Mapping-based building sudden opening and internal and external pressure change numerical simulation method under sudden opening

Abstract

The invention discloses a building sudden opening method based on mapping, and the method comprises the following steps: S1, an opening model and a closed model of a building are created respectively, and in the opening model and the closed model, an opening is formed in the windward side of the opening model, and other sizes are the same; s2, performing numerical simulation on the closed model under a set flow field condition until the flow field is stable, and storing flow field data; s3, setting the same flow field condition for the opening model, and mapping the flow field data stored in the step S2 to numerical simulation of the opening model as an initial condition; and S4, carrying out numerical simulation on the opening model to realize a dynamic simulation process of sudden opening of the building. The invention further discloses an internal and external pressure change numerical simulation method under the sudden opening of the building. According to the mapping-based numerical simulation method for the sudden opening of the building and the internal and external pressure change under the sudden opening, dynamic simulation of the sudden opening of the building can be realized, and numerical simulation of the internal and external pressure change under the sudden opening of the building can be realized.

Description

Technical Field

[0001] The invention belongs to the technical field of civil engineering and water conservancy, and specifically relates to a numerical simulation method for sudden opening of a building and changes in internal and external pressures under the sudden opening based on mapping. Background Art

[0002] In recent years, wind disasters have occurred frequently in coastal areas of my country. Post-disaster data show that the roofs and other enclosure structures of low-rise buildings have been severely damaged, accounting for more than half of the total losses. This type of damage is mostly caused by the flying objects carried by strong winds damaging the doors and windows of the building, causing the internal air pressure of the building to rise sharply, and the combined effect with the external pressure causes the roof and other enclosure structures of the building to be damaged. Regarding the research on the internal and external pressure response of wind-induced opening structures, a large number of scholars have used wind tunnel experiments to conduct relevant research on different opening parameters of buildings (number of openings, opening positions, opening shapes, etc.). At the same time, some scholars have also studied the transient internal pressure response of closed models under sudden openings, but the existing research is mainly based on wind tunnel experiments, and lacks numerical simulation research under the corresponding transient opening conditions, resulting in a lack of more in-depth discussion on the sudden opening of buildings. The key problem causing this phenomenon is that the existing numerical simulation methods are difficult to simulate the dynamic opening process of buildings. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a mapping-based numerical simulation method for sudden openings in buildings and changes in internal and external pressures under sudden openings, which can realize dynamic simulation of sudden openings in buildings and numerical simulation of changes in internal and external pressures under sudden openings in buildings.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] The present invention first proposes a mapping-based building sudden opening method, which includes the following steps:

[0006] S1: creating an open model and a closed model of a building respectively, wherein the open model and the closed model have the same dimensions except that an opening is provided on the windward side of the open model;

[0007] S2: Perform numerical simulation on the closed model under set flow field conditions until the flow field is stable, and save the flow field data;

[0008] S3: setting the same flow field conditions for the opening model, mapping the flow field data saved in step S2 to the numerical simulation of the opening model as initial conditions;

[0009] S4: Perform numerical simulation on the opening model to realize the dynamic simulation process of sudden opening of the building.

[0010] Furthermore, in step S3, the "mapping" tool in OpenFoam is used to map the flow field data saved in step S2 to the numerical simulation of the opening model as initial conditions.

[0011] Furthermore, during the numerical simulation process, the meshing methods of the open model and the closed model are kept consistent.

[0012] The present invention also proposes a numerical simulation method for changes in internal and external pressures under sudden opening of a building, comprising the following steps:

[0013] Step 1: Build the building model

[0014] Creating an open model and a closed model of a building respectively, wherein the open model and the closed model have the same dimensions except that an opening is provided on the windward side of the open model;

[0015] Step 2: Design the computational domain

[0016] Construct two computational domains of size 30H×10H×6H, place the open model and the closed model in the two computational domains respectively, make the origins of the two computational domains located at the bottom center of the open model and the closed model respectively, and the distances between the bottom center of the open model and the closed model and the entrance and exit of the computational domain are both 10H and 20H, and H is the height of the open model and the closed model;

[0017] Step 3: Divide the grid

[0018] The opening model and its computational domain are meshed. In order to ensure that the boundary flow near the wall is accurately solved, a boundary layer region is set near the wall of the opening model.

[0019] The closed model and its computational domain are meshed. In order to ensure that the boundary flow near the wall is accurately solved, a boundary layer region is set near the wall of the closed model.

[0020] The meshing methods of the open model and the closed model are consistent, and the meshing of the two computational domains is consistent;

[0021] Step 4: Set boundary conditions

[0022] Inlet boundary conditions: The inlet adopts atmospheric flow boundary conditions and uses the consistent discrete flow turbulence generation method;

[0023] Outlet boundary condition: The outlet boundary condition is set to pressure outlet;

[0024] The top and two sides of the computational domain are set as slip boundary conditions, and the boundary conditions between the bottom of the computational domain and the building wall are set as no-slip boundary conditions;

[0025] Step 5: Numerical simulation

[0026] 51) Perform numerical simulation on the closed model under set flow field conditions, and perform simulation and solution based on the large eddy turbulence model until the flow field is stable, and then save the flow field data;

[0027] 52) setting the same flow field conditions for the opening model, mapping the flow field data saved in step S2 to the numerical simulation of the opening model as initial conditions;

[0028] 53) The opening model is numerically simulated and solved based on the large eddy turbulence model to realize the dynamic simulation process of the sudden opening of the building.

[0029] Step 6: Numerical analysis

[0030] The pressure and wind speed data collected inside and outside the building under the sudden opening of the building model are numerically analyzed.

[0031] Furthermore, in the step S2, the "mapFields" tool in OpenFoam is used to map the flow field data saved in the step S2 to the numerical simulation of the opening model as the initial condition.

[0032] Furthermore, in step 4, the mathematical expression of the fluctuating wind speed synthesized by the consistent discrete incoming flow turbulence generation method is:

[0033]

[0034] Where: u i , i = 1, 2, 3 represent the pulsating wind speed in the three directions of x, y, and z respectively; j = 1, 2, 3 represent the three directions of x, y, and z respectively; M represents the number of intervals of the spectrum; N represents the number of frequencies in each interval; and All are coefficients; Represents a random vector distributed on the unit sphere of space, ensuring that the velocity field meets the divergence-free condition; represents a dimensionless coordinate vector, and is the correlation coefficient between two points in space; f n,m is the frequency, and its mean is f m , standard deviation Δf is a uniform distribution; t is time; and:

[0035]

[0036] Where: sign is the sign function; r i m,nIndicates random numbers that obey the 0-1 normal distribution in all three directions; S ui (f m ) is the frequency spectrum f m The corresponding power spectral density value in the i direction.

[0037] Furthermore, in the consistent discrete inflow turbulence generation method, an iterative reshaping method is introduced to continuously correct the shape of the wind speed profile at the inlet, so that the turbulent wind field can fit the target wind profile in the target area without affecting the spatial correlation, and ensure the conservation of the flow through the inlet interface; the principle of the iterative reshaping method is:

[0038]

[0039] Where: U mean,t (z) and I i,t (z) is the target mean velocity profile and target turbulence intensity profile; and It is the average wind speed profile and turbulence intensity profile obtained after a simulation period at the center of the building area during the nth correction period; and is the average wind speed profile and turbulence intensity profile of the turbulence field generated at the inlet interface during the nth correction; γ n is the correction factor, which is used to ensure that the flow through the inlet interface after the (n+1)th correction of the average wind speed profile at the inlet interface is always conserved; Δz is the corresponding grid size in the z direction.

[0040] Furthermore, in step 5, the method for simulating and solving the large eddy turbulence model is:

[0041] Filter all vortex scales Φ(x,t) in the flow field:

[0042]

[0043] in: is the large-scale vortex obtained by filtering; Φ′(x, t) is the subgrid scale; G(x, x′) is the spatial filtering function; and:

[0044]

[0045] Where: x is the spatial coordinate before filtering; x′ is the spatial coordinate after filtering; Δ is the filtering scale;

[0046] The governing equation for the incompressible fluid after filtering is:

[0047]

[0048] in: are the three velocity components after filtering in the Cartesian coordinate system; is the filtered pressure; ρ is the air density; ν is the kinematic viscosity; τ ij represents the sub-grid scale stress;

[0049] Small-scale vortices are modeled using the sub-grid eddy viscosity model, where the expression of the standard SGS model is:

[0050]

[0051] Where: μ t is the SGS eddy viscosity coefficient, δ ij is the Kronecker function, is the filtered thickness strain rate tensor;

[0052] Eddy viscosity coefficient μ t Calculated by the Smagorinsky-Lilly model:

[0053]

[0054] Where: k is the von Karman constant; C s is the Smagorinsky constant; Δ is the filtering scale.

[0055] The beneficial effects of the present invention are:

[0056] The mapping-based method for sudden opening of a building of the present invention requires drawing two kinds of grid examples respectively: the first example is an opening model example considering the situation that the building opening has been opened, and the other example is a closed model example for constructing a situation that the building opening is completely closed. The setting conditions of the two examples are consistent with the grid drawing method to ensure the continuity of grid information transmission; in the dynamic simulation process of the sudden opening of the entrance building, the example of the closed model is first calculated until it reaches stability, and the flow field data is saved at this moment, and then the flow field information retained by the closed model example is mapped to the example with the opening model, and this is used as the calculation initial condition of the opening model example for subsequent simulation calculations, thereby realizing the process of sudden opening of the building.

[0057] The mapping-based sudden opening method of buildings in the present invention is an innovative technology that simulates the sudden opening of closed building models through data transfer and model conversion in numerical simulation. It is based on a core idea: by mapping the closed model flow field information that has been stably calculated to the preset opening model grid, and using this as the initial condition of the new model, the simulation of the opening process is realized. The uniqueness of this method is that it can capture and simulate the transient effects in the transformation from a closed model to an opening model without the need for changes in the actual physical model. This feature enables researchers to efficiently analyze the impact of openings on the pressure distribution inside and outside the building, the structural stress state, and the overall safety performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0059] Figure 1 A flowchart of the method for sudden opening of a building based on mapping of the present invention;

[0060] Figure 2 Schematic diagram of the open model and the closed model;

[0061] Figure 3 is the instantaneous velocity field and pressure field before and after the opening;

[0062] Figure 4 is the wind pressure and wind speed time history at the opening inside the building;

[0063] Figure 5 A schematic diagram of a building model;

[0064] Figure 6 It is a schematic diagram of the calculation domain and model location;

[0065] Figure 7 Schematic diagram of mesh encryption for the computational domain;

[0066] Figure 8 Schematic diagram of the encrypted mesh and local mesh with the model opening closed or opened;

[0067] Fig. 9 It is the layout diagram of the model measurement points;

[0068] Fig.10 is the wind field characteristic map;

[0069] Fig.11 It is the layout diagram of the measuring points of the opening external pressure and internal pressure;

[0070] Fig.12 is the comparison between the theoretical value and the simulated value of the average internal pressure;

[0071] Fig.13This is the cloud diagram of average wind pressure coefficient at different opening ratios at an angle of 0°;

[0072] Fig.14 This is the cloud diagram of the pulsating wind pressure coefficient at different opening ratios at an angle of 0°;

[0073] Fig.15 The wind pressure distribution on the central axis of the model at different opening ratios at an angle of 0°;

[0074] Fig.16 is the average external wind pressure of the open model and the closed model at a 45° angle;

[0075] Fig.17 It is the external pulsating wind pressure of the open model and the closed model at a 45° angle. DETAILED DESCRIPTION

[0076] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0077] Example 1: Mapping-based building sudden opening method

[0078] like Figure 1 As shown, the method for sudden opening of a building based on mapping in this embodiment includes the following steps:

[0079] S1: Create an opening model and a closed model of a building respectively. In the opening model and the closed model, except that an opening is provided on the windward side of the opening model, other dimensions are the same, such as Figure 2 shown.

[0080] S2: Perform numerical simulation on the closed model under set flow field conditions until the flow field is stable, and save the flow field data;

[0081] S3: Setting the same flow field conditions for the opening model, mapping the flow field data saved in step S2 to the numerical simulation of the opening model as the initial condition. Specifically, in this embodiment, the "mapFields" tool in OpenFoam is used to map the flow field data saved in step S2 to the numerical simulation of the opening model as the initial condition.

[0082] S4: Perform numerical simulation on the opening model to realize the dynamic simulation process of sudden opening of the building.

[0083] Specifically, during the numerical simulation process, the mesh division methods of the open model and the closed model are kept consistent to ensure the continuity of mesh information transmission.

[0084] The two model grids (open model and closed model) under the mapping method are drawn in the same way, and the inlet adopts a uniform flow of 7m / s. The closed model working condition calculation is carried out, and the current velocity and pressure flow field information is saved at 2s. Then, the "mapFields" tool in OpenFoam is used to map the flow field information of the closed working condition to the calculation example of the open model, so as to realize the process of the sudden opening of the building. The building opening time is one time step, that is, 0.00005s.

[0085] Figure 3 (a)-(d) show the comparison of the instantaneous velocity and pressure field mapping of the numerical example at the 2nd second. It can be found that the internal pressure and velocity of the opening structure remain at 0 at the 2nd second. Figure 3 (a) and (c), it can be seen that the pressure and velocity in the calculation domain of the opening model before and after mapping are consistent with the example model before mapping. Figure 3 (f)-(g) show the pressure and velocity cloud maps inside the building after the opening is opened using the mapping method. It can be found that after the opening, the pressure inside the building becomes positive pressure, and the flow velocity in the area near the opening inside the building is smaller.

[0086] Figure 4 (a)-(b) show the time history curves of wind pressure and wind speed in the longitudinal direction at the opening of the building under the mapping method. It can be found that the wind speed and internal pressure inside the building can be guaranteed to be 0 before the opening. As the opening is opened, the internal pressure suddenly surges, and the peak internal pressure coefficient in a short period of time can reach about 1. The wind speed direction of the opening is also flowing inward, but then the airflow speed at the opening quickly flows outward.

[0087] Example 2: Numerical simulation method for changes in internal and external pressures under sudden opening of a building

[0088] The numerical simulation method of the change of internal and external pressure under the sudden opening of a building in this embodiment includes the following steps:

[0089] Step 1: Build the building model

[0090] An open model and a closed model of a building are created respectively. The open model and the closed model have the same dimensions except that an opening is provided on the windward side of the open model.

[0091] Specifically, the TPU database is a comprehensive database jointly established by Tokyo Polytechnic University. This embodiment selects and refers to the wind tunnel pressure measurement experiment of the atmosphere flowing down low houses in the TPU database. The wind field landform type corresponds to the third type of terrain of the Japanese Wind Load Code 2004, corresponding to an average wind speed profile index of 0.2, a reference height of 10m at full scale, and a corresponding turbulence intensity of 25%. The model is selected as a flat roof rigid model with an aspect ratio of 1:1 and a width-to-height ratio of 2:1. Its dimensions are 160mm×160mm×80mm (L×B×H), and the geometric scale ratio is 1:100. For the convenience of description, this embodiment briefly describes the model as a TPU model.

[0092] Since the pressure distribution of the inner and outer pressure surfaces of the opening structure needs to be paid attention to later, the experimental model of the existing wind-induced opening internal pressure research is referred to. In this embodiment, the TPU model is modified accordingly, and it is set as a double-sided sandwich to ensure the arrangement of the pressure measuring pipeline. The sandwich of the model is treated as a wall surface, and the sandwich plate is 10mm thick. Therefore, the actual internal size of the model is 140×140×60 (mm 3 ). The building model studied in this study is a square opening. For convenience of representation, the side length of the opening is recorded as l0. Specifically, in this embodiment, the side length of the opening is recorded as l0, which is 0.02m. Figure 5 The geometry and cross-sectional schematics of the closed and open building models are shown.

[0093] Step 2: Design the computational domain

[0094] Two computational domains of size 30H×10H×6H are constructed, and the open model and the closed model are placed in the two computational domains respectively, so that the origins of the two computational domains are located at the bottom center of the open model and the closed model respectively, and the distances between the bottom center of the open model and the closed model and the entrance and exit of the computational domain are 10H and 20H, respectively. H is the height of the open model and the closed model to ensure that the inlet flow is fully developed. The distance between the entrance and the center of the model is 10H. At the same time, in order to meet the requirements of the building wind tunnel test, the blockage rate of the model is 3.3%, which meets the requirement that the blockage effect is less than 5%. The same computational domain size is used when the opening of the building model is closed and when it is open.

[0095] Step 3: Divide the grid

[0096] The opening model and its computational domain are meshed. In order to ensure that the boundary flow near the wall is accurately solved, a boundary layer region is set near the wall of the opening model.

[0097] The closed model and its computational domain are meshed. In order to ensure that the boundary flow near the wall is accurately solved, a boundary layer region is set near the wall of the closed model.

[0098] The meshing methods of the open model and the closed model are consistent, and the meshing of the two computational domains is consistent.

[0099] In this embodiment, three sets of mesh schemes are used for TPU model verification, namely coarse mesh, medium mesh and fine mesh for mesh independence analysis, which are recorded as mesh 1, mesh 2 and mesh 3, as shown in Table 1. The pre-processing tools blokMesh and snappyHexMesh in OpenFoam are used to encrypt and pre-process the computational domain, including mesh division, encryption, adding boundary layers and other operation settings. Three sets of mesh schemes are drawn by changing the number of meshes in the x, y and z directions in the blockMesh tool. The whole computational domain drawing method adopts structured grid division, and unstructured grid is used between different encrypted transition zones. A total of 4 encrypted levels of grid areas are set to realize the transition of grids from large to small. The diagonal coordinates of the first-level encrypted area are (-10H, -2.5H, 0), (5H, 2.5H, 2H); the diagonal coordinates of the second-level encrypted area are (-2H, -1.5H, 0), (2H, 1.5H, 1.5H); the diagonal coordinates of the third-level encrypted area are (-1.125H, -1.125H, 0), (1.125H, 1.125H, 1.125H). The specific encryption schematic diagram is shown in Figure 7 .

[0100] In the vicinity of building targets, the mesh size is very important to the simulation accuracy. In order to ensure that the boundary flow near the wall is accurately solved, a boundary layer area needs to be set at the model wall. Figure 8 (a)-(b) show the slices of the encrypted grid along the y=0 direction and the schematic diagram of the boundary layer grid when the model opening is closed. In order to quantitatively study the flow state of the fluid near the wall, the dimensionless distance y+ is introduced. The encryption level scheme of grid 2 ensures that the average y+ value of the first layer of grid near the wall basically meets the simulation requirements, as shown in Table 1. Figure 8 (c)-(d) also show the corresponding slices of the encrypted grid along the y=0 direction under the building model and the schematic diagram of the local grid near the opening. The grid of the entire model internal basin is about 600,000, and the total number of grids is about 3.4 million. When the model opening is open, compared with the grid calculation domain when the opening is closed, except for the different grids near the building opening, the grid size of the rest of the encrypted area is the same.

[0101] Table 1 Closed model grid scheme

[0102]

[0103] Step 4: Set boundary conditions

[0104] Inlet boundary conditions: The inlet adopts atmospheric flow boundary conditions and uses the consistent discrete flow turbulence generation method. Outlet boundary conditions: The outlet boundary conditions are set as pressure outlet. The top and two sides of the computational domain are set as slip boundary conditions, and the boundary conditions between the bottom of the computational domain and the building wall are set as no-slip boundary conditions.

[0105] Specifically, the boundary conditions of the initial physical field of the numerical example of this embodiment are as follows: the inlet adopts the atmospheric flow boundary condition, and the consistent discrete flow turbulence generation method, namely the CDRFG method, is used. The wind profile data of the TPU wind tunnel test used in this embodiment is specifically referred to Table 2.

[0106] Table 2 Parameter settings of inlet turbulent wind field

[0107]

[0108]

[0109] Note: According to European standards (ESDU 85020), some parameters in the table are Z0=0.7m.

[0110] The schematic diagram of the flow field boundary of the computational domain is shown in Figure 7 The outlet boundary condition is set as pressure outlet; the top and two side surfaces of the computational domain are set as slip boundary conditions, which physically means that the tangential velocity of the fluid passing through the boundary surface is not 0, and the velocity direction is parallel to the boundary surface; the boundary conditions of the bottom of the computational domain and the building wall are set as no-slip boundary conditions, which physically means that the fluid does not pass through the boundary surface, and all normal velocity components between it and the boundary surface are 0.

[0111] The turbulent inlet usually refers to the atmospheric boundary layer inflow (ABL for short). In numerical simulation, the purpose is to generate a numerical turbulent wind field with the same statistical characteristics as the natural wind field in reality at the inlet interface. This requires including the average wind speed profile, turbulence intensity, fluctuating wind speed power spectrum, and turbulence integral scale, etc.

[0112] In this embodiment, the mathematical expression of the fluctuating wind speed synthesized by the consistent discrete incoming flow turbulence generation method (CDRFG) is:

[0113]

[0114] Where: u i, i = 1, 2, 3 represent the pulsating wind speed in the three directions of x, y, and z respectively; j = 1, 2, 3 represent the three directions of x, y, and z respectively; M represents the number of intervals of the spectrum; N represents the number of frequencies in each interval; and All are coefficients; Represents a random vector distributed on the unit sphere of space, ensuring that the velocity field meets the divergence-free condition; represents a dimensionless coordinate vector, and is the correlation coefficient between two points in space; f n,m is the frequency, and its mean is f m , standard deviation Δf is a uniform distribution; t is time; and:

[0115]

[0116] Where: sign is the sign function; r i m,n Indicates random numbers that obey the 0-1 normal distribution in all three directions; S ui (f m ) is the frequency spectrum f m The corresponding power spectral density value in the i direction.

[0117] This embodiment uses an artificial synthesis method to generate the inlet atmospheric flow. The parameters of the generated turbulent wind field at the inlet are specified, see Table 2. In order to ensure the accuracy of the wind load on the target surface of the building, it is necessary to monitor the wind profile that is consistent with the TPU test at the building location (i.e., the center of the origin of the calculation domain) under the empty wind field. However, since the pulsating wind speed synthesized in CDRFG only meets some characteristic conditions in the atmospheric flow in some parameters, when the wind field enters the calculation domain, the turbulent wind field monitored at the building location will have certain nonlinear dissipation in the height direction. Secondly, this method cannot completely guarantee that the turbulent inlet strictly meets the zero divergence condition, and it will also cause virtual pressure fluctuation anomalies in numerical calculations. Therefore, this embodiment introduces an improved method of "iterative reshaping" (IRCDRFG) to continuously correct the shape of the wind speed profile at the inlet, so that the turbulent wind field can fit the target wind profile in the target area without affecting the spatial correlation, and always ensure the conservation of the flow through the inlet interface. Specifically, the principle of the iterative reshaping method is:

[0118]

[0119] Where: U mean,t (z) and I i,t (z) is the target mean velocity profile and target turbulence intensity profile; and It is the average wind speed profile and turbulence intensity profile obtained after a simulation period at the center of the building area during the nth correction period; and is the average wind speed profile and turbulence intensity profile of the turbulence field generated at the inlet interface during the nth correction; γ n is the correction factor, which is used to ensure that the flow through the inlet interface after the (n+1)th correction of the average wind speed profile at the inlet interface is always conserved; Δz is the corresponding grid size in the z direction.

[0120] Fig. 9 (a)-(b) show the wind speed profile obtained by monitoring at the building target and the dimensionless power spectrum at the reference height after four cycles of optimization based on the "iterative reshaping (IRCDRFG)" method in an empty wind field. It can be seen that the average wind speed and turbulence intensity of numerical monitoring are consistent with the target values ​​of the TPU wind tunnel experiment, and the wind speed power spectrum at the reference height maintains good consistency with the Karman spectrum, indicating that the turbulent wind field generated based on IRCDRFG is accurate and reliable.

[0121] Step 5: Numerical simulation

[0122] 51) Carry out numerical simulation on the closed model under the set flow field conditions, and perform simulation and solution based on the large eddy turbulence model until the flow field is stable, and then save the flow field data.

[0123] 52) Setting the same flow field conditions for the opening model, mapping the flow field data saved in step S2 to the numerical simulation of the opening model as initial conditions.

[0124] 53) The opening model is numerically simulated and solved based on the large eddy turbulence model to realize the dynamic simulation process of the sudden opening of the building.

[0125] In this embodiment, the numerical solution settings are as follows: using the open source software OpenFoam tool, adopting the LES turbulence model, the sub-grid scale filter function is selected as the WALE sub-grid model according to the literature, and the relevant turbulence model coefficient is: C e =1.048, C k =0.094, C w =0.544, kinematic viscosity is 1.455×10 -5 m 2 / s. In the discrete format setting, the second-order backward difference format is selected for time discretization. The diffusion term and convection term in the control equation use the second-order central difference format and the linear upwind stable transport format (LUST), respectively. The high-order discrete format is selected to ensure the accuracy of the numerical simulation. In the solver setting, the geometric algebraic multigrid (GAMG) and preconditioned biconjugate gradient (PBiCG) solvers are used for pressure and velocity respectively. The iterative calculation convergence residual is set to 1×10 -6 The pimple algorithm is selected for transient solution of velocity-pressure coupling problem.

[0126] In choosing the simulation time step, evaluate the specific effect of the time step on the simulation accuracy. * =tU0 / D (t is the time step of the simulation) does not exceed 0.025, it is observed that the simulation results show consistency within this range, U0 is the average wind speed at the reference height, and D is the characteristic length of the model. The dimensionless time step of this embodiment is 0.00875, which meets the requirements. According to the ratio of the entire calculation basin length to the wind speed at the reference height, it is called the full basin time. In order to obtain a stable converged solution, preliminary calculations show that the wind speed and pressure after 5 full basin time monitoring are basically stable. Therefore, this embodiment selects the calculation results from the 6th to the 47th full basin time for statistical analysis, and the corresponding dimensionless time length tU H / H is about 1400, and the maximum Courant number (CFL) in the calculation is about 1.2, which ensures convergence while meeting the 10-min statistical time in the wind tunnel test specifications.

[0127] In this embodiment, the large eddy turbulence model (LES) in numerical simulation is used to carry out numerical calculations. The LES model was first proposed by Smagorinsky, which is between the Reynolds average model (RANS) and the direct simulation (DNS). It divides the vortex scale in the flow field into large-scale vortices and small-scale vortices through a spatial filtering function. Specifically, the method for simulating and solving the large eddy turbulence model is:

[0128] Filter all vortex scales φ(x,t) in the flow field:

[0129]

[0130] in: is the large-scale vortex obtained by filtering; φ′(x,t) is the subgrid scale; G(x,x′) is the spatial filtering function; and:

[0131]

[0132] Where: x is the spatial coordinate before filtering; x′ is the spatial coordinate after filtering; Δ is the filtering scale;

[0133] The governing equation for the incompressible fluid after filtering is:

[0134]

[0135] in: are the three velocity components after filtering in the Cartesian coordinate system; is the filtered pressure; ρ is the air density; ν is the kinematic viscosity; τ ij represents the sub-grid scale stress;

[0136] Small-scale vortices are modeled using the sub-grid eddy viscosity model, where the expression of the standard SGS model is:

[0137]

[0138] Where: μ t is the SGS eddy viscosity coefficient, δ ij is the Kronecker function, is the filtered thickness strain rate tensor;

[0139] Eddy viscosity coefficient μ t Calculated by the Smagorinsky-Lilly model:

[0140]

[0141] Where: k is the von Karman constant, usually 0.42; C s is the Smagorinsky constant, usually 0.1; Δ is the filtering scale.

[0142] Step 6: Numerical analysis

[0143] The pressure and wind speed data collected inside and outside the building under the sudden opening of the building model are numerically analyzed.

[0144] 6.1 Working conditions and measurement point arrangements for open and closed models

[0145] For the closed model, this embodiment simulates the arrangement of wind pressure measuring points in the reference TPU low-rise building experiment. The arrangement of the roof pressure measuring points is consistent with that of the TPU test pressure measuring points, with a total of 64 pressure measuring points. Secondly, in order to compare the test results, a total of 40 pressure measuring points are arranged along the central axis of the house. Fig.10 For the opening model, this embodiment also arranges 8 external pressure measuring points around the orifice, denoted as W1-W8, and sets 5 internal pressure measuring points at the center of the wall on the windward side, leeward side, side windward side and roof inside the opening model, denoted as N1-N5, see Fig.11In addition, in order to compare the difference in external pressure distribution between the open model and the closed model, two working conditions at 0° and 45° angles were set for the closed TPU model, and the mesh encryption method was the same as Figure 7 Consistent.

[0146] This embodiment conducts research on the building model under different wind directions, with a total of 8 working conditions, and the specific working condition parameters are detailed in Table 3. The numerical model under each working condition is set up in the same way as the closed structure example, and the inlet turbulence conditions are consistent.

[0147] Table 3 Working condition setting table

[0148]

[0149]

[0150] 6.2 Spatial distribution of internal pressure in the model

[0151] For the closed model, for the pressure measuring points on the roof and the pressure measuring points on the central axis of the house, each pressure measuring point is guaranteed to be arranged within the height of the first floor of the near-wall grid, and its wind pressure data results are processed by the following dimensionless wind pressure coefficient formula:

[0152]

[0153] Where: p(t) is the monitored pressure time history at the pressure measuring point; p0 is the static pressure at the reference point, the reference pressure measured at the center of the inlet; ρ is the air density, 1.225 kg / m 3 ; U ref The average wind speed at the reference eaves height, model height H is 0.08m, and the average wind speed of TPU numerical simulation is 13.5m / s. Average wind pressure coefficient Fluctuating wind pressure coefficient C' p And the extreme wind pressure coefficient They correspond to the mean value, standard deviation and extreme value of the wind pressure coefficient respectively.

[0154] For opening stray, considering background leakage and opening conditions, the relationship between the internal average wind pressure coefficient under multiple openings of the building and the external average wind pressure coefficient of the opening is obtained based on Bernoulli's theorem and mass conservation:

[0155]

[0156] Where: A W Indicates the size of the opening area on the windward side; A L Indicates the area size of background leakage; Indicates the average wind pressure coefficient inside the building; It represents the average wind pressure coefficient outside the building opening; The external average wind pressure coefficient at the opening representing the background leakage. Therefore, for a single opening and no leakage, we can get:

[0157]

[0158] The external wind pressure coefficient of the opening structure is the average time course of the measurement points (W1-W8) around the opening that have the greatest correlation with the internal pressure. The average external wind pressure coefficient is then used to derive the theoretical value of the internal pressure inside the single opening structure, which is then compared with the simulated value of the internal pressure measurement points (N1-N5) to verify the accuracy of the internal pressure of the single opening structure. Fig.12 The comparison results between the numerical simulation results of the internal pressure under the windward single opening structure and the theoretical value of the internal pressure are given. It can be seen from the figure that the results estimated by the theoretical equation of the average internal pressure coefficient are highly consistent with the numerical simulation results.

[0159] Depend on Fig.12 (a) It can be seen that the average internal pressure of the open structure varies with the opening ratio in the range of 0.69-0.74, and when the opening increases to a certain extent, the mean internal pressure does not change much. At an angle of 0°, the numerical results of different opening ratios are more consistent with the theoretical results in the case of small opening ratios than in the case of large opening ratios, with a maximum error of about 9%. This may be due to the greater correlation between the external pressure measurement points around the orifice and the internal pressure measurement points in the case of small openings, so the estimation of the average internal pressure coefficient is relatively accurate.

[0160] Depend on Fig.12 (b) It can be seen that under the same opening ratio and different wind direction angles, the numerical results of the average internal pressure coefficient are consistent with the theoretical results, and the maximum error is about 5%. At the same time, the change of the average internal pressure shows a trend of first decreasing and then increasing with the change of the wind direction angle, and the value range is -0.61-0.73. In addition, it can be found that for a single opening with a wind direction angle of 0° on the windward side, the corresponding average internal pressure coefficient is the largest under this condition, so the wind direction angle of 0° is the most unfavorable position for a single opening building.

[0161] From the numerical results, for examples with different opening sizes and different wind directions, the average internal pressure simulated by the LES in this embodiment can fit the theoretical value well, and the maximum error does not exceed 10%. Therefore, it can be considered that the numerical scheme for the TPU opening model is applicable.

[0162] 6.3. Distribution of external pressure around the model

[0163] In addition, in order to explore the external pressure distribution law on the surface of the opening model, the wind pressure on the outer surface of the model of the working case is processed using the dimensionless wind pressure coefficient formula to obtain the surface wind pressure coefficient, and then the average and variance processing are performed to obtain the average wind pressure coefficient and the pulsating wind pressure coefficient of the model surface. The opening ratio (the ratio of the opening area to the area of ​​the wall where the opening is located) is recorded as ρ.

[0164] Fig.13 (a)-(d) The average wind pressure coefficient distribution cloud diagram of the model's outer periphery at a closed model, ρ = 0.3%, ρ = 3.1%, and ρ = 12.5% ​​at a wind direction angle of 0 degrees. Fig.12 (a)-(d), it can be found that compared with the closed model, the maximum positive pressure area on the windward side of the models with different opening ratios will gradually decrease as the opening ratio increases. For the model with ρ=12.5%, the maximum average wind pressure coefficient area on the windward side will be smaller. This may be because when the building has a large opening, the airflow is easier to enter the interior of the building, forming a backflow at the opening, further reducing the airflow speed acting on the wall. It is worth noting that except for the front area where the opening model is located, the negative pressure area on the roof and the side has no obvious change.

[0165] Fig.14 (a)-(b) show the distribution of the pulsating wind pressure coefficient on the external surface of the model at a wind direction angle of 0° for the closed model, ρ=0.3%, ρ=3.1%, and ρ=12.5%. The observation results show that the distribution area of ​​the pulsating wind pressure coefficient of the model with a small opening ratio remains consistent compared to the closed model, and the pulsating wind pressure area around the opening area has not increased significantly. In contrast, the high pulsating wind pressure area near the opening of the model with a large opening ratio has increased significantly, and the high pulsating areas on the roof and sides are significantly larger than those of the closed model. This further illustrates the complexity of the flow around the orifice in the case of a large opening, which increases the area of ​​high pulsating wind pressure coefficient on the surface of the building opening.

[0166] from Figure 13-14 It can be found that the influence of a single opening ratio on the windward surface on the wind pressure is mainly concentrated on the windward surface where the opening is located, and has little influence on the side and roof. In order to quantitatively analyze the influence of the opening ratio on the external pressure distribution of low-rise buildings, the wind pressure coefficient distribution on the central axis of the model is taken, and the opening part of the model is replaced by a dotted line. Fig.15 , showing the changes in the average wind pressure coefficient and pulsating wind pressure coefficient on the central axis of the closed model at an angle of 0° and models with different opening ratios. Fig.15(a) It can be found that on the windward side, the positive pressure range of the closed model is 0.65 to 0.78, but as the windward opening rate increases, the positive pressure on the windward side becomes lower and lower, but the fluctuation amplitude is more intense. Among them, the positive pressure fluctuation range of the windward side in the open model with an opening rate of ρ = 12.5% ​​is -0.54 to 0.72, which is about 15% less than that of the closed model. In the flow separation area at the corner of the roof, the negative pressure will become smaller as the windward opening rate increases, but only the open model with an opening rate of ρ = 12.5% ​​increases by about 8% compared with the closed model. For the other opening rate models, there is no significant change in the wind pressure distribution on the roof and other surrounding areas. Fig.15 (b) It can be found that compared with the closed model, as the opening rate increases, the pulsating wind pressure coefficient near the windward surface is slightly higher than that of the closed model, but the fluctuation amplitude is not too large. The pulsating wind pressure coefficient of the windward surface of each working condition is in the range of 0.35-0.45. It is worth noting that the pulsating wind pressure in the flow separation area at the front edge of the model roof with an opening rate of 3.1% is significantly smaller than that of the closed model. In addition, the pulsating wind pressure distribution of the roof and leeward side of the other opening models does not change much.

[0167] Fig.16 (a)-(b) show the contour coefficient cloud diagrams of the average wind pressure outside the low-rise building for the closed model and the model with openings at a wind direction angle of 45°. It can be seen that at an angle of 45°, there is no significant change in the average wind pressure distribution on the roof of the closed model and the open model, and the roof wind pressure is distributed in a cone shape, showing obvious flow separation. However, in the corner area of ​​the windward side of the model, the average positive pressure area of ​​the open model is larger than that of the closed model, while the average wind pressure area of ​​the surface where the opening is located is smaller than that of the closed model. This may be because the airflow in and out near the orifice reduces the incoming wind speed acting on the surface near the opening, causing the pressure to decrease.

[0168] Fig.17 (a)-(b) show the contour coefficients of the average wind pressure outside the low-rise building under the closed model with the opening model at a wind direction angle of 45°. Fig.16 It can be seen that the distribution of the roof pulsation area of ​​the opening model is basically consistent with the corresponding closed model at a 45° angle, but the high pulsation area of ​​the two sides of the open model is significantly reduced, and the surface pulsation wind pressure on the side where the opening is located is smaller than that of the closed model.

[0169] The above-described embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or changes made by those skilled in the art based on the present invention are within the protection scope of the present invention. The protection scope of the present invention shall be subject to the claims.

Claims

1. A method for sudden opening of a building based on mapping, characterized in that: The steps include: S1: creating an open model and a closed model of a building respectively, wherein the open model and the closed model have the same dimensions except that an opening is provided on the windward side of the open model; S2: Perform numerical simulation on the closed model under set flow field conditions until the flow field is stable, and save the flow field data; S3: setting the same flow field conditions for the opening model, mapping the flow field data saved in step S2 to the numerical simulation of the opening model as initial conditions; S4: Perform numerical simulation on the opening model to realize the dynamic simulation process of sudden opening of the building.

2. The mapping-based building sudden opening method according to claim 1, characterized in that: In the step S3, the "mapping" tool in OpenFoam is used to map the flow field data saved in step S2 to the numerical simulation of the opening model as the initial condition.

3. The mapping-based building sudden opening method according to claim 1, characterized in that: During the numerical simulation, the meshing methods of the open model and the closed model remain consistent.

4. A numerical simulation method for the change of internal and external pressure under sudden opening of a building, characterized by: The steps include: Step 1: Build the building model Creating an open model and a closed model of a building respectively, wherein the open model and the closed model have the same dimensions except that an opening is provided on the windward side of the open model; Step 2: Design the computational domain Construct two computational domains of size 30H×10H×6H, place the open model and the closed model in the two computational domains respectively, make the origins of the two computational domains located at the bottom center of the open model and the closed model respectively, and the distances between the bottom center of the open model and the closed model and the entrance and exit of the computational domain are both 10H and 20H, and H is the height of the open model and the closed model; Step 3: Divide the grid The opening model and its computational domain are meshed. In order to ensure that the boundary flow near the wall is accurately solved, a boundary layer region is set near the wall of the opening model. The closed model and its computational domain are meshed. In order to ensure that the boundary flow near the wall is accurately solved, a boundary layer region is set near the wall of the closed model. The meshing methods of the open model and the closed model are consistent, and the meshing of the two computational domains is consistent; Step 4: Set boundary conditions Inlet boundary conditions: The inlet adopts atmospheric flow boundary conditions and uses the consistent discrete flow turbulence generation method; Outlet boundary condition: The outlet boundary condition is set to pressure outlet; The top and two sides of the computational domain are set as slip boundary conditions, and the boundary conditions between the bottom of the computational domain and the building wall are set as no-slip boundary conditions; Step 5: Numerical simulation 51) Perform numerical simulation on the closed model under set flow field conditions, and perform simulation and solution based on the large eddy turbulence model until the flow field is stable, and save the flow field data; 52) setting the same flow field conditions for the opening model, mapping the flow field data saved in step S2 to the numerical simulation of the opening model as initial conditions; 53) Perform numerical simulation on the opening model and solve it based on the large eddy turbulence model to realize the dynamic simulation process of the sudden opening of the building; Step 6: Numerical analysis The pressure and wind speed data collected inside and outside the building under the sudden opening of the building model are numerically analyzed.

5. The method for numerical simulation of internal and external pressure changes under sudden opening of a building according to claim 1 is characterized by: In the step S2, the "mapFields" tool in OpenFoam is used to map the flow field data saved in step S2 to the numerical simulation of the opening model as the initial condition.

6. The method for numerical simulation of internal and external pressure changes under sudden opening of a building according to claim 4 is characterized by: In step 4, the mathematical expression of the fluctuating wind speed synthesized by the consistent discrete incoming flow turbulence generation method is: Where: u i , i=1, 2, 3 represent the pulsating wind speed in the three directions of x, y, and z respectively; j=1, 2, 3 represent the three directions of x, y, and z respectively; M represents the number of intervals of the spectrum; N represents the number of frequencies in each interval; and All are coefficients; Represents a random vector distributed on the unit sphere of space, ensuring that the velocity field meets the divergence-free condition; represents a dimensionless coordinate vector, and is the correlation coefficient between two points in space; f n，m is the frequency, and its mean is f m , standard deviation Δf is a uniform distribution; t is time; and: Among them: sign is the sign function; Indicates random numbers that obey the 0-1 normal distribution in all three directions; S ui (f m ) is the spectrum f m The corresponding power spectral density value in the i direction.

7. The method for numerical simulation of internal and external pressure changes under sudden opening of a building according to claim 6, characterized in that: In the consistent discrete inflow turbulence generation method, an iterative reshaping method is introduced to continuously correct the shape of the wind speed profile at the inlet, so that the turbulent wind field can fit the target wind profile in the target area without affecting the spatial correlation, and ensure the conservation of the flow through the inlet interface; the principle of the iterative reshaping method is: Where: U medn,t (z) and I i,t (z) is the target mean velocity profile and target turbulence intensity profile; and It is the average wind speed profile and turbulence intensity profile obtained after a simulation period at the center of the building area during the nth correction period; and is the average wind speed profile and turbulence intensity profile of the turbulence field generated at the inlet interface during the nth correction; γ n is the correction factor, which is used to ensure that the flow rate through the inlet interface after the (n+1)th correction of the average wind speed profile at the inlet interface is always conserved; Δz is the corresponding grid size in the z direction.

8. The method for numerical simulation of internal and external pressure changes under sudden opening of a building according to claim 4 is characterized by: In step 5, the method for simulating and solving the large eddy turbulence model is: Filter all vortex scales φ(x,t) in the flow field: in: is the large-scale vortex obtained by filtering; φ′(x,t) is the subgrid scale; G(x,x′) is the spatial filtering function; and: Where: x is the spatial coordinate before filtering; x′ is the spatial coordinate after filtering; Δ is the filtering scale; The governing equation for the incompressible fluid after filtering is: in: are the three velocity components after filtering in the Cartesian coordinate system; is the pressure after filtering; ρ is the air density; ν is the kinematic viscosity; τ ij represents the sub-grid scale stress; Small-scale vortices are modeled using the sub-grid eddy viscosity model, where the standard SGS model is expressed as: Where: μ t is the SGS eddy viscosity coefficient, δ ij is the Kronecker function, is the filtered thickness strain rate tensor; Eddy viscosity coefficient μ t Calculated by the Smagorinsky-Lilly model: Where: k is the von Karman constant; C s is the Smagorinsky constant; Δ is the filtering scale.

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