Pneumatic optimization design method, device and equipment for head type of high-speed train and storage medium

Abstract

The invention discloses a high-speed train head type aerodynamic optimization design method, device and equipment and a storage medium. The optimization design method comprises the steps that a high-speed train aerodynamic simulation model is constructed; performing free-form surface fitting on the front end surface of the high-speed train aerodynamic simulation model to form a grid surface; according to the train head deformation requirement, key spline control molded lines are added to grid lines of the grid face, and grid points are selected from the key spline control molded lines to serve as control points; defining control point parameters and an optimization target; based on the control point parameters and the optimization target, an intelligent optimization algorithm is adopted to carry out optimization solution, and each control point parameter under the optimal target is obtained; and performing high-speed train head optimization design according to the parameters of each control point under the optimal target. According to the method, the free-form surface modeling technology is combined with high-precision computational fluid mechanics and an intelligent optimization algorithm, and the problems that a traditional method is low in design freedom degree, long in period and difficult in global optimization are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of high - speed train design, and particularly relates to a pneumatic optimization design method, device, equipment and storage medium for the head shape of a high - speed train based on free - form surfaces. Background Technique

[0002] The aerodynamic performance of high - speed trains is one of the core factors restricting their speed increase, energy consumption reduction and operation safety. As the operating speed of trains breaks through 400 km / h and moves towards a higher - speed 600 - km / h high - speed maglev train, the traditional head - shape design methods based on empirical formulas or simple geometric configurations are difficult to meet the requirements of aerodynamic performance optimization. The train head shape, as a key component directly affecting the distribution of the surrounding flow field, its geometric shape determines key parameters such as aerodynamic drag, lift, lateral stability and tunnel pressure waves. Traditional designs mostly rely on streamlined templates or experimental iteration methods, which have a series of problems such as low design freedom, long cycle and difficulty in global optimization. Summary of the Invention

[0003] The purpose of the present invention is to provide a pneumatic optimization design method, device, equipment and storage medium for the head shape of a high - speed train, so as to solve the problems of traditional designs mostly relying on streamlined templates or experimental iteration methods, which have low design freedom, long cycle and difficulty in global optimization.

[0004] The present invention solves the above - mentioned technical problems through the following technical solutions: A pneumatic optimization design method for the head shape of a high - speed train, comprising: Constructing a high - speed train aerodynamic simulation model; Performing free - form surface fitting on the front end face of the high - speed train aerodynamic simulation model to form a grid surface; wherein, the grid lines in the grid surface are symmetrically distributed left and right, and the grid points are on the same longitudinal grid line or horizontal grid line; According to the deformation requirements of the high - speed train head, adding key spline control curves on the grid lines of the grid surface, and selecting grid points from the key spline control curves as control points; Defining control point parameters and optimization objectives; Based on the control point parameters and optimization objectives, using an intelligent optimization algorithm to perform optimization and solution to obtain the control point parameters under the optimal objective; Performing optimization design of the high - speed train head according to the control point parameters under the optimal objective.

[0005] The present invention selects control points from the original grid points, deforms the head surface through the control points and the key spline control curves, and combines the free-form surface modeling technology with high-precision computational fluid dynamics (CFD) and intelligent optimization algorithms, providing a new paradigm for the head shape design of high-speed trains. The free-form surface breaks through the traditional geometric constraints through parametric modeling, realizes the refined control of complex surfaces, and achieves global optimization by continuously and automatically adjusting the control point parameters through intelligent optimization algorithms, solving the problems of low design freedom, long cycle, and difficulty in global optimization in traditional methods, improving the aerodynamic performance of the high-speed train head, and thus laying a foundation for the speed increase, energy consumption reduction, and safe operation of high-speed trains.

[0006] Further, the construction of the aerodynamic simulation model of the high-speed train includes: Construct a geometric model of the high-speed train; Based on the geometric model of the high-speed train, construct an aerodynamic performance simulation calculation domain of the high-speed train; wherein, the front end face of the geometric model of the high-speed train is used as the velocity inlet, the rear end face is used as the pressure outlet, the two side faces and the top face are used as symmetry planes, and the bottom face is used as a non-slip wall surface to define the calculation domain boundary; Perform grid division on the calculation domain to obtain a grid model; Select a physical model to simulate the flow field around the train to obtain the aerodynamic simulation model of the high-speed train.

[0007] Further, the construction of the geometric model of the high-speed train includes: Construct a regular cuboid according to the body width, body height, and head streamline of the train; According to the external shape design requirements of the high-speed train, use arcs to modify the front end face and the rear end face of the regular cuboid so that the front end face and the rear end face of the regular cuboid form regular arc surfaces; Perform fillet processing on the edges of the regular cuboid to obtain the geometric model of the high-speed train.

[0008] Further, a three-layer gradually refined grid division method is used to perform grid division on the calculation domain, and the grid aspect ratio is controlled not to be greater than 2:1.

[0009] Further, boundary layer grids are set near the vehicle body surface of the grid model.

[0010] Further, the key spline control curves include three, namely the first spline control curve, the second spline control curve, and the third spline control curve; Add the first spline control curve on the longitudinal center grid line of the grid surface, add the second spline control curve on the maximum horizontal grid line of the grid surface, and add the third spline control curve on the horizontal grid line corresponding to the bottom of the window.

[0011] Further, based on the control point parameters and the optimization objective, the SHERPA algorithm is used for optimization and solution.

[0012] Based on the same concept, the present invention provides a pneumatic optimization design device for a high-speed train head shape, including: A model construction unit for constructing an aerodynamic simulation model of a high-speed train; A fitting unit for performing free-form surface fitting on the front end surface of the aerodynamic simulation model of the high-speed train to form a mesh surface; wherein, the mesh lines in the mesh surface are symmetrically distributed left and right, and the mesh points are on the same longitudinal mesh line or horizontal mesh line; An adding and selecting unit for adding key spline control curves on the mesh lines of the mesh surface according to the deformation requirements of the high-speed train head, and selecting mesh points from the key spline control curves as control points; A defining unit for defining control point parameters and an optimization objective; A solving unit for performing optimization and solution using an intelligent optimization algorithm based on the control point parameters and the optimization objective to obtain the control point parameters under the optimal objective; A design unit for performing optimization design of the high-speed train head according to the control point parameters under the optimal objective.

[0013] Based on the same concept, the present invention also provides an electronic device, including a memory, a processor, and a computer program / instructions stored on the memory, and the processor executes the computer program / instructions to implement the above-mentioned pneumatic optimization design method for the high-speed train head shape.

[0014] Based on the same concept, the present invention also provides a computer-readable storage medium, on which a computer program / instructions are stored, and when the computer program / instructions are executed by a processor, the above-mentioned pneumatic optimization design method for the high-speed train head shape is implemented.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention combines free-form 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. The free-form surface breaks through traditional geometric constraints through parametric modeling, realizing refined control of complex surfaces. Through the intelligent optimization algorithm, the control point parameters are continuously and automatically adjusted to achieve global optimization, solving the problems of low design freedom, long cycle, and difficulty in global optimization of traditional methods, improving the aerodynamic performance of the high-speed train head, and thus laying a foundation for the speed increase, energy consumption reduction, and safe operation of high-speed trains. Description of the Drawings

[0016] To more clearly illustrate the technical solution of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only one embodiment of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 is the flowchart of the aerodynamic optimization design method for the high-speed train head shape in the embodiment of the present invention; Figure 2 is the schematic diagram of the free-form surface in the embodiment of the present invention; Figure 3 is the schematic diagram of the position of the first spline control curve and its control points in the embodiment of the present invention; Figure 4 is the schematic diagram of the position of the second spline control curve and its control points in the embodiment of the present invention; Figure 5 is the schematic diagram of the position of the third spline control curve and its control points in the embodiment of the present invention; Figure 6 is the schematic diagram of the resistance optimization process in the embodiment of the present invention; Figure 7 is the parallel coordinate diagram of the optimization design parameters in the embodiment of the present invention; Figure 8 is the front view of the train head model with the optimal aerodynamic performance in the embodiment of the present invention; Figure 9 is the top view of the train head model with the optimal aerodynamic performance in the embodiment of the present invention; Figure 10 is the side view of the train head model with the optimal aerodynamic performance in the embodiment of the present invention; Figure 11 is the longitudinal velocity field of the train head model with the optimal aerodynamic performance in the embodiment of the present invention; Figure 12 is the surface pressure of the train head model with the optimal aerodynamic performance in the embodiment of the present invention. Detailed implementation manners

[0018] The following will clearly and completely describe the technical solutions in the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0019] The technical solution of the present invention will be described in detail below with 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.

[0020] Embodiment 1 As Figure 1 shown, the high-speed train head aerodynamic optimization design method provided by the embodiment of the present invention includes the following steps: Step 1: Construct a high-speed train aerodynamic simulation model.

[0021] In the specific implementation manner of the present invention, constructing a high-speed train aerodynamic simulation model includes: Step 1.1: Construct a high-speed train geometric model.

[0022] First, a regular cuboid is constructed according to the body width (W: 3 - 3.8 m), body height (H1: 3.5 - 4.2 m) and head streamline of the existing high-speed train. Then, according to the cultural elements and concepts that need to be considered in the high-speed train shape design, the front end face and the rear end face of the regular cuboid are modified using arcs so that the front end face and the rear end face of the regular cuboid form regular arc surfaces. Since the edges of the regular cuboid are sharp, the edges of the regular cuboid also need to be rounded to obtain the high-speed train geometric model.

[0023] In this embodiment, the body width W of the train is used as the width of the regular cuboid, the body height H1 of the train 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 refers to the height of the train bottom from the rail surface (H2: 0.2 - 0.35 m). Using an arc with the body height H1 as the radius, the front end face and the rear end face of the regular cuboid are modified; rounding is performed with a radius of H1 / 10.

[0024] To facilitate obtaining the arc surface coordinates, a coordinate system is constructed with the projection point of the midpoint of the intersection line between the regular arc surface corresponding to the front end face and the top surface of the regular cuboid on the bottom surface of the regular cuboid as the coordinate origin, with the body length direction as the Y-axis, the body width direction as the X-axis, and the height direction as the Z-axis.

[0025] Step 1.2: Based on the high-speed train geometric model, construct a high-speed train aerodynamic performance simulation calculation domain.

[0026] Determine the calculation domain boundary according to the optimization environment and conditions. In this embodiment, the front end face of the high-speed train geometric model is defined as the velocity inlet, the rear end face is defined as the pressure outlet, the two side faces and the top face are defined as symmetry planes, and the bottom face is defined as a non-slip wall surface to define the calculation domain boundary.

[0027] Taking the clear - line and wind - free environment as an example, the blockage ratio of the computational domain 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 of this embodiment has a total of 6 faces. Among them, the front end face is set as the velocity inlet "Inlet" and "Pressure - out", the rear end face is the pressure outlet, the reference pressure is 0 Pa, the bottom face (i.e., the ground) is named "Ground", and the remaining side faces are named symmetry planes "Symmetry".

[0028] Step 1.3: Mesh the computational domain to obtain a mesh model.

[0029] In the specific implementation of the present invention, since the area near the train head is the area where the flow field changes most violently, a three - layer gradually refined mesh generation method is used to mesh the computational domain, and the aspect ratio of the mesh is controlled not to be greater than 2:1 to ensure the mesh quality. In order to more accurately capture the development of the vortex structure on the vehicle body surface, 10 - 15 layers of boundary - layer meshes are set near the vehicle body surface of the mesh model.

[0030] Step 1.4: Select a physical model to simulate the flow field around the train to obtain a high - speed train aerodynamics simulation model.

[0031] To prevent model stress loss and flow separation caused by the mesh, the IDDES method of the unsteady SST k−ω turbulence model is selected in this embodiment to simulate the flow field around the train.

[0032] Step 2: Perform free - form surface fitting on the front end face of the high - speed train aerodynamics simulation model to form a mesh surface.

[0033] Obtain the coordinates of each point on the front end face, perform free - form surface fitting on each point of the front end face to form a mesh surface, as Figure 2 shown. The grid lines in the mesh surface are symmetrically distributed left and right, and the grid points are on the same longitudinal grid line or horizontal grid line. The mesh surface obtained by fitting has an appropriate grid point density to ensure that the free - form 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 mesh surface is not less than 7 rows and 9 columns.

[0034] Step 3: According to the deformation requirements of the high - speed train head, add key spline control curves on the grid lines of the mesh surface, and select grid points from the key spline control curves as control points.

[0035] Through research and analysis, applying a longitudinal center curve, a maximum horizontal profile curve, a cross - sectional curve, auxiliary control curves, and control points at certain positions to the high - speed train head can better control the head deformation requirements.

[0036] In a specific embodiment of the present invention, three key spline control curves are added to the grid lines of the grid surface, namely the first spline control curve, the second spline control curve, and the third spline control curve.

[0037] Specifically, the first spline control curve is added to the longitudinal center grid line of the grid surface to control the longitudinal profile of the head curve. The longitudinal center grid line has 9 grid points, and the first spline control curve has 7 grid points. The area corresponding to the last 3 grid points from bottom to top is the position of the driver's cab. The curvature at this position is small and the slope is gentle. The last 3 grid points are not selected as control points. Finally, the remaining 4 grid points of the first spline control curve are selected as control points, denoted as P1, P2, P3, P4. As shown in Figure 3, the nose thickness is controlled by the control point P2.

[0038] The second spline control curve is added to the maximum horizontal grid line of the grid surface to control the horizontal profile of the head curve, and 4 grid points are selected from the second spline control curve as control points, denoted as P7, P8, P9, P10, as Figure 4 shown.

[0039] The third spline control curve is added to the horizontal grid line corresponding to the bottom of the window as an auxiliary control curve to separately control the deformation of the window position of the train head. As Figure 5 shown, the third spline control curve is located at the second grid line above the second spline control curve. Grid points are selected as control points from the left and right ends of the third spline control curve, denoted as P11, P12. These two control points P11, P12 are symmetrically distributed left and right. The third spline control curve is set on the horizontal grid line corresponding to the bottom of the window, which is beneficial to making the shape of the train head more streamlined.

[0040] Considering that the control point P1 is on the second spline control curve, the curvatures of the control points P7 and P10 can be indirectly determined by adjacent control points. The final control points are P2, P3, P4, P8, P9, P11, P12. All the control points P2, P3, P4, P8, P9, P11, P12 are the original grid points, which is convenient for well controlling the deformation of the train head surface through the control points and the key spline control curves, and greatly improves the degree of freedom of the head optimization design.

[0041] Step 4: Define the control point parameters and optimization objectives.

[0042] In the CFD software function area, enter the free-form surface editing interface, expose the control points to make them editable by the user, and then set the parameters of these control points in sequence. In this embodiment, the control point parameter is the control point displacement.

[0043] Considering that the control points P9 and P11 are slave control points, and the control points P2, P3, P4, P8, and P12 are master control points and each only involves a change in one coordinate, only five displacement parameters need to be defined.

[0044] After defining the control point parameters, create a design project in the CFD software function area, set the optimization type to the weighted sum of all objectives, set all parameter types to "continuous", and set the parameter range and resolution. If there are multiple optimization objectives, the total optimization objective is the weighted sum of multiple optimization objectives. Exemplarily, if the optimization objectives are drag and lift, the total optimization objective is the weighted sum of drag and lift; if the optimization objective is drag, the total optimization objective is drag and the weight is 1.

[0045] Set the normalization type to original design normalization and create a history graph of the optimization objective to facilitate observing the optimization process of the optimization objective.

[0046] Step 5: Based on the control point parameters and the optimization objective, use an intelligent optimization algorithm to perform optimization and solution to obtain the control point parameters under the optimal objective.

[0047] Create a monitor for the optimization objective in the CFD software. Through the monitor plot, the convergence process of each optimization objective can be seen. Then check the scenarios in the required reference simulation file to start the optimization design study.

[0048] In the specific implementation manner of the present invention, the intelligent optimization algorithm selects the SHERPA algorithm. When the optimization objective is a single objective, the single-objective SHERPA algorithm is used; when the optimization objective is a multi-objective, the mo-SHERPA algorithm is used. Multiple search algorithms will be used simultaneously, and the best attributes of each search algorithm will be adopted. If a specific search algorithm is regarded as invalid, SHERPA will reduce its participation. When running the SHERPA algorithm, a combination of global and local searches is used. At any given time, the number of different search algorithms used can range from 2 to 10. Different from traditional optimization algorithms that require manual adjustment of parameters, the adjustment parameters in each algorithm used by SHERPA will be automatically modified during the search. As SHERPA gains a deeper understanding of the design space, it will determine the usage time and scope of each search algorithm. It should be noted that if multiple optimization objectives are defined, the objectives are usually combined in a linear weighted manner because the weight settings between competing objectives are a priori, and the optimal design of a single objective will be returned after running the optimization design.

[0049] Based on the previous optimization result, through continuous automatic adjustment of the local displacement parameters of each control point for multiple local optimizations, the optimal combination of control point parameters is obtained, that is, the control point parameters under the optimal objective are obtained. For example, the displacement parameters of each control point when the drag is minimized are obtained.

[0050] Step 6: Optimize the design of the high-speed train head according to the parameters of each control point under the optimal objective.

[0051] Adjust the head surface of the train according to the parameters of each control point under the optimal objective, and the optimization design of the high-speed train head can be realized.

[0052] Take the resistance as an example of the optimization objective. Figure 6 The curve of the resistance optimization process is shown, and the parameter values near its turning point have the most significant influence on the optimization result. Figure 7 The parallel coordinate diagram of the optimization design parameters is shown, where y1, y2, and y3 respectively represent the ordinates of the control points P2, P3, and P4, x4 represents the abscissa of the control point P8, and z5 represents the Z coordinate of the control point P12. Figure 7 All parameter changes during the optimization process and the finally output optimal design, that is, the optimal parameter combination, are shown. If adjustment is needed again, a set of parameters can be quickly selected from them, and Figure 7 The optimization idea and process can be intuitively displayed. Figures 8 to 10 The train head model with the optimal aerodynamic performance is shown. Figure 11 and Figure 12 respectively show the longitudinal velocity field and surface pressure of the train head model with the optimal aerodynamic performance. From Figure 11 and Figure 12 it can be seen that the streamline degree of the train shape is higher, the transition is smoother, the velocity retardation phenomenon at the front end of the train head is significantly reduced, the range of the high-pressure area is reduced, resulting in a significant reduction in its resistance. Through research, the difference in aerodynamic resistance caused by the subtle surface changes of the train head can exceed 10%. It is difficult to capture such optimization potential due to the limited design space of traditional methods.

[0053] By considering the cultural elements and concepts that need to be considered in the high-speed train shape design, setting the optimization objective and the parameters of the control points, and iteratively optimizing through the intelligent optimization algorithm and outputting an optimal shape and parameter interval, compared with the traditional method of first designing a series of shapes and then importing them into the CFD software for aerodynamic performance comparison, the present invention has a high degree of design freedom, a short cycle, and can achieve global optimization.

[0054] Embodiment 2 The high-speed train head aerodynamic optimization design device provided by the embodiment of the present invention includes a model construction unit, a fitting unit, an adding and selecting unit, a defining unit, a solving unit, and a design unit.

[0055] A model construction unit for constructing an aerodynamic simulation model of a high-speed train; a fitting unit for performing free-form surface fitting on the front end face of the aerodynamic simulation model of the high-speed train to form a mesh surface; wherein, the grid lines in the mesh surface are symmetrically distributed left and right, and the grid points are on the same longitudinal grid line or horizontal grid line; an adding and selecting unit for adding key spline control curves on the grid lines of the mesh surface according to the head deformation requirements of the high-speed train, and selecting grid points from the key spline control curves as control points; a defining unit for defining control point parameters and optimization objectives; a solving unit for performing optimization solution using an intelligent optimization algorithm based on the control point parameters and optimization objectives to obtain the control point parameters under the optimal objective; a design unit for performing optimization design of the high-speed train head according to the control point parameters under the optimal objective.

[0056] In some specific embodiments of the present invention, the aerodynamic optimization design device for the high-speed train head can incorporate the features of the aerodynamic optimization design method for the high-speed train head in Embodiment 1 of the present invention, and vice versa.

[0057] Embodiment 3 The embodiment of the present invention further provides an electronic device, which includes: a memory, a processor, and a computer program / instructions stored on the memory, and the processor executes the computer program / instructions to implement the aerodynamic optimization design method for the high-speed train head in Embodiment 1 of the present invention.

[0058] Although not shown, the electronic device includes a processor, which can perform various appropriate operations and processes according to the programs and / or data stored in the read-only memory (ROM) and / or the programs and / or data loaded from the storage part into the random access memory (RAM). The processor can be a multi-core processor or can include multiple processors. In some embodiments, the processor can include a general main processor and one or more special coprocessors, such as a central processing unit, a graphics processing unit (GPU), a neural network processing unit (NPU), a digital signal processing unit (DSP), and so on. In the RAM, various programs and data required for device operation are also stored. The processor, ROM, and RAM are connected to each other through a bus. The input / output (I / O) interface is also connected to the bus.

[0059] The above-mentioned processor and memory are jointly used to execute the programs / instructions stored in the memory, and when the programs / instructions are executed by a computer, they can implement the methods, steps, or functions described in the above embodiments.

[0060] Although not shown, the embodiment of the present invention further provides a computer-readable storage medium, on which computer programs / instructions are stored, and when the computer programs / instructions are executed by a processor, they implement the aerodynamic optimization design method for the high-speed train head in Embodiment 1 of the present invention.

[0061] A readable storage medium includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The 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, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media do not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0062] The above-disclosed are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or variations, which should all be covered within the protection scope of the present invention.

Claims

1. A pneumatic optimization design method for the head shape of high-speed trains, characterized in that, The optimization design method includes: Constructing a high-speed train aerodynamic simulation model; Performing free-form surface fitting on the front end face of the high-speed train aerodynamic simulation model to form a grid surface; wherein, the grid lines in the grid surface are symmetrically distributed left and right, and the grid points are on the same longitudinal grid line or horizontal grid line; According to the head deformation requirements of the high-speed train, adding key spline control curves on the grid lines of the grid surface, and selecting grid points from the key spline control curves as control points; Defining control point parameters and optimization objectives; Based on the control point parameters and optimization objectives, using an intelligent optimization algorithm to perform optimization solution to obtain the control point parameters under the optimal objective; Performing optimization design on the high-speed train head according to the control point parameters under the optimal objective.

2. The aerodynamic optimization design method for the high-speed train head shape according to claim 1, characterized in that The constructing of the high-speed train aerodynamic simulation model includes: Constructing a high-speed train geometric model; Based on the high-speed train geometric model, constructing a high-speed train aerodynamic performance simulation calculation domain; wherein, taking the front end face of the high-speed train geometric model as the velocity inlet, the rear end 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 calculation domain boundary; Performing grid division on the calculation domain to obtain a grid model; Selecting a physical model to simulate the flow field around the train to obtain a high-speed train aerodynamic simulation model.

3. The aerodynamic optimization design method for the high-speed train head shape according to claim 2, wherein The constructing of the high-speed train geometric model includes: Constructing a regular cuboid according to the body width, body height and head streamline length of the train; According to the external shape design requirements of the high-speed train, using arcs to modify the front end face and the rear end face of the regular cuboid so that the front end face and the rear end face of the regular cuboid form regular arc surfaces; Performing fillet processing on the edges of the regular cuboid to obtain the high-speed train geometric model.

4. The aerodynamic optimization design method for the high-speed train head shape according to claim 2, characterized in that Using a three-layer gradually refined grid division method to perform grid division on the calculation domain, and controlling the grid aspect ratio not to be greater than 2:

1.

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

6. The aerodynamic optimization design method for the high-speed train head shape according to claim 1, characterized in that The key spline control curves include three, namely the first spline control curve, the second spline control curve and the third spline control curve; Adding the first spline control curve on the longitudinal center grid line of the grid surface, adding the second spline control curve on the maximum horizontal grid line of the grid surface, and adding the third spline control curve on the horizontal grid line corresponding to the bottom of the window.

7. The aerodynamic optimization design method for the high-speed train head shape according to claim 1, characterized in that Based on the control point parameters and optimization objectives, using the SHERPA algorithm to perform optimization solution.

8. An aerodynamic optimization design device for the head shape of a high-speed train, characterized in that, The optimization design device includes: A model construction unit for constructing a high-speed train aerodynamic simulation model; A fitting unit for performing free-form surface fitting on the front end face of the high-speed train aerodynamic simulation model to form a grid surface; wherein, the grid lines in the grid surface are symmetrically distributed left and right, and the grid points are on the same longitudinal grid line or horizontal grid line; An adding and selecting unit for adding key spline control curves on the grid lines of the grid surface according to the head deformation requirements of the high-speed train, and selecting grid points from the key spline control curves as control points; A defining unit for defining control point parameters and optimization objectives; A solution unit, configured to perform optimization and solution by using an intelligent optimization algorithm based on the control point parameters and the optimization objective, so as to obtain the control point parameters under each optimal objective; A design unit, configured to perform an optimized design of the high-speed train head according to the control point parameters under each optimal objective.

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

10. A computer-readable storage medium having computer programs / instructions stored thereon, characterized in that, When the computer program / instructions are executed by a processor, the high-speed train head aerodynamic optimization design method according to any one of claims 1 to 7 is implemented.

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