Topology Optimization of Periodic Structures With Substructuring

2019 ◽  
Vol 141 (7) ◽  
Author(s):  
Junjian Fu ◽  
Liang Xia ◽  
Liang Gao ◽  
Mi Xiao ◽  
Hao Li
Keyword(s):  
Topology Optimization ◽  
Linear System ◽  
Periodic Structures ◽  
Computational Cost ◽  
Optimization Method ◽  
Displacement Fields ◽  
Element Analysis ◽  
Level Set Function ◽  
Static Condensation ◽  
Unit Cells

Topology optimization of macroperiodic structures is traditionally realized by imposing periodic constraints on the global structure, which needs to solve a fully linear system. Therefore, it usually requires a huge computational cost and massive storage requirements with the mesh refinement. This paper presents an efficient topology optimization method for periodic structures with substructuring such that a condensed linear system is to be solved. The macrostructure is identically partitioned into a number of scale-related substructures represented by the zero contour of a level set function (LSF). Only a representative substructure is optimized for the global periodic structures. To accelerate the finite element analysis (FEA) procedure of the periodic structures, static condensation is adopted for repeated common substructures. The macrostructure with reduced number of degree of freedoms (DOFs) is obtained by assembling all the condensed substructures together. Solving a fully linear system is divided into solving a condensed linear system and parallel recovery of substructural displacement fields. The design efficiency is therefore significantly improved. With this proposed method, people can design scale-related periodic structures with a sufficiently large number of unit cells. The structural performance at a specified scale can also be calculated without any approximations. What’s more, perfect connectivity between different optimized unit cells is guaranteed. Topology optimization of periodic, layerwise periodic, and graded layerwise periodic structures are investigated to verify the efficiency and effectiveness of the presented method.

scholarly journals An Efficient and High-Resolution Topology Optimization Method Based on Convolutional Neural Networks

2019 ◽  
Author(s):  
Liang Xue ◽  
Jie Liu ◽  
Guilin Wen ◽  
Hongxin Wang
Keyword(s):  
Topology Optimization ◽  
High Resolution ◽  
High Efficiency ◽  
Optimization Problems ◽  
Combined Treatment ◽  
Computational Cost ◽  
Optimization Method ◽  
Element Analysis ◽  
Arbitrary Boundary ◽  
Topology Optimization Method

Topology optimization is a pioneering design method that can provide various candidates with high mechanical properties. However, the high-resolution for the optimum structures is highly desired, normally in turn leading to computationally intractable puzzle, especially for the famous Solid Isotropic Material with Penalization (SIMP) method. In this paper, an efficient and high-resolution topology optimization method is proposed based on the Super-Resolution Convolutional Neural Network (SRCNN) technique in the framework of SIMP. The SRCNN includes four processes, i.e. refining, path extraction & representation, non-linear mapping, and reconstruction. The high computational efficiency is achieved by a pooling strategy, which can balance the number of finite element analysis (FEA) and the output mesh in optimization process. To further reduce the high computational cost of 3D topology optimization problems, a combined treatment method using 2D SRCNN is built as another speeding-up strategy. A number of typical examples justify that the high-resolution topology optimization method adopting SRCNN has excellent applicability and high efficiency for 2D and 3D problems with arbitrary boundary conditions, any design domain shape, and varied load.

Topology Optimization on the Cloud: A Confluence of Technologies

2015 ◽  
Author(s):  
Krishnan Suresh
Keyword(s):  
Topology Optimization ◽  
Computational Cost ◽  
Optimization Method ◽  
Element Analysis ◽  
Structural Problems ◽  
Free Service ◽  
3D Geometry ◽  
Many Core ◽  
3D Topology ◽  
Multiple Clients

Topology optimization is a systematic method of generating designs to meet specific engineering requirements. It is exploited today in several industries including aircraft, automobile, and machinery, and it strongly complements the emerging field of additive manufacturing. Yet, the wide-spread use of topology optimization has been deterred due to high computational cost and significant software/hardware investment. In this paper, we propose a cloud based topology optimization (CTO) framework to overcome these challenges, thereby promoting the wider use of topology optimization. CTO requires a confluence of several methods and technologies, each of which is discussed in this paper. First and foremost, CTO requires a fast 3D topology optimization method that can respond rapidly to multiple clients. Here, PareTO, a topological sensitivity based method is used as the backbone of the framework. PareTO relies on limited-memory finite element analysis with a deflated linear solver that is designed to exploit multi-core and many-core architectures. At the client-end, the framework relies on JavaScript based WebGL and ThreeJS technologies to display 3D geometry and formulate structural problems within a browser. Finally, Ajax, php and HTML5 technologies are exploited to achieve asynchronous and robust user experience. An implementation of this framework is available at www.cloudtopopt.com; to use this free service, JavaScript must be enabled within the browser.

Multiscale Topology Optimization With Gaussian Process Regression Models

2021 ◽  
Author(s):  
Joel C. Najmon ◽  
Homero Valladares ◽  
Andres Tovar
Keyword(s):  
Topology Optimization ◽  
Gaussian Process ◽  
Regression Models ◽  
Computational Cost ◽  
Gaussian Process Regression ◽  
Analytical Sensitivity ◽  
Inverse Homogenization ◽  
Discrete Location ◽  
Unit Cells ◽  
Periodic Microstructures

Abstract Multiscale topology optimization (MSTO) is a numerical design approach to optimally distribute material within coupled design domains at multiple length scales. Due to the substantial computational cost of performing topology optimization at multiple scales, MSTO methods often feature subroutines such as homogenization of parameterized unit cells and inverse homogenization of periodic microstructures. Parameterized unit cells are of great practical use, but limit the design to a pre-selected cell shape. On the other hand, inverse homogenization provide a physical representation of an optimal periodic microstructure at every discrete location, but do not necessarily embody a manufacturable structure. To address these limitations, this paper introduces a Gaussian process regression model-assisted MSTO method that features the optimal distribution of material at the macroscale and topology optimization of a manufacturable microscale structure. In the proposed approach, a macroscale optimization problem is solved using a gradient-based optimizer The design variables are defined as the homogenized stiffness tensors of the microscale topologies. As such, analytical sensitivity is not possible so the sensitivity coefficients are approximated using finite differences after each microscale topology is optimized. The computational cost of optimizing each microstructure is dramatically reduced by using Gaussian process regression models to approximate the homogenized stiffness tensor. The capability of the proposed MSTO method is demonstrated with two three-dimensional numerical examples. The correlation of the Gaussian process regression models are presented along with the final multiscale topologies for the two examples: a cantilever beam and a 3-point bending beam.

Rapid Modeling and Design Optimization of Multi-Topology Lattice Structure Based on Unit-Cell Library

2020 ◽  
Vol 142 (9) ◽  
Author(s):  
Yuan Liu ◽  
Shurong Zhuo ◽  
Yining Xiao ◽  
Guolei Zheng ◽  
Guoying Dong ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Lattice Structure ◽  
Structure Design ◽  
Parametric Modeling ◽  
Unit Cell ◽  
Element Analysis ◽  
Structure Generation ◽  
Cell Library ◽  
Unit Cells ◽  
Property Space

Abstract Lightweight lattice structure generation and topology optimization (TO) are common design methodologies. In order to further improve potential structural stiffness of lattice structures, a method combining the multi-topology lattice structure design based on unit-cell library with topology optimization is proposed to optimize the parts. First, a parametric modeling method to rapidly generate a large number of different types of lattice cells is presented. Then, the unit-cell library and its property space are constructed by calculating the effective mechanical properties via a computational homogenization methodology. Third, the template of compromise Decision Support Problem (cDSP) is applied to generate the optimization formulation. The selective filling function of unit cells and geometric parameter computation algorithm are subsequently given to obtain the optimum lightweight lattice structure with uniformly varying densities across the design space. Lastly, for validation purposes, the effectiveness and robustness of the optimized results are analyzed through finite element analysis (FEA) simulation.

scholarly journals A topology optimization method of robot lightweight design based on the finite element model of assembly and its applications

2020 ◽  
Vol 103 (3) ◽  
pp. 003685042093648
Author(s):  
Liansen Sha ◽  
Andi Lin ◽  
Xinqiao Zhao ◽  
Shaolong Kuang
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Topology Optimization ◽  
Lightweight Design ◽  
Element Model ◽  
Optimization Method ◽  
Maximum Displacement ◽  
Element Analysis ◽  
Upper Limb Exoskeleton ◽  
Topology Optimization Method

Topology optimization is a widely used lightweight design method for structural design of the collaborative robot. In this article, a topology optimization method for the robot lightweight design is proposed based on finite element analysis of the assembly so as to get the minimized weight and to avoid the stress analysis distortion phenomenon that compared the conventional topology optimization method by adding equivalent confining forces at the analyzed part’s boundary. For this method, the stress and deformation of the robot’s parts are calculated based on the finite element analysis of the assembly model. Then, the structure of the parts is redesigned with the goal of minimized mass and the constraint of maximum displacement of the robot’s end by topology optimization. The proposed method has the advantages of a better lightweight effect compared with the conventional one, which is demonstrated by a simple two-linkage robot lightweight design. Finally, the method is applied on a 5 degree of freedom upper-limb exoskeleton robot for lightweight design. Results show that there is a 10.4% reduction of the mass compared with the conventional method.

Analysis of the Wrist-Wearable Energy Harvester With Vibrating Piezoelectric Multiple Bimorph Cantilevers Using FEM and Topology Optimization

2014 ◽  
Author(s):  
Cheol Kim ◽  
Young-Geun Song
Keyword(s):  
Topology Optimization ◽  
Energy Harvester ◽  
Piezoelectric Materials ◽  
Electric Energy ◽  
Optimization Method ◽  
Optimum Shape ◽  
Element Analysis ◽  
Piezoelectric Layers ◽  
Tungsten Tip ◽  
Tip Mass

A small wrist-watch-like wearable electric energy harvester which can extract electricity from swinging motions of people’s arms while walking has been developed newly. The harvester consists of multiple vibrating piezoelectric cantilevered thin beams attached to a round central hub structure radially with tip masses. The cantilevers are made of a polycarbonate substrate beam, PMN-PT piezoelectric material on its both sides, and a high density tungsten tip mass. The swinging of a human arm with the harvester causes the bending deformations in each blade while walking and then produces electricity from strains in two piezoelectric layers. The swinging motion was formulated mathematically and kinematically in terms of swinging angles, angular velocities and accelerations. Finite element analysis was used to model the cantilevered beams and calculate the voltage output. The optimum shape of piezoelectric layers were calculated on the basis of the topology optimization method specialized for piezoelectric materials.

Displacement and Stress Constrained Topology Optimization

2013 ◽  
Author(s):  
Meisam Takalloozadeh ◽  
Krishnan Suresh
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Topology Optimization ◽  
Level Set ◽  
Numerical Experiments ◽  
Optimization Method ◽  
Stress Constraints ◽  
Element Analysis ◽  
The Finite Element Analysis ◽  
Topology Optimization Method

The objective of this paper is to demonstrate a topology optimization method subject to displacement and stress constraints. The method does not rely on pseudo-densities; instead it exploits the concept of topological level-set where ‘partial’ elements are avoided. Consequently: (1) the stresses are well-defined at all points within the evolving topology, and (2) the finite-element analysis is robust and efficient. Further, in the proposed method, a series of topologies of decreasing volume fractions are generated in a single optimization run. The method is illustrated through numerical experiments in 2D.

Application of Regional Strain Energy in Topology Optimization With Inertia Relief Analysis

2013 ◽  
Author(s):  
Wei Song ◽  
Hae Chang Gea ◽  
Ren-Jye Yang ◽  
Ching-Hung Chuang
Keyword(s):  
Finite Element ◽  
Topology Optimization ◽  
Strain Energy ◽  
Computational Cost ◽  
Structure Design ◽  
Protective Structure ◽  
Element Analysis ◽  
Regional Strain ◽  
Unbalanced Loads ◽  
Energy Formulation

In finite element analysis, inertia relief solves the response of an unconstrained structure subject to constant or slowly varying external loads with static analysis computational cost. It is very attractive to utilize it in topology optimization to design structures under unbalanced loads, such as in impact and drop phenomena. In this paper, regional strain energy formulation and inertia relief is integrated into topology optimization to design protective structure under unbalanced loads. For background, the equations of inertia relief are introduced and a commonly used solving method is revisited. Then the regional strain energy formulation for topology optimization with inertia relief is proposed and its sensitivity is derived from the adjoint method. Based on the solving method, the sensitivity is evaluated term by term to simplify the results. The simplified sensitivity can be calculated easily using the output of commercial finite element packages. Finally, the effectiveness of this formulation is shown in the first example and the proposed regional strain energy formulation for topology optimization with inertia relief are presented and discussed in the protective structure design examples.

Application of Topological Optimization on Aluminum Alloy Automobile Wheel Designing

2012 ◽  
Vol 562-564 ◽  
pp. 705-708
Author(s):  
Zhi Jun Zhang ◽  
Hong Lei Jia ◽  
Ji Yu Sun ◽  
Ming Ming Wang
Keyword(s):  
Topology Optimization ◽  
Lightweight Design ◽  
Optimization Method ◽  
Variable Density ◽  
Topological Optimization ◽  
Optimal Topology ◽  
Element Analysis ◽  
Material Interpolation ◽  
Strength And Stiffness

Topology optimization method based on variable density and the minimum compliance objective function was used on designing the wheel spokes. SIMP material interpolation model was established to compensate these deficiencies of variable density method. Considering manufacturing process and stress distribution, five bolt wheels was chose to topology optimization. The percentage of material removal of the optimal topology 40% was reasonable. Finite element analysis was used to test the strength and stiffness of the structure of the wheel, the result meets the requirements after wheel topology optimization, and reduces the quality of wheels to 7.76kg, achieve the goals of lightweight design.

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