CN114638177A - Method and system for acquiring fluid parameters in flue and information data processing terminal - Google Patents
Method and system for acquiring fluid parameters in flue and information data processing terminal Download PDFInfo
- Publication number
- CN114638177A CN114638177A CN202210293309.9A CN202210293309A CN114638177A CN 114638177 A CN114638177 A CN 114638177A CN 202210293309 A CN202210293309 A CN 202210293309A CN 114638177 A CN114638177 A CN 114638177A
- Authority
- CN
- China
- Prior art keywords
- flue
- equation
- kinetic energy
- grid
- turbulent
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- 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
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Fluid Mechanics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Computing Systems (AREA)
- Pure & Applied Mathematics (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Algebra (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method and a system for acquiring fluid parameters in a flue and an information data processing terminal, belonging to the technical field of information processing and comprising the following steps: s1, designing a three-dimensional model of the flue according to the structural parameters of the flue; s2, preprocessing the three-dimensional model to generate a computational grid; s3, establishing a turbulence kinetic energy equation k and a turbulence diffusion equation e based on the grids and given boundary conditions; s4, obtaining physical quantity of each grid through iterative calculation, calculating residual error between each iteration and the last iteration, and obtaining the range of stable distribution of the flow rate of the flue gas through judgment of the residual error; s5, firstly, calculating the velocity of the continuous phase by using a turbulent kinetic energy equation k and a turbulent diffusion equation e or Reynolds stress equations in three directions; then obtaining the fluid density according to a turbulent flow kinetic energy equation k and a turbulent flow diffusion equation e; calculating particle kinetic energy according to an energy conservation equation; the temperature is obtained according to an energy equation, and the gas pressure is obtained according to the on-way loss of a Bernoulli equation.
Description
Technical Field
The invention belongs to the technical field of information processing, and particularly relates to a method and a system for acquiring fluid parameters in a flue and an information data processing terminal.
Background
As is well known, a flue (flue pipe) is a tubular device for exhaust gas and smoke emission, and the size and shape of the flue are one of the important factors affecting the rate and amount of smoke emission; in recent years, with the rapid development of industry, the environmental pollution problem is becoming more severe, and in order to realize sustainable development, human beings need to control the total emission amount of a pollution gas source while purifying the emission of the pollution gas; therefore, human beings set up various sensors (such as the content monitoring of harmful gas, flow rate monitoring, humiture monitoring, etc.) in the flue, then according to the data that the sensor detects, carry on the statistical analysis to various parameters of the flue gas; finally, setting up an emission rule; but practice finds that:
the above conventional scheme is based on monitoring and analyzing of actual values, but in actual production, if various working parameters of the flue can be predicted in advance, the method will play a certain guiding role in production emission (such as emission time, emission rate and emission amount control).
Disclosure of Invention
Technical purpose
The invention provides a method and a system for acquiring fluid parameters in a flue and an information data processing terminal; through the computer model, the emission data of the flue can be obtained in advance, and scientific guidance and planning are further performed on the emission production work.
Technical scheme
The first purpose of the invention is to provide a method for acquiring fluid parameters in a flue, which comprises the following steps:
s1, designing a three-dimensional model of the flue according to the structural parameters of the flue; the structural parameters comprise the inner diameter size of the flue, the height of the flue, the position of a fan inlet and the angle of the fan inlet;
s2, preprocessing the three-dimensional model to generate a computational grid;
s3, establishing a turbulence kinetic energy equation k and a turbulence diffusion equation e based on the grids and given boundary conditions;
the turbulent diffusion equation e is:
wherein G iskTurbulent kinetic energy generated by laminar velocity gradient; gbIs turbulent kinetic energy generated by buoyancy; y ismFluctuations produced for excessive diffusion in compressible turbulence; sigmak,σεTurbulence Plantt numbers of a turbulence kinetic energy equation k and a turbulence diffusion equation e respectively; skAnd SεThe coefficient is self-defined; c1ε,C2ε,C3εIs a constant; a { i, j } ═ dui/dxjRepresents 9 equations, i-1, j-1, 2, 3; i is 2, j is 1, 2, 3; i is 3, j is 1, 2, 3; i.e. the derivatives in the x, y, z directions of u, the derivatives in the x, y, z directions of v, and the derivatives in the x, y, z directions of w.
S4, obtaining physical quantity of each grid through iterative calculation, wherein the physical quantity comprises flue gas flow rate, calculating residual error between each iteration and the last iteration, and obtaining the range of stable distribution of the flue gas flow rate through judgment of the residual error;
s5, firstly, calculating the velocity of the continuous phase by using a turbulent kinetic energy equation k and a turbulent diffusion equation e or Reynolds stress equations in three directions; then obtaining the fluid density according to a turbulent flow kinetic energy equation k and a turbulent flow diffusion equation e; acquiring the mass of the fluid according to the density and the volume of the fluid; calculating particle kinetic energy according to an energy conservation equation; calculating gas buoyancy from the density, mass and volume of the exterior; acquiring temperature according to an energy equation, and then acquiring gas density according to an ideal gas state equation; the gas pressure is obtained from the on-way loss of bernoulli's equation.
Preferably, S1 is specifically: and designing a three-dimensional model by adopting Catia according to the structural parameters of the flue.
Preferably, in S2, the pretreatment specifically includes: based on the three-dimensional shape of the flue generated in the early stage, computing pretreatment is carried out by Gambit software to generate a computing grid, the grid size is within 10mm, and the computing grid is in a mixed grid form combining a hexahedral structural grid and a polyhedral non-structural grid, so that modeling and grid division are completed.
Preferably, in S3, the boundary condition includes: the blowing amount of the fan, the flow rate of the air volume inlet, the smoke volume, the pressure of the flue outlet, the flow of the flue inlet, the volume component of the smoke, the smoke temperature, the smoke density and the dynamic viscosity of the smoke.
A second object of the present invention is to provide a system for acquiring fluid parameters in a flue, including:
the modeling module is used for designing a three-dimensional model of the flue according to the structural parameters of the flue; the structural parameters comprise the inner diameter size of the flue, the height of the flue, the position of a fan inlet and the angle of the fan inlet;
the preprocessing module is used for preprocessing the three-dimensional model to generate a computational grid;
the association module is used for establishing a turbulence kinetic energy equation k and a turbulence diffusion equation e based on the grids and given boundary conditions;
the turbulent diffusion equation e is:
wherein G iskTurbulent kinetic energy generated by laminar velocity gradient; gbIs composed ofTurbulent kinetic energy generated by buoyancy; y ismFluctuations produced for excessive diffusion in compressible turbulence; sigmak,σεTurbulence Plantt numbers of a turbulence kinetic energy equation k and a turbulence diffusion equation e respectively; skAnd SεThe coefficient is self-defined; c1ε,C2ε,C3εIs a constant; a { i, j } ═ dui/dxjRepresents 9 equations, i-1, j-1, 2, 3; i is 2, j is 1, 2, 3; i is 3, j is 1, 2, 3; i.e. the derivatives in the x, y, z directions of u, the derivatives in the x, y, z directions of v, and the derivatives in the x, y, z directions of w.
The information processing module is used for obtaining the physical quantity of each grid through iterative calculation, wherein the physical quantity comprises the flow rate of the flue gas, calculating the residual error between each iteration and the last iteration, and obtaining the range of stable distribution of the flow rate of the flue gas through judgment of the residual error;
the acquisition module calculates the velocity of the continuous phase by using a turbulent kinetic energy equation k and a turbulent diffusion equation e or Reynolds stress equations in three directions; then obtaining the fluid density according to a turbulent flow kinetic energy equation k and a turbulent flow diffusion equation e; acquiring the mass of the fluid according to the density and the volume of the fluid; calculating particle kinetic energy according to an energy conservation equation; calculating gas buoyancy from the density, mass and volume of the exterior; acquiring temperature according to an energy equation, and then acquiring gas density according to an ideal gas state equation; the gas pressure is obtained from the on-way loss of bernoulli's equation.
Preferably, according to the structural parameters of the flue, a three-dimensional model is designed by adopting Catia.
Preferably, in the preprocessing module, the preprocessing specifically includes: based on the three-dimensional shape of the flue generated in the early stage, computing pretreatment is carried out by adopting Gambit software to generate a computing grid, the grid dimension is within 10mm, and the computing grid is in a mixed grid form combining a hexahedral structural grid and a polyhedral non-structural grid, so that modeling and grid division are completed.
Preferably, in the associating means, the boundary condition includes: the blowing amount of the fan, the flow rate of the air quantity inlet, the flue gas quantity, the pressure of the flue outlet, the flow of the flue inlet, the volume component of the flue gas, the flue gas temperature, the flue gas density and the dynamic viscosity of the flue gas.
The third invention of this patent is to provide an information data processing terminal for implementing the method for obtaining fluid parameters in a flue.
A fourth object of the present invention is to provide a computer-readable storage medium, which includes instructions that, when executed on a computer, cause the computer to execute the fluid parameter in a flue described above.
The invention has the advantages and positive effects that: the invention can more intuitively and directly represent the flowing process of the gas in the pipeline, is beneficial to understanding the parameters of the gas flow velocity distribution and the like in the pipeline, and simultaneously provides basis for arranging the flue gas measuring equipment in the pipeline, thereby improving the accuracy of the flue gas flow velocity measurement in the pipeline. Through the computer model, the emission data of the flue can be obtained in advance, and scientific guidance and planning are further performed on the emission production work.
Drawings
FIG. 1 is a flow chart in a preferred embodiment of the present invention;
FIG. 2 is a three-dimensional model obtained at S1 in a preferred embodiment of the present invention;
FIG. 3 is a simulation diagram obtained at S4 in the preferred embodiment of the present invention;
fig. 4 is a block diagram of a system in a preferred embodiment of the invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following examples are given and detailed below.
Referring to fig. 1, a method for obtaining fluid parameters in a flue includes the following steps:
s1, designing a three-dimensional model of the flue by adopting Catia (or other software) according to the structural parameters of the flue (the structural parameters are derived from a drawing of the flue and field actual measurement data); the shape of the chimney is consistent with that of a real chimney, and real data input is provided for later flow field simulation and optimization design. The structural parameters comprise the inner diameter size of the flue, the height of the flue, the position of a fan outlet, the angle of the fan outlet, the diameter of the fan outlet, the flow velocity and the temperature of the fan outlet; taking a cylindrical flue with the height of 150m as an example, the diameter of the inner cavity of the flue is 4 m. The bottom of the flue is provided with a fan inlet 2 inserted at a certain angle, the diameter of the fan inlet is 3.6-4 m, the outlet of the fan and the whole flue are made of metal materials, the inner wall and the outer wall are smooth, and the wall surface of the flue 1 is regarded as a heat insulation wall and does not have heat exchange with the external environment; the three-dimensional model is shown in FIG. 2;
s2, performing calculation pretreatment on the three-dimensional geometric shape of the flue based on the three-dimensional model generated in the early stage to generate a calculation grid, wherein the total amount of the grid is about 500 ten thousand;
the pretreatment specifically comprises the following steps: based on the three-dimensional shape of the flue generated in the early stage, computing pretreatment is carried out by adopting Gambit software to generate a computing grid, the grid dimension is within 10mm, and the computing grid is in a mixed grid form combining a hexahedral structural grid and a polyhedral non-structural grid, so that modeling and grid division are completed.
S3, on the basis of grids and given boundary conditions, assuming that the flue gas is incompressible ideal flow, according to a fluid theory, airflow in a flue is three-dimensional turbulence, and establishing a turbulence kinetic energy equation k and a turbulence diffusion equation e;
the turbulent diffusion equation e is:
wherein G iskTurbulent kinetic energy generated by laminar velocity gradient; gbIs turbulent kinetic energy generated by buoyancy; y ismFluctuations produced for excessive diffusion in compressible turbulence; sigmak,σεTurbulence Plantt numbers of a turbulence kinetic energy equation k and a turbulence diffusion equation e respectively; s. thekAnd SεThe coefficient is self-defined; c1ε,C2ε,C3εIs a constant; a { i, j } ═ dui/dx jRepresenting 9 equations, i-1, j-1, 23, 3; i is 2, j is 1, 2, 3; i is 3, j is 1, 2, 3; i.e. the derivatives in the x, y, z directions of u, the derivatives in the x, y, z directions of v, and the derivatives in the x, y, z directions of w.
i and j are representations of a free coordinate system, and since turbulence is a partial derivative of a three-dimensional equation, i.e., a derivative of each coordinate direction with respect to three spatial coordinates, there are 9 different partial derivatives, i represents the current direction, and j represents the relative direction, which has a value from 1 to 3, respectively.
The parameters (boundary conditions) given are: the flue gas flow is determined by the flue gas flow velocity, different flue gas flow velocities (flows) are determined by different blast volumes of the fans 3, the inlet flow velocity of the air volume under given working conditions is 16-28m/s, and the flue gas volume Q is 7.24 multiplied by 105~1.27×106m3H; giving the outlet pressure (micro positive pressure or micro negative pressure) of the flue, and reversely calculating the inlet pressure according to the outlet pressure; setting the flow rate at the inlet of the flue; given smoke composition (volume fraction): water content (10%), O2(9%),CO2(22%),N2(59%); the fluid is an incompressible fluid; setting the temperature, density and dynamic viscosity of the flue gas;
and S4, obtaining physical quantities such as the flue gas flow velocity of each grid through iterative calculation, calculating the residual error between each iteration and the last iteration, and obtaining the range of stable distribution of the flue gas flow velocity through judgment of the residual error. The results in FIG. 3 show that the flue gas flow velocity of the section in the high range of 20-30m reaches relative stability (range of 6D) under different working conditions;
and S5, calculating the velocity of the continuous phase by using a turbulent kinetic energy equation k and a turbulent diffusion equation e or Reynolds stress equations in three directions, and then calculating the density according to the turbulent kinetic energy equation k and the turbulent diffusion equation e. The mass (m ═ ρ V) can be calculated from the density. The particle kinetic energy is calculated from the conservation of energy. The gas buoyancy is then calculated from the density, mass and volume of the exterior (G ═ mg, m ═ ρ V). The temperature is found from the energy equation and then the gas density is calculated from the ideal gas state equation. The gas pressure is calculated from the on-way loss of bernoulli's equation. .
Referring to fig. 4, a system for obtaining fluid parameters in a flue includes:
the modeling module is used for designing a three-dimensional model of the flue by adopting Catia (or other software) according to the structural parameters of the flue (the structural parameters are derived from a drawing of the flue and field actual measurement data); the shape of the chimney is consistent with that of a real chimney, and real data input is provided for later flow field simulation and optimization design. The structural parameters comprise the inner diameter size of the flue, the height of the flue, the position of a fan outlet, the angle of the fan outlet, the diameter of the fan outlet, the flow velocity and the temperature of the fan outlet; taking a cylindrical flue with the height of 150m as an example, the diameter of the inner cavity of the flue is 4 m. The bottom of the flue is provided with a fan inlet inserted at a certain angle, the diameter of the fan inlet is 3.6-4 m, the outlet of the fan and the whole flue are made of metal materials, the inner wall and the outer wall are smooth, and the wall surface of the flue is regarded as a heat insulation wall and does not have heat exchange with the external environment; the three-dimensional model is shown in FIG. 2;
the pretreatment module is used for carrying out calculation pretreatment on the three-dimensional geometric shape of the flue based on the three-dimensional model generated in the early stage to generate a calculation grid, and the total amount of the grid is about 500 ten thousand;
the pretreatment specifically comprises the following steps: based on the three-dimensional shape of the flue generated in the early stage, computing pretreatment is carried out by Gambit software to generate a computing grid, the grid size is within 10mm, and the computing grid is in a mixed grid form combining a hexahedral structural grid and a polyhedral non-structural grid, so that modeling and grid division are completed.
The association module is used for establishing a turbulent flow kinetic energy equation k and a turbulent flow diffusion equation e on the basis of grids and given boundary conditions, assuming that the flue gas is incompressible ideal flow, and according to a fluid theory, the airflow in the flue is three-dimensional turbulent flow;
the turbulent diffusion equation e is:
wherein, GkTurbulent kinetic energy generated by laminar velocity gradient; gbIs turbulent kinetic energy generated by buoyancy; y ismFluctuations produced for excessive diffusion in compressible turbulence; sigmak,σεTurbulence Plantt numbers of a turbulence kinetic energy equation k and a turbulence diffusion equation e respectively; s. thekAnd SεThe coefficient is self-defined; c1ε,C2ε,C3εIs a constant; a { i, j } ═ dui/dx jRepresents 9 equations, i-1, j-1, 2, 3; i is 2, j is 1, 2, 3; i is 3, j is 1, 2, 3; i.e. the derivatives in the x, y, z directions of u, the derivatives in the x, y, z directions of v, and the derivatives in the x, y, z directions of w.
The parameters (boundary conditions) given are: the flue gas flow is determined by the flue gas flow velocity, different fan blast volumes determine different flue gas flow velocities (flows), the inlet flow velocity of the air volume under given working conditions is 16-28m/s, and the flue gas volume Q is 7.24 multiplied by 105~1.27×106m3H; giving the outlet pressure (micro positive pressure or micro negative pressure) of the flue, and reversely calculating the inlet pressure according to the outlet pressure; setting the flow rate at the inlet of the flue; given smoke composition (volume fraction): water content (10%), O2(9%),CO2(22%),N2(59%); the fluid is an incompressible fluid; setting the temperature, density and dynamic viscosity of the flue gas;
and the information processing module can obtain physical quantities such as the flue gas flow velocity of each grid through iterative calculation, calculate the residual error between each iteration and the last iteration, and obtain the range of stable distribution of the flue gas flow velocity through judgment of the residual error. The results in FIG. 3 show that the flue gas flow velocity of the section in the high range of 20-30m reaches relative stability (range of 6D) under different working conditions;
and the acquisition module is used for calculating the speed of the continuous phase by using a turbulent kinetic energy equation k and a turbulent diffusion equation e or Reynolds stress equations in three directions and then calculating the density according to the turbulent kinetic energy equation k and the turbulent diffusion equation e. The mass (m ═ ρ V) can be calculated from the density. The particle kinetic energy is calculated from the conservation of energy. The gas buoyancy is then calculated from the density, mass and volume of the exterior (G ═ mg, m ═ ρ V). The temperature is found from the energy equation and the gas density is then calculated from the ideal gas state equation. The gas pressure is calculated from the on-way loss of bernoulli's equation.
An information data processing terminal for realizing the method for acquiring the fluid parameters in the flue.
A computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the fluid parameter acquisition method in a flue as described above.
In the above embodiments, all or part of the implementation may be realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (10)
1. A method for acquiring fluid parameters in a flue is characterized by comprising the following steps:
s1, designing a three-dimensional model of the flue according to the structural parameters of the flue; the structural parameters comprise the inner diameter size of the flue, the height of the flue, the position of a fan inlet and the angle of the fan inlet;
s2, preprocessing the three-dimensional model to generate a computational grid;
s3, establishing a turbulence kinetic energy equation k and a turbulence diffusion equation e based on the grids and given boundary conditions;
wherein, GkTurbulent kinetic energy generated by laminar velocity gradient; gbIs turbulent kinetic energy generated by buoyancy; y ismWaves created for excessive diffusion in compressible turbulence; sigmak,σεTurbulence Plantt numbers of a turbulence kinetic energy equation k and a turbulence diffusion equation e respectively; s. thekAnd SεThe coefficient is self-defined; c1ε,C2ε,C3εIs a constant; a { i, j } ═ dui/dxjRepresents 9 equations, i-1, j-1, 2, 3; i is 2, j is 1, 2, 3; i is 3, j is 1, 2, 3; i.e. the derivatives in the x, y and z directions of u, the derivatives in the x, y and z directions of v, and the derivatives in the x, y and z directions of w;
s4, obtaining physical quantity of each grid through iterative calculation, wherein the physical quantity comprises flue gas flow rate, calculating residual error between each iteration and the last iteration, and obtaining the range of stable distribution of the flue gas flow rate through judgment of the residual error;
s5, firstly, calculating the velocity of the continuous phase by using a turbulent kinetic energy equation k and a turbulent diffusion equation e or Reynolds stress equations in three directions; then obtaining the fluid density according to a turbulent flow kinetic energy equation k and a turbulent flow diffusion equation e; acquiring the mass of the fluid according to the density and the volume of the fluid; calculating particle kinetic energy according to an energy conservation equation; calculating gas buoyancy from the density, mass and volume of the exterior; acquiring temperature according to an energy equation, and then acquiring gas density according to an ideal gas state equation; the gas pressure is obtained from the on-way loss of bernoulli's equation.
2. The method for acquiring fluid parameters in a flue according to claim 1, wherein S1 specifically comprises: and designing a three-dimensional model by adopting Catia according to the structural parameters of the flue.
3. The method for acquiring the fluid parameters in the flue according to claim 1, wherein in S2, the pre-processing specifically includes: based on the three-dimensional shape of the flue generated in the early stage, computing pretreatment is carried out by Gambit software to generate a computing grid, and the computing grid is in a mixed grid form combining a hexahedral structural grid and a polyhedral non-structural grid, so that modeling and grid division are completed.
4. The method for obtaining fluid parameters in a flue of claim 1, wherein in S3, the boundary conditions include: the blowing amount of the fan, the flow rate of the air volume inlet, the smoke volume, the pressure of the flue outlet, the flow of the flue inlet, the volume component of the smoke, the smoke temperature, the smoke density and the dynamic viscosity of the smoke.
5. A system for obtaining fluid parameters in a flue, comprising:
the modeling module is used for designing a three-dimensional model of the flue according to the structural parameters of the flue; the structural parameters comprise the inner diameter size of the flue, the height of the flue, the position of a fan inlet and the angle of the fan inlet;
the preprocessing module is used for preprocessing the three-dimensional model to generate a computational grid;
the association module is used for establishing a turbulence kinetic energy equation k and a turbulence diffusion equation e based on the grids and given boundary conditions;
wherein G iskTurbulent kinetic energy generated by laminar velocity gradient; gbIs turbulent kinetic energy generated by buoyancy; y ismWaves created for excessive diffusion in compressible turbulence; sigmak,σεTurbulence Plantt numbers of a turbulence kinetic energy equation k and a turbulence diffusion equation e respectively; skAnd SεThe coefficient is self-defined; c1ε,C2ε,C3εIs a constant; a { i, j } ═ dui/dxjRepresents 9 equations, i-1, j-1, 2, 3; i is 2, j is 1, 2, 3; i is 3, j is 1, 2, 3; i.e. the derivatives in the x, y, z directions of u, the derivatives in the x, y, z directions of v, and the derivatives in the x, y, z directions of w.
The information processing module is used for obtaining the physical quantity of each grid through iterative calculation, wherein the physical quantity comprises the flow rate of the flue gas, calculating the residual error between each iteration and the last iteration, and obtaining the range of stable distribution of the flow rate of the flue gas through judgment of the residual error;
the acquisition module calculates the velocity of the continuous phase by using a turbulent kinetic energy equation k and a turbulent diffusion equation e or Reynolds stress equations in three directions; then obtaining the fluid density according to a turbulent flow kinetic energy equation k and a turbulent flow diffusion equation e; acquiring the mass of the fluid according to the density and the volume of the fluid; calculating particle kinetic energy according to an energy conservation equation; calculating gas buoyancy from the density, mass and volume of the exterior; acquiring temperature according to an energy equation, and then acquiring gas density according to an ideal gas state equation; the gas pressure is taken in terms of the on-way loss of bernoulli's equation.
6. The in-stack fluid parameter acquisition system of claim 5, wherein in the modeling module: and designing a three-dimensional model by adopting Catia according to the structural parameters of the flue.
7. The system for obtaining fluid parameters in a flue of claim 5, wherein in the pre-processing module, the pre-processing is specifically: based on the three-dimensional shape of the flue generated in the early stage, computing pretreatment is carried out by Gambit software to generate a computing grid, the grid size is within 10mm, and the computing grid is in a mixed grid form combining a hexahedral structural grid and a polyhedral non-structural grid, so that modeling and grid division are completed.
8. The in-stack fluid parameter acquisition system of claim 5, wherein in the correlation module, the boundary conditions include: the blowing amount of the fan, the flow rate of the air quantity inlet, the flue gas quantity, the pressure of the flue outlet, the flow of the flue inlet, the volume component of the flue gas, the flue gas temperature, the flue gas density and the dynamic viscosity of the flue gas.
9. An information data processing terminal for implementing the method for acquiring the fluid parameter in the flue of any one of claims 1 to 4.
10. A computer readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the method of fluid parameter acquisition in a flue as claimed in any one of claims 1 to 4.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210293309.9A CN114638177A (en) | 2022-03-23 | 2022-03-23 | Method and system for acquiring fluid parameters in flue and information data processing terminal |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210293309.9A CN114638177A (en) | 2022-03-23 | 2022-03-23 | Method and system for acquiring fluid parameters in flue and information data processing terminal |
Publications (1)
Publication Number | Publication Date |
---|---|
CN114638177A true CN114638177A (en) | 2022-06-17 |
Family
ID=81950669
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210293309.9A Pending CN114638177A (en) | 2022-03-23 | 2022-03-23 | Method and system for acquiring fluid parameters in flue and information data processing terminal |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114638177A (en) |
-
2022
- 2022-03-23 CN CN202210293309.9A patent/CN114638177A/en active Pending
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108304684B (en) | Rocket engine tail jet flow simulation method and system | |
CN113723030B (en) | Actual gas physical property simulation method and system based on computational fluid dynamics | |
CN112765736B (en) | Method for setting boundary of turbulent kinetic energy inlet of hypersonic-velocity blunt leading edge around flow | |
CN111339701B (en) | Pipeline leakage characteristic Godunov simulation method based on Brunone dynamic friction resistance | |
CN113111608B (en) | Novel local turbulence pulsation generation method | |
CN113177370B (en) | Wind flow-dust gas-solid two-phase flow numerical simulation method considering environmental humidity factor | |
CN111985166A (en) | Pipeline hydraulic transient simulation method and storage medium with implicit consideration of dynamic friction resistance | |
CN114841031A (en) | Method for calculating diffusion concentration of simulated toxic and harmful gas in three-dimensional virtual training environment | |
Zheng et al. | Evaluation and comparison of various fast fluid dynamics modeling methods for predicting airflow around buildings | |
CN112163722A (en) | Method and device for predicting gas supply state of natural gas pipe network | |
Cummings et al. | Supersonic, turbulent flow computation and drag optimization for axisymmetric afterbodies | |
CN110866336B (en) | Single-hole supersonic oxygen lance nozzle design optimization system | |
CN114638177A (en) | Method and system for acquiring fluid parameters in flue and information data processing terminal | |
CN108280300B (en) | Big data flowmeter development method based on computational fluid dynamics | |
CN113536640B (en) | Optimization design method for internal flow channel structure of air distributor based on orthogonal test | |
CN116680948A (en) | Simulation method and device for engine surge test | |
Huang et al. | Numerical simulation and experimental verification of the front air intake system of heavy trucks based on fluid-solid coupling and discrete phase models | |
Roy et al. | CFD simulation of wind effects on industrial chimneys | |
CN113536461A (en) | Turbulence model correction method for aerodynamic heat prediction of hypersonic velocity intense shock wave flow field | |
Chernyshev et al. | Research of the flow-over of the mechanical core of four pipes by a wind current, using Control Volume Method | |
Liu et al. | Optimization study of spherical tuyere based on BP neural network and new evaluation index | |
Vasconcellos et al. | Flow past a circular cylinder: a comparison between commercial finite volume and finite element codes | |
Zieße et al. | Validation of a Synthetic-Eddy Method for Modelling Incoming Wakes in Scale-Resolving Simulations of Turbomachinery Cascades | |
Ng et al. | Applications of high‐resolution schemes based on normalized variable formulation for 3D indoor airflow simulations | |
Heinrich et al. | Density-based solver for all Mach number flows |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |