Analysis method and system for geometric free deformation optimization of movable body

Abstract

The invention discloses an analysis method and system for geometric free deformation optimization of a movable body. The method comprises the steps that the boundary of a CAD model is determined; defining a control domain serving as a deformation area in a three-dimensional space corresponding to the CAD model, and selecting a plurality of control points; selecting a sample primary function based on a control domain and engineering requirements, and constructing a total function; determining a total function value corresponding to each control point group based on the three-dimensional coordinates corresponding to each control point group in the control domain; adjusting the three-dimensional coordinates of the control point group, and automatically deforming the deformation optimization target area in the deformation area; a freezing part and a deformation blocking plane can be arranged in the deformation area, and flexible deformation can be achieved; and geometric surface curvature calculation and verification are carried out on the deformed deformation optimization target area, and a deformed CAD model is obtained after verification is passed. Therefore, it is ensured that the design is stable and reliable, the method can be coupled with a simulation optimization process, and the engineering simulation optimization requirement of a complex model is met.

Description

Technical Field

[0001] The present invention relates to a shape deformation technology for engineering geometric models, and in particular to an analysis method and system for geometric free deformation optimization of a movable body based on free deformation technology (FFD). The system and method are suitable for shape deformation applications in various engineering fields, including multidisciplinary simulation design optimization (MDO). Background Art

[0002] Although the existing free deformation technology (FFD) has shown certain application value in the fields of computer graphics and animation, it is difficult to meet the stringent requirements of high precision and high stability in the fields of engineering design and simulation. These technologies will face the following major problems in the application of engineering: the movement achieved by the nodes on the original geometry is very complex, the fault tolerance is low, and it is difficult to achieve flexible and accurate deformation of complex geometry, and it cannot meet the complex scene requirements in the fields of engineering design and simulation; lack of multidisciplinary integration: FFD technology is difficult to seamlessly integrate with CAE simulation analysis, such as finite element analysis (FEA), computational fluid dynamics (CFD), discipline simulation design optimization (MDO) and other engineering simulation technologies, which limits its wide application in the engineering field. Insufficient real-time performance: In the face of application scenarios with high real-time requirements, the performance of existing FFD technology is insufficient, and it is difficult to support instant and efficient shape deformation and optimization operations, thus limiting its application in dynamic simulation, real-time interaction and other fields. Summary of the invention

[0003] The present invention proposes an analysis method and system for optimizing the geometric free deformation of a movable body, which can solve technical problems in the free deformation of geometric models in the field of engineering design and simulation.

[0004] In various method embodiments of the present invention, an analysis method for optimizing geometric free deformation of a movable body includes: step S1: obtaining a CAD model file of the movable body, wherein the CAD model corresponding to the CAD model file is a model to be deformed; converting the CAD model file into a CAD model, and determining the boundary of the CAD model;

[0005] Step S2: defining a control domain in the three-dimensional space corresponding to the CAD model, wherein the control domain is a deformation region that is determined based on the boundary of the CAD model and can cover the deformation optimization target region of the CAD model;

[0006] Step S3: Select spline basis functions based on the control domain and engineering requirements to construct a total function; select control points as optimization design variables from the control domain to form a control point set to be deformed, and select multiple control points from the control point set to be deformed as a control point group; determine the total function value corresponding to the control point group based on the three-dimensional coordinates corresponding to the control point group;

[0007] Step S4: Based on the total function value corresponding to the control point group, the three-dimensional coordinates of the control point group are adjusted, and a deformation operation is performed on the deformation optimization target area to obtain a deformed candidate optimization area, wherein the deformation optimization target area is divided into a plurality of sub-areas based on the adjusted three-dimensional coordinates of the control point group, and the deformation operation includes: freezing the points in the sub-area set to the freezing mode to keep them unchanged, and performing a deformation operation on the sub-area in the non-freezing mode, wherein at least four control points in the same plane are selected from the control point group to form a polygon, and the plane corresponding to the polygon is used as a blocking plane, and the influence order is defined for the deformation blocking plane in such a way that the deformation effect of the deformation operation on one side of the deformation blocking plane on the other side of the deformation blocking plane is reduced by a predetermined degree, and all the sub-areas after the deformation operation constitute the candidate optimization area;

[0008] Step S5: Generate a CAD candidate model corresponding to the candidate optimization area, and determine whether the surface quality of the CAD candidate model is smooth or meets expectations. If it is determined to be yes, proceed to step S6; otherwise, proceed to step S3;

[0009] Step S6: Perform CAE simulation analysis on the CAD candidate model, calculate the fluid mechanics parameters of the CAD candidate model, and determine whether the CAD candidate model meets the preset requirements based on the CAE simulation analysis results and the fluid mechanics parameters. If yes, use the CAD candidate model as the deformed CAD model and proceed to step S7; otherwise, proceed to step S4;

[0010] Step S7: exporting the deformed CAD model as a deformed CAD model file.

[0011] Preferably, in step S3, the total function is

[0012] , where P i,j,k are the corresponding three-dimensional coordinates of the control points in the control point group, i, j, k are the coordinates of the control points in the control point group on the x-axis, y-axis, and z-axis respectively; q, r, s are the maximum number of control points in the x-axis, y-axis, and z-axis directions respectively, u, v, w are the influence parameters on the x-axis, y-axis, and z-axis respectively, N i,p (u) is the spline basis function selected for parameter u, N j,m (v) is the spline basis function selected for parameter v, N k,n (w) is the spline basis function selected for parameter w, W i,j,k is the weight, and P'(u,v,w) is the total function value.

[0013] Preferably, N i,p (u), N j,m (v) Nk,n (w) is a spline basis function of different types, including B-spline basis function, Gaussian spline function, multi-quadratic biharmonic spline function, inverse multi-quadratic biharmonic spline function, and Bernstein function.

[0014] Preferably, based on the CAD model imported in step S1 and the control domain defined in step S2, the control point grid scale and density are automatically determined in step S3, or the position and number of control points are manually adjusted, and the control points are selected by mouse clicks or through a dialog box.

[0015] Preferably, in step S4, the position of the control point group is adjusted in real time based on the deformation optimization target area and the recommended value obtained by the total function (deformation algorithm), and the deformation operation is performed by manually dragging the position of the control point group, or the deformation result of the CAD model is controlled by inputting the displacement size of the control point group in different directions, or the software module encapsulates and calculates the spline basis function values ​​corresponding to each control point group and the adjustment method determined based on the recommended value, and the software module realizes continuous deformation.

[0016] Preferably, the surface curvature of the CAD candidate model is determined, and if the surface curvature of the CAD candidate model meets a predetermined value or a predetermined range, it is judged to be smooth or as expected; alternatively, the surface curvature of the deformed model is calculated based on the CAD candidate model, and the difference is calculated from the surface curvature of the CAD model before deformation determined in step S2 or step S3, and if the difference is less than a preset threshold and the CAD candidate model is smoother than the CAD model, it is judged to be smooth.

[0017] The present invention provides an analysis system for optimizing geometric free deformation of a movable body, comprising:

[0018] Initialization module: configured to obtain a CAD model file of a movable body, wherein the CAD model corresponding to the CAD model file is a model to be deformed; convert the CAD model file into a CAD model, and determine the boundary of the CAD model;

[0019] A control domain definition module: configured to define a control domain in the three-dimensional space corresponding to the CAD model, wherein the control domain is a deformation region that is determined based on the boundary of the CAD model and can cover the deformation optimization target region of the CAD model;

[0020] Selection module: configured to select spline basis functions based on the control domain and engineering requirements to construct a total function; select control points as optimization design variables from the control domain to form a control point set to be deformed, select multiple control points from the control point set to be deformed as a control point group; determine the total function value corresponding to the control point group based on the three-dimensional coordinates corresponding to the control point group;

[0021] Transformation module: configured to adjust the three-dimensional coordinates of the control point group based on the total function value corresponding to the control point group, perform a deformation operation on the deformation optimization target area, and obtain a candidate optimization area after deformation, wherein the deformation optimization target area is divided into a plurality of sub-areas based on the adjusted three-dimensional coordinates of the control point group, and the deformation operation includes: freezing the points in the sub-area set to the freezing mode to keep them unchanged, and performing a deformation operation on the sub-area in the non-freezing mode, wherein at least four control points in the same plane are selected from the control point group to form a polygon, and the plane corresponding to the polygon is used as a blocking plane, and the influence order is defined for the deformation blocking plane in such a way that the deformation effect of the deformation operation on one side of the deformation blocking plane on the other side of the deformation blocking plane is reduced by a predetermined degree, and the candidate optimization area is composed of all the sub-areas after the deformation operation;

[0022] A first verification module: configured to generate a CAD candidate model corresponding to the candidate optimization area, and determine whether the surface quality of the CAD candidate model is smooth or meets expectations. If the determination is yes, the second verification module is triggered; otherwise, the selection module is triggered;

[0023] The second verification module is configured to perform CAE simulation analysis on the CAD candidate model, calculate the fluid mechanics parameters of the CAD candidate model, and determine whether the CAD candidate model meets the preset requirements based on the CAE simulation analysis results and the fluid mechanics parameters. If yes, the CAD candidate model is used as a deformed CAD model to trigger the output module; otherwise, the transformation module is triggered;

[0024] Output module: configured to export the deformed CAD model as a deformed CAD model file.

[0025] In the above method embodiments of the present invention, a computer-readable storage medium is provided, wherein a plurality of instructions are stored in the storage medium, and the plurality of instructions are used for a processor to load and execute the above method.

[0026] In the above-mentioned method embodiments of the present invention, an electronic device includes: a processor for executing multiple instructions; a memory for storing multiple instructions; wherein the multiple instructions are used to be stored by the memory, and loaded by the processor to execute the method as described above.

[0027] In the above-mentioned method embodiments of the present invention, a computer program product is provided, including a computer program, and the computer program implements the above-mentioned method when executed by a processor.

[0028] Thus, the present invention discloses an analysis method and system for geometric free deformation optimization of movable bodies, wherein the method includes: determining the boundary of the CAD model; defining the deformation area in the three-dimensional space corresponding to the CAD model, and selecting a number of control points; selecting spline basis functions based on the polyhedron to be deformed and engineering requirements, and constructing a total function; determining the total function value corresponding to each control point based on the three-dimensional coordinates corresponding to each control point; adjusting the three-dimensional coordinates of the control points, and automatically deforming the geometry within the deformation area based on the adjusted three-dimensional coordinates of the control points; wherein a frozen part and a deformation blocking plane can be set in the deformation area to achieve flexible deformation; calculating and verifying the geometric surface curvature of the deformed polyhedron, and obtaining the deformed CAD model after verification. The present invention ensures that the deformed geometry is robust and reliable in design, and can be coupled with the simulation optimization process to provide an automatic geometric free deformation optimization tool to meet the engineering simulation optimization needs of complex shapes.

[0029] The present invention has the following advantages: The present invention is a geometric free deformation method and program, which has:

[0030] 1) Enhanced versatility and flexibility: This method or system provides a highly versatile FFD framework, which supports Bernstein basis functions, B-Spline basis functions, NURBS (Non-Uniform Rational B-Splines) basis functions, RBF (Radial Basis Function) basis functions, Gaussian Spline basis functions, and IMQBS (InverseMulti Quadratic Biharmonic Spline) basis functions as geometric deformation strategies implemented by spline basis functions. It exhibits excellent adaptability, can seamlessly connect and optimize the shape deformation requirements of various engineering models, and can read and operate most engineering model file formats on the market. In addition, this system introduces a highly customizable control point grid generation mechanism. This innovative design gives users a certain degree of freedom when generating control point grids, allowing them to flexibly select and fine-tune the parameters of the control point layout deformation algorithm based on specific application scenarios, thereby ensuring that the deformation process is both accurate and efficient.

[0031] 2) Excellent high precision and stability: This method or system not only integrates a variety of auxiliary functions, but also designs a variety of rigorously verified stable deformation algorithms to ensure excellent performance in complex and changing operating environments. After completing the deformation operation, the system can automatically generate a detailed and accurate deformation result report, which intuitively displays the deformation effect through quantitative data indicators, providing users with a strong basis for accurately judging whether the deformation of the model accurately meets the preset expectations and standards.

[0032] 3) Instant interaction and real-time adjustment: This method or system implements the instant adjustment function of control points, giving users a real-time shape deformation and optimization experience. Through an intuitive and efficient user interface design, users can instantly view and directly operate each control point to dynamically adjust and optimize the shape of the geometrically specified area. The smoothness and immediacy of this human-computer interaction allows users to instantly observe every subtle change in the deformation effect and make precise adjustments accordingly. Through the combined development of functions, local geometric positioning is accurate and global deformation speed is fast, so the real-time performance is better, which greatly improves work efficiency.

[0033] 4) Interdisciplinary integration and optimization: This system innovatively integrates FFD technology with cutting-edge engineering simulation technologies such as multidisciplinary simulation design optimization (MDO), finite element analysis (FEA), computational fluid dynamics (CFD), etc., to build a comprehensive solution. This integration not only expands the application boundaries of FFD technology, but also ensures that the deformed structure is still robust and reliable in mechanical properties. At the same time, the fluid mechanics characteristics can also accurately meet the complex and changing engineering needs, providing a guarantee for the successful implementation of the project.

[0034] 5) Support uploading, reading, parsing and exporting various mainstream geometric file types on the market.

[0035] Through the above technical effects, the present invention not only improves the overall performance of model optimization design, but also brings innovation and breakthroughs to the field of model optimization, and has important practical application value and market potential.

[0036] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The above and other purposes, features and advantages of the present invention will become more apparent by describing the embodiments of the present invention in more detail in conjunction with the accompanying drawings. The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0038] Figure 1 It is a schematic flow chart of the analysis method for optimizing geometric free deformation of a movable body according to the present invention;

[0039] Figure 2 Calculate the distribution map for the Gaussian curvature of the deformed ship model;

[0040] Figure 3 It is a schematic diagram of the deformation process of the fixed-wing aircraft model;

[0041] Figure 4 The geometric comparison of the fixed-wing aircraft model before and after deformation is schematically shown, wherein (A) corresponds to before deformation and (B) corresponds to after deformation;

[0042] Figure 5 It is a schematic diagram of the deformation process of the vehicle exhaust device model;

[0043] Figure 6 The geometric comparison of the vehicle exhaust device model before and after deformation is schematically shown, wherein (C) corresponds to before deformation and (D) corresponds to after deformation;

[0044] Figure 7 Schematic diagram of the automatic optimization deformation process of the ship model;

[0045] Figure 8 An example of a definition of a deformation region of a ship model is schematically shown;

[0046] Fig. 9 The total resistance distribution of different schemes in the process of optimizing the bulbous bow of the ship is schematically shown;

[0047] Fig.10 The schematic diagram shows the comparison between the original design of the bulbous bow shape of the hull and the two optimized designs, where (E) corresponds to the zx dimension and (F) corresponds to the yz dimension;

[0048] Fig.11 The comparison between the original design and the optimized design of the hull is schematically shown, wherein (G) is a wave-making cloud diagram corresponding to the comparison between the best optimized solution 1 and the original design, (H) is a wave-making cloud diagram corresponding to the comparison between the best optimized solution 2 and the original design, and (I) is a wave difference diagram;

[0049] Fig.12 It is a schematic diagram of the structure of the analysis system for optimizing the geometric free deformation of a movable body according to the present invention;

[0050] Fig.13 Schematic diagram of the structure of an electronic device optimized for geometric free deformation according to the present invention. DETAILED DESCRIPTION

[0051] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein. It should be noted that unless otherwise specifically stated, the relative arrangement of the components and steps, the numerical expressions and the numerical values ​​described in these embodiments do not limit the scope of the present invention. It can be understood by those skilled in the art that the terms "first", "second", S1, S2, etc. in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor represent the necessary logical order between them. It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more. It should also be understood that for any component, data or structure mentioned in the embodiments of the present invention, in the absence of explicit limitation or contrary revelation given in the context, it can generally be understood as one or more. In addition, the term "and / or" in the present invention is only a kind of association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the objects associated with each other are in an "or" relationship. It should also be understood that the description of each embodiment of the present invention emphasizes the differences between the embodiments, and the same or similar aspects can be referred to each other. For the sake of brevity, they will not be described one by one. At the same time, it should be understood that for the convenience of description, the dimensions of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The following description of at least one exemplary embodiment is actually only illustrative and is by no means a limitation on the present invention and its application or use. The techniques, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and equipment should be considered as part of the specification. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0052] The analysis method and system for geometric free deformation optimization of movable bodies provided by the present invention relate to the fields of industrial product design, multidisciplinary simulation design optimization (MDO), industrial software simulation (including finite element analysis (FEA), computational fluid dynamics (CFD) and the like), and particularly to intelligent analysis methods and systems for free deformation of complex geometric surface configurations. The method and system, combined with industrial software simulation, can realize the intelligent optimization design method of complex industrial products, and are particularly suitable for the shape deformation of engineering geometric models of movable bodies such as trains, vehicles, ships, containers, aircraft and robots, and are also suitable for fixed bodies installed in a fluid environment, such as fluid machinery. Due to the relative motion relationship between the fixed body and the fluid interacting with it, it is also regarded as a movable body here.

[0053] Exemplary Methods

[0054] Figure 1 FIG. 1 is a flow chart of an analysis method for optimizing geometric free deformation of a movable body provided by an exemplary embodiment of the present invention. Figure 1 As shown, the following steps are included:

[0055] Step S1: obtaining a CAD model file of a movable body, wherein the CAD model corresponding to the CAD model file is a model to be deformed; converting the CAD model file into a CAD model, and determining a boundary of the CAD model;

[0056] Step S2: defining a control domain in the three-dimensional space corresponding to the CAD model, wherein the control domain is a deformation region that is determined based on the boundary of the CAD model and can cover the deformation optimization target region of the CAD model;

[0057] Step S3: Selecting spline basis functions based on the control domain and engineering requirements to construct a total function; selecting control points as optimization design variables from the control domain to form a control point set to be deformed, and selecting multiple control points from the control point set to be deformed to be recorded as a control point group; determining the total function value corresponding to the control point group based on the three-dimensional coordinates corresponding to the control point group;

[0058] Step S4: Based on the total function value corresponding to the control point group, the three-dimensional coordinates of the control point group are adjusted, and a deformation operation is performed on the deformation optimization target area to obtain a candidate optimization area after deformation, wherein the deformation optimization target area is divided into a plurality of sub-areas, and the deformation operation includes: freezing the points in the sub-area set to the freezing mode so as not to be deformed, and performing a deformation operation on the sub-area in the non-freezing mode, wherein at least four control points in the same plane are selected from the control point group to form a polygon, and the plane corresponding to the polygon is used as a blocking plane, and the influence order is defined for the deformation blocking plane in such a way that the deformation effect of the deformation operation on one side of the deformation blocking plane on the other side of the deformation blocking plane is reduced by a predetermined degree, and the candidate optimization area is composed of all the sub-areas after the deformation operation;

[0059] Step S5: Generate a CAD candidate model corresponding to the candidate optimization area, and determine whether the surface quality of the CAD candidate model is smooth or meets expectations. If it is determined to be yes, proceed to step S6; otherwise, proceed to step S3;

[0060] Step S6: Perform CAE (Computer Aided Engineering) simulation analysis on the CAD candidate model, calculate the fluid mechanics parameters of the CAD candidate model, and determine whether the CAD candidate model meets the preset requirements based on the CAE simulation analysis results and the fluid mechanics parameters. If yes, use the CAD candidate model as the deformed CAD model and proceed to step S7; otherwise, proceed to step S4;

[0061] Step S7: exporting the deformed CAD model as a deformed CAD model file.

[0062] The present invention ensures that the deformed geometry is robust and reliable in design, and can be coupled with the simulation optimization process to provide an automatic geometric free deformation optimization tool to meet the engineering simulation optimization needs of complex shapes.

[0063] This method supports visual viewing of deformation process parameters, and the computer implementation language is C / C++.

[0064] The specific implementation of this method is described in more detail below.

[0065] In the step S1, the movable object may be a vehicle, a ship, or the like.

[0066] The CAD model file may be in a variety of formats. For example, the CAD model of the movable body may be imported and stored in common CAD model formats such as obj\igs\STL, as shown in Table 1 below.

[0067] Table 1: File types supported for reading

[0068]

[0069] The present invention develops a module that supports automatic recognition of the boundary size of a CAD model, thereby creating a three-dimensional space area corresponding to the CAD model.

[0070] In step S2, a control domain is defined in the three-dimensional space corresponding to the CAD model as a deformation region, that is, a geometric part to be deformed covering the movable body is determined based on the boundary of the CAD model (for example, see Figure 6 Preferably, the deformation optimization target area is a geometric part of the movable body, such as the leading edge, middle section and trailing edge of the wing in the first embodiment described later, the middle part of the exhaust duct in the second embodiment, and the bulbous bow of the KCS ship model in the third embodiment, but it is not limited thereto and may also be a geometric whole.

[0071] In step S3, a spline basis function is selected based on the control domain and engineering requirements, and a suitable FFD deformation algorithm can be selected to construct a total function by selecting different spline basis functions. Then, control points used as design variables in the optimization process are selected in the control domain to form a set of control points to be deformed. Sufficient control points can be generated in the control domain as needed. These control points can be embodied as grid points in the control domain (for example, see Figure 6 black dots in the green grid).

[0072] Based on the CAD model imported in step S1 and the control domain defined in step S2, this step S3 can automatically determine the appropriate control point grid size and density, and also allow the user to manually adjust the position and number of control points. For example, the number of control points in the x, y, and z directions can be input and adjusted on the FFD interactive interface. The generation of control points needs to wrap the deformation optimization target area of ​​the CAD model as much as possible (for example, see the following Figure 8 The number of control points is determined according to the required deformation accuracy, so as to generate enough control points in the control domain to ensure the deformation accuracy. For example, the selection of control points may depend on the deformation optimization target area in the control domain. Generally, control points near the deformation optimization target area (i.e., surrounding or adjacent areas) are selected for operation. Control points can be selected in a variety of ways. You can select the required control points by clicking the mouse, or you can select any control point in the control domain grid in the form of a dialog box.

[0073] In this embodiment, a plurality of control points are selected from all control points in the control point set to be deformed to form a control point group, so as to specify and optimize the deformation optimization target area.

[0074] In this embodiment, the step S3 may determine the total function value corresponding to each control point group based on the three-dimensional coordinates corresponding to each control point group, and the total function is:

[0075] (Formula 1)

[0076] Among them, P i,j,k are the three-dimensional coordinates corresponding to the control points in the control point group, i, j, k are the coordinates of the control points in the control point group on the x-axis, y-axis, and z-axis respectively; q, r, s are the maximum number of control points in the x-axis, y-axis, and z-axis directions respectively, u, v, and w are the influence parameters on the x-axis, y-axis, and z-axis respectively, and N i,p (u) is the spline basis function selected for parameter u, N j,m (v) is the spline basis function selected for parameter v, N k,n (w) is the spline basis function selected for parameter w, W i,j,k is the weight, and P'(u, v, w) is the total function value.

[0077] Furthermore, N i,p (u), N j,m (v) N k,n (w) can be different types of spline basis functions.

[0078] Spline basis function N i,p (u), N j,m (v) N k,n (w) It is possible to determine the degree of influence of each control point on the resulting surface at a given parameter position.

[0079] Weight W i,j,k Affects the contribution of control points to the final position. This allows non-uniform scaling and control of the shape of the surface.

[0080] The triple sum aggregates the contributions of all relevant control points based on their corresponding basis functions and weights.

[0081] In step S3, the spline basis function includes but is not limited to a B-spline basis function, a Gaussian spline function, a multi-quadratic biharmonic spline function, an inverse multi-quadratic biharmonic spline function, and a Bernstein function.

[0082] In this embodiment, the supported deformation spline basis functions include B-spline basis functions, Gaussian spline functions, multi-quadratic biharmonic spline functions, inverse multi-quadratic biharmonic spline functions, and Bernstein functions. The present disclosure also supports the expansion of other types of basis functions.

[0083] B-spline basis function N of degree b a,b (t) is defined recursively:

[0084] When the degree b of the B-spline is 0 (constant):

[0085]

[0086] When the degree of B-spline hour:

[0087]

[0088] Among them, N a,b (t) is a combination of two low-order basis functions, ensuring smoothness at the nodes.

[0089] The Gaussian Spline Function is a radial basis function that is often used for smooth interpolation and approximation problems. It takes the maximum value at the center and decreases rapidly as the distance increases. Its equation is expressed as follows:

[0090]

[0091] where w q is the weight, μ q is the center of the Gaussian function, and σ controls the width of the Gaussian function. Then the basis function of the Gaussian spline function can be expressed as: q (t)=G(tc q ), where c q Represents the coordinates of the control point.

[0092] The Multiquadric Thin Plate Spline is a radial basis function that is suitable for multidimensional interpolation and approximation problems. It reaches its minimum value when the distance from the center point is zero and gradually increases as the distance increases. This spline uses multiple quadratic functions to create smooth surfaces. The multiquadric function is defined as:

[0093]

[0094] Where r is the distance from the control point and c is the shape parameter. The basis function of the multi-quadratic biharmonic spline function can be defined as:

[0095]

[0096] Among them, w q is the weight, (x q ,y q ,z q ) is the control point, P(x q ,y q ,z q) is a polynomial function (usually a low-degree polynomial such as a linear or quadratic function) that is used to enhance the smoothness of the surface.

[0097] Inverse Multiquadric Thin Plate Spline is a radial basis function used for multidimensional interpolation and approximation problems. It reaches its maximum value when the distance from the center point is zero and gradually decreases as the distance increases. Its equation is expressed as follows:

[0098]

[0099] The expression of its basis function is the same as that of the multi-quadratic biharmonic spline function.

[0100] The Bernstein Function is defined as:

[0101]

[0102] where p g represents the control point, represents the binomial coefficient. Then the basis function of the Bernstein function can be expressed as:

[0103]

[0104] Among them B h,n (t) is the h-th order Bernstein basis function of degree n.

[0105] In this embodiment, step S4 supports two deformation modes. Mode 1 is manual deformation, that is, based on the deformation optimization target area and the recommended value obtained by the deformation algorithm, the user can adjust the position of the control point group in real time, that is, the user can manually drag the position of the control point group to perform deformation operation (adjacent control points in the control point group can be deformed in a linked manner). For example, the control point group can be operated by dragging the mouse to move it to the expected position, and then the displacement of the adjacent grid points can be calculated according to the displacement of each control point in the control point group, and the adjacent grid points are displaced in a linked manner accordingly, so as to realize continuous deformation including the controlled points. It is also possible to accurately control the deformation result of the model by inputting the displacement size of the control point group in different directions. Mode 2 is automatic deformation, that is, the software module encapsulates the calculation of the spline basis function values ​​corresponding to each control point group and the adjustment method determined based on the recommended value, and the software module realizes continuous deformation. For example, the control point group can be operated by reading a file.

[0106] Optionally, in step S4, the deformation operation includes: freezing the points in the sub-area set to the freeze mode so as to remain unchanged, and performing the deformation operation on the sub-area in the non-freeze mode, which also includes the case where all sub-areas are actually in the non-freeze mode, that is, the number of sub-areas set to the freeze mode is zero. Thus, a geometric freezing function is provided: in the deformation area, this function allows the user to select and freeze certain areas of the model so that they will not be changed or deformed in subsequent operations. For example, a set of points can be frozen in the form of a cuboid or a sphere, that is, (1) the cuboid freezing mode defines the size of the cuboid by entering the length, width, and height, and supports selecting and moving the cuboid in the view to freeze the points therein, and (2) the sphere freezing mode defines the size of the sphere by entering the radius, and supports selecting and moving the sphere in the view to freeze the points therein.

[0107] Optionally, in step S4, a method of deforming a barrier plane is also provided. This function allows the user to select a plane by selecting some control points, mark the plane as a deformed barrier plane, and define an "influence order" for the deformed barrier plane. Defining a deformed barrier plane requires at least four control points, and these control points are required to be on the same plane, otherwise the definition fails. The deformation operation on one side of the deformed barrier plane will reduce the deformation effect on the other side of the deformed barrier plane to a certain extent. The degree depends on the definition of the "influence order". The larger the "influence order", the stronger the deformation barrier effect.

[0108] Optionally, in step S5, a CAD candidate model corresponding to the candidate optimization area is generated, and it is determined whether the surface quality of the CAD candidate model is smooth or meets expectations. A preset reasonable threshold value can be used to determine the surface quality of the deformed model, including whether it is smooth or meets expectations. For example, the surface curvature of the CAD candidate model is determined. If the surface curvature of the CAD candidate model meets a predetermined value or is within a predetermined range, it can be determined to be smooth or meet expectations, and the process proceeds to step S6. Here, meeting expectations, for example, means being within a predetermined range. Alternatively, the surface curvature of the deformed model can be calculated based on the CAD candidate model, and the difference can be obtained from the surface curvature of the CAD model before deformation, which is optionally determined in step S2 or step S3. If the difference is less than a preset threshold value, and the CAD candidate model is smoother than the CAD model, it is determined to be smooth. If the deformed model is distorted or the deformation algorithm cannot meet the engineering requirements, an error prompt will be provided, suggesting that the user proceed to step S3.

[0109] Optionally, the surface curvature is Gaussian curvature. Figure 2 As shown, the calculation method of Gaussian curvature is:

[0110] Suppose you need to calculate the Gaussian curvature of a given point p(x, y, z) on the model surface. You need to first represent the surface using a parametric coordinate system:

[0111] z=f(x, y)

[0112] Then calculate the first-order partial derivative at this point:

[0113] ,

[0114] And the second-order partial derivatives:

[0115] , ,

[0116] Then we can get the Gaussian curvature K of the point:

[0117]

[0118] Figure 2 The calculated distribution of Gaussian curvature using a ship model as an example is shown.

[0119] In step S6, CAE simulation analysis is performed on the candidate model, and the fluid mechanics parameters of the CAD candidate model are calculated. Based on the CAE simulation analysis results and the fluid mechanics parameters, it is determined whether the CAD candidate model meets the preset requirements. For example, the preset requirement is that the hydrostatic resistance of the ship is less than a certain threshold. If it meets the requirement, the CAD candidate model is used as the deformed CAD model and the process proceeds to step S7; otherwise, the process proceeds to step S4.

[0120] Optionally, when determining whether the CAD candidate model meets preset requirements based on CAE simulation analysis results and fluid mechanics parameters, if it does not meet the requirements, step S2 or step S3 may also be entered.

[0121] That is, the CAD candidate model is subjected to CAE simulation analysis, and the fluid mechanics parameters of the CAD candidate model are calculated. Based on the CAE simulation analysis results and the fluid mechanics parameters, it is determined whether the CAD candidate model meets the preset requirements. If so, the CAD candidate model is used as the deformed CAD model and the process proceeds to step S7; otherwise, the process proceeds to step S2.

[0122] Or perform CAE simulation analysis on the CAD candidate model, calculate the fluid mechanics parameters of the CAD candidate model, and determine whether the CAD candidate model meets the preset requirements based on the CAE simulation analysis results and the fluid mechanics parameters. If yes, use the CAD candidate model as the deformed CAD model and enter step S7; otherwise, enter step S3.

[0123] The purpose of returning to step S2 is to regenerate a suitable control domain. If the control domain meets the requirements, return to step S3 to select control points and corresponding deformation algorithms. If the control domain and control point selection do not need to be changed, return to step S4 to perform FFD deformation again.

[0124] In the step S7, the deformed CAD model is exported as a deformed CAD model file, and multiple CAD model formats are supported for export, as shown in Table 2 below.

[0125] In this embodiment, each CAD candidate model in the process of deformation of the CAD model is stored and displayed to the user.

[0126] Table 2 Supported export file types

[0127]

[0128] The present invention is described in more detail below using three geometrically modified embodiments.

[0129] Example 1: Local leading edge deformation of a fixed-wing aircraft wing

[0130] The goal of this embodiment is to improve fuel efficiency or gliding performance and improve flight stability, especially for low-speed flight. Lengthening the wing can increase the aspect ratio (the ratio of wingspan to chord length), thereby reducing induced drag and improving lift-to-drag ratio, which is particularly important for long-range aircraft or high-altitude aircraft; in addition, a longer wingspan can improve lateral stability, making the aircraft fly more smoothly.

[0131] Figure 3 A partial operation flow chart of the deformation process of this embodiment is shown (the description of other steps such as steps S1, S2, S6, etc. is omitted), and the detailed deformation operation steps are as follows:

[0132] i. Load the model (corresponding to Figure 1 Step S1 in (a);

[0133] ii. The system will automatically read the 3D size of the model and generate an appropriate control point grid for the model based on the 3D size. In this embodiment, the number of control points in each coordinate direction is manually entered, that is, a 10×4×4 grid surrounds the entire model (corresponding to Figure 1 Steps S2 and S3 in (a);

[0134] iii. Define the deformation area and select the control points around the target deformation area. In this example, some control points are selected in the form of a face near the leading edge, middle section, and trailing edge of the wing. Specific operation: selected→face Select the control points in the form of a face (corresponding to Figure 1Step S3 in (a);

[0135] face1: xmin=4; xmax=6; ymin=ymax=0; zmin=2; zmax=3; (the relative coordinates of the selected control points in the x direction are 4 to 6, the relative coordinates in the y direction are 0, and the relative coordinates in the z direction are 2 to 3);

[0136] face2: xmin=4; xmax=6; ymin=ymax=1; zmin=2; zmax=3; (the relative coordinates of the selected control points in the x direction are 4 to 6, the relative coordinates in the y direction are 1, and the relative coordinates in the z direction are 2 to 3);

[0137] face3: xmin=4; xmax=6; ymin=ymax=2; zmin=2; zmax=3; (the relative coordinates of the selected control points in the x direction are 4 to 6, the relative coordinates in the y direction are 2, and the relative coordinates in the z direction are 2 to 3);

[0138] iv. Define the control points as deformation barrier planes respectively. The "influence degree" of the deformation barrier plane increases in the order of leading edge, middle section and trailing edge. That is, the deformation operation on the leading edge of the wing will reduce the deformation effect on the middle section and trailing edge. Specific operation: Set face1: degree=1; face2: degree=2; face3: degree=3 (corresponding to Figure 3 Step S4 in (a);

[0139] v. Move the control points appropriately and complete the corresponding deformation operations. Specific operations: Set face1:dy=-40; (indicates a displacement of 40 absolute units in the negative y direction); face2:dy=-40; (indicates a displacement of 40 absolute units in the negative y direction); face3:dy=-40; (indicates a displacement of 40 absolute units in the negative y direction) (corresponding to Figure 3 , step S4 in the above process).

[0140] Figure 4 The geometric model and control point information of this embodiment before and after deformation are displayed.

[0141] Example 2: Deformation of vehicle exhaust device

[0142] In vehicle exhaust systems, back pressure reduces efficiency, and the goal of this embodiment is to reduce the back pressure effect. Reducing the back pressure effect under the given geometry of the end capillary requires design considerations to expand the geometry of the middle section, which can help the gas expand and flow more freely, reducing resistance in the exhaust passage, and helping to improve the performance of the engine or high-flow system. The deformation goal of this embodiment is to collectively deform the exhaust duct in the middle without affecting the end capillary.

[0143] Figure 5 A partial flow chart of the deformation operation of this embodiment is shown (similar to the first embodiment, the description of some steps is omitted), and the detailed deformation operation steps are as follows:

[0144] i. Load the model;

[0145] ii. After loading the model, the system will automatically read the 3D size of the model. Based on the 3D size, with the zero point as the coordinate origin, an appropriate control point grid is generated for the model. In this embodiment, the number of control points in each coordinate direction is manually entered, that is, a 30×4×4 grid surrounds the entire model;

[0146] iii. Select the part that does not need to be deformed, in this embodiment Figure 6 The red pipe part is shown in the figure. Freeze the selected geometric parts, and the frozen geometric parts will not participate in the subsequent deformation operations. Specific operation: Call Frozen Function to select the freezing function; select the Cube option, which means generating a frozen geometric cuboid: length 1000; width 70; height 75 (the red area is the frozen area).

[0147] iv. Define the deformation area, select the control points around the target deformation area, in this example, some control points around the blue part. Specific operation: selected→face Select the control points in the form of a face; enter the relative coordinates of the control points in each coordinate direction:

[0148] face1: xmin=12; xmax=16; ymin=ymax=4; zmin=0; zmax=2 (the relative coordinates of the selected control points in the x direction are 12 to 16, the relative coordinates in the y direction are 4, and the relative coordinates in the z direction are 0 to 2);

[0149] face2: xmin=12; xmax=16; ymin=ymax=2; zmin=0; zmax=2 (the relative coordinates of the selected control points in the x direction are 12 to 16, the relative coordinates in the y direction are 2, and the relative coordinates in the z direction are 0 to 2);

[0150] v. Move the control points appropriately to complete the corresponding deformation operation. Specific operation: face1: input dy=50 (indicates a displacement of 50 absolute units in the positive y direction); face2: dy=-50 (indicates a displacement of 50 absolute units in the negative y direction).

[0151] Figure 6 The geometric model and control point information of this embodiment before and after deformation are displayed.

[0152] Example 3: Simulation-driven automatic optimization of bow deformation

[0153] Figure 7 The flowchart of this embodiment is shown as a variation. On the basis of the FFD geometric deformation module used to realize the free deformation of the above embodiment, an optimization algorithm module and a CFD numerical simulation module are additionally called. Therefore, this embodiment includes three modules:

[0154] Optimization algorithm module: This embodiment adopts the particle swarm optimization algorithm (PSO) to drive the optimization process. The minimum still water resistance of the ship model is used as the optimization objective function. The gap between the resistance and the objective function is calculated through the CFD numerical simulation module. Based on this, the optimization algorithm generates the FFD deformation value of each iteration as the design variable and gives it to the FFD geometric deformation and reconstruction module (corresponding to the aforementioned steps S2-S4).

[0155] FFD geometry deformation and reconstruction module: responsible for parameterization and free deformation of the input model. This module accepts the design variables of the optimization algorithm module, that is, the position of the control points to control the shape of the model. The deformed geometry is passed to the CFD numerical simulation module as input for simulation (corresponding to the above steps S2-S4).

[0156] CFD numerical simulation module: This module is responsible for numerical simulation and evaluation of hydrostatic resistance of the deformed geometric model; this module mainly includes the steps of model import, meshing, simulation setting, CFD post-processing and result export. The output CFD results are compared with the objective function to evaluate whether they meet the established hydrodynamic performance requirements (corresponding to the aforementioned steps S5-S7).

[0157] This embodiment applies the present invention to a KCS ship model to optimize the line shape of its bulbous bow. The deformation area is defined as follows: Figure 8 shown. Fig. 9 The linear deformation of the bulbous bow and all the calculation results of the optimization process are shown. The horizontal axis is the movement position of the control point in the x direction (Delta xl), and the vertical axis is the resistance value of the ship (Drag). The lowest point of the resistance value in the positive and negative directions of x is selected as the optimal case. Fig.10The bulbous bow shapes of the original design and two optimized designs are compared in Figure 2. Fig.11 The comparison of the wave cloud diagram between the optimized design and the original design is shown. The left and right sides are the comparison between the best optimized solutions 1 and 2 and the original design. Fig.11 (G) and (H), the upper part is the wave-making cloud diagram of the original design, and the lower part is the wave-making cloud diagram after the optimized design. Fig.11 The optimal case 1 (OptimalCase1) performs better in reducing the total drag coefficient, achieving a 1.53% reduction, while the reference Fig.11 The optimal case 2 (H) was reduced by 1.04%.

[0158] Optimal Case 1 has advantages in improving navigation efficiency and reducing the volume of the ship, while Optimal Case 2 increases the volume of the ship and also has certain advantages in capacity. Both options are available for designers to make decisions.

[0159] Exemplary Systems

[0160] Fig.12 FIG. 1 is a schematic diagram of a structure of an analysis system for optimizing geometric free deformation of a movable body provided by an exemplary embodiment of the present invention. Fig.12 As shown, this embodiment includes:

[0161] Initialization module: configured to obtain a CAD model file of a movable body, wherein the CAD model corresponding to the CAD model file is a model to be deformed; convert the CAD model file into a CAD model, and determine the boundary of the CAD model;

[0162] A control domain definition module: configured to define a control domain in the three-dimensional space corresponding to the CAD model, wherein the control domain is a deformation region that is determined based on the boundary of the CAD model and can cover the deformation optimization target region of the CAD model;

[0163] Selection module: configured to select spline basis functions based on the control domain and engineering requirements to construct a total function; select control points as optimization design variables from the control domain to form a control point set to be deformed, select multiple control points from the control point set to be deformed as a control point group; determine the total function value corresponding to the control point group based on the three-dimensional coordinates corresponding to the control point group;

[0164] Transformation module: configured to adjust the three-dimensional coordinates of the control point group based on the total function value corresponding to the control point group, perform a deformation operation on the deformation optimization target area, and obtain a candidate optimization area after deformation, wherein the deformation optimization target area is divided into a plurality of sub-areas based on the adjusted three-dimensional coordinates of the control point group, and the deformation operation includes: freezing the points in the sub-area set to the freezing mode to keep them unchanged, and performing a deformation operation on the sub-area in the non-freezing mode, wherein at least four control points in the same plane are selected from the control point group to form a polygon, and the plane corresponding to the polygon is used as a blocking plane, and the influence order is defined for the deformation blocking plane in such a way that the deformation effect of the deformation operation on one side of the deformation blocking plane on the other side of the deformation blocking plane is reduced by a predetermined degree, and the candidate optimization area is composed of all the sub-areas after the deformation operation;

[0165] A first verification module: configured to generate a CAD candidate model corresponding to the candidate optimization area, and determine whether the surface quality of the CAD candidate model is smooth or meets expectations. If the determination is yes, the second verification module is triggered; otherwise, the selection module is triggered;

[0166] The second verification module is configured to perform CAE simulation analysis on the CAD candidate model, calculate the fluid mechanics parameters of the CAD candidate model, and determine whether the CAD candidate model meets the preset requirements based on the CAE simulation analysis results and the fluid mechanics parameters. If yes, the CAD candidate model is used as a deformed CAD model to trigger the output module; otherwise, the transformation module is triggered;

[0167] Output module: configured to export the deformed CAD model as a deformed CAD model file.

[0168] Exemplary Electronic Devices

[0169] Fig.13 This is the structure of the electronic device 130 provided by an exemplary embodiment of the present invention. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the collected input signals from them. Fig.13 FIG. 1 is a block diagram of an electronic device according to an embodiment of the present disclosure. Fig.13 As shown, the electronic device includes one or more processors 131 and a memory 132 .

[0170] The processor 131 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0171] The memory 132 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 131 may run the program instructions to implement the methods of the software programs of the various embodiments of the present disclosure described above and / or other desired functions. In one example, the electronic device may also include: an input device 133 and an output device 134, which are interconnected through a bus system and / or other forms of connection mechanisms (not shown). In addition, the input device 133 may also include, for example, a keyboard, a mouse, etc. The output device 134 may output various information to the outside. The output device 134 may include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, etc.

[0172] Of course, to simplify, Fig.13 Only some of the components related to the present disclosure in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device may further include any other appropriate components.

[0173] Exemplary computer program products and computer-readable storage media

[0174] In addition to the above-mentioned methods and devices, an embodiment of the present disclosure may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present disclosure described in the above-mentioned "Exemplary Method" section of this specification.

[0175] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the disclosed embodiments, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0176] In addition, an embodiment of the present disclosure may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present disclosure described in the above “Exemplary Method” section of this specification.

[0177] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0178] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to the necessity of adopting the above specific details to be implemented.

[0179] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0180] The block diagrams of the devices, apparatuses, equipment, and systems involved in this disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including," "comprising," "having," and the like are open words, referring to "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or," and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0181] The method and system of the present disclosure may be implemented in many ways. For example, the method and system of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present disclosure may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present disclosure. Therefore, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

[0182] It should also be noted that in the system, device and method of the present disclosure, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present disclosure. The above description of the disclosed aspects is provided to enable any technician in the field to make or use the present disclosure. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown here, but to the widest scope consistent with the principles and novel features disclosed herein.

[0183] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. An analytical method for optimizing geometric free deformation of a movable body, characterized in that: The method comprises the following steps: Step S1: obtaining a CAD model file of a movable body, wherein the CAD model corresponding to the CAD model file is a model to be deformed; converting the CAD model file into a CAD model, and determining a boundary of the CAD model; Step S2: defining a control domain in the three-dimensional space corresponding to the CAD model, wherein the control domain is a deformation region that is determined based on the boundary of the CAD model and can cover the deformation optimization target region of the CAD model; Step S3: Selecting spline basis functions based on the control domain and engineering requirements to construct a total function; selecting control points as optimization design variables from the control domain to form a control point set to be deformed, and selecting multiple control points from the control point set to be deformed to be recorded as a control point group; Determine the total function value corresponding to the control point group based on the three-dimensional coordinates corresponding to the control point group; Step S4: Based on the total function value corresponding to the control point group, the three-dimensional coordinates of the control point group are adjusted, and a deformation operation is performed on the deformation optimization target area to obtain a candidate optimization area after deformation, wherein the deformation optimization target area is divided into a plurality of sub-areas, and the deformation operation includes: freezing the points in the sub-area set to the freezing mode to keep them unchanged, and performing a deformation operation on the sub-area in the non-freezing mode, wherein at least four control points in the same plane are selected from the control point group to form a polygon, and the plane corresponding to the polygon is used as a blocking plane, and the influence order is defined for the deformation blocking plane in such a way that the deformation effect of the deformation operation on one side of the deformation blocking plane on the other side of the deformation blocking plane is reduced by a predetermined degree, and all the sub-areas after the deformation operation constitute the candidate optimization area; Step S5: Generate a CAD candidate model corresponding to the candidate optimization area, and determine whether the surface quality of the CAD candidate model is smooth or meets expectations. If it is determined to be yes, proceed to step S6; otherwise, proceed to step S3; Step S6: Perform CAE simulation analysis on the CAD candidate model, calculate the fluid mechanics parameters of the CAD candidate model, and determine whether the CAD candidate model meets the preset requirements based on the CAE simulation analysis results and the fluid mechanics parameters. If yes, use the CAD candidate model as the deformed CAD model and proceed to step S7; otherwise, proceed to step S4; Step S7: exporting the deformed CAD model as a deformed CAD model file.

2. The method according to claim 1, characterized in that In step S3, the total function is: ， Among them, P i,j,k are the three-dimensional coordinates corresponding to the control points in the control point group, i, j, k are the coordinates of the control points in the control point group on the x-axis, y-axis, and z-axis respectively; q, r, s are the maximum number of control points in the x-axis, y-axis, and z-axis directions respectively, u, v, w are the influence parameters on the x-axis, y-axis, and z-axis respectively, N i,p (u) is the spline basis function selected for parameter u, N j,m (v) is the spline basis function selected for parameter v, N k,n (w) is the spline basis function selected for parameter w, W i,j,k is the weight, and P'(u,v,w) is the total function value.

3. The method according to claim 2, characterized in that N i,p (u), N j,m (v) N k,n (w) is a spline basis function of different types, including a B-spline basis function, a Gaussian spline function, a multi-quadratic biharmonic spline function, an inverse multi-quadratic biharmonic spline function, and a Bernstein function.

4. The method according to claim 1, characterized in that Based on the CAD model imported in step S1 and the control domain defined in step S2, the control point grid scale and density are automatically determined in step S3, or the position and number of control points are manually adjusted. The control points are selected by mouse clicks or through a dialog box.

5. The method according to claim 2, characterized in that In step S4, based on the deformation optimization target area and the recommended value obtained by the total function, the position of the control point group is adjusted in real time, and the deformation operation is performed by manually dragging the position of the control point group, or the deformation result is controlled by inputting the displacement size of the control point group in different directions, or the software module encapsulates and calculates the spline basis function values ​​corresponding to each control point group and the adjustment method determined based on the recommended value, and the software module realizes continuous deformation.

6. The method according to claim 5, characterized in that Determine the surface curvature of the CAD candidate model, and if the surface curvature of the CAD candidate model meets a predetermined value or a predetermined range, determine that the surface is smooth or meets expectations; Alternatively, the surface curvature of the deformed model is calculated based on the CAD candidate model, and the difference is obtained from the surface curvature of the CAD model before deformation determined in step S2 or step S3. If the difference is less than a preset threshold and the CAD candidate model is smoother than the CAD model, smoothing is determined.

7. An analysis system for optimizing geometric free deformation of a movable body, characterized in that: The system comprises: Initialization module: configured to obtain a CAD model file of a movable body, wherein the CAD model corresponding to the CAD model file is a model to be deformed; convert the CAD model file into a CAD model, and determine the boundary of the CAD model; A control domain definition module: configured to define a control domain in the three-dimensional space corresponding to the CAD model, wherein the control domain is a deformation region that is determined based on the boundary of the CAD model and can cover the deformation optimization target region of the CAD model; Selection module: configured to select spline basis functions based on the control domain and engineering requirements to construct a total function; select control points as optimization design variables from the control domain to form a control point set to be deformed, select multiple control points from the control point set to be deformed as a control point group; determine the total function value corresponding to the control point group based on the three-dimensional coordinates corresponding to the control point group; Transformation module: configured to adjust the three-dimensional coordinates of the control point group based on the total function value corresponding to the control point group, perform a deformation operation on the deformation optimization target area, and obtain a candidate optimization area after deformation, wherein the deformation optimization target area is divided into a plurality of sub-areas, and the deformation operation includes: freezing the points in the sub-area set to the freezing mode so as not to be deformed, and performing a deformation operation on the sub-area in the non-freezing mode, wherein at least four control points in the same plane are selected from the control point group to form a polygon, and the plane corresponding to the polygon is used as a blocking plane, and the influence order is defined for the deformation blocking plane in such a way that the deformation effect of the deformation operation on one side of the deformation blocking plane on the other side of the deformation blocking plane is reduced by a predetermined degree, and the candidate optimization area is composed of all the sub-areas after the deformation operation; A first verification module: configured to generate a CAD candidate model corresponding to the candidate optimization area, and determine whether the surface quality of the CAD candidate model is smooth or meets expectations. If the determination is yes, the second verification module is triggered; otherwise, the selection module is triggered; The second verification module is configured to perform CAE simulation analysis on the CAD candidate model, calculate the fluid mechanics parameters of the CAD candidate model, and determine whether the CAD candidate model meets the preset requirements based on the CAE simulation analysis results and the fluid mechanics parameters. If yes, the CAD candidate model is used as a deformed CAD model to trigger the output module; otherwise, the transformation module is triggered; Output module: configured to export the deformed CAD model as a deformed CAD model file.

8. A computer-readable storage medium, characterized in that: The storage medium stores a plurality of instructions; the plurality of instructions are used for a processor to load and execute the method as described in any one of claims 1 to 6.

9. An electronic device, characterized in that: The electronic device comprises: A processor, which is used to execute multiple instructions; A memory for storing a plurality of instructions; The plurality of instructions are used to be stored in the memory and loaded and executed by the processor according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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