Diving platform skiing clothing resistance reduction optimization design method and device based on numerical simulation

Abstract

The invention discloses a resistance reduction optimization design method and device for diving platform skiing clothes based on numerical simulation and a medium. The method comprises the following steps: acquiring typical attitude data of a skiing assisting stage and a flight stage of a skiing athlete; establishing a flow field computational domain geometric model formed by the athlete-snowboard and the surrounding environment; performing tetrahedral mesh generation and boundary condition setting on the geometric model, and performing numerical simulation calculation to obtain lift-drag ratio and pressure distribution data borne by the sportsman-snowboard overall system under different garment surface roughness; and adjusting the surface roughness setting according to the data, repeating the numerical simulation process, and ending the numerical simulation process until the amplification of the maximum lift-drag ratio reaches a set condition. According to the method provided by the invention, the three-dimensional posture of the athlete, the aerodynamic characteristics of the surface of the clothing and environmental factors can be comprehensively considered, so that a more accurate and personalized optimal design scheme of the diving platform skiing clothing is provided.

Description

Technical Field

[0001] This invention relates to the field of optimization design technology for ski jumping suits, and in particular to a method, apparatus, and computer-readable storage medium for drag reduction optimization design of ski jumping suits based on numerical simulation. Background Technology

[0002] Ski jumping, a high-speed sport influenced by multiple factors, depends not only on the athlete's skill level but also on environmental conditions, the athlete's posture, and the equipment used. The International Ski Federation (FIS) has set strict standards for ski jumping attire, which limit design flexibility and room for innovation. However, research shows that the structural design of the attire surface has a significant impact on athlete performance.

[0003] Although scholars at home and abroad have conducted extensive research on the aerodynamics of ski jumping, these studies have mainly focused on the overall impact of athletes' posture, ambient wind, and clothing surface roughness on air resistance. There has been no in-depth exploration of specific methods for using numerical simulation to play an auxiliary role in the design of athletes' competition and training clothing (such as reducing drag).

[0004] Existing numerical simulation techniques for ski jumping apparel fail to fully consider the complexity of the interaction between the apparel and the athlete's movement posture, environmental wind, etc., when simulating drag reduction on the surface of ski jumping apparel. As a result, existing methods cannot provide accurate and personalized design references for ski jumping apparel and training clothing. Summary of the Invention

[0005] This application provides a method for drag reduction optimization design of ski jumping clothing based on numerical simulation. This method can comprehensively consider the athlete's three-dimensional posture, the aerodynamic characteristics of the clothing surface, and environmental factors to provide a more accurate and personalized ski jumping clothing optimization design scheme.

[0006] To address the aforementioned problems, in a first aspect, embodiments of this application provide a method for drag reduction optimization design of ski jumping clothing based on numerical simulation, comprising the following steps:

[0007] Acquire typical posture data of ski jumpers during the approach and flight phases;

[0008] Based on the typical posture data, a geometric model of the flow field computational domain formed by the athlete, skis, and surrounding environment is established; and the athlete's body and skis in the flow field computational domain geometric model are segmented to form a block geometric model.

[0009] The block geometric model is divided into tetrahedral meshes and boundary conditions are set. Numerical simulation calculations are then performed to obtain the lift-drag ratio and pressure distribution data of the athlete-ski system under different clothing surface roughness.

[0010] Based on the pressure distribution under the surface roughness condition of the clothing corresponding to the highest lift-to-drag ratio, the segmentation of the block geometric model and the surface roughness setting are updated, and numerical simulation calculations are performed again to obtain new lift-to-drag ratio and pressure distribution data.

[0011] Calculate whether the increase in the new maximum lift-to-drag ratio relative to the original maximum lift-to-drag ratio meets the set conditions; if it does, end the numerical simulation process; otherwise, adjust the surface roughness settings according to the new lift-to-drag ratio and pressure distribution data, and repeat the numerical simulation process until the increase in the maximum lift-to-drag ratio meets the set conditions and then end the numerical simulation process; the final numerical simulation result is the drag reduction optimization design scheme for ski jumping suits.

[0012] Preferably, when segmenting the athlete's body parts and skis in the geometric model of the flow field calculation domain, the athlete is divided into four separate modules: head, torso, upper limbs, and lower limbs, and the skis are treated as a separate module.

[0013] Preferably, after dividing the segmented geometric model into tetrahedral meshes, a mesh refinement region is created around the athlete-ski geometric model. + Set the target value to 1.

[0014] Preferably, the height of the first layer of mesh near the wall is set not higher than the lowest surface roughness of the garment, which is 1 / 3 to 3 / 4 of the lowest surface roughness of the garment.

[0015] Preferably, the boundary condition settings include at least one of the following:

[0016] The athlete's inlet face is set as a velocity inlet, and the inlet velocity is determined based on the takeoff / flight speed.

[0017] The boundary of the computational domain at the wake is the pressure outlet, with a pressure value of 101325 Pa (standard atmospheric pressure).

[0018] The surface of the athlete-ski geometry model is set as a non-slip wall boundary;

[0019] The gas is incompressible air;

[0020] Based on the principle of equivalent roughness, assuming the surface of a ski jump suit is covered with a layer of tightly packed, uniformly shaped circular solid particles, the equivalent roughness h is used. s + The surface roughness of ski jumping suit fabric is characterized by values ​​derived from experimental measurements of fabric surface roughness.

[0021] Preferably, in the numerical simulation calculation, the Reynolds-averaged equation is used to solve the aerodynamic characteristics of the flow field around the ski jumper, and the SST k-ω turbulence model is used to study the effect of fabric differences in different parts of the ski suit on the aerodynamic characteristics of ski jump flight.

[0022] Preferably, the numerical simulation calculation targets the lift-to-drag ratio and surface pressure. Different garment surface roughness corresponds to different lift-to-drag ratios. Through numerical simulation calculation of different garment surface roughnesses, the surface roughness geometric model corresponding to the maximum lift-to-drag ratio is obtained. Furthermore, the location range of the maximum surface pressure corresponding to the surface roughness geometric model corresponding to the maximum lift-to-drag ratio is determined.

[0023] Preferably, updating the segmentation of the block geometry model and the surface roughness setting based on the pressure distribution under the garment surface roughness condition corresponding to the highest lift-to-drag ratio specifically involves:

[0024] Based on the pressure distribution under the clothing surface roughness condition corresponding to the highest lift-to-drag ratio, the location of the maximum pressure distribution is found. Within the range of the maximum pressure point to 20% of the maximum pressure around the perimeter, the torso module of the athlete's geometric model is divided along the horizontal plane. The area above the horizontal plane up to the head is defined as Region II, and the remaining area is defined as Region I. The geometric models of Region I and Region II are meshed, and an equivalent roughness h is set for Region I. s + The surface roughness of the garment corresponding to the highest lift-to-drag ratio is set, and the equivalent roughness h is set for region II. s + For the other various surface roughnesses.

[0025] Secondly, embodiments of this application also provide a drag reduction optimization design device for ski jumping clothing based on numerical simulation, the device comprising:

[0026] The data acquisition module is used to acquire typical posture data of ski jumpers during the flight and approach phases.

[0027] The geometric model building module is used to build a geometric model of the flow field computational domain formed by the athlete, skis and surrounding environment based on the typical posture data; and to segment the athlete's body and skis in the flow field computational domain geometric model to form a block geometric model.

[0028] The numerical simulation calculation module is used to perform tetrahedral meshing and boundary condition setting on the block geometric model, and to perform numerical simulation calculations to obtain the lift-drag ratio and pressure distribution data of the athlete-ski system under different clothing surface roughness.

[0029] The drag reduction optimization module is used to update the segmentation of the block geometry model and the surface roughness setting based on the pressure distribution under the clothing surface roughness condition corresponding to the highest drag ratio, and then perform numerical simulation calculations again to obtain new drag ratio and pressure distribution data.

[0030] The iterative optimization module is used to calculate whether the increase in the new maximum lift-to-drag ratio relative to the original maximum lift-to-drag ratio meets the set conditions. If it does, the numerical simulation process ends. Otherwise, based on the new lift-to-drag ratio and pressure distribution data, the surface roughness setting is adjusted, and the numerical simulation process is repeated until the increase in the maximum lift-to-drag ratio meets the set conditions and the numerical simulation process ends. The final numerical simulation result is the drag reduction optimization design scheme for ski jumping suits.

[0031] Thirdly, this application also provides a device for drag reduction optimization design of ski jumping clothing based on numerical simulation, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the drag reduction optimization design method for ski jumping clothing based on numerical simulation as described above.

[0032] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method for optimizing drag reduction of ski jumping clothing based on numerical simulation.

[0033] This application proposes a numerical simulation-based drag reduction optimization design method for ski jumping suits. Utilizing computational fluid dynamics (CFD) technology, it simulates the air resistance experienced by athletes during the flight and approach phases under different surface roughness conditions, and analyzes the aerodynamic characteristics under different postures. The method provided in this embodiment comprehensively considers the influence of suit surface roughness, athlete posture, and environmental factors on air resistance, offering personalized design references for competition and training suits for high-level ski jumping athletes. This method reduces the manpower and material resources required for traditional wind tunnel experiments, providing an efficient and economical solution for drag reduction optimization of ski jumping suits. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0035] Figure 1 This is a flowchart of the drag reduction optimization design method for ski jumping clothing based on numerical simulation provided in Embodiment 1 of this application;

[0036] Figure 2 This is a schematic diagram illustrating the segmentation of the various parts of the three-dimensional solid geometric model of the athlete-ski in Embodiment 1 of this application;

[0037] Figure 3 This is a schematic diagram of tetrahedral mesh generation for the three-dimensional solid geometric model of the athlete-ski in Embodiment 1 of this application;

[0038] Figure 4 for Figure 3 A magnified view of a close-up of the Chinese athlete's head;

[0039] Figure 5 This is a schematic diagram of the final numerical simulation results obtained in Embodiment 1 of this application;

[0040] Figure 6 This is a structural block diagram of the ski jumping suit drag reduction optimization design device based on numerical simulation provided in Embodiment 2 of this application;

[0041] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0042] This application provides a method for drag reduction optimization design of ski jumping clothing based on numerical simulation. This method can comprehensively consider the athlete's three-dimensional posture, the aerodynamic characteristics of the clothing surface, and environmental factors to provide a more accurate and personalized ski jumping clothing optimization design scheme.

[0043] To better understand the above technical solutions, exemplary embodiments will be described in detail below, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses consistent with some aspects of this application as detailed in the appended claims.

[0044] Example 1

[0045] Figure 1 This is a flowchart of the drag reduction optimization design method for ski jumping suits based on numerical simulation provided in this embodiment. The drag reduction optimization design method for ski jumping suits based on numerical simulation includes the following steps:

[0046] Step S1: Obtain typical posture data of ski jumpers during the flight and approach phases;

[0047] Specifically, a high-precision 3D scanner was used to scan the typical postures of ski jumpers wearing competition equipment during the approach and flight phases, generating point cloud data and saving it as a .scan file.

[0048] The acquired typical pose data are preprocessed; the preprocessing methods include: denoising and smoothing the point cloud data, and the processed data is saved as a .pre file.

[0049] Step S2: Establish a geometric model of the flow field computational domain formed by the athlete, skis, and surrounding environment; divide the athlete's body and skis in the geometric model of the flow field computational domain to form a block geometric model.

[0050] Specifically, the preprocessed data is modeled and solidified into a 3D solid geometric model of an athlete and ski. Specifically, the reverse engineering software Geomagic Wrap is used to model and solidify the preprocessed point cloud data into a 3D solid geometric model of an athlete and ski, and then exported as a .stl or .step file.

[0051] Preferably, the athlete-ski three-dimensional solid geometric model includes different postures during the ski jump approach phase and during the flight phase.

[0052] Furthermore, a finite element model was established using the numerical simulation software ANSYS, specifically including: establishing the flow field calculation domain formed by the athlete, skis, and surrounding environment, and forming the geometric model of the overall athlete-ski system.

[0053] In one alternative implementation, when segmenting the athlete's body parts and skis, the athlete is divided into four separate modules: head, torso, upper limbs, and lower limbs. The skis are treated as a separate module, and the entire system is divided into five segmented geometric models.

[0054] Step S3: Perform tetrahedral meshing and boundary condition setting on the segmented geometric model; and perform numerical simulation calculations to obtain the lift-drag ratio and pressure distribution data of the athlete-ski system under different clothing surface roughness.

[0055] Furthermore, after tetrahedral meshing the segmented geometric model, a mesh refinement region is created around the athlete-ski geometric model, dividing it into smaller mesh cells, while ensuring y + Keep it around 1.

[0056] Furthermore, the height of the first layer of mesh near the wall is set not higher than the lowest surface roughness of the garment, which is 1 / 3 to 3 / 4 of the lowest surface roughness of the garment.

[0057] Furthermore, setting boundary conditions for the geometric model includes:

[0058] The athlete's inlet face is set as a velocity inlet, and the inlet velocity is determined based on the takeoff / flight speed.

[0059] The boundary of the computational domain at the wake is the pressure outlet, with a pressure value of 101325 Pa (standard atmospheric pressure).

[0060] The surface of the athlete-ski geometry model is set as a non-slip wall boundary;

[0061] The gas is incompressible air;

[0062] Based on the principle of equivalent roughness, assuming the surface of the ski jump suit is covered with a layer of small, uniformly shaped, and tightly packed circular solid particles, the equivalent roughness h is used. s + The surface roughness of the ski jumping suit fabric is characterized by values ​​derived from experimental measurements of fabric surface roughness (different fabrics have different roughness values; four or more equivalent roughness values ​​can be used, such as #1, #2, #3, and #4). The roughness constant is set to 0.5, and the surface roughness is assumed to be uniformly distributed. The equivalent roughness h for each part of the body is also specified. s + The values ​​are optimized based on the pressure distribution calculation results.

[0063] Furthermore, a fluid mathematical model is established based on the gridded block geometric model, the flow field is initialized according to the flow field boundary conditions, and the flow field is numerically solved according to the fluid mathematical model to obtain the flow field data.

[0064] In one optional implementation, the Reynolds-averaged Navier-Stokes (RANS) equations and the SST k-ω turbulence model are used to perform numerical simulation calculations on the gridded block geometric model. Solver parameters are set in ANSYS software, and the SIMPLEC algorithm is used to perform numerical simulation calculations until the calculation results converge, generating a .rst file.

[0065] Specifically, the Reynolds-averaged equation was used to solve the aerodynamic characteristics of the flow field around the ski jumper in the gridded block geometric model, and the SST k-ω turbulence model was used to study the effect of fabric differences in different parts of the ski suit on the aerodynamic characteristics of ski jump flight.

[0066] The SST k-ω model stands for Menter's Shear Stress Transport k-omega model. It was proposed by FRMenter in 1994.

[0067] The SIMPLEC (Semi-Implicit Method for Pressure-Linked Equations Consistent) algorithm is a pressure-velocity coupling algorithm widely used in computational fluid dynamics (CFD). In this embodiment, the numerical simulation model does not consider small changes in air density and its compressibility, assuming that the air density is a constant. All simulation conditions of the aerodynamic performance during the ski jump flight phase are assumed to be incompressible steady flow problems, and the SIMPLEC algorithm is used for numerical simulation calculations.

[0068] The goal of the numerical simulation is to determine the lift-to-drag ratio and the surface pressure contour map. Different surface roughnesses of clothing correspond to different lift-to-drag ratios. Through numerical simulation calculations of different clothing surface roughnesses, the surface roughness geometric model corresponding to the maximum lift-to-drag ratio is obtained. Furthermore, the location range of the maximum surface pressure corresponding to the surface roughness geometric model corresponding to the maximum lift-to-drag ratio is determined.

[0069] Step S4: Based on the pressure distribution under the surface roughness condition of the clothing corresponding to the highest lift-to-drag ratio, update the segmentation of the block geometric model and the surface roughness setting, and perform numerical simulation calculations again to obtain new lift-to-drag ratio and pressure distribution data.

[0070] Specifically, based on the pressure distribution under the garment surface roughness conditions corresponding to the highest lift-to-drag ratio, the location of the maximum pressure distribution is found; within the range of the maximum pressure point to 20% of the maximum pressure around the perimeter, the torso module in the segmented geometric model is divided along the horizontal plane, with the area above the horizontal plane up to the head defined as Region II, and the remaining area defined as Region I; step S3 is repeated to mesh the geometric models of Region I and Region II, and the .msh file is updated; an equivalent roughness h is set for Region I. s + The surface roughness of the garment corresponding to the highest lift-to-drag ratio is set, and the equivalent roughness h is set for region II. s + For various other surface roughnesses, numerical simulations were performed to collect new lift-to-drag ratio and pressure distribution data.

[0071] Here, "other surface roughnesses" refers to the surface roughness values ​​set above, excluding the surface roughness corresponding to the highest lift-to-drag ratio. For example, if the surface roughness corresponding to the highest lift-to-drag ratio is 2#, then the other surface roughnesses are 1#, 3#, and 4#.

[0072] Step S5: Calculate whether the increase in the new maximum lift-to-drag ratio relative to the original maximum lift-to-drag ratio meets the set conditions; if it does, end the numerical simulation process; otherwise, adjust the surface roughness setting according to the new lift-to-drag ratio and pressure distribution data, and repeat the numerical simulation process until the increase in the maximum lift-to-drag ratio meets the set conditions and then end the numerical simulation process; the final numerical simulation result is the drag reduction optimization design scheme for ski jumping suits.

[0073] In a preferred embodiment, the condition for setting the increase in the maximum lift-to-drag ratio is: the numerical simulation process ends when the new maximum lift-to-drag ratio increases by 1% or more from the original maximum lift-to-drag ratio. Here, the original maximum lift-to-drag ratio refers to the maximum lift-to-drag ratio obtained in the first data acquisition.

[0074] Furthermore, based on the new lift-to-drag ratio and pressure distribution data, the equivalent roughness of different regions is adjusted. When repeating the numerical simulation process, in each optimization, the equivalent roughness of each region is the surface roughness of the clothing corresponding to the current highest lift-to-drag ratio.

[0075] The selected surface roughness matching schemes of clothing fabrics were communicated with clothing designers to prepare finished products, providing a theoretical basis for the selection and personalized customization of special clothing fabrics for ski jumping suits.

[0076] This embodiment proposes a drag reduction optimization design method for ski jumping clothing based on numerical simulation. Utilizing computational fluid dynamics (CFD) technology, it simulates the air resistance experienced by athletes during the flight and approach phases under different surface roughness conditions, and analyzes the aerodynamic characteristics under different postures. This method comprehensively considers the influence of clothing surface roughness, athlete posture, and environmental factors on air resistance, providing personalized design references for competition and training clothing for high-level ski jumping athletes. This method reduces the manpower and material resources required for traditional wind tunnel experiments, providing an efficient and economical solution for drag reduction optimization of ski jumping clothing.

[0077] The following is an illustration through a specific example.

[0078] A method for drag reduction optimization design of ski jumping clothing based on numerical simulation includes the following steps:

[0079] (1): A high-precision 3D scanner was used to scan typical postures of ski jumpers wearing competition equipment during the flight phase that have a significant aerodynamic impact. The athlete's height was 1.73m and weight was 53kg; the ski length was 2.51m, width was 0.115m, and thickness was 0.01m; the angle between the ski and the athlete's body was β = 20.8°, the athlete's upper body bending angle was γ = 163.0°, and the ski angle was λ = 37.5°. Point cloud data was generated and saved as a .scan file.

[0080] (2): Preprocess the point cloud data scanned in step (1), including noise reduction and smoothing, and save the processed data as a .pre file.

[0081] (3): Using the reverse engineering software Geomagic Wrap, the point cloud data preprocessed in step 2 is transformed into a surface model and converted into a three-dimensional solid geometric model of an athlete-ski. The model is then exported as a .stl or .step file.

[0082] (4): Establish a geometric model of the flow field computation domain formed by the athlete and the surrounding environment of the skis. The computation domain size is 10m long, 5m wide and 5m high along the flight direction. Divide the athlete's head, torso, upper limbs, lower limbs and skis in the geometric model so that each part becomes a separate whole and forms a block geometric model. Figure 2 The diagram shown is a schematic representation of the segmentation.

[0083] (5): such as Figure 3 and Figure 4 As shown, the block geometry model is tetrahedralized, and a mesh refinement region is created around the athlete-ski geometry model, while ensuring that y + The value should be controlled at around 1; the height of the first layer of mesh near the wall should not exceed the lowest surface roughness of the garment, taking 1 / 3 to 3 / 4 of the lowest surface roughness of the garment, and the height of the first layer of mesh should be 3.5 × 10. -6 m, with 15 million grid cells.

[0084] (6): Set boundary conditions for the segmented geometric model, including: setting the athlete's inlet face as a velocity inlet, with the inlet velocity set to 29 m / s based on the flight speed; setting the computational domain boundary at the wake as a pressure outlet, with a pressure value of 101325 Pa (standard atmospheric pressure); setting the surface of the athlete-ski three-dimensional solid geometric model as a non-slip wall boundary; and setting the gas as incompressible air. Based on the principle of equivalent roughness, it is assumed that the surface of the ski jump suit is covered with a layer of small, uniformly shaped, and compactly arranged circular solid particles, using an equivalent roughness h. s + The surface roughness of ski jumping suit fabric is characterized by values ​​derived from experimental measurements of surface roughness. A roughness constant of 0.5 is set, assuming a uniform surface roughness distribution. Based on the differences in surface structure parameters of ski jumping suit fabrics specified by the International Ski Federation (FIS), four fabrics with different surface roughnesses (7.776 μm, 10.922 μm, 17.036 μm, and 28.206 μm) were selected through cylindrical wind tunnel drag experiments to evaluate the surface roughness of each segment of the geometric model. s + Make the appropriate settings.

[0085] (7): Select the angle of attack α of the ski as 14°, use the Reynolds average equation and SST k-ω turbulence model for the block geometric model after meshing, set the solver parameters in ANSYS software, use the SIMPLEC algorithm to perform numerical simulation calculation until the calculation results converge, and generate the .rst file.

[0086] (8): Data was collected from the numerical simulation results, including lift-to-drag ratio and pressure distribution data of the athlete-ski system under different clothing surface roughness. The results showed that the maximum lift-to-drag ratios of the ski jumping system corresponding to the four different clothing surface roughnesses were 2.1228, 2.1006, 2.0817, and 2.1151, respectively. It can be seen that the lift-to-drag ratio is the largest when the surface roughness is 28.206 μm, which is 2.1151. Compared with the other surface roughnesses, this surface roughness has the best aerodynamic performance, and the corresponding maximum pressure is mainly concentrated on the windward side of the upper body, hip joint, and knee joint, especially the upper body;

[0087] Furthermore, the model with a surface roughness of 28.206 μm was further optimized. From below the shoulder to the waist, the upper body of the geometric model was divided along the horizontal plane around the area of ​​maximum pressure on the shoulder and up to 2 / 3 of the way up to the waist. The area above the horizontal plane to the head was defined as Region II, and the remaining area was defined as Region I. Step (5) was repeated to mesh the geometric models of Region I and Region II and update the .msh file. Step (6) was repeated to set the equivalent roughness h for Region I. s + The equivalent roughness h is set to 28.206 μm for region II. s + For the other three surface roughnesses (7.776μm, 10.922μm, and 17.036μm, respectively); repeat step (7) to perform numerical simulation calculations and collect new lift-to-drag ratio and pressure distribution data.

[0088] (9): The results show that setting an equivalent roughness h in region II is effective. s + At a roughness of 7.776 μm, the lift-to-drag ratio of the athlete-ski system reached its maximum, at 2.1467. Compared to the previous maximum lift-to-drag ratio of 2.1151, the increase was 1.49%, concluding the optimization process. An equivalent roughness h was set for region I. s + An equivalent roughness h is set for region II at 28.206 μm. s + The numerical simulation results at a drag reduction value of 7.776 μm represent the final optimized design scheme for ski jumping suit drag reduction obtained in this embodiment. Figure 5The image shown is a surface pressure cloud map at this time.

[0089] Example 2

[0090] Based on the same inventive concept as the numerical simulation-based drag reduction optimization design method for ski jumping suits in Embodiment 1 above, this embodiment also provides a numerical simulation-based drag reduction optimization design device for ski jumping suits, such as... Figure 6 As shown, the device includes:

[0091] Data acquisition module 1 is used to acquire typical posture data of ski jumpers during the flight and approach phases.

[0092] Geometric model building module 2 is used to build a geometric model of the flow field calculation domain formed by the athlete, skis and surrounding environment based on the typical posture data; and to segment the athlete's body and skis in the geometric model of the flow field calculation domain to form a block geometric model.

[0093] The numerical simulation calculation module 3 is used to perform tetrahedral meshing and boundary condition setting on the block geometric model, and to perform numerical simulation calculations to obtain the lift-drag ratio and pressure distribution data of the athlete-ski system under different clothing surface roughness.

[0094] The drag reduction optimization module 4 is used to update the segmentation of the block geometry model and the surface roughness setting according to the pressure distribution under the clothing surface roughness condition corresponding to the highest drag ratio, and to perform numerical simulation calculations again to obtain new drag ratio and pressure distribution data.

[0095] The loop optimization module 5 is used to calculate whether the increase of the new maximum lift-to-drag ratio relative to the original maximum lift-to-drag ratio reaches the set condition. If it does, the numerical simulation process ends. Otherwise, based on the new lift-to-drag ratio and pressure distribution data, the surface roughness setting is adjusted, and the numerical simulation process is repeated until the increase of the maximum lift-to-drag ratio reaches the set condition and the numerical simulation process ends. The final numerical simulation result is the drag reduction optimization design scheme for ski jumping suits.

[0096] The various specific processes and examples of the numerical simulation-based ski jumping suit drag reduction optimization design method in the aforementioned Embodiment 1 are also applicable to the numerical simulation-based ski jumping suit drag reduction optimization design device in this embodiment. Through the detailed description of Embodiment 1, those skilled in the art can clearly understand the implementation method of the numerical simulation-based ski jumping suit drag reduction optimization design device in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0097] Example 3

[0098] Based on the same inventive concept as the numerical simulation-based ski jumping suit drag reduction optimization design method in Embodiment 1 above, this embodiment also provides a numerical simulation-based ski jumping suit drag reduction optimization design device, which stores a computer program. When the program is executed by a processor, it implements the steps of the numerical simulation-based ski jumping suit drag reduction optimization design method described in Embodiment 1.

[0099] Example 4

[0100] Based on the same inventive concept as the numerical simulation-based ski jumping suit drag reduction optimization design method in Embodiment 1 above, this embodiment also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the numerical simulation-based ski jumping suit drag reduction optimization design method described in Embodiment 1.

[0101] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0102] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0103] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0104] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0105] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0106] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for drag reduction optimization design of ski jumping suits based on numerical simulation, characterized in that, Includes the following steps: Acquire typical posture data of ski jumpers during the approach and flight phases; Based on the typical posture data, a geometric model of the flow field computational domain formed by the athlete, skis, and surrounding environment is established; and the athlete's body and skis in the flow field computational domain geometric model are segmented to form a block geometric model. The block geometric model is divided into tetrahedral meshes and boundary conditions are set. Numerical simulation calculations are then performed to obtain the lift-drag ratio and pressure distribution data of the athlete-ski system under different clothing surface roughness. Based on the pressure distribution under the surface roughness condition of the clothing corresponding to the highest lift-to-drag ratio, the segmentation of the block geometric model and the surface roughness setting are updated, and numerical simulation calculations are performed again to obtain new lift-to-drag ratio and pressure distribution data. Calculate whether the increase in the new maximum lift-to-drag ratio relative to the original maximum lift-to-drag ratio meets the set conditions; if it does, end the numerical simulation process; otherwise, adjust the surface roughness settings according to the new lift-to-drag ratio and pressure distribution data, and repeat the numerical simulation process until the increase in the maximum lift-to-drag ratio meets the set conditions and then end the numerical simulation process; the final numerical simulation result is the drag reduction optimization design scheme for ski jumping suits.

2. The method for drag reduction optimization design of ski jumping suits based on numerical simulation as described in claim 1, characterized in that, When segmenting the athlete's body parts and skis in the geometric model of the flow field computation domain, the athlete is divided into four separate modules: head, torso, upper limbs, and lower limbs, while the skis are treated as a separate module.

3. The method for drag reduction optimization design of ski jumping suits based on numerical simulation as described in claim 1, characterized in that, After tetrahedral meshing of the segmented geometric model, a mesh refinement region is created around the athlete-ski geometric model. + Set the target value to 1.

4. The method for drag reduction optimization design of ski jumping suits based on numerical simulation as described in claim 3, characterized in that, Set the height of the first layer of mesh near the wall to be no higher than the lowest surface roughness of the garment, taking 1 / 3 to 3 / 4 of the lowest surface roughness of the garment.

5. The method for drag reduction optimization design of ski jumping suits based on numerical simulation as described in claim 1, characterized in that, The boundary condition settings include at least one of the following: The athlete's inlet face is set as a velocity inlet, and the inlet velocity is determined based on the takeoff / flight speed. The boundary of the computational domain at the wake is the pressure outlet, with a pressure value of 101325 Pa (standard atmospheric pressure). The surface of the athlete-ski geometry model is set as a non-slip wall boundary; The gas is incompressible air; Based on the principle of equivalent roughness, assuming the surface of a ski jump suit is covered with a layer of tightly packed, uniformly shaped circular solid particles, the equivalent roughness h is used. s + The surface roughness of ski jumping suit fabric is characterized by values ​​derived from experimental measurements of fabric surface roughness.

6. The method for drag reduction optimization design of ski jumping suits based on numerical simulation as described in claim 1, characterized in that, The numerical simulation calculation targets the lift-to-drag ratio and surface pressure. Different surface roughnesses of clothing correspond to different lift-to-drag ratios. Through numerical simulation calculations of different surface roughnesses of clothing, the surface roughness geometric model corresponding to the maximum lift-to-drag ratio is obtained. Furthermore, the location range of the maximum surface pressure corresponding to the surface roughness geometric model corresponding to the maximum lift-to-drag ratio is determined.

7. The method for drag reduction optimization design of ski jumping suits based on numerical simulation as described in claim 1, characterized in that, The step of updating the segmentation of the block geometric model and the surface roughness settings based on the pressure distribution under the garment surface roughness condition corresponding to the highest lift-to-drag ratio is as follows: Based on the pressure distribution under the clothing surface roughness condition corresponding to the highest lift-to-drag ratio, the location of the maximum pressure distribution is found. Within the range of the maximum pressure point to 20% of the maximum pressure around the perimeter, the torso module of the athlete's geometric model is divided along the horizontal plane. The area above the horizontal plane up to the head is defined as Region II, and the remaining area is defined as Region I. The geometric models of Region I and Region II are meshed, and an equivalent roughness h is set for Region I. s + The surface roughness of the garment corresponding to the highest lift-to-drag ratio is set, and the equivalent roughness h is set for region II. s + For the other various surface roughnesses.

8. A drag reduction optimization design device for ski jumping clothing based on numerical simulation, characterized in that, The device includes: The data acquisition module is used to acquire typical posture data of ski jumpers during the flight and approach phases. The geometric model building module is used to build a geometric model of the flow field computational domain formed by the athlete, skis and surrounding environment based on the typical posture data; and to segment the athlete's body and skis in the flow field computational domain geometric model to form a block geometric model. The numerical simulation calculation module is used to perform tetrahedral meshing and boundary condition setting on the block geometric model, and to perform numerical simulation calculations to obtain the lift-drag ratio and pressure distribution data of the athlete-ski system under different clothing surface roughness. The drag reduction optimization module is used to update the segmentation of the block geometry model and the surface roughness setting based on the pressure distribution under the clothing surface roughness condition corresponding to the highest drag ratio, and then perform numerical simulation calculations again to obtain new drag ratio and pressure distribution data. The iterative optimization module is used to calculate whether the increase in the new maximum lift-to-drag ratio relative to the original maximum lift-to-drag ratio meets the set conditions. If it does, the numerical simulation process ends. Otherwise, based on the new lift-to-drag ratio and pressure distribution data, the surface roughness setting is adjusted, and the numerical simulation process is repeated until the increase in the maximum lift-to-drag ratio meets the set conditions and the numerical simulation process ends. The final numerical simulation result is the drag reduction optimization design scheme for ski jumping suits.

9. A device for drag reduction optimization design of ski jumping clothing based on numerical simulation, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the numerical simulation-based drag reduction optimization design method for ski jumping clothing as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the numerical simulation-based drag reduction optimization design method for ski jumping clothing as described in any one of claims 1 to 7.

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