the output dust removal simulation result includes: and displaying an image of the dust removal simulation result, wherein the image comprises one or more of pressure, flow speed, flow direction, dust concentration and distribution state information of the dust-containing gas in the tunnel.
In this embodiment, the output of the dust removal simulation result is to display an image of the dust removal simulation, and one or more of the pressure, the flow velocity, the flow direction, the dust concentration and the distribution state of the dust-containing gas in the tunnel can be observed in the image, so that the flow field in the tunnel model can be better observed, how the dust is distributed in the tunnel model can be known, and how the dust concentration of the dust at different positions can be better observed, so that the dust removal effect of the current parameter configuration can be better observed.
A third aspect of the present invention provides a computer readable storage medium having stored thereon a program or instructions which, when executed by a processor, implement the steps of the flow field analysis method in any of the embodiments described above.
According to the computer-readable storage medium provided by the embodiment of the present invention, since the program or the instructions stored thereon can implement the steps of the flow field analysis method in any of the embodiments described above when being executed by the processor, all the beneficial technical effects of the flow field analysis method described above are achieved, and are not described herein again.
The flow field analysis system and the flow field analysis method provided by the present application will be further described with reference to a specific embodiment.
In another aspect, embodiments of the present invention provide flow field analysis software, which employs the flow field analysis system and the flow analysis method in the foregoing embodiments. The display interface of the flow field analysis software is shown in fig. 3, and includes a human-computer interaction module 302, a parameter input module 304, a calculation control module 306, a display module 308, a main display module 310, and a function selection module 312. The human-computer interaction module 302 is used for selecting a display mode of a dust removal simulation result image, wherein the "SHOW-3D" represents that a three-dimensional model is displayed, the "X-PLANE" represents that the model is cut by an XZ PLANE and a model section is displayed, the "Y-PLANE" represents that the model is cut by a YZ PLANE and a model section is displayed, and the "Z-PLANE" represents that the model is cut by an XY PLANE and a model section is displayed. The X axis of an XYZ coordinate system relative to a display interface is right, the Y axis is vertical to the screen inwards, the Z axis is upward, a three-dimensional image, a front view, a side view and a vertical view can be selectively observed through the module, the position of an observation section can be randomly set, so that the view for observation can be selected through the arrangement of the man-machine interaction module, the result of dust removal simulation at multiple visual angles and multiple angles is observed, and the dust removal effect is conveniently judged. The parameter input module 304 is used for inputting parameters for tunnel model building and flow field calculation. The calculation control module 306 is configured to select whether the calculation is a single calculation or an optimized calculation, where the single calculation only needs to calculate a flow field and output a dust removal simulation image, and the optimized calculation needs to perform optimization processing to output modified configuration parameters, that is, the size and the position of the air inlet, the size and the position of the air outlet, the air speed of the air inlet, and the air speed of the air outlet. The display module 308 is used for selecting the image type, i.e. selecting and displaying all the example velocity distribution images, air distribution images or dust distribution images in the tunnel model. The main display module 310 is configured to display images of tunnel simulation and wind field simulation in a tunnel, and as shown in fig. 4a, 4b, 4c, and 4d, the main display module is a dust removal simulation image in which air is supplied to a rectangular tunnel on a left wall surface, and air is discharged on a right wall surface in sequence, i.e., a three-dimensional view, a side view, a front view, and a top view. The function selection module 312 can drag, rotate, and zoom the model in different ways, for example, pressing the left button of the mouse is translation, pressing the right button of the mouse is rotation, and pressing the middle button of the mouse is zoom. The flow field analysis software establishes a tunnel model and calculates a flow field in the tunnel by inputting various parameters, optimizes the current flow field to finally obtain the parameter configuration with the best dust removal effect, and further can configure instruments in the tunnel according to the finally obtained optimal parameter configuration in practical application to ensure that the dust removal effect of the dust remover is the best when the dust remover works.
In this specification, the term "plurality" means two or more unless explicitly defined otherwise. The terms "mounted," "connected," "fixed," and the like are to be construed broadly, and for example, "connected" may be a fixed connection, a removable connection, or an integral connection; "coupled" may be direct or indirect through an intermediary. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description of the present specification, the description of the terms "one embodiment," "some embodiments," or the like, 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, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (13)

1. A flow field analysis system, comprising:
the parameter acquisition module is used for acquiring tunnel simulation parameters and fan configuration parameters;
the tunnel model establishing module is used for establishing a tunnel model according to the tunnel simulation parameters;
the meshing module is used for meshing the tunnel model;
the flow field calculation and output module is used for carrying out dust removal simulation according to the fan configuration parameters and the tunnel model subjected to grid division and outputting a dust removal simulation result;
and the flow field optimization and output module is used for carrying out dust removal simulation correction based on a preset dust removal target and the dust removal simulation result until corrected fan configuration parameters meeting the preset dust removal target are obtained and output.
2. The flow field analysis system of claim 1,
the tunnel simulation parameters comprise the shape and the size of the tunnel, the position of a dust generating point and the dust generating amount;
the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet;
the corrected fan configuration parameters are parameters obtained by correcting the size and the position of the air supply opening, the size and the position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet.
3. The flow field analysis system of claim 2,
the parameter acquisition module is also used for acquiring the corrected fan configuration parameters;
and the flow field calculation and output module is also used for carrying out dust removal simulation according to the corrected fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result.
4. The flow field analysis system of claim 1,
the flow field calculation and output module adopts a SIMPLEC algorithm when carrying out dust removal simulation;
and the flow field optimization and output module is used for carrying out dust removal simulation correction based on a preset dust removal target and the dust removal simulation result, and specifically, a real number coding technology, a variable precision cross operator and a dynamic punishment are adopted to process, calculate and solve the fan configuration parameters to obtain the corrected fan configuration parameters and output the corrected fan configuration parameters.
5. The flow field analysis system of claim 1, further comprising:
and the human-computer interaction unit is used for selecting a display mode of the dust removal simulation result image, wherein the display mode of the flow field image comprises displaying a three-dimensional model, displaying an XZ plane cutting model and a model section, displaying a YZ plane cutting model and a model section, and displaying an XY plane cutting model and a model section, and an XYZ coordinate system is arranged on a display interface, wherein the X axis is rightward, the Y axis is vertically inward, and the Z axis is upward.
6. The flow field analysis system of claim 5,
the output dust removal simulation result comprises: and displaying an image of the dust removal simulation result, wherein the image comprises one or more of pressure, flow speed, flow direction, dust concentration and distribution state information of the dust-containing gas in the tunnel.
7. A method of flow field analysis, comprising:
acquiring tunnel simulation parameters;
establishing a tunnel model according to the tunnel simulation parameters;
meshing the tunnel model;
acquiring fan configuration parameters;
carrying out dust removal simulation according to the fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result;
and carrying out dust removal simulation correction based on a preset dust removal target and the dust removal simulation result until a corrected fan configuration parameter meeting the preset dust removal target is obtained and output.
8. The flow field analysis method of claim 7,
the tunnel simulation parameters comprise the shape and the size of the tunnel, the position of a dust generating point and the dust generating amount;
the fan configuration parameters comprise the size and the position of an air supply opening, the size and the position of an air outlet, the air speed of the air supply opening and the air speed of the air outlet;
the corrected fan configuration parameters are parameters obtained by correcting the size and the position of the air supply opening, the size and the position of the air outlet, the air speed of the air supply opening and the air speed of the air outlet.
9. The flow field analysis method of claim 8, further comprising:
acquiring the configuration parameters of the corrected fan;
and carrying out dust removal simulation according to the corrected fan configuration parameters and the tunnel model subjected to grid division, and outputting a dust removal simulation result.
10. The flow field analysis method of claim 7,
a SIMPLEC algorithm is adopted when dust removal simulation is carried out;
and performing dust removal simulation correction based on a preset dust removal target and the dust removal simulation result, specifically, processing, calculating and solving the fan configuration parameters by adopting a real number coding technology, a variable precision cross operator and a dynamic penalty to obtain and output the corrected fan configuration parameters.
11. The flow field analysis method of claim 7, further comprising:
selecting a display mode of the dust removal simulation result image, wherein the display mode of the flow field image comprises displaying a three-dimensional model, displaying an XZ plane cutting model and a model section, displaying a model section on a YZ plane cutting model and a model section, and displaying an XY plane cutting model and a model section, and an XYZ coordinate system is arranged on a display interface, wherein the X axis is rightward, the Y axis is vertically inward, and the Z axis is upward.
12. The flow field analysis method of claim 11,
the output dust removal simulation result comprises: and displaying an image of the dust removal simulation result, wherein the image comprises one or more of pressure, flow speed, flow direction, dust concentration and distribution state information of the dust-containing gas in the tunnel.
13. A computer readable storage medium, characterized in that a program or instructions are stored thereon, which when executed by a processor, implement the steps of the flow field analysis method according to any one of claims 7 to 12.
CN202210064667.2A 2022-01-20 2022-01-20 Flow field analysis system, flow field analysis method, and computer-readable storage medium Pending CN114491751A (en)

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