A method for simulating diffusion of toxicants based on Fluent

Abstract

The application provides a toxicant diffusion simulation method based on Fluent, which comprises the following steps: data input, receiving explosion data; first simulation, explosion dispersion simulation according to the explosion data; second simulation, cloud diffusion simulation according to the explosion data and the first simulation result, to obtain a diffusion model. In the application, the concentration and diffusion of toxic substances in a unit space within a short time after the explosion are measured and estimated according to the diffusion model, the explosion process can be simulated and modeled according to the initial explosion data, the radial velocity of explosion diffusion, the concentration of toxic substances, and the size, range, temperature field and pressure field effect of the formed aerosol cloud are obtained, the effective assistance of rescue work under the explosion situation is realized, and the exclusion work or optimization of the space layout of the flammable and explosive scene is realized to improve the safety factor of the scene.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of explosion simulation, in particular to a toxic substance diffusion simulation method based on Fluent. BACKGROUND

[0002] With the development of industry, many industrial raw materials with important use value have the properties of flammability and explosiveness, and such dangerous chemical explosion accidents also have the characteristics of "burning, explosion and toxicity". In a short time after the explosion, toxic substances will be thrown far away with the explosion, and the concentration and diffusion law of toxic substances are unknown and difficult to determine, which brings great difficulties to emergency rescue or early prevention work. Therefore, the explosion diffusion of toxic substances is very common in the field. However, due to the difficulty, high risk and poor repeatability of the explosion diffusion experiment of toxic substances, it brings great difficulties to the normal explosion diffusion research of toxic substances. With the continuous progress of computer technology, computer technology can be used to assist in simulating various experimental scenes, and numerical simulation method can realize the simulation calculation of explosion diffusion process.

[0003] Therefore, there is an urgent need in the field for a toxic substance diffusion simulation method based on Fluent.

[0004] In view of this, the present application is proposed. SUMMARY

[0005] The purpose of the present application is to provide a toxic substance diffusion simulation method based on Fluent to solve at least one technical problem in the prior art.

[0006] Specifically, the present application provides a toxic substance diffusion simulation method based on Fluent, which comprises the following steps:

[0007] Data entry, receiving explosion data;

[0008] First simulation, explosion dispersion simulation according to the explosion data;

[0009] Second simulation, cloud diffusion simulation according to the explosion data and the first simulation result, to obtain a diffusion model.

[0010] Adopting the above scheme, the concentration and diffusion of toxic substances in unit space in a short time after explosion are measured and estimated according to the diffusion model, the explosion process can be simulated and modeled according to the initial explosion data, the radial velocity of explosion diffusion, the concentration of toxic substances, and the size, range, and temperature field and pressure field effect of the formed aerosol cloud are obtained, the effective assistance of rescue work under explosion situation is realized, and the exclusion work or optimization of space layout of flammable and explosive scene is realized to improve the safety factor of the scene.

[0011] Preferably, the explosion data in the data entry step includes: environmental data, explosion original data, the environmental data is the temperature, wind speed and air density at the explosion site, and the explosion original data is the type and content of the explosive and the type and content of the toxic substance.

[0012] Further, the explosion data further includes real-time measurement data, and the real-time measurement data is aerosol cloud data, temperature field data and pressure field data formed after explosion.

[0013] Adopting the above scheme, sufficient basic data can be provided, subsequent simulation calculation work can be carried out, calculation accuracy and efficiency can be improved, environmental variables can be fully brought into the calculation process, and the embodiment of environmental variables in the calculation result is ensured.

[0014] Preferably, in the first simulation step, the following steps are included.

[0015] Establishing a control equation;

[0016] Establishing a turbulent flow model;

[0017] Establishing a discrete phase model;

[0018] According to the turbulent flow model and the discrete phase model, calibration data is obtained.

[0019] Further, the step of establishing a control equation includes: according to mass conservation, momentum conservation and energy conservation, a two-dimensional steady-state incompressible Navier-Stokes equation is established for the gas phase flow field, and a SIMPLE algorithm is used to solve the gas phase flow field, and the equation set is as follows:

[0020] Continuity equation: the calculation of the interface between two phases is realized by solving the volume fraction connectivity of one or more phases, and the equation of the qth phase is expressed as follows:

[0021]

[0022] In the formula, ρ q is the density of the qth phase (kg / m 3 ); it can be the density of gas; v is the velocity of fluid motion (m / s); ρp p density (kg / m3) 3 p density (kg / m3) qp q to p mass transfer p to q mass transfer zero

[0023] The volume fraction equations for the primary phases are not solved, and the calculations are based on the following constraints:

[0024]

[0025] The continuity equations are solved using implicit or explicit time formulations.

[0026] Property calculations: Each property appearing in the continuity equations is determined by the presence of the component phases in each control volume, so for an n-phase system, the volume-fraction averaged density is given by:

[0027] p = å a q p q .

[0028] The property calculations apply to properties such as viscosity.

[0029] Momentum equations: By solving the single momentum equation throughout the domain, the velocity field is shared among the phases, and all phase volume fractions of properties such as p and m are given by:

[0030]

[0031] where F is the body force.

[0032] Due to the limitations of the shared field approximation, the accuracy of the velocity near the interface can be adversely affected in cases where there is a large velocity difference between phases, and the convergence problem can be effectively solved when the viscosity ratio is greater than 1000 using the CICSAM method.

[0033] Energy equation:

[0034]

[0035] where k eff is the effective thermal conductivity, i.e., k + k t , k t is the turbulent thermal conductivity, which is obtained from the turbulence model used; J j is the diffusion flux of species j; h jrq is the enthalpy of species j in phase q; J jrq is the diffusion flux of species j in phase q; is the effective viscosity; S his a volumetric heat source; the first three terms on the right-hand side represent energy transfer due to conduction, species diffusion, and viscous dissipation, respectively.

[0036] According to the VOF model, the energy E is regarded as a mass average variable:

[0037]

[0038]

[0039] where: h of each phase q Determined by the specific heat of the phase and the shared temperature; the physical properties p, the effective thermal conductivity k eff and the effective viscosity Calculated by the volume average of the phase.

[0040] Further, the step of establishing the turbulent flow model comprises: using the Reynolds average method, using the standard k-ε model to simulate the dispersion process.

[0041] Further, the step of establishing the discrete phase model comprises: defining air as a continuous phase, toxic substances as discrete phase particles, using the Euler-Lagrange discrete phase model method, first calculating the continuous phase flow field, then tracking the trajectory of each particle, and finally using the Stokes tracking random trajectory model to shape.

[0042] Further, the step of obtaining calibration data according to the turbulent flow model and the discrete phase model comprises: re-determining the number, grid length size and grid structure of the grid for the explosion experiment according to the turbulent flow model and the discrete phase model, and the calibration data is the number, grid length size and grid structure of the grid for the explosion experiment.

[0043] By using the above scheme, the explosion process can be effectively simulated, and according to the simulation result, the explosion process can be corrected, so that the subsequent explosion experiment can be verified with the previous simulation process, and the simulation accuracy can be effectively improved.

[0044] Preferably, the second simulation step comprises:

[0045] Establishing an initial cloud cluster;

[0046] Toxic substance cloud cluster diffusion simulation.

[0047] Further, the step of establishing an initial cloud cluster comprises: constructing an initial cloud cluster based on the Euler-Lagrange method of uniformly generating random particles in an ellipsoid, and using MATLAB software to construct and generate the initial cloud cluster.

[0048] Further, the step of establishing an initial cloud cluster further comprises: setting the lateral radius of the initial cloud cluster as r, the height as 2h, and the explosion center position as (x cx, y c z c If the following condition is met: x2+y2+z2=R2, then all particle coordinates (x, y, z) constituting the initial cloud meet the following relationship:

[0049]

[0050] Further, the toxic substance cloud diffusion simulation step comprises: simulating the diffusion of toxic particles by using Fluent and a discrete phase model to obtain the spatiotemporal distribution of the mass, velocity and concentration of the toxic particles.

[0051] Further, the toxic substance cloud diffusion simulation step further comprises: setting the atmosphere as an incompressible ideal gas, establishing the Navier-Stokes control equation of incompressible viscous fluid flow; the turbulence model adopts the Reynolds averaging method, and the standard k-ε model is used to simulate the dispersion process.

[0052] By using the above scheme, the explosive physical and chemical process with rapid changes in an instant can be solved in a non-steady state, and the spatiotemporal distribution of the mass, velocity and concentration of the toxic particles can be obtained. Multiple iterations are performed in time, the nonlinearity and coupling between equations are fully considered, the separation error is reduced, the calculation is simple, the influence of the turbulent fluid on the particles is fully considered, and the numerical calculation of the motion of the particle tracking can be effectively realized.

[0053] In summary, the present application has the following beneficial effects:

[0054] 1. In the present application, the concentration and diffusion of toxic substances in a unit space within a short time after the explosion are measured and estimated according to the diffusion model. According to the initial explosion data, the explosion process can be simulated and modeled to obtain the radial velocity of the explosion diffusion, the concentration of toxic substances, and the size, range, and temperature field and pressure field effect of the formed aerosol cloud, etc. parameters, which can effectively assist the rescue work under the explosion situation, and exclude or optimize the spatial layout of the flammable and explosive scene to improve the safety factor of the scene.

[0055] 2. The present application can solve the explosive physical and chemical process with rapid changes in an instant in a non-steady state, and can obtain the spatiotemporal distribution of the mass, velocity and concentration of the toxic particles. Multiple iterations are performed in time, the nonlinearity and coupling between equations are fully considered, the separation error is reduced, the calculation is simple, the influence of the turbulent fluid on the particles is fully considered, and the numerical calculation of the motion of the particle tracking can be effectively realized. BRIEF DESCRIPTION OF DRAWINGS

[0056] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a flowchart of a toxic substance diffusion simulation method based on Fluent according to this application;

[0058] Figure 2 This is a flowchart of a preferred embodiment of a Fluent-based toxic substance diffusion simulation method according to this application;

[0059] Figure 3 This is a schematic diagram of the three-dimensional computational model of this application;

[0060] Figure 4 This is a schematic diagram of the two-dimensional planar computational model of this application;

[0061] Figure 5 This is a spatial concentration cloud map of toxic aerosol clouds 30 seconds after the explosion.

[0062] Figure 6 This is a ground concentration cloud map of toxic aerosol clouds 30 seconds after the explosion. Detailed implementation method:

[0063] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0064] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0065] The present application will be described in detail below through examples.

[0066] like Figure 1 and Figure 2 As shown, this application provides a Fluent-based method for simulating toxic substance diffusion, which includes the following steps:

[0067] S100. Data entry, receiving explosion data;

[0068] In the specific implementation process, the explosion data in the S100. Data entry step includes: environmental data, explosion original data, the environmental data is the temperature, wind speed and air density at the explosion site, the explosion original data is the type and content of the explosive, the type and content of the toxic substance, and the explosion data also includes real-time measurement data, the real-time measurement data is the aerosol cloud data, temperature field data and pressure field data formed after the explosion.

[0069] As shown in Figure 3 , a three-dimensional calculation model of cloud diffusion under a wind speed of 2.7 m / s, the model is composed of a cubic air domain, an initial cloud, a ground, an air inlet and an air outlet. In order to completely describe the change of the cloud diffusion in space, the height of the air domain is 20 meters, the width is 40 meters, the wind of a certain speed is blown in from the air inlet, acts on the initial cloud, and flows out from the air outlet, the distance of the cloud from the air outlet is 50 meters, so as to ensure the concentration distribution within a certain distance in the blowing direction. The size and concentration of the initial cloud are determined by the test results and the explosion dispersion numerical simulation results. The boundary conditions are: the air inlet is a velocity inflow boundary, the air outlet and both sides are pressure outflow boundaries, and the ground is a reflective boundary. At a distance of 0.5 meters and 1.5 meters from the ground height, the cloud is 10 meters, 20 meters, 30 meters and 40 meters away from the blowing direction, respectively, detection surfaces are set up, so as to obtain the spatial distribution of the cloud concentration at different times. Along the axis of the cloud, monitoring points are established in the blowing direction, so as to obtain the change of the cloud concentration with time at different positions.

[0070] As shown in Figure 4 , a two-dimensional plane calculation model of cloud diffusion under a wind speed of 2.7 m / s, in order to obtain the law of cloud diffusion with wind over a long period of time, a two-dimensional plane calculation model is established, the model is composed of a plane air domain, an initial cloud, a ground, an air inlet and an air outlet. The distance of the cloud from the air outlet is 1500 meters, under a wind speed of 2.7 m / s, the calculation time of more than 20 minutes can be ensured, so as to obtain the distribution of the cloud concentration at a long distance. The height of the air domain is 30 meters, the wind flows in from the left side and flows out from the right side, the size and concentration of the initial cloud are determined by the test results and the explosion dispersion numerical simulation results. The air inlet is a velocity inflow boundary, the air outlet is a pressure outflow boundary, and the ground is a reflective boundary. Along the axis of the cloud, monitoring points are established in the blowing direction, so as to obtain the change of the cloud concentration with time at different positions.

[0071] The above scheme can provide sufficient basic data, facilitate subsequent simulation calculation, improve calculation accuracy and efficiency, bring environmental variables into the calculation process, and ensure the embodiment of environmental variables in the calculation results.

[0072] S200. First simulation, explosion dispersion simulation according to explosion data;

[0073] In the specific implementation process, the S200. First simulation step includes: S201. Establishing control equations; S202. Establishing a turbulent flow model; S203. Establishing a discrete phase model; and S204. Obtaining calibration data according to the turbulent flow model and the discrete phase model.

[0074] In the specific implementation process, the S202. Establishing a turbulent flow model step includes: using Reynolds averaging method and standard k-ε model to simulate the dispersion process, the S203. Establishing a discrete phase model step includes: defining air as a continuous phase and toxic substances as discrete phase particles, using Euler-Lagrange discrete phase model method to first calculate the continuous phase flow field, then tracking the trajectory of each particle, and finally using Stokes tracking random trajectory model to shape, and the S204. Obtaining calibration data according to the turbulent flow model and the discrete phase model step includes: according to the turbulent flow model and the discrete phase model, re-determining the number, grid size and grid structure of the grid for explosion experiment, and the calibration data is the number, grid size and grid structure of the grid for explosion experiment. The above scheme can effectively simulate the explosion process, and according to the simulation results, correct the explosion process, so that the subsequent explosion experiment can be verified with the previous simulation process, and the simulation accuracy is effectively improved.

[0075] S300. Second simulation, cloud diffusion simulation according to explosion data and first simulation results to obtain a diffusion model.

[0076] In the specific implementation process, the S300. Second simulation step includes: S301. Establishing an initial cloud; and S302. Toxic substance cloud diffusion simulation.

[0077] In the specific implementation process, the S301. Establishing an initial cloud step includes: constructing the initial cloud based on the Euler-Lagrange method of uniformly generating random particles in an ellipsoid, and using MATLAB software to construct and generate the initial cloud, and the establishing an initial cloud step further includes: setting the initial cloud transverse radius as r, height as 2h, and explosion center position as (x c , y c , z c), the S302. toxic substance cloud diffusion simulation step includes: simulating diffusion of toxic particles by using Fluent and a discrete phase model to obtain a space-time distribution of mass, velocity and concentration of the toxic particles, and the S302. toxic substance cloud diffusion simulation step further includes: setting the atmosphere as an incompressible ideal gas, establishing a Navier-Stokes control equation of incompressible viscous fluid flow; a turbulent flow model adopts a Reynolds average method, and a standard k-ε model is used to simulate the dispersion process.

[0078] By using the above scheme, the concentration and diffusion of the toxic substance in a unit space in a short time after the explosion are measured and estimated according to a diffusion model, the explosion process can be simulated and modeled according to initial explosion data, radial velocity of explosion diffusion, concentration of toxic substances, size and range of the formed aerosol cloud, and temperature field and pressure field effects and other parameters are obtained, effective assistance for rescue work under explosion conditions is realized, and exclusion work or optimization of space layout of flammable and explosive scene is realized to improve the safety factor of the scene.

[0079] In some preferred embodiments of the present application, the step of establishing a control equation includes: according to mass conservation, momentum conservation and energy conservation, a two-dimensional steady-state incompressible Navier-Stokes equation is established for a gas phase flow field, and a SIMPLE algorithm is used to solve the gas phase flow field, and the equation set is as follows:

[0080] Continuity equation: the calculation of the interface between two phases is realized by solving the connectivity of the volume fraction of one or more phases, and the equation of the qth phase is expressed as follows:

[0081]

[0082] In the formula, ρ q is the density of the qth phase (kg / m 3 ); it can be the density of the gas; v is the velocity of fluid motion (m / s); ρ p is the density of the pth phase (kg / m 3 ), which can be the density of the particle; ∇ is the Laplace operator; m qp is the mass transfer from the qth phase to the pth phase; is the mass transfer from the pth phase to the qth phase; the source term is zero.

[0083] The volume fraction equation of the main phase is not solved, and the calculation is based on the following constraint conditions:

[0084]

[0085] The continuity equation is solved by using an implicit or explicit time formula.

[0086] Property calculation: Each property appearing in the conservation equations is determined by the presence of each component phase in each control volume. For an n-phase system, the volume-fraction averaged density is expressed as follows:

[0087] ρ = ∑α q ρ q .

[0088] The property calculation applies to properties such as viscosity.

[0089] Momentum equation: By solving the single momentum equation throughout the domain, the velocity field is shared among the phases, as are all phase volume fractions of properties such as density p and viscosity μ, which are expressed as follows:

[0090]

[0091] where F is the body force.

[0092] Due to the limitations of the shared field approximation, the accuracy of the velocity near the interface is adversely affected in the presence of large velocity differences between phases. When the viscosity ratio is greater than 1000, the poor convergence problem can be effectively solved by using the CICSAM method.

[0093] Energy equation:

[0094]

[0095] where k eff is the effective thermal conductivity, i.e., k+k t , k t is the turbulent thermal conductivity, which is obtained from the turbulence model used; J j is the diffusion flux of species j; h jrq is the enthalpy of species j in phase q; J jrq is the diffusion flux of species j in phase q; is the effective viscosity; S h is the volumetric heat source; The first three terms on the right side of the equation represent energy transfer due to conduction, species diffusion, and viscous dissipation, respectively.

[0096] According to the VOF model, the energy E is considered as a mass-averaged variable:

[0097]

[0098]

[0099] where h q of each phase is determined by the specific heat of the phase and the shared temperature; Properties such as p, k eff , and are calculated by volume-averaging over the phase.

[0100] In some preferred embodiments of the present application, the calculation result is as shown in Figure 5 , Figure 6 The calculation condition is 45g central charge, and the toxic agent concentration is 11.7g / m 3 The cloud in the calculation model is an ellipsoid with a long axis of 7.6m and a short axis of 3m, and the height of the short axis to the ground surface is 1.5m.

[0101] According to the test result, 421g of a certain toxic agent will form a basically stable ellipsoid cloud with a radius of 3.8m and a height of 1.5m under the action of 45g central charge for about 20ms, and the wind speed is 2m / s. According to the calculation result of the explosion scattering numerical simulation, the concentration of the toxic agent at this time is 11.7g / m3. According to the cloud picture, the cloud in the calculation model is an ellipsoid with a long axis of 7.6m and a short axis of 3m, and the height of the short axis to the ground surface is 1.5m.

[0102] By using the above scheme, the explosive physical and chemical process with rapid instantaneous change can be solved in a non-steady state, and the time and space distribution of the toxic particle mass, velocity and concentration can be obtained. Multiple iterations are performed in time, the nonlinearity and coupling between equations are fully considered, the separation error is reduced, the calculation is simple, the influence of turbulent fluid on particles is fully considered, and the numerical calculation of particle tracking movement can be effectively realized.

[0103] In summary, in the present application, the concentration and diffusion of toxic substances in a unit space within a short time after explosion are measured and estimated according to the diffusion model. The explosion process can be simulated and modeled according to the initial explosion data to obtain the radial velocity of explosion diffusion, the concentration of toxic substances, the size and range of the formed aerosol cloud, and the temperature field and pressure field effect, etc. parameters, to effectively assist rescue work under explosion conditions, and to exclude or optimize the spatial layout of flammable and explosive scene to improve the safety factor of the scene. The present application can solve the explosive physical and chemical process with rapid instantaneous change in a non-steady state, and obtain the time and space distribution of the toxic particle mass, velocity and concentration. Multiple iterations are performed in time, the nonlinearity and coupling between equations are fully considered, the separation error is reduced, the calculation is simple, the influence of turbulent fluid on particles is fully considered, and the numerical calculation of particle tracking movement can be effectively realized.

[0104] It should be noted that, for those skilled in the art, without departing from the principles of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the claims of the present application.

Claims

1. A Fluent-based method for simulating toxic substance diffusion, characterized in that: The Fluent-based toxic substance diffusion simulation method includes the following steps: Data entry, receiving explosion data; The first simulation involves simulating the explosion dispersion based on the explosion data. The second simulation, based on the explosion data and the results of the first simulation, simulates the cloud diffusion to obtain a diffusion model; The explosion data in the data entry step includes: environmental data and original explosion data. The environmental data includes the temperature, wind speed and air density at the explosion site. The original explosion data includes the type and content of explosives and the type and content of toxic substances. The first simulation step includes: Establish the governing equations; Establish a turbulent flow model; Establish a discrete phase model; The calibration data were obtained based on the turbulent flow model and the discrete phase model; The steps for establishing the governing equations include: establishing a two-dimensional steady-state incompressible Navier-Stokes equation for the gas phase flow field based on the conservation of mass, momentum, and energy, and solving the gas phase flow field using the SIMPLE algorithm; The steps for establishing the turbulent flow model include: using the Reynolds averaging method and employing the standard k-ε model to simulate the dispersion process; The steps for establishing the discrete phase model include: defining air as a continuous phase and toxic substances as discrete phase particles; using the Eulerian-Lagrange discrete phase model method, first calculating the continuous phase flow field, then tracking the trajectory of each particle, and finally using the Stokes tracking random trajectory model to form the model. The step of obtaining calibration data based on the turbulent flow model and the discrete phase model includes: redetermining the number of grids, grid side lengths, and grid structure for the explosion experiment based on the turbulent flow model and the discrete phase model, wherein the calibration data is the number of grids, grid side lengths, and grid structure for the explosion experiment.

2. The Fluent-based toxic substance diffusion simulation method according to claim 1, characterized in that: The second simulation step includes: Establish the initial cloud cluster; Simulation of the diffusion of toxic substance clouds.

3. The Fluent-based toxic substance diffusion simulation method according to claim 2, characterized in that: The steps for establishing the initial cloud cluster include: constructing the initial cloud cluster based on the Euler-Lagrange method of uniformly generating random particles within an ellipsoid, and using MATLAB software to construct and generate the initial cloud cluster.

4. The Fluent-based toxic substance diffusion simulation method according to claim 3, characterized in that: The step of establishing the initial cloud cluster also includes: setting the horizontal radius of the initial cloud cluster to r, the height to 2h, and the epicenter position to (x). c y c , z c If the coordinates (x, y, z) of all particles constituting the initial cloud are related as follows:

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