A method and device for part structure topology optimization based on improved SIMP

Abstract

The present invention discloses a method and device for optimizing the topology of a part structure based on improved SIMP, the method comprising accelerating the SIMP algorithm, obtaining the residual safety margin after the algorithm is accelerated, and preparing for subsequent optimization; discretizing the fuzzy boundary of the part structure, and optimizing the structure; identifying the structural features of the optimized part structure, and performing digital extraction and classification thereof; and reconstructing the boundary of the part structure according to the extracted digital features. The optimization method proposed by the present invention allocates the residual safety margin in the acceleration module according to the weight coefficient, divides the structural unit into a stable unit and a variable unit, calculates the variable relative density, and finally updates the structure based on this structure.

Description

Technical Field

[0001] The present invention relates to the field of structural optimization and structural manufacturing technology, and in particular to a method for optimizing the topology of a part structure based on an improved SIMP. One or more embodiments of the present application also relate to an apparatus for the method for optimizing the topology of a part structure based on an improved SIMP, a computing device, and a computer-readable storage medium. Background Art

[0002] In recent years, structural optimization methods have gradually come into people's view. Lightweight design of structures can not only effectively reduce the weight of the structure, but also improve the flexibility of the structure. Especially in the field of aerospace, the structural design of old aircraft is often considered from the safety level, and the structural design of the aircraft is too conservative, which leads to the increase of the weight of the aircraft. The weight reduction of the aircraft structure can not only increase the flight distance of the aircraft, but also improve the flexibility of the aircraft. At the same time, the fuel consumption rate of the aircraft will be greatly reduced, and the economic benefits brought are very obvious. As an emerging structural lightweight method, topological optimization is a design method that optimizes the distribution of materials in the design domain under the premise of ensuring sufficient structural strength.

[0003] At present, the optimization of structural parts is mainly based on the finite element method, which updates the material distribution in the design domain by analyzing the stress of the unit structure. Without affecting the safety performance of the structure, the units with small contribution to the structure are deleted to achieve the purpose of lightweight design of the structure. The main structural optimization methods currently include SIMP, BESO, MMC, level set and other methods.

[0004] The most widely used method at present is the SIMP method, which has the advantages of being easy to understand and less sensitive to meshes. However, there are a large number of fuzzy units in the optimized structure, and the selection of these units is a problem. These fuzzy meshes affect the accuracy of the structure, so many subsequent studies are devoted to how to obtain clear and accurate structures. Among them, the accuracy of mesh division is a crucial issue. The clarity of the boundary is proportional to the density of the mesh division, but the problem that follows is the calculation time. It has been verified that for the same structure, under the same working conditions, the number of meshes changes from 200*50 to 400*100, that is, the number of meshes becomes 4 times the original, and the calculation time will increase by 20 times, which may be more for large and complex structures. Secondly, the manufacturability of the structural optimization method is poor. Since the optimized structure is often porous, this poses a huge challenge to traditional manufacturing methods. Summary of the invention

[0005] The purpose of the present invention is to provide a method and device for part structure topology optimization based on improved SIMP.

[0006] To this end, the technical solution of the present invention is as follows:

[0007] A method for part structure topology optimization based on improved SIMP, including

[0008] Accelerate the SIMP algorithm to obtain the remaining safety margin after the algorithm is accelerated, in preparation for subsequent optimization;

[0009] Discretize the fuzzy boundaries of the part structure and optimize the structure;

[0010] Identify optimized part structural features, and digitally extract and classify them;

[0011] Reconstruct the boundary of the part structure based on the extracted digital features.

[0012] Furthermore, the method for accelerating the SIMP algorithm specifically includes:

[0013] Change the termination condition of SIMP method to ΔC <= 0.001C1.

[0014] Among them, ΔC is the change of the objective function after optimization, that is, the difference between the i-th objective function Ci and the i-1-th objective function Ci-1, C1 is the initial objective function value of the first input structure, and the ΔC output at the end of the cycle is the remaining safety margin.

[0015] Furthermore, the fuzzy boundaries of the discretized part structure specifically include

[0016] 1) Reasonably allocate the remaining safety margin ΔC. The expression of the remaining safety margin ΔC is:

[0017]

[0018] Among them, k e is the stiffness matrix of the unit and is a constant matrix, u e is the displacement matrix of the unit, ρ e is the relative density of the unit, Ne is the total number of variable units in the structure, and P is the penalty factor;

[0019] 2) According to formula 1), the average variable relative density of the variable unit is calculated: Divide the units in the structure that are in a changing state into Four gradients;

[0020] 3) Calculate the weight coefficient ω on each gradient i ,

[0021]

[0022] in, is the total number of units in the gradient, Ne is the total number of variable units;

[0023] 4) The saved remaining safety margin ΔC is calculated according to the weight coefficient ω i Assign to each gradient and perform the final structural unit update.

[0024] Furthermore, the structural features of the parts are identified and digitally extracted and classified.

[0025] a) Binarizing the updated part structure to obtain the overall unit matrix;

[0026] b) By filtering the radius r, the continuous boundary is distinguished from the discontinuous boundary, the continuous curve in the entire unit matrix is ​​obtained, and the continuous curve is saved in segments;

[0027] c) Determine the type of curve, classify closed curves and non-closed curves, and mark and save them;

[0028] d) Obtain all digital features of the model and save it as an xls format file.

[0029] The method for obtaining continuous curves in the entire unit matrix specifically includes:

[0030] Through the filtering radius r, the distance between the read boundary and the left side of the saved boundary is calculated and compared. If there is a unit that exceeds the filtering radius, it is the unit of the next hole boundary, and it is distinguished in this way until all feature boundaries are extracted and classified, and a digital feature parameter table of the structure is obtained.

[0031] Furthermore, the specific methods for determining the curve type include:

[0032] The data in the extracted parameter feature table are judged one by one according to the segmented curves;

[0033] For each curve, the parameters are sorted from left to right in the i-th row and from top to bottom in each row.

[0034] Determine whether the x-coordinate of the first row element of the i+1th row is less than the x-coordinate of the first row element of the i-th row. If the judgment result is "yes", proceed to the next step, otherwise it is judged as "non-closed curve";

[0035] Read the number of elements in the i+1 row, and determine whether there is an element in the row whose x coordinate is greater than the maximum x coordinate of the i-th element. If so, determine that the curve is a closed curve and mark it, until all curves are read and determined;

[0036] The segmented curves are finally processed and sorted in a clockwise direction to obtain complete and orderly digital model parameters.

[0037] Furthermore, the method for reconstructing the part structure boundary specifically includes:

[0038] The data coordinates in the xls file are obtained and the model is digitally reconstructed in Patran.

[0039] A device for part structure topology optimization based on improved SIMP, comprising:

[0040] The acceleration module is used to accelerate the SIMP algorithm and provide residual safety margin for subsequent optimization;

[0041] The boundary processing module performs boundary discretization processing on the accelerated model through the residual safety margin calculated by the acceleration module, in order to obtain a clear and stable structure. Specifically, it includes a variable unit counting module, a gradient division module, a weight coefficient calculation module and a safety margin allocation module;

[0042] The model digitization module is a module that identifies, classifies, and extracts the model boundaries of the optimized structure and saves the extracted digital features. It specifically includes a boundary identification module, a boundary classification module, a sorting module, and a digital preservation module.

[0043] The digital model reconstruction module obtains the boundary coordinates through the boundary recognition module, and redraws the boundary of the structure through the selected fitting method.

[0044] A computer device comprising

[0045] Memory and processor;

[0046] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions, wherein the processor implements the steps of the above-mentioned part structure topology optimization method based on improved SIMP when executing the computer executable instructions.

[0047] A computer-readable storage medium stores computer instructions, which, when executed by a processor, implement the steps of the above-mentioned part structure topology optimization method based on improved SIMP.

[0048] Compared with the prior art, the part structure topology optimization method and device based on improved SIMP provided by the present invention have the following advantages:

[0049] 1) The present invention proposes a new convergence condition, which shortens the optimization time of large structures and expands the applicability of the SIMP method while ensuring the stability of small structures;

[0050] 2) The present invention proposes a new acceleration algorithm, which can save more than double the calculation time for the optimization calculation of large structures and shorten the production cycle;

[0051] 3) In the present invention, the discretization process of the fuzzy boundary effectively deletes useless units and obtains a relatively clear boundary;

[0052] 4) The present invention digitally saves the optimized model, and the digitally saved model can be used to verify the effectiveness of the optimized structure, or combined with an effective curve fitting method to obtain an easily controllable manufacturing path, which greatly improves the manufacturability of the optimized structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A flow chart of the part structure topology optimization method based on improved SIMP provided by the present invention.

[0054] Figure 2 This is the effect diagram of the classic SIMP method.

[0055] Figure 3 This is a diagram of the acceleration effect provided by the present invention.

[0056] Figure 4 It is a schematic diagram of judging whether the acquired boundary curve is continuous according to the collective implementation of the present invention.

[0057] Figure 5 It is a schematic diagram of a non-closed curve.

[0058] Figure 6 It is a schematic diagram of a closed curve.

[0059] Figure 7 This is an application example of the digital model of the present invention. DETAILED DESCRIPTION

[0060] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but the following embodiments are by no means intended to limit the present invention in any way.

[0061] The present invention provides a method for optimizing the topology of a part structure based on improved SIMP. Figure 1 As shown, the following steps are included:

[0062] Accelerate the SIMP algorithm to obtain the remaining safety margin after the algorithm is accelerated, in preparation for subsequent optimization. It should be further explained that the termination cycle parameter in the SIMP algorithm is replaced with ΔC <= 0.001C 1 , C 1 The optimized parameter conditions are highly applicable, which can not only obtain the correct structure for small structures, but also avoid the defects of long optimization iteration time and inconspicuous structure change due to small change of objective function for calculation of large structures, which can save about 50% of time and greatly shorten the time cost.

[0063] The fuzzy boundary of the discretized part structure is optimized. It should be further explained that the improved and accelerated SIMP algorithm terminates the iteration early, and the structure is still in a safe state. The variable function that jumps out of the loop in advance is the remaining safety margin of the structure. The remaining safety margin is saved and used to deal with the fuzzy boundary. Most of the units in the structure are already in a stable state at this time, and these units are stable units. The units in the structure that are in a changing state are called variable units.

[0064] First, the variable unit density on the variable unit is calculated, which is used as the judgment condition for dividing the variable unit gradient. The expression of the remaining safety margin ΔC is:

[0065]

[0066] Among them, k e is the stiffness matrix of the unit and is a constant matrix, u e is the displacement matrix of the unit, ρ e is the relative density of the unit, Ne is the total number of variable units in the structure, and P is the penalty factor;

[0067] According to formula 1), the average variable relative density of the variable unit is calculated Divide the units in the structure that are in a changing state into Four gradients;

[0068] Secondly, the weight coefficient ω of each gradient is calculated according to the formula i , and save,

[0069]

[0070] in, is the total number of units in the gradient, Ne is the total number of variable units;

[0071] Finally, the saved remaining safety margin ΔC is divided by the weight coefficient ω i Assign to each gradient and perform the final structural unit update.

[0072] like Figure 2-3 As shown in the figure, it is a comparison chart of the topology optimization results after the acceleration algorithm and the fuzzy boundary processing. It can be found that for the same structure under the same working condition, the number of iterations of the acceleration algorithm is 35 times, while the number of iterations of the original SIMP algorithm is 84 times, the efficiency is improved by 58%, the number of fuzzy grids is reduced from 3762 to 2460, and the time efficiency is improved by 59%.

[0073] Identify the structural features of the optimized parts, and digitally extract and classify them, including identifying the structural features of the parts, and digitally extract and classify them, including

[0074] a) Binarizing the updated part structure to obtain the overall unit matrix;

[0075] b) By filtering the radius r, the continuous boundary is distinguished from the discontinuous boundary, the continuous curve in the entire unit matrix is ​​obtained, and the continuous curve is saved in segments, and the continuous curve is obtained by filtering the radius r, such as Figure 4 As shown, the distance between the read boundary and the left side of the saved boundary is calculated and compared. If there is a unit that exceeds the filtering radius, it is the unit of the next hole boundary, and this is used to distinguish until all feature boundaries are extracted and classified, and a digital feature parameter table of the structure is obtained;

[0076] c) Determine the type of curve, such as Figure 5-6 As shown, closed curves and non-closed curves are classified and marked and saved; the specific methods for determining the curve type include

[0077] The data in the extracted parameter feature table are judged one by one according to the segmented curves;

[0078] For each curve, the parameters are sorted from left to right in the i-th row and from top to bottom in each row.

[0079] Determine whether the x-coordinate of the first row element of the i+1th row is less than the x-coordinate of the first row element of the i-th row. If the judgment result is "yes", proceed to the next step, otherwise it is judged as "non-closed curve";

[0080] Read the number of elements in the i+1 row, and determine whether there is an element in the row whose x coordinate is greater than the maximum x coordinate of the i-th element. If so, determine that the curve is a closed curve and mark it, until all curves are read and determined;

[0081] The segmented curves are finally processed and sorted in a clockwise direction to obtain complete and orderly digital model parameters.

[0082] d) Obtain all digital features of the model and save it as an xls format file.

[0083] Reconstruct the boundary of the part structure based on the extracted digital features, and reconstruct the structure by combining the required modeling software or any curve fitting method that meets the requirements. Reconstruct the model digitally in Patran, and the effect is as follows: Figure 7 As shown, the main purpose of the coordinate data is to improve the manufacturability of the structure so that the geometric boundary can be expressed in a controllable manner.

[0084] A device for part structure topology optimization based on improved SIMP, comprising: an acceleration module, a boundary processing module, a model digitization module, and a digital model reconstruction module;

[0085] The acceleration module is used to accelerate the SIMP algorithm, improve the calculation efficiency, and provide a residual safety margin for subsequent optimization;

[0086] The boundary processing module is used to perform the final optimization of the structure and discretize the fuzzy boundary, including the variable unit counting module, gradient division module, weight coefficient calculation, and safety margin allocation. The residual safety margin calculated by the acceleration module is used to discretize the boundary of the accelerated model in order to obtain a clear and stable structure.

[0087] The model digitization module is a module that identifies, classifies, and extracts model boundaries of the optimized structure and saves the extracted digital features, including a boundary identification module, a boundary classification module, a sorting module, and a digital preservation module;

[0088] The boundary recognition module is a module for judging the boundary of the optimized model, identifying and marking modules with different holes and different boundaries by filtering the radius r; the boundary classification module is a module for judging and automatically classifying the boundaries of different holes by digital features; the sorting module is a module for adjusting the classified boundaries in clockwise order; the digital preservation module is a module for digitally outputting the modules that have been identified, processed and classified;

[0089] The digital model reconstruction module is a method for reconstructing the digital model by using the boundary coordinates obtained by the boundary recognition module and redrawing the boundary of the structure through a selected fitting method.

[0090] An embodiment of the present application provides a computer device, comprising:

[0091] Memory and processor;

[0092] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, wherein the processor implements the steps of the above-mentioned method for repairing missing low-voltage area user measurement data when executing the computer-executable instructions.

[0093] An embodiment of the present application provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the steps of the method for repairing missing measurement data of users in a low-voltage area.

[0094] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the above data repair method belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the above data repair method.

[0095] The above describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0096] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0097] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present application are not limited by the described action sequence, because according to the embodiments of the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of the present application.

[0098] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] The preferred embodiments of the present application disclosed above are only used to help explain the present application. The optional embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of the present application. The present application selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of the present application, so that those skilled in the art can understand and use the present application well. The present application is only limited by the claims and their full scope and equivalents.

Claims

1. A method for part structure topology optimization based on improved SIMP, It is characterized in that include Accelerate the SIMP algorithm to obtain the remaining safety margin after the algorithm is accelerated, in preparation for subsequent optimization. The specific methods for accelerating the SIMP algorithm include: Change the termination condition of SIMP method to ΔC <= 0.001C1. Among them, ΔC is the change of the objective function after optimization, that is, the difference between the i-th objective function Ci and the i-1-th objective function Ci-1, C1 is the initial objective function value of the first input structure, and the ΔC output at the end of the cycle is the remaining safety margin; Discretize the fuzzy boundary of the part structure and optimize the structure. The fuzzy boundary of the discretized part structure specifically includes: 1) Reasonably allocate the remaining safety margin ΔC. The expression of the remaining safety margin ΔC is: Among them, k e is the stiffness matrix of the unit and is a constant matrix, u e is the displacement matrix of the unit, ρ e is the relative density of the unit, Ne is the total number of variable units in the structure, and P is the penalty factor; 2) According to formula 1), the average variable relative density of the variable unit is calculated: Divide the units in the structure that are in a changing state into Four gradients; 3) Calculate the weight coefficient ω on each gradient i , Among them, is the total number of units in the gradient, Ne is the total number of variable units; 4) Allocate the saved remaining safety margin ΔC to each gradient according to the weight coefficient ωi, and perform the last structural unit update; Identify optimized part structural features, and digitally extract and classify them; Reconstruct the boundary of the part structure based on the extracted digital features.

2. The part structure topology optimization method based on improved SIMP according to claim 1, It is characterized in that Identify the structural features of parts, and digitally extract and classify them. a) Binarizing the updated part structure to obtain the overall unit matrix; b) By filtering the radius r, the continuous boundary is distinguished from the discontinuous boundary, the continuous curve in the entire unit matrix is ​​obtained, and the continuous curve is saved in segments; c) Determine the type of curve, classify closed curves and non-closed curves, and mark and save them; d) Obtain all digital features of the model and save it as an xls format file.

3. The part structure topology optimization method based on improved SIMP according to claim 2, It is characterized in that The method for obtaining continuous curves in the entire unit matrix specifically includes: Through the filtering radius r, the distance between the read boundary and the left side of the saved boundary is calculated and compared. If there is a unit that exceeds the filtering radius, it is the unit of the next hole boundary, and it is distinguished in this way until all feature boundaries are extracted and classified, and a digital feature parameter table of the structure is obtained.

4. The part structure topology optimization method based on improved SIMP according to claim 2, It is characterized in that Specific methods for determining curve types include: The data in the extracted parameter feature table are judged one by one according to the segmented curves; For each curve, the parameters are sorted from left to right in the i-th row and from top to bottom in each row. Determine whether the x-coordinate of the first row element of the i+1th row is less than the x-coordinate of the first row element of the i-th row. If the judgment result is "yes", proceed to the next step, otherwise it is judged as "non-closed curve"; Read the number of elements in the i+1 row, and determine whether there is an element in the row whose x coordinate is greater than the maximum x coordinate of the i-th element. If so, determine that the curve is a closed curve and mark it, until all curves are read and determined; The segmented curves are finally processed and sorted in a clockwise direction to obtain complete and orderly digital model parameters.

5. The part structure topology optimization method based on improved SIMP according to claim 1, It is characterized in that The method of reconstructing the part structure boundary specifically includes The data coordinates in the xls file are obtained and the model is digitally reconstructed in Patran.

6. An optimization device based on the improved SIMP part structure topology optimization method according to claim 1, It is characterized in that include: The acceleration module is used to accelerate the SIMP algorithm and provide residual safety margin for subsequent optimization; The boundary processing module performs boundary discretization processing on the accelerated model through the residual safety margin calculated by the acceleration module, in order to obtain a clear and stable structure. Specifically, it includes a variable unit counting module, a gradient division module, a weight coefficient calculation module and a safety margin allocation module; The model digitization module is a module that identifies, classifies, and extracts the model boundaries of the optimized structure and saves the extracted digital features. It specifically includes a boundary identification module, a boundary classification module, a sorting module, and a digital preservation module. The digital model reconstruction module obtains the boundary coordinates through the boundary recognition module, and redraws the boundary of the structure through the selected fitting method.

7. A computer device, It is characterized in that include Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions, wherein the processor implements the steps of the part structure topology optimization method based on improved SIMP as described in claims 1-5 when executing the computer executable instructions.

8. A computer-readable storage medium, It is characterized in that It stores computer instructions, which, when executed by a processor, implement the steps of the part structure topology optimization method based on improved SIMP as described in claims 1-5.

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