A wind-resistant design method and system for large-span warehouse structures based on numerical simulation of wind loads

Abstract

The present invention discloses a method and system for wind-resistant design of large-span warehouse structures based on numerical simulation of wind loads. An initial computational fluid dynamics model is established according to the initial structural data of the large-span warehouse structure; the corresponding fluid control equations and turbulence models are constructed based on the initial computational fluid dynamics model; the wind load numerical simulation is performed according to the preset working conditions, the initial computational fluid dynamics model, the fluid control equations, and the turbulence model to obtain wind load data; the wind load data and the initial structural data are input into a wind load-stress mapping model to obtain the predicted component stress value of the large-span warehouse structure; the predicted component stress value is compared with the maximum component stress value to determine the wind-resistant design result of the initial structural data of the large-span warehouse structure. The scheme of the present invention simulates the wind load of the large-span warehouse structure through actual dynamic working conditions, and evaluates the wind-resistant design result of the large-span warehouse structure according to the simulated wind load, so that the evaluation result is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of large-span warehouse structures, and in particular to a wind-resistant design method and system for large-span warehouse structures based on numerical simulation of wind loads. Background Art

[0002] Large-span structural buildings refer to various types of structures that span a space of more than 60 meters horizontally. They are mostly used in theaters, gymnasiums, exhibition halls, conference halls, airport terminals and other large public buildings in civil buildings, as well as large-span factories, aircraft assembly workshops and large warehouses in industrial buildings. For example, the fully enclosed capsule bulk shed at Yueyang Chenglingji Port is a large-span warehouse structure.

[0003] Due to the needs of functional use and aesthetics, large-span warehouse structures are gradually developing in the direction of lightweight, large size and complex shape, which makes them more sensitive to wind loads. Moreover, this type of structure has low stiffness and low damping, and the wind-induced vibration effect is more significant. Therefore, when designing the wind resistance of large-span warehouse structures, it is necessary to ensure that the structure has sufficient strength to reliably withstand the stress under wind loads. Choosing reasonable structural size and shape is the key to the wind resistance design of large-span warehouse structures.

[0004] When existing designers or engineers verify whether the selected structural dimensions and shapes are reasonable, they often first select the wind direction angle that has the greatest impact on the model structure based on experience, and then set a constant wind speed under the selected wind direction angle to calculate the wind load on the large-span warehouse structure. If the wind load is less than the allowable stress value calculated based on the cross-sectional characteristics and materials at the corresponding position of the structure, it is preliminarily determined that the selected structural dimensions and shapes are reasonable. However, the wind load calculated based on the above method often has a large error with the actual one, and the wind-resistant structure design selected based on the wind load has a low reliability. To solve this problem, in reality, conservative values ​​are often selected and the design reserve margin is increased to improve reliability. However, this method is prone to waste of resources, and an accurate wind-resistant design method for large-span warehouse structures has not yet been given. Summary of the invention

[0005] In order to solve the technical problem that the prior art lacks an accurate wind-resistant design method for large-span warehouse structures, an embodiment of the present invention provides a wind-resistant design method and system for large-span warehouse structures based on numerical simulation of wind loads.

[0006] The technical solution of the embodiment of the present invention is achieved as follows:

[0007] The embodiment of the present invention provides a method for wind-resistant design of a large-span warehouse structure based on numerical simulation of wind loads, the method comprising: obtaining initial structural data of the large-span warehouse structure; the initial structural data comprising warehouse structure type, warehouse main body dimension parameters, warehouse ventilation pipe dimension parameters, warehouse main body material data and warehouse ventilation pipe material data; establishing an initial computational fluid dynamics model of the large-span warehouse structure according to the initial structural data; and constructing corresponding fluid control equations and turbulence models based on the initial computational fluid dynamics model; obtaining preset working conditions; the preset working conditions comprising wind direction angle time series data and wind speed time series data ; Perform numerical simulation of the wind load of the large-span warehouse structure according to the preset working condition, the initial computational fluid dynamics model, the fluid control equation, and the turbulence model to obtain the wind load data of the large-span warehouse structure; obtain the wind load-stress mapping model of the large-span warehouse structure, input the wind load data and the initial structural data into the wind load-stress mapping model to obtain the predicted component stress value of the large-span warehouse structure; compare the predicted component stress value with the maximum component stress value of the large-span warehouse structure to determine the wind-resistant design result of the initial structural data of the large-span warehouse structure.

[0008] In one embodiment, an initial computational fluid dynamics model of the large-span warehouse structure is established according to the initial structural data, including: establishing a full-scale warehouse model of the large-span warehouse structure using SCDM geometric modeling software according to the initial structural data; determining the computational domain and boundary conditions of the full-scale warehouse model; using a preset grid division tool to divide the full-scale warehouse model into a first-size grid, and divide the area within a preset range near the full-scale warehouse model into a second-size grid, and divide the other areas in the computational domain except the full-scale warehouse model and the area within the preset range nearby into a third-size grid; and determining the divided geometric model as the initial computational fluid dynamics model of the large-span warehouse structure.

[0009] In one embodiment, determining the computational domain and boundary conditions of the full-scale model of the warehouse includes: determining the size of the computational domain of the full-scale model of the warehouse according to the size of the full-scale model of the warehouse, and determining the layout position of the full-scale model of the warehouse in the computational domain; the geometric model blockage ratio calculated by the computational domain size and the size of the full-scale model of the warehouse needs to be less than a preset value; determining the boundary conditions of the computational domain according to the layout position of the full-scale model of the warehouse in the computational domain; the boundary conditions include the incoming flow direction, the incoming flow inlet boundary, the fluid outlet boundary, the no-slip wall and the symmetric interface.

[0010] In one embodiment, based on the initial computational fluid dynamics model, corresponding fluid control equations and turbulence models are constructed, including: the fluid control equations include a mass control equation, a momentum control equation, and an energy control equation:

[0011] The quality control equation is:

[0012]

[0013] in, ρ is the fluid density, t It's time. u , v , w are the components of the total fluid velocity in the x, y, and z directions;

[0014] The momentum control equation is:

[0015]

[0016]

[0017]

[0018] in, P is the pressure on the initial computational fluid dynamics model microelement; τ x , τ y , τ z is the viscous stress acting on the surface of the microelement of the initial computational fluid dynamics model τ The weight, subscript x , y , z Represents viscous stress τ The amount of x , y , z Components in three directions; Fx , F , F is the body force acting on the microelement of the initial computational fluid dynamics model;

[0019] The energy control equation is:

[0020]

[0021] in, e represents the internal energy per unit mass; k' represents the heat transfer coefficient of the fluid; T is the temperature of the fluid; S T represents the viscous dissipation term; Indicates the velocity of the fluid;

[0022] The turbulence model is:

[0023]

[0024]

[0025] Among them, Γ k , G k , Y k , S k Turbulent kinetic energy k Diffusion term, generation term, dissipation term, and custom source term of Γ ω , G ω , Y ω , S ω Dissipation rate ω Diffusion term, generation term, dissipation term, custom source term, is the i-direction coordinate, is the j-direction coordinate, is the component of the fluid velocity in the i direction.

[0026] In one embodiment, a numerical simulation of the wind load of the large-span warehouse structure is performed according to the preset working condition, the initial computational fluid dynamics model, the fluid control equation, and the turbulence model to obtain the wind load data of the large-span warehouse structure, including: constructing a simulated dynamic wind field according to the wind direction angle time series data and the wind speed time series data in the preset working condition; applying the simulated dynamic wind field in the initial computational fluid dynamics model to obtain the real-time wind speed sequence of each microelement in the initial computational fluid dynamics model; solving the fluid control equation and the turbulence model by using the SIMPLE algorithm, and determining the wind pressure coefficient of each microelement in the initial computational fluid dynamics model according to the solution results; calculating the wind load of each microelement in the initial computational fluid dynamics model according to the real-time wind speed sequence of each microelement in the initial computational fluid dynamics model and the wind pressure coefficient of each microelement in the initial computational fluid dynamics model by using the following calculation formula to obtain the wind load sequence of each microelement in the initial computational fluid dynamics model;

[0027]

[0028] in, is the wind load of each microelement, is the air density, is the value in the real-time wind speed series, is the wind pressure coefficient of each microelement, is the control range area of ​​each microelement;

[0029] The wind load data of the long-span warehouse structure are obtained according to the wind load sequences of all micro-elements in the initial computational fluid dynamics model.

[0030] In one embodiment, obtaining the wind load-stress mapping model of the large-span warehouse structure includes: when the warehouse structure type of the large-span warehouse structure is a three-center circle type, the wind load-stress mapping model is:

[0031]

[0032] in, is the stress value of the i-th microelement of the warehouse body; is the coordinate of the i-th microelement of the warehouse body in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse body, is the slope of the tangent line of the surface of the i-th microelement of the warehouse body; is the main length of the warehouse; is the width of the warehouse body; The main height of the warehouse; is the stress value of the i-th microelement of the warehouse ventilation pipe; is the coordinate of the i-th microelement of the warehouse ventilation duct in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse ventilation duct, is the slope of the tangent line of the surface of the i-th microelement of the warehouse ventilation pipe; is the length of the warehouse ventilation pipe; is the width of the warehouse ventilation pipe; is the height of the warehouse ventilation pipe;

[0033] When the warehouse structure type of the large-span warehouse structure is a bullet-shaped structure, the wind load-stress mapping model is:

[0034]

[0035] in, is the stress value of the i-th microelement of the warehouse body; is the coordinate of the i-th microelement of the warehouse body in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse body, is the slope of the tangent line of the surface of the i-th microelement of the warehouse body; is the length of the warehouse body; is the width of the warehouse body; The main height of the warehouse; is the stress value of the i-th microelement of the warehouse ventilation pipe; is the coordinate of the i-th microelement of the warehouse ventilation duct in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse ventilation duct, is the slope of the tangent line of the surface of the i-th microelement of the warehouse ventilation pipe; is the length of the warehouse ventilation pipe; is the width of the warehouse ventilation pipe; Height of warehouse ventilation pipe.

[0036] In one embodiment, the predicted component stress value is compared with the maximum component stress value of the large-span warehouse structure to determine the wind-resistant design result of the initial structural data of the large-span warehouse structure, including: comparing the predicted component stress value of each microelement of the large-span warehouse structure with the maximum component stress value corresponding to the microelement; if there is any microelement of the large-span warehouse structure whose predicted component stress value is greater than the maximum component stress value corresponding to the microelement, then the wind-resistant design result of the initial structural data of the large-span warehouse structure is unqualified; if the predicted component stress values ​​of all microelement of the large-span warehouse structure are less than the maximum component stress value corresponding to the microelement, then the wind-resistant design result of the initial structural data of the large-span warehouse structure is qualified.

[0037] In one embodiment, when the wind-resistant design result is unqualified, the method further includes: randomly adjusting the initial structural data, inputting the adjusted initial structural data into a trained stress prediction network model, and obtaining a predicted component stress value output by the stress prediction network model; the input of the stress prediction network model is structural data, and the output of the stress prediction network model is a predicted component stress value; comparing the predicted component stress value output by the stress prediction network model with the maximum component stress value of the large-span warehouse structure, if the predicted component stress value output by the stress prediction network model is greater than the maximum component stress value of the large-span warehouse structure, continuing to adjust the initial structural data until the predicted component stress value output by the stress prediction network model is less than the maximum component stress value of the large-span warehouse structure; obtaining the initial structural data adjusted for the last time; and using the initial structural data adjusted for the last time as the recommended modification value of the initial structural data.

[0038] In one embodiment, the training process of the stress prediction network model includes: obtaining multiple sets of structural data of large-span warehouse structures and predicted component stress values ​​of the structural data under preset working conditions; using the structural data and the corresponding predicted component stress values ​​as training sets, training a preset initial network model, and obtaining a trained stress prediction network model.

[0039] An embodiment of the present invention also provides a wind-resistant design system for large-span warehouse structures based on numerical simulation of wind loads, comprising: a processor and a memory for storing a computer program that can be run on the processor; wherein the processor executes the steps of the above-described method when running the computer program.

[0040] This embodiment has the following beneficial effects:

[0041] This embodiment uses dynamic wind direction angle time series data and wind speed time series data to simulate the calculation of wind load, and designs the large-span warehouse structure on this basis, and the design result is highly reliable. The method of this embodiment can accurately and efficiently calculate the structural wind load, which has a direct impact on the safety, applicability and economy of the structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a method for wind-resistant design of a large-span warehouse structure based on numerical simulation of wind loads according to an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of the three-center circular warehouse structure according to an embodiment of the present invention; wherein: Figure 2 (a) is the front view of the three-center circular warehouse structure; Figure 2 (b) is the side view of the three-center circular warehouse structure;

[0044] Figure 3 This is a schematic diagram of the structure of a bullet-shaped warehouse according to an embodiment of the present invention; wherein: Figure 3 (a) is the front view of the bullet-shaped warehouse structure; Figure 3 (b) is a side view of the bullet-shaped warehouse structure;

[0045] Figure 4 A schematic diagram of the calculation domain and boundary conditions determined for an embodiment of the present invention;

[0046] Figure 5 This is a schematic diagram of the surface mesh of the warehouse and the computational domain in an embodiment of the present invention;

[0047] Figure 6 A schematic diagram of a boundary layer grid for grid division according to an embodiment of the present invention;

[0048] Figure 7 A schematic diagram of wind direction angle definition for a warehouse virtual wind tunnel test according to an embodiment of the present invention;

[0049] Figure 8 Schematic diagram of numerical simulation results of wind loads on a three-center circular large-span warehouse structure at time i according to an embodiment of the present invention;

[0050] Fig. 9 Schematic diagram of numerical simulation results of wind loads on a three-center circular large-span warehouse structure at time j according to an embodiment of the present invention;

[0051] Fig.10 Schematic diagram of numerical simulation results of wind load on a bullet-shaped large-span warehouse structure at time i according to an embodiment of the present invention;

[0052] Fig.11 Schematic diagram of numerical simulation results of wind load on a bullet-shaped large-span warehouse structure at time j according to an embodiment of the present invention;

[0053] Fig.12 Schematic diagram of numerical simulation results of wind load on ventilation duct of three-center circular large-span warehouse structure at time i according to an embodiment of the present invention;

[0054] Fig.13 Schematic diagram of numerical simulation results of wind load on ventilation duct of three-center circular large-span warehouse structure at time j according to an embodiment of the present invention;

[0055] Fig.14 1 is a diagram showing the internal structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0057] The embodiment of the present invention provides a wind-resistant design method for a large-span warehouse structure based on numerical simulation of wind loads. Figure 1 As shown, the method includes:

[0058] Step S101: Acquire initial structural data of a large-span warehouse structure; the initial structural data includes warehouse structure type, warehouse body size parameters, warehouse ventilation pipe size parameters, warehouse body material data, and warehouse ventilation pipe material data;

[0059] Step S102: establishing an initial computational fluid dynamics model of the large-span warehouse structure according to the initial structural data; and constructing corresponding fluid control equations and turbulence models based on the initial computational fluid dynamics model;

[0060] Step S103: obtaining a preset working condition; the preset working condition includes wind direction angle time series data and wind speed time series data; performing a numerical simulation of the wind load of the large-span warehouse structure according to the preset working condition, the initial computational fluid dynamics model, the fluid control equation, and the turbulence model, and obtaining the wind load data of the large-span warehouse structure;

[0061] Step S104: obtaining a wind load-stress mapping model of the large-span warehouse structure, inputting the wind load data and the initial structural data into the wind load-stress mapping model, and obtaining a predicted component stress value of the large-span warehouse structure;

[0062] Step S105: Compare the predicted component stress value with the maximum component stress value of the large-span warehouse structure to determine the wind-resistant design result of the initial structural data of the large-span warehouse structure.

[0063] Almost all current mainstream research assumes that the wind direction angle and wind speed remain unchanged when calculating wind loads and designing large-span warehouse structures. However, in reality, the wind direction angle and wind speed in the environment where the large-span warehouse structure is located are dynamically changing, which is a non-stationary random process. Therefore, the existing research methods do not take into account the actual non-stationary conditions, the calculated wind load errors are large, and the reliability of the large-span warehouse structure design is low. The inaccuracy of the analysis caused by non-stationarity is ignored, which reduces the reliability of the structural wind-resistant design. To this end, this embodiment provides a wind-resistant design method for a large-span warehouse structure, which simulates the calculation of wind loads by using dynamic wind direction angle time series data and wind speed time series data, and designs large-span warehouse structures on this basis, and the design results are highly reliable. The method of this embodiment can accurately and efficiently calculate the structural wind load, which has a direct impact on the safety, applicability and economy of the structure.

[0064] Specifically, the initial structure data in this embodiment includes warehouse structure type, warehouse body size parameters, warehouse ventilation pipe size parameters, warehouse body material data and warehouse ventilation pipe material data. Here, the warehouse structure type can be a common warehouse structure type, such as a three-center circle type and a bullet type. Figure 2 and Figure 3 , Figure 2 This is a schematic diagram of the three-center circular warehouse structure; Figure 3 This is a schematic diagram of the bullet-shaped warehouse structure. The warehouse body size parameters include the length, width and height of the warehouse body; the warehouse ventilation pipe size parameters include the length, width and height of the warehouse ventilation pipe.

[0065] Wind load refers to the dynamic pressure exerted on a building by air flow. In this embodiment, an initial computational fluid dynamics model of a large-span warehouse structure may be established based on initial structural data, so as to calculate the wind load using the initial computational fluid dynamics model. Here, the steps of establishing the initial computational fluid dynamics model may include:

[0066] A full-scale model of the warehouse of the large-span warehouse structure is established according to the initial structural data using SCDM geometric modeling software; the computational domain and boundary conditions of the full-scale model of the warehouse are determined; the full-scale model of the warehouse is divided into a first-size grid using a preset grid division tool, the area within a preset range near the full-scale model of the warehouse is divided into a second-size grid, and the other areas in the computational domain except the full-scale model of the warehouse and the area within the preset range nearby are divided into a third-size grid; the divided geometric model is determined as the initial computational fluid dynamics model of the large-span warehouse structure.

[0067] In this embodiment, SCDM geometric modeling software can be used to establish a full-scale model of the warehouse. The established full-scale model of the warehouse can be found in Figure 2 and Figure 3 . Figure 2 The warehouse structure is a three-center circular warehouse, which is 33.6 m high, 73 m wide and 180 m long. The ventilation pipe is 3.5 m high, 9 m wide and 180 m long. Figure 3 The warehouse structure is a bullet-shaped structure. In this embodiment, the bottom area of ​​the bullet-shaped warehouse is Figure 2 The bottom area of ​​the central three-center circular warehouse is kept consistent to facilitate the comparison of wind loads of the two structural types.

[0068] This embodiment simplifies the warehouse structure and simplifies the details of the structure to keep the geometric similarity with the real object in appearance. That is, unnecessary details in the architectural drawings are removed while retaining the main features and structure of the building, thereby obtaining the basic shape of the building. This process may involve identifying the main contours of the building and optimizing and smoothing them to ensure that the final extracted shape accurately reflects the overall layout and appearance of the building while meeting the requirements of numerical simulation.

[0069] After the full-scale model of the warehouse is established, the computational domain and boundary conditions of the full-scale model of the warehouse can be determined; and the full-scale model of the warehouse can be meshed using a preset meshing tool to complete the establishment of an initial computational fluid dynamics model.

[0070] Determining the calculation domain and boundary conditions of the full-scale model of the warehouse, including: determining the size of the calculation domain of the full-scale model of the warehouse according to the size of the full-scale model of the warehouse, and determining the layout position of the full-scale model of the warehouse in the calculation domain; the blockage ratio of the geometric model calculated by the calculation domain size and the size of the full-scale model of the warehouse needs to be less than a preset value; determining the boundary conditions of the calculation domain according to the layout position of the full-scale model of the warehouse in the calculation domain; the boundary conditions include the incoming flow direction, the incoming flow inlet boundary, the fluid outlet boundary, the no-slip wall and the symmetric interface.

[0071] See also Figure 4 In this embodiment, the calculation domain can be set to 300 m high, 730 m wide, and 800 m long, and the warehouse is located on the side close to the entrance boundary of the calculation domain. Such an asymmetric arrangement can fully develop the flow field on the leeward side, reduce the backflow, and thus improve the accuracy of the calculation results. The blockage ratio calculated by the calculation domain size set in this embodiment is 1.12%, which meets the virtual wind tunnel test requirement that the blockage ratio of the geometric model in the virtual wind tunnel should not exceed 5%.

[0072] In addition, in this embodiment, the incoming flow direction can be set to be parallel to the length direction of the warehouse, the incoming flow inlet boundary is the velocity inlet, the fluid outlet boundary is the pressure outlet, the warehouse surface, the left and right sides of the calculation domain and the lower surface are no-slip walls, and the upper surface is a symmetrical interface.

[0073] After the full-scale warehouse model is established, the Fluent Meshing software can be used for meshing. Figure 5 In this embodiment, the entire geometric model can be divided into polyhedral unstructured grids. However, different grid sizes are used for different areas. The full-scale warehouse model is divided into grids of the first size; the area within a preset range near the full-scale warehouse model (i.e., the surrounding area) is divided into grids of the second size; and the other areas in the computational domain except the full-scale warehouse model and the area within the preset range are divided into grids of the third size. In addition, see Figure 6 In this embodiment, the grid near the warehouse is encrypted and 5 layers of boundary layer grids are set, which can better simulate the flow field structure near the wall area and improve the accuracy of the calculation.

[0074] After the initial computational fluid dynamics model is established, the corresponding fluid control equations and turbulence models can be constructed.

[0075] Here, the fluid control equations may include the mass control equation, the momentum control equation, and the energy control equation:

[0076] The mass control equation (i.e., the increase in mass in a fluid microelement per unit time is equal to the net mass flowing into the microelement in the same time interval) is:

[0077]

[0078] in, ρ is the fluid density, t It's time. u , v , w are the components of the total fluid velocity in the x, y, and z directions;

[0079] The momentum control equation (the rate of change of the momentum of the fluid in the microelement with respect to time is equal to the sum of various forces acting on the microelement from the outside) is:

[0080]

[0081]

[0082]

[0083] in, P is the pressure on the initial computational fluid dynamics model microelement; τ x , τ y , τ z is the viscous stress acting on the surface of the microelement of the initial computational fluid dynamics model τ The weight, subscript x , y , z Represents viscous stress τ The amount of x , y , z Components in three directions; Fx , F , F is the body force acting on the microelement of the initial computational fluid dynamics model;

[0084] The energy control equation (the rate of increase of energy in the microelement is equal to the net energy entering the microelement plus the work done by the body force and the surface force on the microelement) is:

[0085]

[0086] in, e represents the internal energy per unit mass; k' represents the heat transfer coefficient of the fluid; T is the temperature of the fluid; S T represents the viscous dissipation term; Indicates the velocity of the fluid;

[0087] The turbulence model is:

[0088]

[0089]

[0090] Among them, Γ k , G k , Y k , S k Turbulent kinetic energy k Diffusion term, generation term, dissipation term, and custom source term of Γ ω , G ω , Y ω , S ω Dissipation rate ω Diffusion term, generation term, dissipation term, custom source term, is the i-direction coordinate, is the j-direction coordinate, is the component of the fluid velocity in the i direction.

[0091] Since the wind load and wind effect of large-span warehouse structures are very complex, they have the characteristics of multiple load forms, multiple response vibration modes, and multiple equivalent targets. And considering the extreme conditions in some regions, such as the southern coastal areas where typhoons are frequent, simulating the performance of building structures under different wind speeds, wind directions, etc. can help designers optimize structural design.

[0092] In this embodiment, the preset working condition can be selected according to the extreme weather conditions, or according to the environmental characteristics of the area where the object to be designed is located. Here, the preset working condition includes the time series data of the wind direction angle and the wind speed that change with time. Figure 7 , Figure 7 Several wind directions in reality are defined. By using dynamic wind direction angle time series data and wind speed time series data to simulate the calculation of wind load, the design results of large-span warehouse structures can be highly reliable and applicable.

[0093] According to the preset working conditions, the initial computational fluid dynamics model, the fluid control equations and the turbulence model, the wind load numerical simulation of the large-span warehouse structure can be carried out to obtain the wind load data of the large-span warehouse structure.

[0094] Here, the numerical simulation of wind load includes: constructing a simulated dynamic wind field according to the wind direction angle time series data and the wind speed time series data in the preset working condition; applying the simulated dynamic wind field in the initial computational fluid dynamics model to obtain the real-time wind speed sequence of each microelement in the initial computational fluid dynamics model; solving the fluid control equation and the turbulence model by using the SIMPLE algorithm, and determining the wind pressure coefficient of each microelement in the initial computational fluid dynamics model according to the solution results; calculating the wind load of each microelement in the initial computational fluid dynamics model according to the real-time wind speed sequence of each microelement in the initial computational fluid dynamics model and the wind pressure coefficient of each microelement in the initial computational fluid dynamics model by using the following calculation formula to obtain the wind load sequence of each microelement in the initial computational fluid dynamics model;

[0095]

[0096] in, is the wind load of each microelement, is the air density, is the value in the real-time wind speed series, is the wind pressure coefficient of each microelement, is the control range area of ​​each microelement;

[0097] The wind load data of the long-span warehouse structure are obtained according to the wind load sequences of all micro-elements in the initial computational fluid dynamics model.

[0098] In the field of wind engineering, accurate calculation of the distribution and size of wind loads on buildings is crucial to the safety and reliability of building structures. Wind load is actually a random time-varying live load, and the impact of wind load on buildings is mainly reflected in horizontal displacement. This embodiment is based on a full-scale warehouse model, and the numerical simulation calculation domain of the model is discretized into units, and the geometric shape of the building is discretized into a series of small units (i.e., micro-elements) for numerical calculation. The numerical simulation calculation domain can be calculated to simulate the airflow movement and wind pressure distribution of the building under different wind directions, and the numerical simulation results can be obtained.

[0099] The stress of each component of the structure under the action of dynamic wind load is the key to the wind-resistant safety design of the structure. After performing wind load numerical simulation to obtain the wind load data of the large-span warehouse structure, this embodiment can further obtain the predicted component stress value of the large-span warehouse structure according to the wind load-stress mapping model, and then perform the wind-resistant design evaluation of the large-span warehouse structure according to the predicted component stress value.

[0100] Since the stress values ​​of different positions of the long-span warehouse structure under the action of wind load are closely related to the warehouse structure type, the present embodiment needs to select the corresponding wind load-stress mapping model according to the different warehouse structure types.

[0101] That is, when the warehouse structure type of the large-span warehouse structure is a three-center circle type, the wind load-stress mapping model is:

[0102]

[0103] in, is the stress value of the i-th microelement of the warehouse body; is the coordinate of the i-th microelement of the warehouse body in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse body, is the slope of the tangent line of the surface of the i-th microelement of the warehouse body; is the length of the warehouse body; is the width of the warehouse body; The main height of the warehouse; is the stress value of the i-th microelement of the warehouse ventilation pipe; is the coordinate of the i-th microelement of the warehouse ventilation duct in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse ventilation duct, is the slope of the tangent line of the surface of the i-th microelement of the warehouse ventilation pipe; is the length of the warehouse ventilation pipe; is the width of the warehouse ventilation pipe; is the height of the warehouse ventilation pipe;

[0104] When the warehouse structure type of the large-span warehouse structure is a bullet-shaped structure, the wind load-stress mapping model is:

[0105]

[0106] in, is the stress value of the i-th microelement of the warehouse body; is the coordinate of the i-th microelement of the warehouse body in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse body, is the slope of the tangent line of the surface of the i-th microelement of the warehouse body; is the main length of the warehouse; is the width of the warehouse body; The main height of the warehouse; is the stress value of the i-th microelement of the warehouse ventilation pipe; is the coordinate of the i-th microelement of the warehouse ventilation duct in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse ventilation duct, is the slope of the tangent line of the surface of the i-th microelement of the warehouse ventilation pipe; is the length of the warehouse ventilation pipe; is the width of the warehouse ventilation pipe; Height of warehouse ventilation pipe.

[0107] The large-span warehouse structure actually includes two parts: the warehouse body and the warehouse ventilation duct. The two parts have different structures. Therefore, the wind load-stress mapping model of this embodiment needs to establish corresponding wind load-stress mapping models for these two different structures. That is, different wind load-stress mapping models are used for the warehouse body and the warehouse ventilation duct to obtain the corresponding predicted component stress values.

[0108] Although this embodiment will obtain the corresponding predicted component stress values ​​for the warehouse body and the warehouse ventilation duct respectively. But in fact, for the structural wind resistance design, the safety of the structure is fundamentally determined by the safety of each micro-element after the structure is divided, and whether each micro-element is safe is determined by the maximum stress it bears. Therefore, this embodiment adopts the following wind resistance design evaluation method, which can provide an effective and practical evaluation basis for the actual structural wind resistance safety design. The evaluation method can be:

[0109] The predicted component stress value of each microelement of the large-span warehouse structure is compared with the maximum component stress corresponding to the microelement; if the predicted component stress value of any microelement of the large-span warehouse structure is greater than the maximum component stress corresponding to the microelement, the wind-resistant design result of the initial structural data of the large-span warehouse structure is unqualified; if the predicted component stress values ​​of all microelement of the large-span warehouse structure are less than the maximum component stress corresponding to the microelement, the wind-resistant design result of the initial structural data of the large-span warehouse structure is qualified.

[0110] In the case where the wind resistance design result is unqualified, this embodiment also provides a method for modifying the initial structural data of the large-span warehouse structure. The suggested modification value of the initial structural data provided in this embodiment is only a modification suggestion provided to designers and engineers. In fact, whether the wind resistance design result of the suggested modification value is qualified needs to be further evaluated and determined using the above-mentioned wind load numerical simulation method and wind load-stress mapping model. This embodiment only provides designers and engineers with a suggested modification value that may make the evaluation result qualified.

[0111] Specifically, the method for obtaining the modification suggestion value of the initial structural data in this embodiment is: randomly adjusting the initial structural data, inputting the adjusted initial structural data into the trained stress prediction network model, and obtaining the predicted component stress value output by the stress prediction network model; the input of the stress prediction network model is the structural data, and the output of the stress prediction network model is the predicted component stress value; comparing the predicted component stress value output by the stress prediction network model with the maximum component stress value of the large-span warehouse structure, if the predicted component stress value output by the stress prediction network model is greater than the maximum component stress value of the large-span warehouse structure, then continuing to adjust the initial structural data until the predicted component stress value output by the stress prediction network model is less than the maximum component stress value of the large-span warehouse structure; obtaining the initial structural data adjusted for the last time; and using the initial structural data adjusted for the last time as the modification suggestion value of the initial structural data.

[0112] Here, the training process of the stress prediction network model includes: obtaining multiple sets of structural data of large-span warehouse structures and predicted component stress values ​​of the structural data under preset working conditions; using the structural data and the corresponding predicted component stress values ​​as training sets, training a preset initial network model, and obtaining a trained stress prediction network model.

[0113] This embodiment uses historical data to train a network model to identify the changing relationship between structural data and predicted component stress values, so as to use the trained model to provide designers and engineers with a structural data modification suggestion value with a potentially qualified evaluation result.

[0114] In addition, this embodiment takes the large-span warehouse structure of the Changsha Tongguan Port Phase II project as a prototype, and obtains the initial structural data of two different structural types of large-span warehouse structures by establishing an initial computational fluid dynamics model and a wind load-stress mapping model, providing a reference for the wind-resistant design of large-span warehouse structures.

[0115] See also Figure 8 and Fig. 9 , which is a schematic diagram of the numerical simulation results of wind loads on a three-center circular large-span warehouse structure at two different times. Fig.10 and Fig.11 , which is a schematic diagram of the numerical simulation results of wind loads on a bullet-shaped large-span warehouse structure at two different times. Fig.12 and Fig.13 , which is a schematic diagram of the numerical simulation results of wind loads on the ventilation duct of a three-center circular large-span warehouse structure at two different times.

[0116] In order to implement the method of an embodiment of the present invention, an embodiment of the present invention also provides a large-span warehouse structure wind-resistant design system based on numerical simulation of wind loads, including: a processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, it executes the steps of the above-mentioned method.

[0117] The above-mentioned system provided in this embodiment belongs to the same concept as the above-mentioned method embodiment. The specific implementation process thereof is detailed in the method embodiment and will not be repeated here.

[0118] In order to implement the method of the embodiment of the present invention, the embodiment of the present invention also provides a computer program product, which includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps of the above method.

[0119] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present invention, the embodiment of the present invention further provides an electronic device (computer device). Specifically, in one embodiment, the computer device may be a terminal, and its internal structure diagram may be as follows: Fig.14 As shown. The computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05 and a memory (not shown in the figure) connected through a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A06. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor A01, the method of any one of the above embodiments is implemented. The display screen A04 of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device A05 of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0120] Those skilled in the art will understand that Fig.14 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0121] The device provided by the embodiment of the present invention includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the method of any one of the above embodiments is implemented.

[0122] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0123] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0124] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0126] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0127] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0128] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0129] It can be understood that the memory of the embodiment of the present invention can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAMbus random access memory (DRRAM, Direct Rambus Random Access Memory).The memories described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memories.

[0130] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0131] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A wind-resistant design method for large-span warehouse structures based on numerical simulation of wind loads, characterized in that: The method comprises: Acquire initial structural data of a large-span warehouse structure; the initial structural data includes warehouse structure type, warehouse main body size parameters, warehouse ventilation pipe size parameters, warehouse main body material data and warehouse ventilation pipe material data; According to the initial structural data, an initial computational fluid dynamics model of the large-span warehouse structure is established; and based on the initial computational fluid dynamics model, corresponding fluid control equations and turbulence models are constructed; Acquire a preset working condition; the preset working condition includes wind direction angle time series data and wind speed time series data; perform a numerical simulation of the wind load of the large-span warehouse structure according to the preset working condition, the initial computational fluid dynamics model, the fluid control equation, and the turbulence model, and acquire the wind load data of the large-span warehouse structure; Obtaining a wind load-stress mapping model of the long-span warehouse structure, inputting the wind load data and the initial structural data into the wind load-stress mapping model, and obtaining a predicted component stress value of the long-span warehouse structure; Comparing the predicted component stress value with the maximum component stress value of the large-span warehouse structure to determine the wind-resistant design result of the initial structural data of the large-span warehouse structure; Wherein, obtaining the wind load-stress mapping model of the large-span warehouse structure includes: When the warehouse structure type of the large-span warehouse structure is a three-center circle type, the wind load-stress mapping model is: in, is the stress value of the i-th microelement of the warehouse body; is the coordinate of the i-th microelement of the warehouse body in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse body, is the slope of the tangent line of the surface of the i-th microelement of the warehouse body; is the length of the warehouse body; is the width of the warehouse body; The main height of the warehouse; is the stress value of the i-th microelement of the warehouse ventilation pipe; is the coordinate of the i-th microelement of the warehouse ventilation duct in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse ventilation duct, is the slope of the tangent line of the surface of the i-th microelement of the warehouse ventilation pipe; is the length of the warehouse ventilation pipe; is the width of the warehouse ventilation pipe; is the height of the warehouse ventilation pipe; When the warehouse structure type of the large-span warehouse structure is a bullet-shaped structure, the wind load-stress mapping model is: in, is the stress value of the i-th microelement of the warehouse body; is the coordinate of the i-th microelement of the warehouse body in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse body, is the slope of the tangent line of the surface of the i-th microelement of the warehouse body; is the length of the warehouse body; is the width of the warehouse body; The main height of the warehouse; is the stress value of the i-th microelement of the warehouse ventilation pipe; is the coordinate of the i-th microelement of the warehouse ventilation duct in the x, y, and z directions; is the material coefficient; is the wind load of the i-th microelement of the warehouse ventilation duct, is the slope of the tangent line of the surface of the i-th microelement of the warehouse ventilation pipe; is the length of the warehouse ventilation pipe; is the width of the warehouse ventilation pipe; Height of warehouse ventilation duct.

2. The wind-resistant design method for large-span warehouse structures based on numerical simulation of wind loads according to claim 1 is characterized in that: According to the initial structural data, an initial computational fluid dynamics model of the large-span warehouse structure is established, including: Establishing a full-scale warehouse model of the large-span warehouse structure using SCDM geometric modeling software according to the initial structural data; Determine the computational domain and boundary conditions of the full-scale model of the warehouse; Using a preset grid division tool to divide the warehouse full-scale model into a first-size grid, dividing the area within a preset range near the warehouse full-scale model into a second-size grid, and dividing the other areas in the calculation domain except the warehouse full-scale model and the area within the preset range nearby into a third-size grid; The divided geometric model is determined as an initial computational fluid dynamics model of the long-span warehouse structure.

3. The wind-resistant design method for large-span warehouse structures based on numerical simulation of wind loads according to claim 2 is characterized in that: Determine the computational domain and boundary conditions of the warehouse full-scale model, including: Determine the size of the calculation domain of the warehouse full-scale model according to the size of the warehouse full-scale model, and determine the layout position of the warehouse full-scale model in the calculation domain; the geometric model blocking ratio calculated by the calculation domain size and the warehouse full-scale model size must be less than a preset value; According to the layout position of the full-scale model of the warehouse in the calculation domain, the boundary conditions of the calculation domain are determined; the boundary conditions include the incoming flow direction, the incoming flow inlet boundary, the fluid outlet boundary, the no-slip wall and the symmetric interface.

4. The wind-resistant design method for large-span warehouse structures based on wind load numerical simulation according to claim 1 is characterized in that: Based on the initial computational fluid dynamics model, corresponding fluid control equations and turbulence models are constructed, including: The fluid control equations include mass control equations, momentum control equations and energy control equations: The quality control equation is: in, ρ is the fluid density, t It's time. , , are the components of the total fluid velocity in the x, y, and z directions; The momentum control equation is: in, P is the pressure on the initial computational fluid dynamics model microelement; , , is the viscous stress acting on the surface of the microelement of the initial computational fluid dynamics model The weight, subscript x , y , z Represents viscous stress The amount of x , y , z Components in three directions; , , is the body force acting on the microelement of the initial computational fluid dynamics model; The energy control equation is: in, e represents the internal energy per unit mass; k' represents the heat transfer coefficient of the fluid; T is the temperature of the fluid; represents the viscous dissipation term; Indicates the velocity of the fluid; The turbulence model is: in, , , , Turbulent kinetic energy k Diffusion term, generation term, dissipation term, and custom source term; , , , Dissipation rate ω Diffusion term, generation term, dissipation term, custom source term, is the i-direction coordinate, is the j-direction coordinate, is the component of the fluid velocity in the i direction.

5. The wind-resistant design method for large-span warehouse structures based on wind load numerical simulation according to claim 1 is characterized in that: According to the preset working condition, the initial computational fluid dynamics model, the fluid control equation, and the turbulence model, a numerical simulation of the wind load of the large-span warehouse structure is performed to obtain wind load data of the large-span warehouse structure, including: Constructing a simulated dynamic wind field according to the wind direction angle time series data and wind speed time series data in the preset working condition; Applying the simulated dynamic wind field in the initial computational fluid dynamics model to obtain a real-time wind speed sequence of each microelement in the initial computational fluid dynamics model; Solving the fluid control equation and the turbulence model using the SIMPLE algorithm, and determining the wind pressure coefficient of each microelement in the initial computational fluid dynamics model according to the solution results; According to the real-time wind speed sequence of each micro-element in the initial computational fluid dynamics model and the wind pressure coefficient of each micro-element in the initial computational fluid dynamics model, the wind load of each micro-element in the initial computational fluid dynamics model is calculated using the following calculation formula to obtain the wind load sequence of each micro-element in the initial computational fluid dynamics model; in, is the wind load of each microelement, is the air density, is the value in the real-time wind speed series, is the wind pressure coefficient of each microelement, is the control range area of ​​each microelement; The wind load data of the long-span warehouse structure are obtained according to the wind load sequences of all micro-elements in the initial computational fluid dynamics model.

6. The wind-resistant design method for large-span warehouse structures based on numerical simulation of wind loads according to claim 1 is characterized in that: The predicted component stress value is compared with the maximum value of the component stress of the large-span warehouse structure to determine the wind-resistant design result of the initial structural data of the large-span warehouse structure, including: Compare the predicted component stress value of each microelement of the large-span warehouse structure with the maximum component stress value corresponding to the microelement; If the predicted component stress value of any of the micro-element bodies of the large-span warehouse structure is greater than the maximum component stress value corresponding to the micro-element body, the wind resistance design result of the initial structural data of the large-span warehouse structure is unqualified; If the predicted component stress values ​​of all the micro-elements of the large-span warehouse structure are less than the maximum component stress values ​​corresponding to the micro-elements, the wind-resistant design results of the initial structural data of the large-span warehouse structure are qualified.

7. The wind-resistant design method for large-span warehouse structures based on numerical simulation of wind loads according to claim 6 is characterized in that: When the wind resistance design result is unqualified, the method further includes: Randomly adjusting the initial structural data, inputting the adjusted initial structural data into a trained stress prediction network model, and obtaining a predicted component stress value output by the stress prediction network model; the input of the stress prediction network model is the structural data, and the output of the stress prediction network model is the predicted component stress value; Comparing the predicted component stress value output by the stress prediction network model with the maximum component stress value of the long-span warehouse structure, if the predicted component stress value output by the stress prediction network model is greater than the maximum component stress value of the long-span warehouse structure, continuing to adjust the initial structure data until the predicted component stress value output by the stress prediction network model is less than the maximum component stress value of the long-span warehouse structure; The last adjusted initial structural data is obtained; and the last adjusted initial structural data is used as a modification suggestion value of the initial structural data.

8. The wind-resistant design method for large-span warehouse structures based on numerical simulation of wind loads according to claim 7 is characterized in that: The training process of the stress prediction network model includes: Acquire multiple sets of structural data of large-span warehouse structures and predicted component stress values ​​of the structural data under preset working conditions; The structural data and the corresponding predicted component stress values ​​are used as a training set to train a preset initial network model to obtain a trained stress prediction network model.

9. A wind-resistant design system for large-span warehouse structures based on numerical simulation of wind loads, characterized in that: include: A processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, the steps of the method according to any one of claims 1 to 8 are executed.

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