Nodal Evolutionary Computation Enhanced Level Set Algorithm for Structural Topology Optimization

2010 ◽  
Vol 29-32 ◽  
pp. 337-342
Author(s):  
Hai Peng Jia ◽  
Chun Dong Jiang ◽  
Bo Liu ◽  
Dong Xing Cao ◽  
Chun Bo Jiang

This paper proposes an improved computational algorithm for structure topology optimization. It integrates the merits of Evolutionary Structure Optimization and Level Set Method (LSM) for structure topology optimization. Traditional LSM algorithm has some drawbacks, for instance, its optimal topology configuration is largely dependent on the structural topology initialization. Additionally, new holes cannot be evolved within the updated topology during the optimization iteration. The method proposed in this paper combines the merits of ESO techniques with the LSM scheme, allowing new holes to be automatically inserted in regions with low deformation energy at prescribed iterations of the optimization. The nodal neighboring region is a good selection. For complex structures in which holes cannot be properly inserted in advance, the proposed method considerably improves the ability of LSM to search the optimal topology. In addition to achieving more accurate results, the proposed method also yields higher efficiency during optimization. Benchmark problems are presented to show the effectiveness and robustness of the new proposed algorithm.

2012 ◽  
Vol 433-440 ◽  
pp. 3080-3085 ◽  
Author(s):  
Huan Yuan Chen ◽  
Yong Jun Xie ◽  
Dong Song Yan ◽  
Hao Liu ◽  
Jing Ming Li

In order to enhance the working performance of micro-capacitive accelerometer in high temperature environment, the structure topology optimization of a micro-capacitive accelerometer is proposed. After the study of thermo-structural coupled governing equations and sensitivity analysis, the mass-block and elastic-beam structure of comb micro-capacitive accelerometer topology optimization model is established. Then the optimal topology forms of mass-block and elastic-beam structure are obtained with the MMA (method of moving asymptotes) method. At last, the calculating results indicate that the maximum deformation at acceleration detection direction is only 22nm at the operating temperature range of 0~300°C, which less than the maximum deformation of the limit value (25nm), and provides a reliable way for innovative design of micro-capacitive accelerometer.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Meisam Takalloozadeh ◽  
Gil Ho Yoon

Purpose Body forces are always applied to structures in the form of the weight of materials. In some cases, they can be neglected in comparison with other applied forces. Nevertheless, there is a wide range of structures in civil and mechanical engineering in which weight or other types of body forces are the main portions of the applied loads. The optimal topology of these structures is investigated in this study. Design/methodology/approach Topology optimization plays an increasingly important role in structural design. In this study, the topological derivative under body forces is used in a level-set-based topology optimization method. Instability during the optimization process is addressed, and a heuristic solution is proposed to overcome the challenge. Moreover, body forces in combination with thermal loading are investigated in this study. Findings Body forces are design-dependent loads that usually add complexity to the optimization process. Some problems have already been addressed in density-based topology optimization methods. In the present study, the body forces in a topological level-set approach are investigated. This paper finds that the used topological derivative is a flat field that causes some instabilities in the optimization process. The main novelty of this study is a technique used to overcome this challenge by using a weighted combination. Originality/value There is a lack of studies on level-set approaches that account for design-dependent body forces and the proposed method helps to understand the challenges posed in such methods. A powerful level-set-based approach is used for this purpose. Several examples are provided to illustrate the efficiency of this method. Moreover, the results show the effect of body forces and thermal loading on the optimal layout of the structures.


Author(s):  
Kuang-Wu Chou ◽  
Chang-Wei Huang

This study proposes a new element-based method to solve structural topology optimization problems with non-uniform meshes. The objective function is to minimize the compliance of a structure, subject to a volume constraint. For a structure of a fixed volume, the method is intended to find a topology that could almost conform to the compliance minimum. The method is refined from the evolutionary switching method, whose policy of exchanging elements is improved by replacing some empirical decisions with ones according to optimization theories. The method has the evolutionary stage and the element exchange stage to conduct topology optimization. The evolutionary stage uses the evolutionary structural optimization method to remove inefficient elements until the volume constraint is satisfied. The element exchange stage performs a procedure refined from the element exchange method. Notably, the procedures of both stages are refined to conduct non-uniform finite element meshes. The proposed method was implemented to use the Abaqus Python scripting interface to call the services of Abaqus such as running analysis and retrieving the output database of an analysis. Numerical examples demonstrate that the proposed optimization method could determine the optimal topology of a structure that is subject to a volume constraint and whose mesh is non-uniform.


2020 ◽  
Vol 15 (3) ◽  
pp. 390-405
Author(s):  
Peng Wei ◽  
Wenwen Wang ◽  
Yang Yang ◽  
Michael Yu Wang

Abstract The level set method (LSM), which is transplanted from the computer graphics field, has been successfully introduced into the structural topology optimization field for about two decades, but it still has not been widely applied to practical engineering problems as density-based methods do. One of the reasons is that it acts as a boundary evolution algorithm, which is not as flexible as density-based methods at controlling topology changes. In this study, a level set band method is proposed to overcome this drawback in handling topology changes in the level set framework. This scheme is proposed to improve the continuity of objective and constraint functions by incorporating one parameter, namely, level set band, to seamlessly combine LSM and density-based method to utilize their advantages. The proposed method demonstrates a flexible topology change by applying a certain size of the level set band and can converge to a clear boundary representation methodology. The method is easy to implement for improving existing LSMs and does not require the introduction of penalization or filtering factors that are prone to numerical issues. Several 2D and 3D numerical examples of compliance minimization problems are studied to illustrate the effects of the proposed method.


2020 ◽  
Vol 7 (4) ◽  
pp. 514-526
Author(s):  
Zijun Wu ◽  
Shuting Wang ◽  
Renbin Xiao ◽  
Lianqing Yu

Abstract This paper develops a new topology optimization approach for minimal compliance problems based on the parameterized level set method in isogeometric analysis. Here, we choose the basis functions as level set functions. The design variables are obtained with Greville abscissae based on the corresponding collocation points. The zero-level set boundaries are derived from the level set function values of the interpolation points in all knot spans. In the optimization iteration process, the whole design domain is discretized into two types of subdomains around the zero-level set boundaries, undesign area with void materials and redesign domain with solid materials. To decrease the size of equations and the computational consumptions, only the solid material area is recalculated and the void material area is discarded according to the high accuracy of isogeometric analysis. Numerical examples demonstrate the validity of the proposed optimization method.


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