Methods, devices, equipment and storage media for aerodynamic optimization design of high-speed train head shape

Abstract

This invention discloses a method, apparatus, device, and storage medium for aerodynamic optimization design of high-speed train head shapes. The optimization design method includes: constructing an aerodynamic simulation model of a high-speed train; fitting a free-form surface to the front face of the aerodynamic simulation model to form a mesh surface; adding key spline control lines to the mesh lines according to the deformation requirements of the train head, and selecting mesh points as control points from the key spline control lines; defining control point parameters and optimization objectives; using an intelligent optimization algorithm to optimize and solve based on the control point parameters and optimization objectives to obtain the optimal control point parameters under the optimal objective; and performing high-speed train head optimization design based on the optimal control point parameters under the optimal objective. This invention combines free-form surface modeling technology with high-precision computational fluid dynamics and intelligent optimization algorithms, solving the problems of low design freedom, long cycle time, and difficulty in global optimization of traditional methods.

Description

Technical Field

[0001] This invention belongs to the field of high-speed train design technology, and particularly relates to a method, device, equipment and storage medium for aerodynamic optimization design of high-speed train head shape based on freeform surfaces. Background Technology

[0002] The aerodynamic performance of high-speed trains is one of the core factors restricting their speed increase, fuel consumption reduction, and operational safety. As train operating speeds exceed 400 km / h and advance towards even higher speeds like 600 km / h high-speed maglev trains, traditional head-shape design methods based on empirical formulas or simple geometric configurations are no longer sufficient to meet the demands of aerodynamic performance optimization. The train head shape, as a key component directly affecting the surrounding flow field distribution, determines crucial parameters such as aerodynamic drag, lift, lateral stability, and tunnel pressure waves. Traditional designs often rely on streamlined templates or iterative experimental methods, resulting in a series of problems including low design freedom, long design cycles, and difficulty in achieving global optimization. Summary of the Invention

[0003] The purpose of this invention is to provide a method, device, equipment and storage medium for aerodynamic optimization design of high-speed train head shape, so as to solve the problems of low design freedom, long cycle and difficulty in global optimization that traditional design relies on streamline templates or experimental iteration methods.

[0004] This invention solves the above-mentioned technical problems through the following technical solution: a method for aerodynamic optimization design of high-speed train head shape, comprising:

[0005] Constructing an aerodynamic simulation model for high-speed trains;

[0006] The front end face of the high-speed train aerodynamic simulation model is fitted with a free-form surface to form a mesh surface; wherein the mesh lines in the mesh surface are symmetrically distributed from left to right, and the mesh points are located on the same longitudinal mesh line or horizontal mesh line;

[0007] Based on the deformation requirements of the high-speed train head, key spline control lines are added to the grid lines of the grid surface, and grid points are selected from the key spline control lines as control points.

[0008] Define control point parameters and optimization objectives;

[0009] Based on the control point parameters and optimization objectives, an intelligent optimization algorithm is used to solve the optimization problem and obtain the control point parameters under the optimal objective.

[0010] The head of the high-speed train is optimized based on the parameters of each control point under the optimal objective.

[0011] This invention selects control points from the original grid points and uses these control points and key splines to control the deformation of the head surface. By combining freeform surface modeling technology with high-precision computational fluid dynamics (CFD) and intelligent optimization algorithms, it provides a new paradigm for the design of high-speed train head shapes. Freeform surfaces break through traditional geometric constraints through parametric modeling, enabling refined control of complex surfaces. The intelligent optimization algorithm continuously and automatically adjusts the control point parameters to achieve global optimization, solving the problems of low design freedom, long cycle, and difficulty in global optimization in traditional methods. This improves the aerodynamic performance of high-speed train head shapes, thus laying the foundation for speed increase, energy saving, and safe operation of high-speed trains.

[0012] Furthermore, the construction of the high-speed train aerodynamic simulation model includes:

[0013] Construct a geometric model of a high-speed train;

[0014] Based on the high-speed train geometric model, the aerodynamic performance of the high-speed train is constructed, and the simulation computational domain is defined. The front face of the high-speed train geometric model is used as the velocity inlet, the rear face as the pressure outlet, the two sides and the top face as symmetry planes, and the bottom face as a non-slip wall, thus defining the boundary of the computational domain.

[0015] The computational domain is divided into grids to obtain a grid model;

[0016] A physical model is selected to simulate the flow field around the train, resulting in an aerodynamic simulation model of the high-speed train.

[0017] Furthermore, the construction of the high-speed train geometric model includes:

[0018] Based on the train's body width, body height, and streamlined front shape, construct a regular cuboid;

[0019] According to the design requirements of high-speed trains, the front and rear faces of the regular cuboid are modified by using arcs to make the front and rear faces of the regular cuboid form regular arc surfaces.

[0020] The edges of the regular cuboid are rounded to obtain the geometric model of the high-speed train.

[0021] Furthermore, a three-layer progressively denser meshing method is used to mesh the computational domain, and the aspect ratio of the mesh is controlled to be no greater than 2:1.

[0022] Furthermore, a boundary layer mesh is set near the vehicle body surface of the mesh model.

[0023] Furthermore, the key spline control profile includes three lines: the first spline control profile, the second spline control profile, and the third spline control profile.

[0024] Add a first spline control line to the longitudinal center grid line of the grid surface, add a second spline control line to the maximum horizontal grid line of the grid surface, and add a third spline control line to the horizontal grid line corresponding to the bottom of the window.

[0025] Furthermore, based on the control point parameters and the optimization objective, the SHERPA algorithm is used for optimization.

[0026] Based on the same concept, the present invention provides a high-speed train head aerodynamic optimization design device, comprising:

[0027] Model building unit, used to build aerodynamic simulation model of high-speed train;

[0028] The fitting unit is used to perform free-form surface fitting on the front end face of the high-speed train aerodynamic simulation model to form a mesh surface; wherein, the mesh lines in the mesh surface are symmetrically distributed from left to right, and the mesh points are located on the same longitudinal mesh line or horizontal mesh line;

[0029] The addition and selection unit is used to add key spline control lines on the grid lines of the grid surface according to the deformation requirements of the high-speed train head, and select grid points as control points from the key spline control lines.

[0030] Define the unit, used to define control point parameters and optimization objectives;

[0031] The solution unit is used to perform optimization based on the control point parameters and the optimization objective using an intelligent optimization algorithm to obtain the parameters of each control point under the optimal objective.

[0032] The design unit is used to optimize the design of the high-speed train head based on the parameters of each control point under the optimal target.

[0033] Based on the same concept, the present invention also provides an electronic device, including a memory, a processor, and a computer program / instructions stored in the memory, wherein the processor executes the computer program / instructions to implement the high-speed train head aerodynamic optimization design method as described above.

[0034] Based on the same concept, the present invention also provides a computer-readable storage medium having a computer program / instruction stored thereon, which, when executed by a processor, implements the high-speed train head aerodynamic optimization design method as described above.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0036] This invention combines freeform surface modeling technology with high-precision computational fluid dynamics (CFD) and intelligent optimization algorithms, providing a new paradigm for the design of high-speed train head shapes. Freeform surfaces break through traditional geometric constraints through parametric modeling, enabling refined control of complex surfaces. Intelligent optimization algorithms continuously and automatically adjust control point parameters to achieve global optimization, solving the problems of low design freedom, long cycle, and difficulty in global optimization in traditional methods. This improves the aerodynamic performance of high-speed train head shapes, thus laying the foundation for speed increase, energy saving, and safe operation of high-speed trains. Attached Figure Description

[0037] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only one embodiment of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart of the aerodynamic optimization design method for the head shape of a high-speed train in an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of a freeform surface in an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram showing the position of the first control line and its control points in an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram showing the position of the second spline control profile and its control points in an embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram showing the position of the third spline control profile and its control points in an embodiment of the present invention;

[0043] Figure 6 This is a schematic diagram of the resistance optimization process in an embodiment of the present invention;

[0044] Figure 7 This is a parallel coordinate graph of the optimized design parameters in an embodiment of the present invention;

[0045] Figure 8 This is the front view of the train head model with the best aerodynamic performance in this embodiment of the invention;

[0046] Figure 9 This is a top view of the train head model with optimal aerodynamic performance in this embodiment of the invention;

[0047] Figure 10 This is a side view of the train head model with optimal aerodynamic performance in this embodiment of the invention;

[0048] Figure 11 This is the longitudinal velocity field of the train head model with the best aerodynamic performance in this embodiment of the invention;

[0049] Figure 12 This refers to the surface pressure of the train head model with the best aerodynamic performance in this embodiment of the invention. Detailed Implementation

[0050] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0052] Example 1

[0053] like Figure 1 As shown, the aerodynamic optimization design method for the high-speed train head shape provided in this embodiment of the invention includes the following steps:

[0054] Step 1: Construct an aerodynamic simulation model for high-speed trains.

[0055] In a specific embodiment of the present invention, constructing a high-speed train aerodynamic simulation model includes:

[0056] Step 1.1: Construct the geometric model of the high-speed train.

[0057] First, a regular cuboid is constructed based on the existing high-speed train's body width (W: 3~3.8m), body height (H1: 3.5~4.2m), and streamlined head shape. Then, based on the cultural elements and concepts that need to be considered in the high-speed train's exterior design, the front and rear faces of the regular cuboid are modified using arcs to form regular curved surfaces. Since the edges of the regular cuboid are sharp, the edges of the regular cuboid also need to be rounded to obtain the geometric model of the high-speed train.

[0058] In this embodiment, the width W of the train body is used as the width of the regular cuboid, the height H1 of the train body is used as the height of the regular cuboid, and 1.5 times the length of a single car is used as the length of the regular cuboid; the ground clearance is referenced to the height of the train's undercarriage from the rail surface (H2: 0.2~0.35m). Using the train body height H1 as the radius, the front and rear faces of the regular cuboid are modified with arcs; rounded corners are performed with a radius of H1 / 10.

[0059] To facilitate obtaining the coordinates of the curved surface, a coordinate system is constructed with the projection point of the midpoint of the intersection line between the regular curved surface corresponding to the front face and the top face of the regular cuboid onto the bottom face of the regular cuboid as the origin. The length direction of the vehicle body is the Y-axis, the width direction of the vehicle body is the X-axis, and the height direction is the Z-axis.

[0060] Step 1.2: Construct the aerodynamic performance of the high-speed train based on the geometric model of the high-speed train and simulate the computational domain.

[0061] The computational domain boundary is determined based on the optimized environment and conditions. In this embodiment, the front face of the high-speed train geometric model is used as the velocity inlet, the rear face as the pressure outlet, the two side faces and the top face as symmetry planes, and the bottom face as a non-slip wall surface to define the computational domain boundary.

[0062] Taking a windless environment with an open line as an example, the computational domain blockage ratio must be less than 15%. When the blockage ratio is between 5% and 15%, the results need to be corrected; when the blockage ratio is less than 5%, no correction is required. The computational domain in this embodiment has a total of 6 faces. The front face is designated as the velocity inlet "Inlet" and "Pressure-out", the rear face is designated as the pressure outlet, the reference pressure is 0 Pa, the bottom face (i.e., the ground) is named "Ground", and the remaining sides are named the symmetry face "Symmetry".

[0063] Step 1.3: Grid the computational domain to obtain a grid model.

[0064] In a specific embodiment of the present invention, since the area near the train head is where the flow field changes most drastically, a three-layer progressively finer meshing method is used to mesh the computational domain, and the aspect ratio of the mesh is controlled to be no greater than 2:1 to ensure mesh quality. To more accurately capture the development of vortex structures on the vehicle body surface, 10 to 15 boundary layer meshes are set near the vehicle body surface of the mesh model.

[0065] Step 1.4: Select a physical model to simulate the flow field around the train and obtain the aerodynamic simulation model of the high-speed train.

[0066] To prevent model stress loss and flow separation caused by mesh, this embodiment selects the IDDES method of the unsteady SST k−ω turbulence model to simulate the flow field around the train.

[0067] Step 2: Fit a free-form surface to the front end of the high-speed train aerodynamic simulation model to form a mesh surface.

[0068] Obtain the coordinates of each point on the front face, and perform freeform surface fitting on each point on the front face to form a mesh surface, such as... Figure 2As shown, the grid lines in the grid surface are symmetrically distributed from left to right, and the grid points are located on the same vertical or horizontal grid line. The fitted grid surface has a suitable grid point density, ensuring that the freeform surface deformation can meet the optimization requirements of the key positions of the train head. In this embodiment, the number of rows and columns of the grid surface is not less than 7 rows and 9 columns.

[0069] Step 3: Based on the deformation requirements of the high-speed train head, add key spline control lines on the grid lines of the grid surface, and select grid points from the key spline control lines as control points.

[0070] Through research and analysis, it has been found that applying longitudinal center lines, maximum horizontal profile lines, cross-sectional lines, auxiliary control lines, and control points at certain locations to the head of high-speed trains can effectively control head deformation requirements.

[0071] In a specific embodiment of the present invention, three key spline control lines are added to the grid lines of the grid surface, namely the first spline control line, the second spline control line, and the third spline control line.

[0072] Specifically, a first control line is added to the longitudinal center grid line of the grid surface to control the longitudinal contour of the head curve. The longitudinal center grid line has 9 grid points, and the first control line has 7 grid points. The area corresponding to the last 3 grid points from bottom to top is the driver's cab position. This position has a smaller curvature and a gentler slope, so the last 3 grid points are not selected as control points. Finally, the remaining 4 grid points of the first control line are selected as control points and denoted as P1, P2, P3, and P4, as shown in Figure 3. The thickness of the nose is controlled by the control point P2.

[0073] Add a second spline control line to the maximum horizontal grid line of the grid surface to control the horizontal profile of the head curve, and select four grid points from the second spline control line as control points, denoted as P7, P8, P9, and P10. Figure 4 As shown.

[0074] A third spline control line is added to the horizontal grid line corresponding to the bottom of the train window as an auxiliary control line. This third spline control line is used to independently control the deformation of the train's front window position. For example... Figure 5 As shown, the third spline control line is located on the second grid line above the second spline control line. Grid points are selected from both ends of the third spline control line as control points, denoted as P11 and P12. These two control points, P11 and P12, are symmetrically distributed. The third spline control line is set on the horizontal grid line corresponding to the bottom of the window, which helps to make the shape of the front of the car more streamlined.

[0075] Considering that control point P1 is located on the second spline control profile, the curvature of control points P7 and P10 can be indirectly determined by adjacent control points. The final control points are P2, P3, P4, P8, P9, P11, and P12. All control points P2, P3, P4, P8, P9, P11, and P12 are the original grid points, which facilitates the deformation control of the train head surface through control points and key spline control profiles, greatly improving the freedom of head optimization design.

[0076] Step 4: Define control point parameters and optimization objectives.

[0077] In the CFD software's function area, enter the freeform surface editing interface, expose the control points to make them editable, and then set the parameters of these control points sequentially. In this embodiment, the control point parameters are the control point displacements.

[0078] Considering that control points P9 and P11 are driven control points, and control points P2, P3, P4, P8, and P12 are active control points and each involves only one coordinate change, only five displacement parameters need to be defined.

[0079] After defining the control point parameters, create a design project in the CFD software's function area. Set the optimization type to a weighted sum of all objectives, the parameter type to "continuous," and set the parameter range and resolution. If there are multiple optimization objectives, the overall optimization objective is the weighted sum of all objectives. For example, if the optimization objectives are drag and lift, the overall optimization objective is the weighted sum of drag and lift; if the optimization objective is drag, the overall optimization objective is drag with a weight of 1.

[0080] Set the normalization type to the original design normalization and create a historical graph of the optimization objective to facilitate observation of the optimization process.

[0081] Step 5: Based on the control point parameters and the optimization objective, use an intelligent optimization algorithm to solve the problem and obtain the parameters of each control point under the optimal objective.

[0082] In CFD software, create a monitor for the optimization objectives. By plotting on the monitor, you can see the convergence process of each optimization objective. Then, select the scenarios in the required reference simulation files to begin the optimization design study.

[0083] In a specific embodiment of this invention, the SHERPA algorithm is selected as the intelligent optimization algorithm. When the optimization objective is single-objective, a single-objective SHERPA algorithm is used; when the optimization objective is multi-objective, a mo-SHERPA algorithm is used, employing multiple search algorithms simultaneously and utilizing the best properties of each. If a particular search algorithm is deemed ineffective, SHERPA will reduce its participation. When running the SHERPA algorithm, a combination of global and local searches is used, and the number of different search algorithms used at any given time can be between 2 and 10. Unlike traditional optimization algorithms that require manual parameter adjustment, the adjustment parameters in each algorithm used by SHERPA are automatically modified during the search. As SHERPA gains a deeper understanding of the design space, it determines the usage time and scope of each search algorithm. It is worth noting that if multiple optimization objectives are defined, they are typically combined using a linear weighting method because the weight settings between competing objectives are prior, and running the optimization design will return the optimal design for a single objective.

[0084] Based on the previous optimization results, the optimal combination of control point parameters is obtained by continuously and automatically adjusting the displacement parameters of each control point multiple times in a localized optimization process. This yields the optimal control point parameters under the optimal objective. For example, the displacement parameters of each control point when the resistance is minimized can be obtained.

[0085] Step 6: Optimize the design of the high-speed train head based on the parameters of each control point under the optimal target.

[0086] By adjusting the parameters of each control point under the optimal target, the head surface of the train can be optimized, thus achieving the head design optimization of high-speed trains.

[0087] Take the optimization objective as an example. Figure 6 The curves of the resistance optimization process are shown, and the parameter values ​​near the inflection point have the most significant impact on the optimization results. Figure 7 The diagram shows the parallel coordinates of the optimized design parameters, where y1, y2, and y3 represent the ordinates of control points P2, P3, and P4, respectively; x4 represents the abscissa of control point P8; and z5 represents the Z-coordinate of control point P12. Figure 7 It demonstrates all parameter changes during the optimization process and the final output of the optimal design, i.e., the optimal parameter combination. If further adjustments are needed, a set of parameters can be quickly selected from this set. Figure 7 It can intuitively display the optimization ideas and processes. Figures 8 to 10 This shows a train head model with optimal aerodynamic performance. Figure 11 and Figure 12 The longitudinal surface velocity field and surface pressure of the train head model with optimal aerodynamic performance are shown respectively. Figure 11 and Figure 12It is evident that the train's streamlined shape results in a smoother transition, significantly reducing speed stagnation at the front of the train and minimizing the high-pressure zone, thus leading to a marked reduction in drag. Research shows that subtle changes in the curvature of the train's front can cause aerodynamic drag differences exceeding 10%, a potential that traditional methods struggle to capture due to design space limitations.

[0088] This invention takes into account the cultural elements and concepts that need to be considered in the design of high-speed trains, sets optimization targets and control point parameters, and iteratively optimizes and outputs an optimal shape and parameter range through intelligent optimization algorithms. Compared with the traditional method of designing a series of shapes first and then importing them into CFD software for aerodynamic performance comparison, this invention has a high degree of design freedom, a short cycle, and can achieve global optimization.

[0089] Example 2

[0090] The aerodynamic optimization design device for high-speed train head shape provided in this embodiment of the invention includes a model building unit, a fitting unit, an adding and selecting unit, a definition unit, a solution unit, and a design unit.

[0091] The system comprises the following units: a model building unit for constructing a high-speed train aerodynamic simulation model; a fitting unit for fitting a free-form surface to the front face of the high-speed train aerodynamic simulation model to form a mesh surface, wherein the mesh lines in the mesh surface are symmetrically distributed from left to right, and the mesh points are located on the same longitudinal or horizontal mesh line; an adding and selecting unit for adding key spline control lines to the mesh surface according to the deformation requirements of the high-speed train head, and selecting mesh points from the key spline control lines as control points; a defining unit for defining control point parameters and optimization objectives; a solving unit for optimizing and solving based on the control point parameters and optimization objectives using an intelligent optimization algorithm to obtain the optimal control point parameters under the optimal objective; and a design unit for optimizing the high-speed train head based on the optimal control point parameters under the optimal objective.

[0092] In some specific embodiments of the present invention, the high-speed train head aerodynamic optimization design device can combine the features of the high-speed train head aerodynamic optimization design method in Embodiment 1 of the present invention, and vice versa.

[0093] Example 3

[0094] This invention also provides an electronic device, which includes a memory, a processor, and a computer program / instructions stored in the memory. The processor executes the computer program / instructions to implement the high-speed train head aerodynamic optimization design method in Embodiment 1 of this invention.

[0095] Although not shown, the electronic device includes a processor that can perform various appropriate operations and processes based on programs and / or data stored in read-only memory (ROM) or loaded from a storage portion into random access memory (RAM). The processor can be a multi-core processor or may contain multiple processors. In some embodiments, the processor may include a general-purpose main processor and one or more specialized coprocessors, such as a central processing unit, graphics processing unit (GPU), neural network processor (NPU), digital signal processor (DSP), etc. Various programs and data required for device operation are also stored in RAM. The processor, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0096] The processor and memory described above are used together to execute programs / instructions stored in the memory. When the program / instructions are executed by the computer, they can implement the methods, steps, or functions described in the above embodiments.

[0097] Although not shown, embodiments of the present invention also provide a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the high-speed train head aerodynamic optimization design method of Embodiment 1 of the present invention.

[0098] Readable storage media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. 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 technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient media, such as modulated data signals and carrier waves.

[0099] The above description only discloses specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or modifications that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for aerodynamic optimization design of the head shape of a high-speed train, characterized in that, The optimization design method includes: Constructing an aerodynamic simulation model for high-speed trains; The front end face of the high-speed train aerodynamic simulation model is fitted with a free-form surface to form a mesh surface; wherein the mesh lines in the mesh surface are symmetrically distributed from left to right, and the mesh points are located on the same longitudinal mesh line or horizontal mesh line; Based on the deformation requirements of the high-speed train head, key spline control lines are added to the grid lines of the grid surface, and grid points are selected from the key spline control lines as control points. The key spline control lines include three lines: a first spline control line added to the longitudinal center grid line of the grid surface, a second spline control line added to the maximum horizontal grid line of the grid surface, and a third spline control line added to the horizontal grid line corresponding to the bottom of the window. The control points are selected from specific grid points on the first, second, and third spline control lines, and by adjusting the displacement parameters of the control points, the longitudinal profile, horizontal profile, and surface deformation of the train head, as well as the window position, are jointly controlled. Define control point parameters and optimization objectives; wherein, the control point parameters are control point displacements, and the optimization objectives are drag and lift, or drag; Based on the control point parameters and the optimization objective, the SHERPA algorithm is used to optimize and solve the problem, and the parameters of each control point under the optimal objective are obtained. The head of the high-speed train is optimized based on the parameters of each control point under the optimal objective.

2. The aerodynamic optimization design method for high-speed train head shape according to claim 1, characterized in that, The construction of the high-speed train aerodynamic simulation model includes: Construct a geometric model of a high-speed train; Based on the high-speed train geometric model, the aerodynamic performance of the high-speed train is constructed, and the simulation computational domain is defined. The front face of the high-speed train geometric model is used as the velocity inlet, the rear face as the pressure outlet, the two sides and the top face as symmetry planes, and the bottom face as a non-slip wall, thus defining the boundary of the computational domain. The computational domain is divided into grids to obtain a grid model; A physical model is selected to simulate the flow field around the train, resulting in an aerodynamic simulation model of the high-speed train.

3. The aerodynamic optimization design method for high-speed train head shape according to claim 2, characterized in that, The construction of the high-speed train geometric model includes: Construct a regular cuboid based on the train's body width, body height, and streamlined front length; According to the design requirements of high-speed trains, the front and rear faces of the regular cuboid are modified by using arcs to make the front and rear faces of the regular cuboid form regular arc surfaces. The edges of the regular cuboid are rounded to obtain the geometric model of the high-speed train.

4. The aerodynamic optimization design method for high-speed train head shape according to claim 2, characterized in that, The computational domain is divided into grids using a three-layer progressively denser grid division method, and the aspect ratio of the grid is controlled to be no greater than 2:

1.

5. The aerodynamic optimization design method for high-speed train head shape according to claim 2, characterized in that, A boundary layer mesh is set near the vehicle body surface of the mesh model.

6. A high-speed train head aerodynamic optimization design device, characterized in that, The optimized design device includes: Model building unit, used to build aerodynamic simulation model of high-speed train; The fitting unit is used to perform free-form surface fitting on the front end face of the high-speed train aerodynamic simulation model to form a mesh surface; wherein, the mesh lines in the mesh surface are symmetrically distributed from left to right, and the mesh points are located on the same longitudinal mesh line or horizontal mesh line; An addition and selection unit is used to add key spline control lines on the grid lines of the grid surface according to the deformation requirements of the high-speed train head, and to select grid points as control points from the key spline control lines. The key spline control lines include three lines: a first spline control line added to the longitudinal center grid line of the grid surface, a second spline control line added to the maximum horizontal grid line of the grid surface, and a third spline control line added to the horizontal grid line corresponding to the bottom of the window. The control points are selected from specific grid points on the first, second, and third spline control lines, and by adjusting the displacement parameters of the control points, the longitudinal profile, horizontal profile, and surface deformation of the train head and the window position are jointly controlled. A definition unit is used to define control point parameters and optimization objectives; wherein, the control point parameters are control point displacements, and the optimization objectives are drag and lift, or drag; The solution unit is used to perform optimization and solution using the SHERPA algorithm based on the control point parameters and the optimization objective, so as to obtain the control point parameters under the optimal objective. The design unit is used to optimize the design of the high-speed train head based on the parameters of each control point under the optimal target.

7. An electronic device comprising a memory, a processor, and a computer program / instructions stored in the memory, characterized in that, The processor executes the computer program / instructions to implement the high-speed train head aerodynamic optimization design method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instruction is executed by the processor, it implements the aerodynamic optimization design method for the high-speed train head as described in any one of claims 1 to 5.

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