Topology Optimization of an Automotive Tailor-Welded Blank Door

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
Guangyao Li ◽  
Fengxiang Xu ◽  
Xiaodong Huang ◽  
Guangyong Sun
Keyword(s):  
Topology Optimization ◽  
Optimization Problems ◽  
Lightweight Design ◽  
Optimization Procedure ◽  
Fe Model ◽  
Optimal Thickness ◽  
Evolutionary Structural Optimization ◽  
Wide Range ◽  
Beso Method ◽  
Tailor Welded Blank

Bidirectional evolutionary structural optimization (BESO) method has been successfully applied for a wide range of topology optimization problems. In this paper, the BESO method is further extended to the optimal design of an automotive tailor-welded blank (TWB) door with multiple thicknesses. Different from the traditional topology optimization for solid-void designs, topology optimization of the TWB door needs to identify the weld lines which joint sheets with different thicknesses. The finite element (FE) model of the automotive door assembly is established and verified by a series of stiffness experiments. Then, the proposed optimization procedure is applied to the optimization of the automotive TWB indoor panel for the optimal thickness layout and weld lines locations. Numerical results give guidelines for the lightweight design of TWB components to some extent.

Topology optimization of continuum structures with uncertain-but-bounded parameters for maximum non-probabilistic reliability of frequency requirement

2015 ◽  
Vol 23 (16) ◽  
pp. 2557-2566 ◽  
Author(s):  
Bin Xu ◽  
Lei Zhao ◽  
Yi Min Xie ◽  
Jiesheng Jiang
Keyword(s):  
Topology Optimization ◽  
Reliability Index ◽  
Optimization Problems ◽  
Mass Density ◽  
Limit State ◽  
Optimization Procedure ◽  
State Equation ◽  
Outer Loop ◽  
Continuum Structures ◽  
Beso Method

A method for the non-probabilistic reliability optimization on frequency of continuum structures with uncertain-but-bounded parameters is proposed. The objective function is to maximize the non-probabilistic reliability index of frequency requirement.The corresponding bi-level optimization model is built, where the constraints are applied on the material volume in the outer loop and the limit state equation in the inner loop. The non-probabilistic reliability index of frequency requirement is derived by the analytical method for the continuum structure with the uncertain elastic module and mass density. Further, the sensitivity of the non-probabilistic reliability index with respect to the design variables is analyzed. The topology optimization in the outer loop is performed by a bi-directional evolutionary structural optimization (BESO) method, where the numerical techniques and the optimization procedure of BESO method are presented. Numerical results show that the proposed BESO method is efficient, and convergent optimal solutions can be achieved for a variety of optimization problems on frequency non-probabilistic reliability of continuum structures.

Research on Evolutionary Topology Optimization in ANSYS

2013 ◽  
Vol 572 ◽  
pp. 547-550 ◽  
Author(s):  
Dong Yan Shi ◽  
Jia Shan Han ◽  
Ling Cheng Kong ◽  
Lin Lin
Keyword(s):  
Topology Optimization ◽  
Optimization Method ◽  
Secondary Development ◽  
Filter Method ◽  
Ansys Software ◽  
Evolutionary Structural Optimization ◽  
Elemental Sensitivity ◽  
Beso Method ◽  
Optimization Function ◽  
2D And 3D

Topology optimization function in ANSYS software is inefficient with the limitation of element types. By using the secondary developing language APDL and UIDL, the secondary development of bi-directional evolutionary structural optimization (BESO) method with volume constraint and stiffness maximization is completed in ANSYS. To suppress the checkerboard patterns, the elemental sensitivity numbers are recalculated by a filter method. To ensure the convergence of the optimization method in ANSYS, the elemental sensitivity numbers are updated by adding in their historical information. Two classic numerical examples are calculated to obtain the best topology structure. The numerical results indicate that the secondary method can solve the 2D and 3D problems effectively, which makes up for the deficiency of topology optimization part in ANSYS and broadens the application scope of the evolutionary optimization method.

Motorcycle Tire Modeling

2015 ◽  
Author(s):  
Federico Ballo ◽  
Massimiliano Gobbi ◽  
Giampiero Mastinu ◽  
Giorgio Previati ◽  
Roberto Zerboni
Keyword(s):  
Analytical Model ◽  
Lightweight Design ◽  
Experimental Tests ◽  
Contact Forces ◽  
Fe Model ◽  
Actual Distribution ◽  
Axial Forces ◽  
Wide Range ◽  
Tire Modeling ◽  
Explicit Formulae

The knowledge of the actual distribution of the contact forces transmitted by the tire to the rim is of crucial importance for the lightweight design of motorcycles wheels. In this paper, an analytical model of a motorcycle tire is developed and explicit formulae giving the distribution of the static radial and axial forces acting between the tyre and the rim for a given vertical load have been derived. The analytical model has been validated by means of a FE model of the tire and wheel and on the basis of indoor experimental tests. The proposed analytical model is able to predict the radial static deflection of both a front and a rear tire for a racing motorbike with very good accuracy over a wide range of inflating pressures and vertical loads. The force distributions are in very good agreement with the results of the FE model.

Topology Optimization of Compliant Mechanisms Using Evolutionary Algorithm With Design Geometry Encoded as a Graph

2002 ◽  
Author(s):  
Shamim Akhtar ◽  
Kang Tai ◽  
Jitendra Prasad
Keyword(s):  
Topology Optimization ◽  
Evolutionary Algorithm ◽  
Optimization Problems ◽  
Compliant Mechanism ◽  
Evolutionary Process ◽  
Optimization Procedure ◽  
Structural Topology ◽  
Mutation Operators ◽  
Design Variables ◽  
Straight Line

This paper describes an intuitive way of defining geometry design variables for solving structural topology optimization problems using an evolutionary algorithm (EA). The geometry representation scheme works by defining a skeleton which represents the underlying topology/connectivity of the continuum structure. As the effectiveness of any EA is highly dependent on the chromosome encoding of the design variables, the encoding used here is a graph which reflects this underlying topology so that the genetic crossover and mutation operators of the EA can recombine and preserve any desirable geometric characteristics through succeeding generations of the evolutionary process. The overall optimization procedure is applied to design a straight-line compliant mechanism : a large displacement flexural structure that generates a vertical straight line path at some point when given a horizontal straight line input displacement at another point.

scholarly journals A Hole Nucleation Method Combining BESO and Topological Sensitivity for Level Set Topology Optimization

Materials ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2119
Author(s):  
Shuangyuan Cao ◽  
Hanbin Wang ◽  
Jianbin Tong ◽  
Zhongqi Sheng
Keyword(s):  
Topology Optimization ◽  
Level Set ◽  
Volume Ratio ◽  
Optimization Method ◽  
Sensitivity Threshold ◽  
Design Domain ◽  
Topological Sensitivity ◽  
Classical Level ◽  
Evolutionary Structural Optimization ◽  
Beso Method

As is known to all, the incapacity to nucleate holes automatically in the design domain is one of the main issues of the classical level set topology optimization method. To solve the issue of hole nucleation, this paper employs the bi-directional evolutionary structural optimization (BESO) method based on the material removal scheme and the frequently used topological sensitivity and proposes the combining BESO and topological sensitivity (CBT) method for level set topology optimization. This method can replace the existing hole nucleation method for level set topology optimization. First, the topological sensitivity is combined with BESO, and the BESO method based on topological sensitivity is proposed. Second, the method is integrated into level set topology optimization to solve the issue of hole nucleation. Two sensitivity thresholds are defined depending on the evolutionary volume ratio and boundary topological sensitivity, respectively, and the smaller one is used as the sensitivity threshold for hole nucleation. The material is removed from the design domain to nucleate holes based on this threshold. Three classical two-dimensional numerical examples are used to validate the proposed hole nucleation method.

An Efficient Method for Topology Optimization of Continuum Structures in the Presence of Uncertainty in Loading Direction

2016 ◽  
Vol 14 (05) ◽  
pp. 1750054 ◽  
Author(s):  
Jie Liu ◽  
Guilin Wen ◽  
Qixiang Qing ◽  
Yi Min Xie
Keyword(s):  
Topology Optimization ◽  
Efficient Method ◽  
Continuum Structures ◽  
Topology Optimization Problem ◽  
Multiple Load Cases ◽  
Evolutionary Structural Optimization ◽  
Interval Uncertainties ◽  
Beso Method ◽  
Multiple Load ◽  
Nonsymmetric Loading

This paper presents a simple yet efficient method for the topology optimization of continuum structures considering interval uncertainties in loading directions. Interval mathematics is employed to equivalently transform the uncertain topology optimization problem into a deterministic one with multiple load cases. An efficient soft-kill bi-directional evolutionary structural optimization (BESO) method is proposed to solve the problem, which only requires two finite element analyses per iteration for each external load with directional uncertainty regardless of the number of the multiple load cases. The presented algorithm leads to significant computational savings when compared with Monte Carlo-based optimization (MCBO) algorithms. A series of numerical examples including symmetric and nonsymmetric loading variations demonstrate the considerable improvement of computational efficiency of the proposed approach as well as the significance of including uncertainties in topology optimization when to design a structure. Optimums obtained from the proposed algorithm are verified by MCBO method.

A Two-Stage Optimization Procedure for the Design of an EAP-Actuated Soft Gripper

2019 ◽  
Author(s):  
Wei Zhang ◽  
Jonathan Hong ◽  
Saad Ahmed ◽  
Zoubeida Ounaies ◽  
Mary Frecker
Keyword(s):  
Design Optimization ◽  
Compliant Mechanisms ◽  
Optimization Problems ◽  
Beam Theory ◽  
Optimization Procedure ◽  
Analytical Models ◽  
Euler Beam ◽  
Two Stage ◽  
Nsga Ii ◽  
Wide Range

Abstract An increasing range of engineering applications require soft grippers, which use compliant mechanisms instead of stiff components to achieve grasping action, have high conformability and exert gentle contact with target objects compared to traditional grippers. In this study, a three-fingered gripper is first designed based on a notched self-folding mechanism actuated using an electrostrictive PVDF-based terpolymer. Then the design optimization problem is formulated, where the design objectives are to maximize the free deflection Δfree and the blocked force Fb. A computationally efficient two-stage design optimization procedure is proposed and successfully applied in the gripper design. NSGA-II is adopted as the optimization algorithm for its capacity to deal with multi-objective optimization problems and to find the global optima with high design variables and large design domains. In stage one, computationally less expensive analytical models are developed based on Bernoulli-Euler beam theory and Castigliano’s theorem to calculate Δfree and Fb. Utility function is applied to determine the best design in the last generation of stage one. In stage two, 3D FEA models are developed, using the dimensions determined by the best design from stage one, to investigate effect of the shape of segment surfaces on the design objectives. Overall, the proposed two-stage optimization procedure is successfully applied in the actuator design and shows the potential to solve a wide range of structural optimization problems.

scholarly journals Influence of Density-Based Topology Optimization Parameters on the Design of Periodic Cellular Materials

Materials ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 3736
Author(s):  
Hugo A. Alvarez ◽  
Habib R. Zambrano ◽  
Olavo M. Silva
Keyword(s):  
Topology Optimization ◽  
Optimization Problems ◽  
Optimization Procedure ◽  
Optimality Criteria ◽  
Cellular Materials ◽  
Initial Guess ◽  
Method Of Moving Asymptotes ◽  
Optimization Parameters ◽  
Common Technique ◽  
Moving Asymptotes

The density based topology optimization procedure represented by the SIMP (Solid isotropic material with penalization) method is the most common technique to solve material distribution optimization problems. It depends on several parameters for the solution, which in general are defined arbitrarily or based on the literature. In this work the influence of the optimization parameters applied to the design of periodic cellular materials were studied. Different filtering schemes, penalization factors, initial guesses, mesh sizes, and optimization solvers were tested. In the obtained results, it was observed that using the Method of Moving Asymptotes (MMA) can be achieved feasible convergent solutions for a large amount of parameters combinations, in comparison, to the global convergent method of moving asymptotes (GCMMA) and optimality criteria. The cases of studies showed that the most robust filtering schemes were the sensitivity average and Helmholtz partial differential equation based filter, compared to the Heaviside projection. The choice of the initial guess demonstrated to be a determining factor in the final topologies obtained.

A New ESO-Based Method to Find the Optimal Topology of Structures Subject to Multiple Load Conditions

2014 ◽  
Vol 670-671 ◽  
pp. 902-906
Author(s):  
Davide Tumino ◽  
Tommaso Ingrassia ◽  
Vincenzo Nigrelli
Keyword(s):  
Topology Optimization ◽  
Optimization Problems ◽  
Load Condition ◽  
Optimal Topology ◽  
Mass Reduction ◽  
Evolutionary Structural Optimization ◽  
Definition Of ◽  
Computational Resources ◽  
Multiple Load ◽  
Load Conditions

In the field of topology optimization problems, the Evolutionary Structural Optimization (ESO) method is one of the most popular and easy to use. When dealing with problems of reasonable difficulty, the ESO method is able to give very good results in reduced times and with a limited request of computational resources. Generally, main applications of this method are addressed to the definition of the optimal topology of a component subjected to a single load condition. In this work, a new methodology, based on the ESO approach, is introduced for the study of the optimal topology of a component subjected to multiple load conditions. The new procedure, entirely developed in the APDL programming language, has been tested with a holed plate subject to two different load conditions; the obtained results are promising in terms of mass reduction and structural performances.

Creating Innovative and Efficient Structures and Materials

2013 ◽  
Vol 438-439 ◽  
pp. 439-444
Author(s):  
Yi Min Xie ◽  
Zhi Hao Zuo ◽  
Xiao Dong Huang ◽  
Ji Wu Tang ◽  
Xiao Ying Yang ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Optimal Design ◽  
Structural Optimization ◽  
Structural Systems ◽  
Design Problems ◽  
Practical Applications ◽  
Evolutionary Structural Optimization ◽  
Recent Developments ◽  
Beso Method ◽  
Industrial Projects

Novel and efficient structural and material designs can be realized by topology optimization that is capable of maximizing the performance of structural systems under given constraints. The bi-directional evolutionary structural optimization (BESO) method has been developed into an effective tool for topology optimization of load-bearing structures and materials. The latest advances of BESO are aimed at expanding its practical applications to a wider range of structural systems on both macro and micro scales. This paper presents recent developments of BESO for optimal design problems of a variety of structural systems ranging from buildings of large scales to materials of micro scales. Selected applications are introduced to demonstrate the capability of BESO. Examples presented in this paper are based on research and industrial projects of the Centre for Innovative Structures and Materials (http://www.rmit.edu.au/research/cism) at RMIT University.

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