Numerical simulation method for building sudden opening and internal and external pressure changes under sudden opening based on sliding mesh

Abstract

This invention discloses a method for sudden opening of a building based on a sliding mesh, comprising the following steps: S1: Create a building model, and set a sliding mesh region on at least one side of the reserved opening position on the windward side of the building model, while the other areas of the building model are stationary mesh regions; define the interface between the stationary mesh region and the sliding mesh region as the AMI interface; S2: Apply a piecewise function of velocity and time to the given sliding mesh region, causing the sliding mesh region to be located at its initial position and close the building model; during the numerical simulation, move the sliding mesh region along the AMI interface to transfer external flow field information to the internal flow field of the building through the AMI interface, thereby achieving the dynamic simulation effect of sudden opening. This invention also discloses a numerical simulation method for the change of internal and external pressure under sudden opening of a building.

Description

Technical Field

[0001] This invention belongs to the field of civil engineering technology, specifically a numerical simulation method for sudden openings in buildings based on sliding grids and the changes in internal and external pressures under sudden openings. Background Technology

[0002] In recent years, coastal areas of my country have experienced frequent wind disasters. Post-disaster data shows that the roofs and other envelopes of low-rise buildings suffer severe damage, accounting for more than half of the total losses. This damage is often caused by projectiles carried by strong winds damaging building doors and windows, leading to a sharp increase in internal air pressure. The combined effect of this and external pressure causes damage to the building's roof and other envelope structures. Regarding the internal and external pressure responses of wind-induced opening structures, many scholars have used wind tunnel experiments to study different opening parameters (number of openings, opening location, opening shape, etc.). Some scholars have also studied the transient internal pressure response of closed models under sudden opening conditions. However, existing research is mainly based on wind tunnel experiments and lacks numerical simulation studies of corresponding transient opening conditions, resulting in a lack of in-depth exploration of sudden openings in buildings. The key problem causing this phenomenon is that existing numerical simulation methods are insufficient 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 numerical simulation method for sudden openings in buildings and changes in internal and external pressure under sudden openings based on sliding meshes, which can realize the dynamic simulation of sudden openings in buildings and the numerical simulation of changes in internal and external pressure under sudden openings in buildings.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] This invention first proposes a method for sudden openings in buildings based on sliding meshes, comprising the following steps:

[0006] S1: Create a building model and set a sliding mesh area on at least one side of the reserved opening on the windward side of the building model, while the other areas of the building model are static mesh areas; define the interface where the static mesh area and the sliding mesh area meet as the AMI interface;

[0007] S2: Given a piecewise function of velocity and time for the slip mesh region, the slip mesh region is positioned at its initial location and closes the building model. During the numerical simulation, the slip mesh region moves along the AMI interface, transmitting external flow field information to the internal flow field of the building through the AMI interface to achieve a dynamic simulation effect of a sudden opening.

[0008] Furthermore, in step S1, the method for constructing the building model includes the following steps:

[0009] 11) Construct a building model, and reserve a sliding mesh area on at least one side of the reserved opening position in the building model, and make the size of the sliding mesh area consistent with that of the building model;

[0010] 12) Divide the building model into mesh regions: divide the exterior of the building model into mesh region 0, the interior of the building into mesh region 1, and the sliding mesh region into mesh region 2;

[0011] 13) Define AMI interfaces: Define two interfaces that connect the sliding mesh region and the stationary mesh region as interface 1 and interface 3, and two stationary region interfaces located at the reserved opening as interface 2 and interface 4; define interface 1, interface 2, interface 3 and interface 4 as AMI interfaces.

[0012] Furthermore, the piecewise functions for velocity and time are as follows:

[0013]

[0014] Among them: U sliding Δt represents the velocity of the sliding mesh region; t represents the simulation time; t0 represents the moment of sudden opening; Δt represents the motion time of the sliding mesh; ΔL represents the distance the sliding mesh moves to achieve a complete opening.

[0015] This invention also proposes a numerical simulation method for the change of internal and external pressure under sudden openings in a building, comprising the following steps:

[0016] Step 1: Construct a building model with a sudden opening.

[0017] Create a building model and set a sliding mesh area on at least one side of the reserved opening on the windward side of the building model, while the other areas of the building model are static mesh areas; define the interface where the static mesh area and the sliding mesh area meet as the AMI interface;

[0018] Step 2: Design the computational domain

[0019] Construct a computational domain with dimensions of 30H×10H×6H, place the building model within the computational domain, and position the origin of the computational domain at the center of the bottom of the building model. The distances from the center of the bottom of the building model to the entrance and exit of the computational domain are 10H and 20H, respectively, where H is the height of the building model.

[0020] Step 3: Grid Generation

[0021] The building model and the computational domain are meshed separately. To ensure that the boundary flow near the wall of the building model is solved accurately, a boundary layer region is set at the wall of the building model.

[0022] Step 4: Set boundary conditions

[0023] Inlet boundary conditions: Atmospheric inflow boundary conditions are used at the inlet, and the uniform discrete inflow turbulence generation method is employed;

[0024] Export boundary conditions: The export boundary conditions are set to pressure outlet;

[0025] The top and two sides of the computational domain are set as sliding boundary conditions, while the bottom of the computational domain and the building wall boundary conditions are set as non-slip boundary conditions.

[0026] Step 5: Numerical Simulation

[0027] Given a piecewise function of velocity and time in a slip grid region, the simulation is solved based on the large eddy turbulence model. Under initial conditions, the slip grid region is placed in its initial position and the building model is closed. After the wind speed and pressure in the entire watershed stabilize, the slip grid region is moved along the AMI interface to transfer the external flow field information to the internal flow field of the building through the AMI interface, so as to achieve the dynamic simulation effect of sudden opening.

[0028] Step Six: Numerical Analysis

[0029] Numerical analysis was performed on the pressure and wind speed data inside and outside the building collected under the condition of a sudden opening in the building model.

[0030] Furthermore, the method for constructing the building model in step one is as follows:

[0031] 11) Construct a building model, and reserve a sliding mesh area on at least one side of the reserved opening position in the building model, and make the size of the sliding mesh area consistent with that of the building model;

[0032] 12) Divide the building model into mesh regions: divide the exterior of the building model into mesh region 0, the interior of the building into mesh region 1, and the sliding mesh region into mesh region 2;

[0033] 13) Define AMI interfaces: Define two interfaces that connect the sliding mesh region and the stationary mesh region as interface 1 and interface 3, and two stationary region interfaces located at the reserved opening as interface 2 and interface 4; define interface 1, interface 2, interface 3 and interface 4 as AMI interfaces.

[0034] Furthermore, in step five, the piecewise function relating speed and time is:

[0035]

[0036] Among them: U slidingΔt represents the velocity of the sliding mesh region; t represents the simulation time; t0 represents the moment of sudden opening; Δt represents the motion time of the sliding mesh; ΔL represents the distance the sliding mesh moves to achieve a complete opening.

[0037] Furthermore, in step four, the mathematical expression for the fluctuating wind speed synthesized using the consistent discrete incoming flow turbulence generation method is as follows:

[0038]

[0039] Where: u i i = 1, 2, 3 represent the fluctuating wind speeds in the x, y, and z directions, respectively; j = 1, 2, 3 represent the x, y, and z directions, respectively; M represents the number of frequency intervals in the spectrum; N represents the number of frequencies in each interval. and All are coefficients; It represents a random vector distributed on a unit sphere in space, ensuring that the velocity field satisfies the divergence-free condition; Represents a dimensionless coordinate vector, and f is the correlation coefficient between two points in space; n,m Let f be the frequency, and let f be the mean. m The standard deviation Δf is a uniform distribution; t is time; and:

[0040]

[0041] Where: sign is the sign function; S represents a random number that follows a 0-1 normal distribution in all three directions; ui (f m ) is the spectrum f m The corresponding power spectral density value in the i-direction.

[0042] Furthermore, in the consistent discrete incoming flow turbulence generation method, an iterative reshaping method is introduced to continuously correct the shape of the wind speed profile at the inlet. This ensures that the turbulent wind field can fit the target wind profile within the target region without affecting spatial correlation, while guaranteeing the conservation of flow rate through the inlet interface. The principle of the iterative reshaping method is as follows:

[0043]

[0044] In the formula: U mean,t (z) and I i,t (z) represents the target mean velocity profile and the target turbulence intensity profile; and It is the average wind speed profile and turbulence intensity profile obtained from a simulated time history at the center of the building area during the nth correction period; and These are the mean wind speed profile and turbulence intensity profile of the turbulent field generated at the inlet interface during the nth correction; γ n Δz is a correction factor used to ensure that the flow rate through the inlet interface remains constant after the (n+1)th correction of the average wind speed profile at the inlet interface; Δz is the grid scale corresponding to the z-direction.

[0045] Furthermore, in step five, the method for simulating and solving the large eddy turbulence model is as follows:

[0046] Filter all vortex scales Φ(x,t) in the flow field:

[0047]

[0048] in: For large-scale vortices obtained through filtering; Φ′(x,t) is the subgrid scale; G(x,x′) is the spatial filtering function; and:

[0049]

[0050]

[0051] Where: x is the spatial coordinate before filtering; x′ is the spatial coordinate after filtering; Δ is the filtering scale;

[0052] The filtered incompressible fluid control equations are as follows:

[0053]

[0054] in: These are the three velocity components after filtering in the Cartesian coordinate system; ρ is the filtered pressure; ν is the air density; ν is the kinematic viscosity; τ is the pressure after filtering. ij Represents subgrid-scale stress;

[0055] Small-scale vortices are modeled using a subgrid-based eddy viscosity model, where the expression for the standard SGS model is:

[0056]

[0057] Where: μ t It is the SGS eddy viscosity coefficient, δ ij It is the Kronecker function. It is the filter thickness strain rate tensor;

[0058] Eddy viscosity coefficient μ t Calculated using the Smagorinsky-Lilly model:

[0059]

[0060] Where: k is the von Karman constant; C s Δ is the Smagorinsky constant; Δ is the filtering scale.

[0061] The beneficial effects of this invention are as follows:

[0062] This invention is based on a method for sudden openings in buildings using sliding meshes. It constructs a sliding mesh region at the reserved opening location in the building model, and defines the interface between the sliding mesh region and the stationary mesh region as the "AMI" interface to simulate the fluid interaction between different parts. The unique advantage of sliding meshes is that they can continuously and smoothly simulate the dynamic changes of the flow field without interrupting the calculation process. This allows researchers to capture the transient response of the flow field at the moment of opening and the subsequent flow field, including key phenomena such as the sharp rise in internal pressure and the disturbance of the external wind field. Attached Figure Description

[0063] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the following figures are provided for illustration:

[0064] Figure 1 This is a flowchart of the method for sudden opening of a building based on a sliding mesh according to the present invention;

[0065] Figure 2 A schematic diagram of the building model; Figure 3 A schematic diagram of grid region division and interface in a building model;

[0066] Figure 4 The instantaneous velocity and pressure fields before and after the opening are shown. Figure 5 Time history of wind pressure and wind speed at the openings inside the building;

[0067] Figure 6 This is a schematic diagram of the computational domain and model location; Figure 7 A schematic diagram of a computational domain encrypted grid;

[0068] Figure 8 A schematic diagram of a dense mesh and a local mesh for a model with closed or open openings;

[0069] Figure 9 This is a wind field characteristic map; Figure 10 A diagram showing the layout of measurement points for the model;

[0070] Figure 11 Diagram showing the layout of external and internal pressure measuring points for the opening; Figure 12 Comparison of theoretical and simulated values ​​for average internal pressure;

[0071] Figure 13 A cloud map showing the average wind pressure coefficient at different opening ratios under a 0° angle; Figure 14 Cloud maps of fluctuating wind pressure coefficients at different opening ratios at a 0° angle;

[0072] Figure 15 The wind pressure distribution on the central axis of the model under different aperture ratios at a 0° angle; Figure 16 The external average wind pressure is given by the open and closed models at a 45° angle.

[0073] Figure 17 External pulsating wind pressure for the open and closed models at a 45° angle;

[0074] Figure 18 A schematic diagram of the roof measuring points and axis division; Figure 19 A comparison of wind pressure distribution along the central axis in the closed model and the slip model;

[0075] Figure 20 Comparison of internal and external pressure coefficient curves around the orifice; Figure 21 The variation of the internal pressure coefficient at the N2 measuring point under different opening rates;

[0076] Figure 22 The variation of the external pressure coefficient at measuring point B25 on the roof under different opening rates;

[0077] Figure 23 Time histories of wind speed in the X direction at orifices with different opening rates; Figure 24 This is the probability density function of the internal pressure coefficient under typical working conditions;

[0078] Figure 25 The time histories of the transient net wind pressure coefficients of each surface of the model under typical working condition G1;

[0079] Figure 26 The correlation between internal and external pressures at the orifice with different opening ratios at a 0° angle;

[0080] Figure 27 The correlation between internal and external pressures in the model under different wind angles;

[0081] Figure 28 The correlation between external and internal pressure at different locations on the roof under operating condition G2;

[0082] Figure 29 The net wind pressure distribution on the roof before and after the opening at the bottom of G1; Figure 30 The net wind pressure distribution on the roof before and after the G2 opening;

[0083] Figure 31 The net wind pressure distribution on the roof before and after the opening at the bottom of G5 is shown. Detailed Implementation

[0084] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0085] I. A Method for Sudden Openings in Buildings Based on Sliding Grids

[0086] like Figure 1 As shown, this embodiment of the building sudden opening method based on sliding mesh includes the following steps:

[0087] S1: Create a building model, and set a sliding mesh region on at least one side of the reserved opening location on the windward side of the building model; the other areas of the building model are static mesh regions; define the interface where the static mesh region and the sliding mesh region meet as the AMI interface, such as... Figure 2 As shown.

[0088] Specifically, the steps for constructing a building model are as follows:

[0089] 11) Construct a building model, and reserve a sliding mesh area on at least one side of the reserved opening position in the building model, and make the size of the sliding mesh area consistent with that of the building model;

[0090] 12) Divide the building model into mesh regions: divide the exterior of the building model into mesh region 0, the interior of the building into mesh region 1, and the sliding mesh region into mesh region 2;

[0091] 13) Define AMI interfaces: Define interface 1 and interface 3 as the two interfaces connecting the sliding mesh region and the stationary mesh region, and interface 2 and interface 4 as the two stationary region interfaces located at the reserved opening; define interface 1, interface 2, interface 3 and interface 4 as AMI interfaces, such as... Figure 3 As shown.

[0092] S2: Given a piecewise function of velocity and time for the slip mesh region, the slip mesh region is positioned at its initial location and closes the building model. During the numerical simulation, the slip mesh region moves along the AMI interface, transmitting external flow field information to the internal flow field of the building through the AMI interface to achieve a dynamic simulation effect of a sudden opening.

[0093] Specifically, the piecewise function relating velocity and time is:

[0094]

[0095] Among them: U sliding Δt represents the velocity of the sliding mesh region; t represents the simulation time; t0 represents the moment of sudden opening; Δt represents the motion time of the sliding mesh; ΔL represents the distance the sliding mesh moves to achieve a complete opening.

[0096] In this way, the sliding grid area can be controlled to start moving at a certain moment t0. When the sliding grid movement area intersects with the inner and outer grid interfaces at the building opening, the flow field information of the outer grid has been transmitted to the building interior through the "AMI" interface, thus simulating the process of the building's windows or doors being suddenly opened.

[0097] To realize a sudden opening in a building model using the sliding mesh method, it is necessary to construct the sliding mesh area in advance. The example model using the sliding mesh needs to set the reserved area of ​​the sliding mesh in advance according to the size of the opening. Figure 2 A closed model using the sliding mesh method is shown. The purpose of this model is to construct the "AMI" interface. The wall thickness of the model at the opening is 6 mm, and a sliding mesh area is reserved above the opening. The size of the sliding mesh area is exactly the same as the size of the simulated door and window.

[0098] Figure 3 A two-dimensional schematic diagram incorporating a sliding mesh is shown, dividing the building's background mesh region into three parts: mesh region 0 outside the building, mesh region 1 inside the building, and sliding mesh region 2. The geometry of the sliding mesh region matches the building's opening area. To ensure that flow field information from the external mesh region can be transmitted to the internal mesh region, "AMI" interfaces are defined: interfaces 1 and 3 where the sliding mesh region meets the stationary mesh region, and interfaces 2 and 4 where the two stationary regions are located at the building opening. When sliding mesh region 2 moves downwards, interfaces 1 and 3 coincide with interfaces 2 and 4 respectively, thus transmitting external flow field information to the internal flow field through the "AMI" interfaces.

[0099] This embodiment uses a sliding mesh-based method for sudden building openings (hereinafter referred to as the "sliding mesh method"), employing a uniform inlet flow of 7 m / s. Furthermore, regarding boundary conditions, an additional "AMI" interactive interface needs to be defined for the sliding mesh region. The area for defining the "AMI" interface is detailed below. Figure 3 The motion mode of the sliding mesh to achieve the opening requires specifying the motion time of the sliding mesh. In this embodiment, the opening time τ is 0.00005, corresponding to one time step.

[0100] Figure 4Images (a)-(d) show two-dimensional slices of the simulation results along the y=0 axis using the sliding mesh method, illustrating the instantaneous combined velocity and pressure fields inside and outside the model at 0.5 s before and after the opening. It can be observed that at 2 s after the opening, the opening is tightly closed, preventing airflow from entering the building. As the sliding mesh above the opening moves downwards, external airflow enters the building through the "AMI" interface, and the internal pressure changes from zero to positive pressure. This embodiment ensures that both the internal pressure and wind speed are zero at the corresponding moment before the opening, consistent with actual conditions.

[0101] Figure 5 (a)-(b) show the time history curves of wind pressure and longitudinal wind speed at the opening inside the building under the sliding grid method. It can be observed that before the sliding grid moves, both the wind speed and internal pressure inside are 0. As the opening is opened, the internal pressure suddenly surges, reaching a maximum internal pressure coefficient of approximately 1.5, and the wind speed at the opening also flows inward. This aligns with the real-world phenomenon of a building door being suddenly opened, causing a sudden and rapid influx of air into the building.

[0102] II. Numerical Simulation Method for Internal and External Pressure Changes under Sudden Openings in Buildings

[0103] The numerical simulation method for changes in internal and external pressure under sudden openings in a building, as described in this embodiment, includes the following steps:

[0104] Step 1: Construct a building model with a sudden opening.

[0105] Create a building model and set a sliding mesh area on at least one side of the reserved opening position on the windward side of the building model, while the other areas of the building model are static mesh areas; define the interface where the static mesh area and the sliding mesh area meet as the AMI interface.

[0106] Specifically, the steps for constructing a building model are as follows:

[0107] 11) Construct a building model, and reserve a sliding mesh area on at least one side of the reserved opening position in the building model, and make the size of the sliding mesh area the same as that of the building model.

[0108] 12) Divide the grid regions: Divide the exterior of the building model into grid region 0, the interior of the building into grid region 1, and the sliding grid region into grid region 2.

[0109] 13) Define AMI interfaces: Define two interfaces that connect the sliding mesh region and the stationary mesh region as interface 1 and interface 3, and two stationary region interfaces located at the reserved opening as interface 2 and interface 4; define interface 1, interface 2, interface 3 and interface 4 as AMI interfaces.

[0110] Specifically, the TPU database is a comprehensive database jointly established by Tokyo Polytechnic University. This embodiment uses the wind tunnel pressure measurement experiment of a low-rise building under atmospheric flow from the TPU database. The wind field topography type corresponds to Class III terrain in the Japanese Wind Load Code 2004, with a mean wind speed profile index of 0.2, a reference height of 10m at full size, and a corresponding turbulence intensity of 25%. The model selected is a rigid flat roof model with an aspect ratio of 1:1 and a width-to-height ratio of 2:1, with dimensions of 160mm × 160mm × 80mm (L × B × H) and a geometric scale ratio of 1:100. For ease of description, this embodiment refers to this model as the TPU model.

[0111] Since subsequent monitoring of the pressure distribution on the inner and outer pressure surfaces of the opening structure is necessary, this embodiment references existing experimental models for studying wind-induced opening internal pressure. The TPU model has been modified accordingly, featuring a double-sided sandwich structure to ensure proper arrangement of the pressure measuring pipes. The sandwich layer is treated as a wall surface, with a thickness of 10mm. Therefore, the actual internal dimensions of the model are 140×140×60 (mm). 3 The building model used in this study has a square opening. For ease of representation, the side length of the opening is denoted as l0. Specifically, in this embodiment, the side length of the opening, l0, is 0.02m.

[0112] Step 2: Design the computational domain

[0113] like Figure 6 As shown, this embodiment constructs a computational domain with dimensions of 30H×10H×6H (H=80mm). The building model is placed within the computational domain, with the origin of the domain located at the center of the bottom of the building model. The distances from the center of the bottom of the building model to the inlet and outlet of the computational domain are 10H and 20H, respectively, where H is the height of the building model. This ensures sufficient development of the inlet flow. The distance from the inlet to the center of the model is 10H. To meet the requirements of building wind tunnel testing, the model's blockage rate is 3.3%, satisfying the requirement that the blockage effect is less than 5%. The same computational domain size is used whether the building model's opening is closed or open.

[0114] Step 3: Grid Generation

[0115] The building model and the computational domain are meshed separately. To ensure that the boundary flow near the wall of the building model is solved accurately, a boundary layer region is set at the wall of the building model.

[0116] In this embodiment, three mesh schemes were used for TPU model verification: coarse mesh, medium mesh, and fine mesh for mesh independence analysis, denoted as mesh 1, mesh 2, and mesh 3, as shown in Table 1. The computational domain was preprocessed using the OpenFoam preprocessing tools blockMesh and snappyHexMesh, including mesh generation, densification, and boundary layer addition. The three mesh schemes were generated by changing the number of meshes in the x, y, and z directions within the blockMesh tool. The entire computational domain was drawn using a structured mesh, with unstructured meshes used between different density transition zones. Four density levels of mesh regions were established, achieving a gradual transition from large to small mesh sizes. The diagonal coordinates of the first-level density region were (-10H, -2.5H, 0) and (5H, 2.5H, 2H); the diagonal coordinates of the second-level density region were (-2H, -1.5H, 0) and (2H, 1.5H, 1.5H); and the diagonal coordinates of the third-level density region were (-1.125H, -1.125H, 0) and (1.125H, 1.125H, 1.125H). A detailed density diagram can be found below. Figure 7 .

[0117] Near the building target, the mesh size is very important for the simulation accuracy. To ensure that the boundary flow near the wall is solved accurately, a boundary layer region needs to be set at the model wall. Figure 8 (a)-(b) show the slices of the refined mesh along the y=0 direction and the schematic diagram of the boundary layer mesh when the model opening is closed. A dimensionless distance y+ is introduced to quantify the flow state of the fluid near the wall. The mesh refinement scheme of mesh 2 ensures that the average y+ value of the first layer of mesh near the wall basically meets the simulation requirements, as shown in Table 1. Figure 8 (c)-(d) also show schematic diagrams of slices of the refined mesh along the y=0 direction and local meshes near the opening under the building model. The watershed mesh inside the entire model is approximately 600,000, and the total number of meshes is approximately 3.4 million. When the model opening is open, compared with the mesh computation domain when the opening is closed, except for the mesh near the building opening, the mesh size is the same in the other refined areas.

[0118] Table 1 Mesh Scheme for Closed Model

[0119]

[0120] Step 4: Set boundary conditions

[0121] Inlet boundary conditions: Atmospheric inflow boundary conditions are used at the inlet, and a consistent discrete inflow turbulence generation method is employed. Outlet boundary conditions: The outlet boundary conditions are set as a pressure outlet. Slip boundary conditions are set at the top and both sides of the computational domain, while no-slip boundary conditions are set at the bottom of the computational domain and the building wall.

[0122] Specifically, the initial physical field boundary conditions for the numerical example in this embodiment are as follows: the inlet adopts atmospheric inflow boundary conditions, and the consistent discrete inflow turbulence generation method, i.e., the CDRFG method, is used. The wind profile data from the TPU wind tunnel test used in this embodiment are shown in Table 2.

[0123] Table 2 Parameter settings for the inlet turbulent wind field

[0124]

[0125] Note: According to European standard (ESDU 85020), some parameters in the table have Z0 = 0.7m.

[0126] For a detailed schematic diagram of the flow field boundary in the computational domain, please refer to [link / reference]. Figure 7 The outlet boundary condition is set to pressure outlet; the top and two sides of the computational domain are set to slip boundary conditions, which means that the tangential velocity of the fluid passing through the boundary surface is not zero and the velocity direction is parallel to the boundary surface; the bottom of the computational domain and the building wall boundary conditions are set to no-slip boundary conditions, which means that the fluid does not pass through the boundary surface and all its normal velocity components with the boundary surface are zero.

[0127] Turbulent inlet typically refers to atmospheric boundary layer (ABL) inflow. In numerical simulations, the goal is to generate a numerical turbulent wind field at the inlet interface with statistical characteristics similar to real-world natural wind fields. This requires including mean wind speed profiles, turbulence intensity, fluctuating wind speed power spectra, and turbulence integral scales, among other things.

[0128] In this embodiment, the mathematical expression for the fluctuating wind speed synthesized using the Consistent Discrete Incoming Turbulence Generation Method (CDRFG) is as follows:

[0129]

[0130] Where: u i i = 1, 2, 3 represent the fluctuating wind speeds in the x, y, and z directions, respectively; j = 1, 2, 3 represent the x, y, and z directions, respectively; M represents the number of frequency intervals in the spectrum; N represents the number of frequencies in each interval. and All are coefficients; It represents a random vector distributed on a unit sphere in space, ensuring that the velocity field satisfies the divergence-free condition; Represents a dimensionless coordinate vector, and f is the correlation coefficient between two points in space; n,m Let f be the frequency, and let f be the mean. m The standard deviation Δf is a uniform distribution; t is time; and:

[0131]

[0132]

[0133] Where: sign is the sign function; r i m,n S represents a random number that follows a 0-1 normal distribution in all three directions; ui (f m ) is the spectrum f m The corresponding power spectral density value in the i-direction.

[0134] This embodiment uses an artificial synthesis method to generate the inlet atmospheric flow. The specified parameters for the generated turbulent wind field at the inlet are shown in Table 2. To ensure the accuracy of the wind load on the target building surface, a wind profile consistent with the TPU experiment needs to be monitored at the building location (i.e., the center of the computational domain origin) under an open wind field. However, since the pulsating wind speed synthesized in CDRFG only satisfies some characteristic conditions of the atmospheric flow on some parameters, when the wind field enters the computational domain, the turbulent wind field monitored at the building location will exhibit a certain degree of nonlinear dissipation in the height direction. Secondly, this method cannot completely guarantee that the turbulent inlet strictly meets the dispersion condition, which can also lead to abnormal virtual pressure fluctuations in the numerical calculation. Therefore, this embodiment introduces an improved "Iterating-Reshaping" method (IRCDRFG) to continuously correct the shape of the wind speed profile at the inlet. This ensures that the turbulent wind field can fit the target wind profile within the target area without affecting spatial correlation, and maintains the conservation of flow through the inlet interface at all times. Specifically, the principle of the iterative reshaping method is as follows:

[0135]

[0136] In the formula: U mean,t (z) and I i,t (z) represents the target mean velocity profile and the target turbulence intensity profile; and It is the average wind speed profile and turbulence intensity profile obtained from a simulated time history at the center of the building area during the nth correction period; and These are the mean wind speed profile and turbulence intensity profile of the turbulent field generated at the inlet interface during the nth correction; γ nΔz is a correction factor used to ensure that the flow rate through the inlet interface remains constant after the (n+1)th correction of the average wind speed profile at the inlet interface; Δz is the grid scale corresponding to the z-direction.

[0137] Figure 9 (a)-(b) show the wind speed profile at the building target and the dimensionless power spectrum at the reference height after four iterations of optimization based on the "Iterative Reshaping (IRCDRFG)" method under the air-wind field. It can be seen that the average wind speed and turbulence intensity of the 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 IRCDRRFG is accurate and reliable.

[0138] Step 5: Numerical Simulation

[0139] Given a piecewise function of velocity and time in a slip grid region, the simulation is solved based on the large eddy turbulence model. Under initial conditions, the slip grid region is placed in its initial position and the building model is closed. After the wind speed and pressure in the entire watershed stabilize, the slip grid region is moved along the AMI interface to transfer the external flow field information to the internal flow field of the building through the AMI interface, so as to achieve the dynamic simulation effect of a sudden opening.

[0140] The piecewise function relating velocity and time is:

[0141]

[0142] Among them: U sliding Δt represents the velocity of the sliding mesh region; t represents the simulation time; t0 represents the moment of sudden opening; Δt represents the motion time of the sliding mesh; ΔL represents the distance the sliding mesh moves to achieve a complete opening.

[0143] In this embodiment, the numerical solution settings are as follows: the open-source software OpenFoam is used, the LES turbulence model is adopted, the subgrid-scale filtering function is selected as the WALE subgrid model according to the literature, and the relevant turbulence model coefficients are: C e =1.048, C k =0.094, C w =0.544, kinematic viscosity is 1.455×10 -5 m 2 / s. In the discretization scheme settings, a second-order backward difference scheme was selected for time discretization. The diffusion and convection terms in the governing equations were handled using a second-order central difference scheme and a linear upwind stable transport scheme (LUST), respectively. Higher-order discretization schemes were chosen to ensure the accuracy of the numerical simulation. In the solver settings, a geometric algebraic multigrid (GAMG) solver and a preprocessed bijugate gradient (PBiCG) solver were used for pressure and velocity solutions, respectively. The convergence residual for iterative calculations was set to 1×10⁻⁶. -6 The Pimple algorithm was selected for transient solutions to velocity-pressure coupling problems.

[0144] In selecting the simulation time step, the specific impact of the time step on simulation accuracy is evaluated. This is especially relevant when the dimensionless time step t... * When tU0 / D (t is the simulation time step) does not exceed 0.025, the simulation results show consistency within this range. U0 is the average wind speed at the reference height, and D is the model characteristic length. In this embodiment, the dimensionless time step is 0.00875, which meets the requirements. The ratio of the entire calculation basin length to the wind speed at the reference height is called the full basin time. To obtain a stable convergent solution, preliminary calculations show that the wind speed and wind pressure are basically stable after 5 full basin time monitoring periods. Therefore, this embodiment selects the calculation results from the 6th to the 47th full basin time periods for statistical analysis, and the corresponding dimensionless time length tU H The value of / H is approximately 1400, and the maximum Courland number (CFL) in the calculation is approximately 1.2, which ensures convergence while also meeting the 10-minute statistical time requirement in the wind tunnel test specifications.

[0145] In this embodiment, the Large Eddy Turbulence (LES) model from numerical simulation is used for numerical calculations. The LES model, first proposed by Smagorinsky, lies between the Reynolds-averaged flow model (RANS) and direct simulation (DNS). It divides the eddy scale in the flow field into large-scale and small-scale eddies using a spatial filtering function. Specifically, the method for simulating and solving the Large Eddy Turbulence model is as follows:

[0146] Filter all vortex scales Φ(x,t) in the flow field:

[0147]

[0148] in: For large-scale vortices obtained through filtering; Φ′(x,t) is the subgrid scale; G(x,x′) is the spatial filtering function; and:

[0149]

[0150] Where: x is the spatial coordinate before filtering; x′ is the spatial coordinate after filtering; Δ is the filtering scale;

[0151] The filtered incompressible fluid control equations are as follows:

[0152]

[0153] in: These are the three velocity components after filtering in the Cartesian coordinate system; ρ is the filtered pressure; ν is the air density; ν is the kinematic viscosity; τ is the pressure after filtering. ij Represents subgrid-scale stress;

[0154] Small-scale vortices are modeled using a subgrid-based eddy viscosity model, where the expression for the standard SGS model is:

[0155]

[0156] Where: μ t It is the SGS eddy viscosity coefficient, δ ij It is the Kronecker function. It is the filter thickness strain rate tensor;

[0157] Eddy viscosity coefficient μ t Calculated using the Smagorinsky-Lilly model:

[0158]

[0159] Where: k is the von Karman constant, usually taken as 0.42; C s Δ is the Smagorinsky constant, typically 0.1; Δ is the filtering scale.

[0160] Step Six: Numerical Analysis

[0161] Numerical analysis was performed on the pressure and wind speed data inside and outside the building collected under the condition of a sudden opening in the building model.

[0162] 6.1 Working conditions and measurement point layout of the building model

[0163] When the model opening is closed, this embodiment simulates the wind pressure measurement point layout of the TPU low-rise building experiment. The roof pressure measurement points are arranged in the same way as the TPU test pressure measurement points, with a total of 64 pressure measurement points. Secondly, to compare the test results, a total of 40 pressure measurement points are also arranged along the central axis of the building, with increased density along the line. See [link to relevant documentation]. Figure 10 After the model opening is opened, this embodiment also arranges 8 external pressure measuring points around the opening, denoted as W1-W8. Inside the building model, on the windward, leeward, crosswind, and roof surfaces, 5 internal pressure measuring points are set at the center of the wall, denoted as N1-N5. (See...) Figure 11Furthermore, to compare the difference in external pressure distribution when the model opening is open or closed, two working conditions were set for the closed TPU model at 0° and 45° angles, with the mesh refinement method being the same as... Figure 7 Consistent.

[0164] This embodiment studies the building model under different wind angles, totaling eight operating conditions. Specific parameters for each condition are detailed in Table 3. The numerical model for each condition is set up in the same way as the closed structure example, and the inlet turbulence conditions are consistent.

[0165] Table 3 Operating Condition Settings

[0166]

[0167] 6.2 Spatial distribution of pressure within the model

[0168] When building openings are closed, for pressure measurement points on the roof and along the building's central axis, each pressure measurement point is ensured to be located within the first-floor height of the near-wall grid. The wind pressure data is processed using the following dimensionless wind pressure coefficient formula:

[0169]

[0170] In the formula: p(t) is the pressure monitoring time history at the pressure measuring point; p0 is the static pressure at the reference point, the reference pressure measured at the inlet center; ρ is the air density, 1.225 kg / m³. 3 U ref To reference the average wind speed at the eaves height, the model height H is 0.08m, and the average wind speed in the TPU numerical simulation is taken as 13.5m / s. Average wind pressure coefficient... Pulsating wind pressure coefficient C' p and extreme wind pressure coefficient These correspond to the average value, standard deviation, and extreme value of the wind pressure coefficient, respectively.

[0171] When a building has openings, considering background leakage and the opening itself, the relationship between the average internal wind pressure coefficient and the average external wind pressure coefficient of the openings under multiple openings is derived based on Bernoulli's theorem and the law of conservation of mass:

[0172]

[0173] In the formula: A W Indicates the size of the opening area on the windward side; A L Indicates the size of the area where the background is leaked; This indicates the average wind pressure coefficient inside the building; This indicates the average wind pressure coefficient outside the building opening; This represents the average external wind pressure coefficient at the orifice where there is a background leak. Therefore, for a single opening with no leak, we can obtain:

[0174]

[0175] The external wind pressure coefficient of the opening structure is obtained by taking the average time history of the measuring points (W1-W8) around the orifice that are highly correlated 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. This value is then compared with the simulated values ​​at the internal pressure measuring points (N1-N5) to verify the accuracy of the internal pressure of the single opening structure. Figure 12 The numerical simulation results of the internal pressure under a single open structure facing the wind are presented, and the theoretical value of the internal pressure is compared with that of the formula. As can be seen from the figure, the result estimated by the theoretical equation of the average internal pressure coefficient is in good agreement with the numerical simulation result.

[0176] Depend on Figure 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 the average internal pressure does not change much when the opening increases to a certain extent. At 0° angle, the numerical results for different opening ratios are in better agreement with the theoretical results than those for larger opening ratios, with a maximum error of about 9%. This may be because the external pressure measurement points and internal pressure measurement points around the orifice are more correlated when the opening is small, so the estimate of the average internal pressure coefficient is relatively accurate.

[0177] Depend on Figure 12 (b) It can be seen that, for the same opening ratio but different wind angles, the numerical results of the average internal pressure coefficient are in good agreement with the theoretical results, with a maximum error of about 5%. Furthermore, the average internal pressure changes with the wind angle, first decreasing and then increasing, with a range of -0.61 to 0.73. In addition, it can be found that for a single opening at a wind angle of 0° on the windward side, the average internal pressure coefficient is the highest under this condition. Therefore, a wind angle of 0° is the most unfavorable location for a single-opening building.

[0178] Numerical results show that for examples with different opening sizes and wind angles, the average internal pressure simulated by 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.

[0179] 6.3 Distribution of External Pressure Around the Model

[0180] Furthermore, to investigate the distribution law of external pressure on the surface of the building model, the surface wind pressure of the model in the working case example was processed using the dimensionless wind pressure coefficient formula to obtain the surface wind pressure coefficient. Subsequently, averaging and variance processing were performed to obtain the average wind pressure coefficient and the fluctuating wind pressure coefficient of the model surface. The aperture ratio (the ratio of the opening area to the area of ​​the wall where the opening is located) is denoted as ρ.

[0181] Figure 13 (a)-(d) are cloud maps showing the average wind pressure coefficient distribution around the outer perimeter of a closed model with ρ = 0.3%, ρ = 3.1%, and ρ = 12.5% ​​at a wind direction angle of 0 degrees. Figure 12 From (a) to (d), it can be observed that, compared to the closed model, the maximum positive pressure area on the windward side of models with different opening ratios gradually decreases as the opening ratio increases. For the model with ρ = 12.5%, the area with the maximum average wind pressure coefficient on the windward side is even smaller. This may be because, with large openings in the building, airflow can more easily enter the building interior, forming a backflow at the opening, further reducing the airflow velocity acting on the wall. It is worth noting that, apart from the front area where the building model is located, the negative pressure areas on the roof and sides do not change significantly.

[0182] Figure 14 (a)-(b) present the distribution of fluctuating wind pressure coefficients on the external surface of the closed model, with ρ = 0.3%, ρ = 3.1%, and ρ = 12.5% ​​at a wind direction angle of 0°. The observations show that the distribution area of ​​the fluctuating wind pressure coefficient remains consistent between the closed and small opening ratio models, and the fluctuating wind pressure area around the opening does not increase significantly. In contrast, the high fluctuating wind pressure area near the opening of the large opening ratio model increases significantly, and the high fluctuating 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 opening under large opening conditions, increasing the area of ​​high fluctuating wind pressure coefficients on the surface where the building opening is located.

[0183] from Figure 13-14 It can be observed that the impact of a single opening ratio on wind pressure on the windward side is mainly concentrated on the windward side where the opening is located, with a smaller impact on the sides and roof. To quantify the impact of the opening ratio on the external pressure distribution of low-rise buildings, the wind pressure coefficient distribution along the central axis of the model is taken, and the opening parts of the model are replaced by dashed lines. Figure 15 The paper shows the changes in the average wind pressure coefficient and fluctuating wind pressure coefficient along the central axis of the closed model at 0° angle and the models with different opening ratios. Figure 15(a) It can be observed that at the windward side, the positive pressure range for the closed model is 0.65 to 0.78. However, as the opening ratio increases, the positive pressure at the windward side decreases, but the fluctuation is more pronounced. Specifically, the positive pressure fluctuation range for the open model with an opening ratio ρ = 12.5% ​​is -0.54 to 0.72, a reduction of approximately 15% compared to the closed model. In the flow separation area at the corner of the roof, the negative pressure decreases with increasing opening ratio, but only the open model with an opening ratio ρ = 12.5% ​​shows an increase of approximately 8% compared to the closed model. For the other opening ratio models, there is no significant change in wind pressure distribution on the roof and in other surrounding areas. Figure 15 (b) It can be observed that, compared with the closed model, as the opening ratio increases, the fluctuating wind pressure coefficient near the windward face is slightly higher than that of the closed model, but the fluctuation range is not too large. The fluctuating wind pressure coefficient on the windward face in all operating conditions is within the range of 0.35-0.45. It is worth noting that the fluctuating wind pressure in the flow separation area at the front edge of the roof of the model with an opening ratio of 3.1% is significantly smaller than that of the closed model. Apart from this, the fluctuating wind pressure distribution on the roof and leeward face of the other open models does not change much.

[0184] Figure 16 (a)-(b) show the contour maps of the average wind pressure on the exterior of the low-rise building under a 45° wind angle for the closed and open models. It can be seen that at a 45° angle, the average wind pressure distribution on the roof of both the closed and open models does not change significantly, and the roof wind pressure exhibits a conical distribution, showing clear flow separation. However, in the corner region 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 on the surface where the opening is located is smaller than that of the closed model. This may be because the airflow near the opening reduces the incoming wind speed acting on the surface near the opening, resulting in a decrease in pressure.

[0185] Figure 17 (a)-(b) show the contour maps of the average wind pressure outside the low-rise building under a 45° wind angle, representing the closed-off model with an open section. Figure 16 It can be seen that the distribution of the roof pulsation area in the open model is basically consistent with that in the closed model at the corresponding 45° angle. However, the open model has a significant reduction in the high pulsation area on the two windward sides, and the surface pulsation wind pressure on the open side is smaller than that in the closed model.

[0186] III. Numerical Simulation of Wind Pressure on Low-Rise Buildings Under Sudden Openings

[0187] 3.1 Model Design and Numerical Scheme

[0188] In this embodiment, the model dimensions are set to match the TPU dimensions of the opening. The wall model near the opening is created using a sliding mesh method, and the wall thickness near the opening is 6mm. Figure 2 The operating conditions considered factors such as different opening ratios, different wind direction angles, and dynamic mesh opening velocities. The operating condition for the closed model example is denoted as K1, and the operating conditions for the open model example are denoted as G1-G10, totaling 11 operating conditions. Specific operating condition settings are detailed in Table 4. In addition, a total of 64 measuring points were arranged on the roof. This embodiment focuses on studying the roof wind pressure change law after transient opening, and the roof measuring points are divided into B1-B64, as shown in... Figure 4 .

[0189] Table 4 Operating Condition Settings

[0190]

[0191]

[0192] For mesh plotting and boundary condition settings of the computational domain in the numerical scheme, see [link to documentation]. Figure 7 The inlet conditions adopt the atmospheric inflow boundary conditions from Chapter 3. For the specific wind field profile, see [link to relevant documentation]. Figure 6 The layout diagrams of the internal pressure measuring points (N1-N5), external pressure measuring points (W1-W8), and roof pressure measuring points for the roof and open structures are shown below. Figure 10 and Figure 11 The numerical simulation time step was 0.00005 s. The opening movement time of the building was t0 = 2 s, and the remaining 7 s after opening was recorded, for a total simulation time of 9 s. Since the building model was scaled at 1:100, the wind speed at 1:1, and the time at 1:100, the sampling time of the numerical results corresponded to 700 s in the actual structure, meeting the requirement of 10 min for actual structure sampling as stipulated in the "Standard for Wind Tunnel Testing Methods for Building Engineering". For the different opening rates, namely G9 and G10, the calculations for both were based on the flow field information calculated up to 2 s from the G2 condition (opening rate 3.1%, wind direction angle 0°) as initial conditions, and then the calculations were performed. This ensures the consistency of the initial conditions for the different opening rates, thus guaranteeing that the opening rate is treated as a single variable.

[0193] 3.2 Verification of TPU simulation results under the sliding mesh method

[0194] For details on the mesh drawing method used in the sliding mesh method, please refer to [link / reference]. Figure 2 Therefore, to eliminate the influence of different mesh drawing methods at the opening, it is necessary to consider the difference between the external pressure on the surface of the sliding mesh and the external pressure of the closed reference model before the sliding mesh moves, and compare the calculated results with the TPU experimental results to verify the accuracy of the numerical simulation under the sliding mesh method.

[0195] This embodiment uses the "IRCDRFG" method to generate inlet turbulence. Figure 19 The external pressure distribution on the central axis of a building surface under turbulent wind conditions is shown in the unopened sliding mesh model and the closed model at a wind direction angle of 0°.

[0196] Combination Figure 19 (a)-(b) show that before the opening, the pressure coefficient distribution along the central axis of the building surface in the slip mesh model maintains good consistency with the pressure variation trend on the roof (section BC) and the leeward side (section CD) compared to the closed reference model. However, on the windward side (section AB), the numerical results of the slip mesh model show a small abrupt change in the average pressure coefficient and fluctuating pressure coefficient curves near the opening, unlike the smooth curves of the closed model. Furthermore, the wind pressure coefficients near the opening in both the closed model and the slip mesh model are similar to the TPU experimental results, with a fluctuation error of approximately 5%. This phenomenon may be due to localized depressions in the geometric model established using the slip mesh method at the opening. Based on the measurement data of TPU experiments on the building surface, it can be found that for the numerical results of the slip mesh model, the maximum error of the average pressure coefficient on the surface is within 10%, while in the leading edge area of ​​the roof (section BC), the error of the pulsating pressure coefficient in this local area is within 20%. This may be because the spatial filtering function in the large eddy simulation filters out the high-frequency components of the vortex, resulting in the pulsating results being smaller than the experimental values.

[0197] Numerical simulation results show that the pressure coefficient on the surface of the slip mesh model before the opening movement is consistent with that of the closed model. Comparing the numerical results of the slip mesh with TPU experiments, the numerical results of the slip mesh show excessive deviations in some local areas, but the error area is small and the overall error magnitude is low. Therefore, it can be concluded that the numerical results of the slip mesh method regarding the wind pressure on the outer surface of the model before the opening movement are accurate and reliable.

[0198] 3.3 Transient Study of Internal and External Pressures in Sudden Opening Structures

[0199] 3.3.1 Time history analysis of internal and external pressures in a suddenly open structure

[0200] In this embodiment, the pressure obtained from the monitoring of internal and external pressure points is processed to obtain the corresponding wind pressure coefficient, and the average wind speed at the reference height of the model roof is 13.5 m / s. Figure 20 (a)-(b) respectively show the time history curves of the internal and external pressure measuring points at the orifice under working conditions G1 and G8. Since the spatial distribution of internal pressure in a single opening is equal everywhere, the time history of the N2 pressure coefficient is used as the internal pressure time history curve, while the external pressure time history curve is the external pressure time history of the measuring point W1 around the orifice, which is highly correlated with the internal pressure.

[0201] pass Figure 20 (a)-(b) clearly show that under operating conditions G1 (ρ=0.3%, θ=0°) and G8 (ρ=3.1%, θ=180°), when the building suddenly opens after t0=2s, the external wind pressure coefficient around the opening exhibits a high degree of synchronicity with the internal wind pressure coefficient in the time history response, independent of the opening ratio, wind direction angle, and opening rate. It can also be observed that after the building opens at t0, there is a sharp increase in the pressure coefficient, followed by a decrease. The maximum value during the transient phase can be considered as the transient internal pressure peak. The transient internal pressure peak coefficient for operating condition G1 is 1.84, and for operating condition G8 it is -0.38. Furthermore, it can be observed that the sign of the internal pressure coefficient after the building opens depends primarily on whether the surface before the opening experiences pressure or suction.

[0202] Figure 21 and Figure 22 The diagram illustrates the pressure coefficient time history curves at internal pressure measuring point N2 and external pressure coefficient time history at measuring point B25 on the windward edge of the roof under different opening rates (G2, G9, G10). Both G9 and G10 conditions are calculated based on the initial values ​​of condition G2 at time 2 seconds; pressure changes before time 2 seconds are considered consistent. Figure 21 It can be observed that because a certain distance is required for the initial sliding mesh movement to the opening of the building opening, the time when internal pressure appears is later in case G10, which has the slowest opening time, compared to the other two cases. Furthermore, case G10, with its slow opening rate, has the smallest instantaneous peak pressure of only 1.59, while G9 has an instantaneous internal pressure peak of 1.94, and G2 has 1.92. The opening rate does not seem to affect the time of instantaneous peak pressure appearance, possibly because the internal pressure response is determined by the excitation load of external wind pressure.

[0203] Figure 22 The time history curves of the external pressure coefficient at measuring point B25 on the windward edge of the roof in the sudden opening model are shown under different opening rates (G2, G9, G10). It can be observed that the transient response change of the external pressure at the measuring point on the roof corresponding to the different opening rates is consistent within approximately 0.1 seconds after the opening. Therefore, it can be inferred that the transient change of the external pressure on the building surface far from the opening is independent of the opening's movement rate.

[0204] Figure 23 Under different opening rates (G2, G9, G10), the wind speed time history curves in the X direction monitored at the center of the orifice inside the model show that the airflow at the orifice in the slow opening rate condition moves back and forth at the orifice due to the change in the internal and external pressure difference, reflecting the complexity of the wind speed flow at the orifice.

[0205] 3.3.2 Overshoot Ratio

[0206] In studies of the internal pressure response of transient openings in enclosed buildings, researchers discovered a peak value in the instantaneous internal pressure response when a building suddenly opens; this phenomenon is known as the overshoot effect. The overshoot ratio (R) reflects the intensity of the transient internal pressure response.

[0207]

[0208] In the formula, C pi,i This represents the peak transient internal pressure coefficient, typically taken as the maximum (absolute value) of the fluctuation time history curve of the internal pressure coefficient from the opening moment to the steady-state state. Figure 20 Observations show that the transient peak internal pressure coefficient can be taken as the maximum value of the internal pressure coefficient within the time history segment of 0.1s to 0.4s at the moment of building opening. C pi,s Represents the peak steady-state internal pressure coefficient. C' represents the average internal pressure coefficient during the steady-state phase. pi denoted by , g represents the pulsating internal pressure coefficient during the steady-state phase, and g is the transient internal pressure peak factor.

[0209] Transient internal pressure peak coefficient, through Figure 20 The internal pressure fluctuation time history can be taken as the maximum internal pressure coefficient value (absolute value) within 0.2s-0.4s after the opening moment. Figure 24 The steady-state internal pressure probability density of the building is shown under the corresponding G1 and G8 working conditions. It can be found that the probability density of internal pressure changes in the steady-state stage basically follows a Gaussian distribution. For the peak factor value of the Gaussian distribution of building internal pressure, this embodiment gives a value of g=3.

[0210] Table 5 shows the steady-state and transient peak internal pressure coefficients and overshoot ratios after opening for various operating conditions under different opening ratios, wind direction angles, and flow rates. It can be observed that under operating conditions G1–G4, the overshoot ratio ranges from 0.88 to 1 for different opening ratios; under operating conditions G5–G8, the overshoot ratio ranges from 0.56 to 0.92 for the same opening ratio but different wind direction angles, showing a phenomenon of first decreasing and then increasing; for operating conditions G2, G9, and G10, the numerical simulation results for different opening rates at the same initial time of 2 seconds are shown, with corresponding overshoot ratios of 1.04, 0.99, and 0.84, respectively. Comparing this overshoot phenomenon, it can be found that the faster the opening rate, the stronger the overshoot effect. The overshoot effect may be partly due to the randomness of the external wind pressure at the time of opening and the magnitude of the oncoming wind speed. Although the overshoot ratio is slightly smaller, compared to other wind direction angle conditions, the overshoot effect is stronger when the opening is at a 0° wind direction angle and the opening ratio is small. Furthermore, the faster the opening rate, the slightly higher the corresponding overshoot ratio. Therefore, for structural openings caused by wind-induced projectiles under strong winds, the opening rupture speed is exceptionally fast, and the instantaneous peak internal pressure generated in this situation requires attention.

[0211] Table 5 Overshoot ratio under different operating conditions

[0212]

[0213] 3.3.3 Time History Analysis of Instantaneous Net Wind Pressure at Different Locations

[0214] In addition, this embodiment also sets an external pressure measuring point in the central area of ​​the three sides of the low-rise building other than the opening side and the roof side. That is, the external center measuring points of the two side walls are denoted as C1 and D1, respectively, and the center measuring point of the leeward wall is denoted as E1. Each external center measuring point corresponds to an internal center measuring point of the building, namely (N3, N4, N5). See details. Figure 12 .

[0215] The dimensionless wind pressure coefficient for the structural surface is referenced to the average wind speed at height. For open structures, the wind pressure on the building surface will be affected by the combined effects of indoor and outdoor wind pressures. The net wind load for the roof of an open structure can be calculated using the following formula:

[0216] Cpnet=C pext -C pint

[0217] In the formula: C pnet C represents the net wind pressure coefficient of the model's outer surface. pext C is the external wind pressure coefficient of the building. pint This refers to the wind pressure coefficient inside the building.

[0218] In this embodiment, the external pressure coefficients of each outer surface of the model are processed to obtain the net wind pressure coefficient time history at each measuring point on the outer surface of the model. Compared with other wind direction angles at 0°, the overshoot effect after the transient opening of the closed building is the most obvious, and the average internal pressure is the largest. At this time, the combined effect with the external pressure is the most unfavorable. However, the average internal pressure of the model does not differ much between different opening ratios. Therefore, one of the 0° conditions is selected. Figure 25 The time history of the net wind pressure coefficient at a typical location under operating condition G1 is shown. Based on the time history fluctuations, significant changes in the wind pressure coefficient before and after the opening can be observed. The net wind pressure coefficient can be divided into three stages based on the fluctuation trend: the steady-state stage before the opening, the transient stage during the sudden opening, and the steady-state stage after the opening. See details below. Figure 25 .

[0219] Figure 25(a)-(c) show the time history curves of the net wind pressure coefficient at 2 seconds after the opening at typical locations on the windward side, side, and roof of building condition G1. It can be observed that the net wind pressure on the windward side decreases from positive pressure to near 0 after the opening, indicating that the opening is beneficial to the windward side. For the side and roof, the net wind pressure increases with suction after the opening, then decreases, but the negative pressure increases compared to before the opening. Therefore, it can be seen that the net wind pressure on the surface of the wall where the opening is located is beneficial after a transient opening. However, other surrounding surfaces of the building after the opening, such as doors and windows on the sides and roof, are more easily damaged instantaneously, and the extreme values ​​of the pulse wind load generated on the surface during the transient opening phase require attention.

[0220] 3.4 Steady-state study of internal and external pressures of the model before and after opening

[0221] 3.4.1 Steady-state study of internal and external pressures of the model before and after opening

[0222] Table 6 presents the internal and external wind pressure coefficients around the opening and the estimation error of the average wind pressure coefficient under various operating conditions during the steady-state stage after the building opening. The average external pressure coefficient around the opening is used as the estimated value, and the average internal pressure coefficient inside the opening is used as the measured value. C′ is the average external pressure coefficient. Pe This represents the coefficient of pulsating external pressure. C′ represents the average internal pressure coefficient. Pi This represents the pulsating external pressure coefficient.

[0223] Table 6 shows that under the 0° wind angle (G1-G4, G9, G10) conditions, the maximum estimation error is approximately 14%, occurring in condition G4 with an opening ratio of 12.5%. The errors for the other conditions are all less than 10%, and the smaller the opening ratio, the smaller the estimation error for the average internal and external pressures. Furthermore, it can be determined that as the opening ratio increases, the average external pressure around the orifice gradually decreases, while the internal pressure gradually increases and eventually remains constant. For the same opening ratio but different wind angles (G5-G8), the maximum error is approximately 16%, occurring in condition G5 with a 45° wind angle. The error estimates for the other conditions are less than 10%. This may be because at the opening under a 45° wind angle, there is a complex flow separation phenomenon on the side of the building, making the flow at the orifice more complex. For the same opening ratio but different opening velocities (G2, G9, G10) at a 0° angle, it can be found that the difference between the average internal and external pressures in the steady-state stage does not exceed 5%, indicating that the opening rate has little impact on the internal and external pressures of the model in the steady-state stage. Furthermore, the theoretical value of the average internal pressure estimated using the steady-state method agrees well with the monitored value. Table 6 also shows that the steady-state method can estimate the average internal pressure well, further demonstrating the reliability of the numerical results of the internal and external pressures of the structure in the steady-state stage. In addition, under various working conditions, the pulsating wind pressure coefficients outside and inside the building opening are quite similar, which again illustrates the high synchronicity between the external and internal pressures around the opening in terms of time history response. Figure 19 .

[0224] Table 6. Theoretical and simulated values ​​of internal pressure during steady-state phase.

[0225]

[0226] 3.4.2 Correlation Analysis of Internal and External Pressures Before and After Opening

[0227] Figure 26 and Figure 27 These figures represent the correlation trajectories between the internal structural pressure and the external pressure near the opening at the moment of transient opening under different operating conditions. The horizontal axis represents the time history of the internal pressure coefficient at measuring point N1 (the inner wall on the windward side) at the opening, and the vertical axis represents the time history of the external pressure coefficient at measuring point W1, which has the highest correlation with the internal pressure. Figure 26 It can be seen that at 0° angle, the internal and external pressures near the orifice with different aperture ratios show a positive correlation, and the correlation coefficient r decreases as the aperture ratio increases, reaching a maximum of r = 0.956. From Figure 27It can be seen that for the same opening ratio, the correlation coefficient r between the internal and external pressures at the opening first decreases and then increases with the increase of the wind direction angle. The smallest r (0.75) is observed at a wind direction angle of 90°. Furthermore, it can be found that at a wind direction angle of 0°, the positive correlation between the internal and external pressures at the opening is significantly higher than at other wind direction angles. For the windward single-opening model, the correlation between the internal and external pressures at the orifice is high, which precisely reflects... Figure 20 After the opening was shown, the pressure inside the model and the pressure outside the opening exhibited a high degree of consistency.

[0228] Figure 28 This paper presents the correlation trajectory diagrams of measuring points N2 inside the roof surface at different locations on the roof of the open model under load condition G2 (windward corner B1, windward leading edge B25, roof center B28, and roof rear edge B32) with an opening ratio of 3.1% at a wind direction angle of 0°. The horizontal axis represents the time history of the internal pressure coefficient, and the vertical axis represents the time history of the external pressure coefficient of the roof. Figure 28 It can be observed that the external pressure and the internal pressure of the model are not significantly correlated in various regions of the outer surface of the open roof structure, and there is no obvious positive or negative correlation trend, indicating that the fluctuation of the internal pressure of the open structure is unrelated to the change of the external pressure of the roof. Among them, the external pressure of the windward edge and corner areas of the roof shows a weak negative correlation with the internal pressure of the model, with correlation coefficients r of -0.34 and -0.395, respectively. This suggests that the external pressure at the opening of the wind-induced transient open structure is highly correlated with the internal pressure of the model, while the external pressure on the building surface, except for the external pressure around the opening, shows no significant correlation with the internal pressure of the other walls, and a weak negative correlation in some local areas.

[0229] 3.4.3 Changes in net wind pressure distribution on the roof structure before and after opening

[0230] In building structure design, the wind pressure load on the surface of the building envelope, such as the roof, is usually the primary concern. Regarding the net wind load on the roof, the mean internal pressure of the open model at a wind angle of 0° is the highest compared to other angles, while the external negative pressure caused by roof flow separation at a wind angle of 45° is also unfavorable. Therefore, this embodiment mainly explores the impact of openings on the distribution of the net wind pressure coefficient of the roof at wind angles of 0° and 45°.

[0231] In this embodiment, the measuring point on the windward edge of the roof is taken as the X-axis, and the central area of ​​the roof is taken as the Y-axis. Due to symmetry, the measuring point is the average of the measuring points on both sides. Figure 18 We analyzed the changes in net wind pressure on the roof before and after the sudden opening along both the X and Y axes.

[0232] Figure 19 , Figure 20 , Figure 21The data represent the changes in net wind pressure distribution on the roof before and after opening in operating conditions G1 (opening ratio 0.3%, wind direction angle 0°), G2 (opening ratio 3.1%, wind direction angle 0°), and G5 (opening ratio 3.1%, wind direction angle 45°).

[0233] pass Figure 29 and Figure 30 It can be observed that for both G1 and G2 conditions, the windward wind pressure distribution at the eaves is almost identical before and after the opening, showing a trend of lower negative pressure in the middle and higher negative pressure at both ends along the Y-axis. The most unfavorable net wind pressure coefficient after the opening is approximately -1.9, located in the corner area of ​​the eaves; this is about 1.5 times the net wind pressure coefficient before the opening. Looking along the X-axis, the net wind pressure coefficient of the roof in both G1 and G3 conditions gradually decreases along the axis. It can be seen that the distribution trend of the net wind pressure coefficient of the roof before and after the opening is consistent across different opening ratios.

[0234] Depend on Figure 30 It can be seen that the net wind pressure coefficient of the roof at a 45° wind angle exhibits a "V"-shaped distribution along the Y-axis, first decreasing and then increasing, reflecting the flow separation phenomenon on the roof before and after the opening. The negative pressure is greatest at the measuring point 100mm along the Y-axis, with a net wind pressure coefficient of -2.5, approximately 1.3 times that before the opening. Subsequently, at the measuring point 120mm from the end of the Y-axis, the difference in net wind pressure coefficient before and after the opening is minimal. Looking at the X-axis, the net wind pressure coefficient is smallest near the windward edge before and after the opening, exhibiting a downward "C"-shaped distribution that first rises sharply and then slowly decreases. This is likely due to severe flow separation and drastic negative pressure fluctuations in the lower edge region at a 45° angle. However, it is noteworthy that the net wind pressure coefficient at 20mm along the X-axis remains consistent before the opening.

[0235] Note: In this article, "open model" refers to the model of a building when the opening is open, and "closed model" refers to the model of a building when the opening is closed.

[0236] The above-described embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention. The scope of protection of the present invention is defined by the claims.

Claims

1. A numerical simulation method for changes in internal and external pressure under sudden openings in a building, characterized in that: Includes the following steps: Step 1: Construct a building model with a sudden opening. Create a building model and set a sliding mesh area on at least one side of the reserved opening on the windward side of the building model, while the other areas of the building model are static mesh areas; define the interface where the static mesh area and the sliding mesh area meet as the AMI interface; Step 2: Design the computational domain The size of the building is 30. H ×10 H ×6 H The computational domain is defined, and the building model is placed within it, with the origin of the computational domain located at the center of the bottom of the building model. The distances from the center of the bottom of the building model to the entrance and exit of the computational domain are 10. H and 20 H , H The height of the building model; Step 3: Grid Generation The building model and the computational domain are meshed separately. To ensure that the boundary flow near the wall of the building model is solved accurately, a boundary layer region is set at the wall of the building model. Step 4: Set boundary conditions Inlet boundary conditions: Atmospheric inflow boundary conditions are used at the inlet, and the uniform discrete inflow turbulence generation method is employed; Export boundary conditions: The export boundary conditions are set to pressure outlet; The top and two sides of the computational domain are set as sliding boundary conditions, while the bottom of the computational domain and the building wall boundary conditions are set as non-slip boundary conditions. Step 5: Numerical Simulation Given a piecewise function of velocity and time in a slip mesh region, the simulation is solved based on a large eddy turbulence model; under initial conditions, the slip mesh region is positioned at the initial location and the building model is closed. Once the wind speed and pressure across the entire watershed have stabilized, the sliding grid region is moved along the AMI interface to transmit external flow field information to the internal flow field of the building through the AMI interface, thereby achieving a dynamic simulation effect of a sudden opening. Step Six: Numerical Analysis Numerical analysis was performed on the pressure and wind speed data inside and outside the building collected under a sudden opening in the building model. In step one, the method for constructing the building model consists of the following steps: 11) Construct a building model, and reserve a sliding mesh area on at least one side of the reserved opening location in the building model; 12) Divide the grid regions: Divide the exterior of the building model into grid region 0, the interior of the building into grid region 1, and the sliding grid region into grid region 2; 13) Define AMI interfaces: Define two interfaces that connect the sliding mesh region and the stationary mesh region as interface 1 and interface 3, and two stationary region interfaces located at the reserved opening as interface 2 and interface 4; define interface 1, interface 2, interface 3 and interface 4 as AMI interfaces; In step five, the piecewise function relating velocity and time is: in: Indicates the movement speed of the sliding grid region; Indicates the time required for the simulation calculation; Indicates the moment when someone suddenly speaks; Indicates the motion time of the sliding mesh; This represents the distance the sliding mesh moves to achieve a full opening.

2. The numerical simulation method for internal and external pressure changes under sudden openings in a building according to claim 1, characterized in that: In step four, the mathematical expression for the fluctuating wind speed synthesized using the consistent discrete incoming flow turbulence generation method is as follows: in: They represent x , y , z Pulsating wind speeds in three directions; They represent x , y , z Three directions; M Indicates the number of intervals in the spectrum; N This indicates the number of frequencies within each interval. and All are coefficients; It represents a random vector distributed on a unit sphere in space, ensuring that the velocity field satisfies the divergence-free condition; Represents a dimensionless coordinate vector, and , The correlation coefficient between two points in space; Let be the frequency, and follow the mean. Standard deviation For a uniform distribution of ; t is time; and: in: It is a symbolic function; This represents a random number that follows a normal distribution of 0-1 in all three directions. For the spectrum corresponding i Power spectral density value in the direction.

3. The numerical simulation method for internal and external pressure changes under sudden openings in a building according to claim 2, characterized in that: In the uniform discrete incoming flow turbulence generation method, an iterative reshaping method is introduced to continuously correct the shape of the wind speed profile at the inlet. This ensures that the turbulent wind field can fit the target wind profile within the target region without affecting spatial correlation, while maintaining the conservation of flow rate through the inlet interface. The principle of the iterative reshaping method is as follows: In the formula: and These are the target mean velocity profile and the target turbulence intensity profile; and It is the first n During the secondary correction period, the average wind speed profile and turbulence intensity profile were obtained by monitoring at the center of the building area after a simulated time history. and It is in the n The average wind speed profile and turbulence intensity profile of the turbulent field generated at the inlet interface during the second correction; This is a correction factor used to ensure that the average wind speed profile at the inlet interface is in the ( ) n After the +1) correction, the traffic through the entry interface remains constant. yes z The grid scale corresponding to the direction.

4. The numerical simulation method for internal and external pressure changes under sudden openings in a building according to claim 1, characterized in that: In step five, the method for simulating and solving the large eddy turbulence model is as follows: All vortex scales in the flow field Perform filtering: in: This refers to large-scale vortices obtained through filtering. Subgrid scale; Let be a spatial filtering function; and: in: These are the spatial coordinates before filtering; Filtered spatial coordinates; The filtering scale; The filtered incompressible fluid control equations are as follows: in: ( i , j =1,2,3) are the three filtered velocity components in the Cartesian coordinate system; It is the pressure after filtering; ρ It is air density; ν It is kinematic viscosity; Represents subgrid-scale stress; Small-scale vortices are modeled using a subgrid-based eddy viscosity model, where the expression for the standard SGS model is: in: It is the SGS eddy viscosity coefficient. It is the Kronecker function. It is the filter thickness strain rate tensor; Eddy viscosity coefficient Calculated using the Smagorinsky-Lilly model: in: k It is von Karman's constant; This is Smagorinsky's constant; This is the filtering scale.

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