Optimal Cantilever Design by Topology and Shape Optimization Methods

2015 ◽  
Vol 789-790 ◽  
pp. 306-310
Author(s):  
Jin Woo Lee
Keyword(s):  
Shape Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Mode Frequency ◽  
Torsional Mode ◽  
Initial Shape ◽  
Topology Optimization Problem ◽  
Torsion Mode ◽  
Topology And Shape Optimization

This work presents the framework to optimally design a cantilever for torsion mode frequency maximization. A cantilever design problem is formulated by topology and shape optimization methods. The torsion mode frequency is selected as an objective function, and the volume of the cantilever and the first bending mode frequency are constrained. Two optimization problems are defined and sequentially solved for the specific values. A new idea in this work is using a final topology obtained in the topology optimization problem as an initial shape in the shape optimization problem. The torsional mode frequency of the optimized cantilever is well improved in comparison with a nominal cantilever.

Topology Optimization Design of Bars Structure Based on SKO Method

2013 ◽  
Vol 394 ◽  
pp. 515-520 ◽  
Author(s):  
Wen Jun Li ◽  
Qi Cai Zhou ◽  
Xu Hui Zhang ◽  
Xiao Lei Xiong ◽  
Jiong Zhao
Keyword(s):  
Global Optimization ◽  
Topology Optimization ◽  
Optimization Design ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Topology Optimization Problem ◽  
Proposed Model ◽  
Continuum Structure ◽  
The Impact

There are less topology optimization methods for bars structure than those for continuum structure. Bionic intelligent method is a powerful way to solve the topology optimization problems of bars structure since it is of good global optimization capacity and convenient for numerical calculation. This article presents a SKO topology optimization model for bars structure based on SKO (Soft Kill Option) method derived from adaptive growth rules of trees, bones, etc. The model has been applied to solve the topology optimization problem of a space frame. It uses three optimization strategies, which are constant, decreasing and increasing material removed rate. The impact on the optimization processes and results of different strategies are discussed, and the validity of the proposed model is proved.

scholarly journals Coupled topology and shape optimization using an embedding domain discretization method

2021 ◽  
Vol 64 (4) ◽  
pp. 2687-2707
Author(s):  
Gabriel Stankiewicz ◽  
Chaitanya Dev ◽  
Paul Steinmann
Keyword(s):  
Topology Optimization ◽  
Shape Optimization ◽  
Optimization Problem ◽  
Optimization Methods ◽  
Density Field ◽  
Discretization Method ◽  
Topological Features ◽  
Topology And Shape Optimization ◽  
Discretization Technique ◽  
Domain Discretization

AbstractDensity-based topology optimization and node-based shape optimization are often used sequentially to generate production-ready designs. In this work, we address the challenge to couple density-based topology optimization and node-based shape optimization into a single optimization problem by using an embedding domain discretization technique. In our approach, a variable shape is explicitly represented by the boundary of an embedded body. Furthermore, the embedding domain in form of a structured mesh allows us to introduce a variable, pseudo-density field. In this way, we attempt to bring the advantages of both topology and shape optimization methods together and to provide an efficient way to design fine-tuned structures without predefined topological features.

Solving Mono- and Multi-Objective Problems Using Hybrid Evolutionary Algorithms and Nelder-Mead Method

2021 ◽  
Vol 12 (4) ◽  
pp. 98-116
Author(s):  
Noureddine Boukhari ◽  
Fatima Debbat ◽  
Nicolas Monmarché ◽  
Mohamed Slimane
Keyword(s):  
Convergence Rate ◽  
Optimization Problem ◽  
Optimization Problems ◽  
State Of The Art ◽  
Hybrid Approach ◽  
Optimization Methods ◽  
Global Optimum ◽  
Stochastic Methods ◽  
Local Optima ◽  
Portfolio Optimization Problem

Evolution strategies (ES) are a family of strong stochastic methods for global optimization and have proved their capability in avoiding local optima more than other optimization methods. Many researchers have investigated different versions of the original evolution strategy with good results in a variety of optimization problems. However, the convergence rate of the algorithm to the global optimum stays asymptotic. In order to accelerate the convergence rate, a hybrid approach is proposed using the nonlinear simplex method (Nelder-Mead) and an adaptive scheme to control the local search application, and the authors demonstrate that such combination yields significantly better convergence. The new proposed method has been tested on 15 complex benchmark functions and applied to the bi-objective portfolio optimization problem and compared with other state-of-the-art techniques. Experimental results show that the performance is improved by this hybridization in terms of solution eminence and strong convergence.

Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering

2011 ◽  
Vol 1 (1) ◽  
pp. 57-79 ◽  
Author(s):  
A. Andrade-Campos
Keyword(s):  
Inverse Problems ◽  
Shape Optimization ◽  
Parameter Identification ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimum Shape ◽  
Optimization Framework ◽  
Search Optimization ◽  
Initial Geometry

The use of optimization methods in engineering is increasing. Process and product optimization, inverse problems, shape optimization, and topology optimization are frequent problems both in industry and science communities. In this paper, an optimization framework for engineering inverse problems such as the parameter identification and the shape optimization problems is presented. It inherits the large experience gain in such problems by the SiDoLo code and adds the latest developments in direct search optimization algorithms. User subroutines in Sdl allow the program to be customized for particular applications. Several applications in parameter identification and shape optimization topics using Sdl Lab are presented. The use of commercial and non-commercial (in-house) Finite Element Method codes to evaluate the objective function can be achieved using the interfaces pre-developed in Sdl Lab. The shape optimization problem of the determination of the initial geometry of a blank on a deep drawing square cup problem is analysed and discussed. The main goal of this problem is to determine the optimum shape of the initial blank in order to save latter trimming operations and costs.

scholarly journals Truss’ topology and shape optimization by genetic algorithms

2021 ◽  
Vol 47 ◽  
Author(s):  
Dmitrij Šešok ◽  
Paulius Ragauskas
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Shape Optimization ◽  
Optimization Problem ◽  
Numerical Solutions ◽  
Search Algorithm ◽  
Truss Topology ◽  
Modified Genetic Algorithm ◽  
Topology And Shape Optimization ◽  
System Characteristics

In the paper the global optimization problem of truss systems is studied.  The genetic algorithms are employed for the optimization. As the objective function the structure mass is treated; the constraints include equilibrium, local stability and other requirements.  All the truss system characteristics needed for genetic algorithm are obtained via finite element solution. Topology optimization of truss system is performed using original modified genetic algorithm, while the shape optimization – using ordinary genetic algorithm. Numerical solutions are presented. The obtained solutions are compared with global extremes obtained using full search algorithm.  All the numerical examples are solved using original software.

scholarly journals A class of shape optimization problems for some nonlocal operators

2018 ◽  
Vol 11 (4) ◽  
pp. 373-386 ◽  
Author(s):  
Julián Fernández Bonder ◽  
Antonella Ritorto ◽  
Ariel Martin Salort
Keyword(s):  
Shape Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
State Equation ◽  
The State ◽  
Local State ◽  
Nonlocal Operator ◽  
State Equations ◽  
Nonlocal Operators ◽  
Shape Optimization Problem

AbstractIn this work we study a family of shape optimization problem where the state equation is given in terms of a nonlocal operator. Examples of the problems considered are monotone combinations of fractional eigenvalues. Moreover, we also analyze the transition from nonlocal to local state equations.

Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering

2012 ◽  
pp. 1-24
Author(s):  
A. Andrade-Campos
Keyword(s):  
Inverse Problems ◽  
Shape Optimization ◽  
Parameter Identification ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimum Shape ◽  
Optimization Framework ◽  
Search Optimization ◽  
Initial Geometry

The use of optimization methods in engineering is increasing. Process and product optimization, inverse problems, shape optimization, and topology optimization are frequent problems both in industry and science communities. In this paper, an optimization framework for engineering inverse problems such as the parameter identification and the shape optimization problems is presented. It inherits the large experience gain in such problems by the SiDoLo code and adds the latest developments in direct search optimization algorithms. User subroutines in Sdl allow the program to be customized for particular applications. Several applications in parameter identification and shape optimization topics using Sdl Lab are presented. The use of commercial and non-commercial (in-house) Finite Element Method codes to evaluate the objective function can be achieved using the interfaces pre-developed in Sdl Lab. The shape optimization problem of the determination of the initial geometry of a blank on a deep drawing square cup problem is analysed and discussed. The main goal of this problem is to determine the optimum shape of the initial blank in order to save latter trimming operations and costs.

Layout Optimization of a Multiple Pinned Joint Under Bending in a Limited Contact Area

2013 ◽  
Author(s):  
Amir Mohsen Hejazi ◽  
Mohammad Pourgol Mohammad
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Stress Concentration ◽  
Stress Analysis ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Limited Area ◽  
Design Factor ◽  
Finite Element Software

Layout determination of connectors in different mechanical configurations improves the design characteristics. The issue has recently become more practical in sensitive industries, especially in montage processes. Since connections are under different loads like bending, the layout of connection should be considered as an effective design factor in different loading conditions which is itself a step forward in achieving the optimized connection and also increases the connection life. This paper analyses the layout effects in a multiple pinned joint under bending in a limited area. The goal is to minimize the average stress and having a uniform stress distribution in the connections in order to prevent the failure inducing effect of stress concentration. The common method for solving these optimization problems is to couple two finite element numerical stress analysis software with an optimization tool or independent software which is a highly time consuming method due to enormous volume of the calculations in each iteration. In this paper the optimization problem is mathematically modeled and solved using Genetic Algorithm (GA). Genetic algorithm is found applicable here due to nonlinear behavior and complexity of the objective function in the optimization problem where analytical optimization methods are not useful. The validation results of stress analysis are obtained using finite element software. The optimized connections have longer lifetime and can carry higher loads because of degraded effects of stress concentration and minimized stresses.

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