Multi-objective optimization of tensile properties of the corrugated composite sheet

2021 ◽  
pp. 002199832110595
Author(s):  
Nastaran Bahrami-Novin ◽  
Ehsan Mahdavi ◽  
Mahdi Shaban ◽  
Hashem Mazaheri
Keyword(s):  
Tensile Test ◽  
Optimization Problems ◽  
Lightweight Design ◽  
Industrial Applications ◽  
Experimental Results ◽  
Displacement Curve ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Programming Technique ◽  
Multi Objective

Corrugated sheets with optimized mechanical properties are crucial for lightweight design in industrial applications. This study considered and optimized a corrugated sheet with a sinusoidal profile to enhance elastic modulus, tensile-bending coupling, and weight reduction. For this aim, first, flat specimens consisting of E-glass woven fiber and epoxy resin were made by hand lay-up method, following ASTM D3039. The tensile test determined young’s modulus of flat samples. Afterward, two molds with supports were fabricated. The corrugated specimens were constructed and exposed to a standard tensile test. The finite element analysis was used to simulate the tensile test of corrugated samples. The numerical force-displacement curve is derived from numerical analysis and verified by experimental results. After that, two multi-objective optimization problems, mass-constraint and global optimization, were implemented. Analytical formulations were verified by numerical and experimental results and utilized for optimization purposes. The genetic algorithm was used to examine and confirm trade-off behavior between objective functions. The Pareto fronts diagrams for mentioned two multi-objective optimization problem were obtained. Finally, the optimum parameters are calculated by using the LINMAP (Linear Programming Technique for Multi-dimensional Analysis of Preference) method.

Lightweight Design of a Brake Caliper

2013 ◽  
Author(s):  
Federico Maria Ballo ◽  
Massimiliano Gobbi ◽  
Giampiero Mastinu ◽  
Amir Pishdad
Keyword(s):  
Cross Sections ◽  
Lightweight Design ◽  
Optimal Solution ◽  
Element Model ◽  
Industrial Applications ◽  
Structural Topology ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Beam Elements ◽  
Starting Point

As lightweight design assumes greater importance in road vehicles development, the present paper is mainly devoted to the structural optimization of a brake caliper. In the first part of the study a simplified finite element model based on beam elements of a brake caliper has been developed and validated. By using the developed model, a multi-objective optimization has been completed. The total mass of the caliper and the deformations at some critical locations have been minimised. The considered design variables are related to the shape of the caliper and the cross sections of the beam elements. The obtained optimal solutions are characterized by an asymmetric shape of the caliper. Optimised symmetric shapes currently used have been compared with the asymmetric ones in terms of performance. In the second part of the study, a detailed analysis on the optimal caliper shape has been carried out by performing a structural topology optimization. The minimum compliance problem has been solved using the SIMP (solid isotropic material with penalization) approach and the optimal solution has been compared with the ones obtained by applying the multi-objective optimization on the simplified model (beam elements). The obtained design solutions represent a good starting point for future developments in actual industrial applications.

scholarly journals Non-dominated sorting Harris’s hawk multi-objective optimizer based on reference point approach

2019 ◽  
Vol 15 (3) ◽  
pp. 1603 ◽  
Author(s):  
Shaymah Akram Yasear ◽  
Ku Ruhana Ku-Mahamud
Keyword(s):  
Reference Point ◽  
Pareto Front ◽  
Optimization Problems ◽  
Population Diversity ◽  
Experimental Results ◽  
Multi Objective Optimization ◽  
Next Generation ◽  
Multi Objective ◽  
Objective Space ◽  
Reference Point Approach

A non-dominated sorting Harris’s hawk multi-objective optimizer (NDSHHMO) algorithm is presented in this paper. The algorithm is able to improve the population diversity, convergence of non-dominated solutions toward the Pareto front, and prevent the population from trapping into local optimal. This was achieved by integrating fast non-dominated sorting with the original Harris’s hawk multi-objective optimizer (HHMO).  Non-dominated sorting divides the objective space into levels based on fitness values and then selects non-dominated solutions to produce the next generation of hawks. A set of well-known multi-objective optimization problems has been used to evaluate the performance of the proposed NDSHHMO algorithm. The results of the NDSHHMO algorithm were verified against the results of an HHMO algorithm. Experimental results demonstrate the efficiency of the proposed NDSHHMO algorithm in terms of enhancing the ability of convergence toward the Pareto front and significantly improve the search ability of the HHMO.

scholarly journals An integrated cuckoo search optimizer for single and multi-objective optimization problems

2021 ◽  
Vol 7 ◽  
pp. e370
Author(s):  
Xiangbo Qi ◽  
Zhonghu Yuan ◽  
Yan Song
Keyword(s):  
Optimization Problems ◽  
Cuckoo Search ◽  
Search Strategies ◽  
Comprehensive Analysis ◽  
Experimental Results ◽  
Test Problems ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multiple Strategies ◽  
Single Objective

Integrating heterogeneous biological-inspired strategies and mechanisms into one algorithm can avoid the shortcomings of single algorithm. This article proposes an integrated cuckoo search optimizer (ICSO) for single objective optimization problems, which incorporates the multiple strategies into the cuckoo search (CS) algorithm. The paper also considers the proposal of multi-objective versions of ICSO called MOICSO. The two algorithms presented in this paper are benchmarked by a set of benchmark functions. The comprehensive analysis of the experimental results based on the considered test problems and comparisons with other recent methods illustrate the effectiveness of the proposed integrated mechanism of different search strategies and demonstrate the performance superiority of the proposed algorithm.

Multi-Objective Optimization of a Large-Span Wing Analog Beam with Variable Cross-Sections

2012 ◽  
Vol 215-216 ◽  
pp. 735-740
Author(s):  
Kui Li ◽  
Yuan Ying Qiu ◽  
Ying Sheng
Keyword(s):  
Curve Fitting ◽  
Optimization Design ◽  
Von Mises Stress ◽  
Deformation Condition ◽  
Displacement Curve ◽  
Variable Cross ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Large Span ◽  
Multi Objective

Aiming at the difficulty with structure and parameter design for a wing analog beam under a large deformation condition, a large-span cantilever truss model with Pro/e is designed. Then a mathematical model of the wing beam based on the Multi-objective Genetic Algorithm is proposed. Thereby the sizing optimization and shape optimization for the wing analog beam are conducted with the finite element analysis and meanwhile two main objectives minimizing the maximum von Mises stress and the mean-square error of the deformation displacement curve fitting are satisfied. A Pareto optimal solution aggregate is obtained after the optimization. Finally an optimal structure is concluded via the multi-objective optimization design, which improves the curve fitting accuracy of the wing and satisfies the stress strength requirement as well.

scholarly journals Multi-Objective Optimization of Microstructure of Gravure Cell Based on Response Surface Method

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 403
Author(s):  
Shuang Wu ◽  
Jiefang Xing ◽  
Ling Dong ◽  
Honjuan Zhu
Keyword(s):  
Response Surface ◽  
Optimization Design ◽  
Design Method ◽  
Cell Structure ◽  
Lightweight Design ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Maximum Deformation ◽  
Multi Objective ◽  
Direct Laser

In order to improve the structural stiffness of the gravure cell structure in the solid printing process and realize a lightweight design, a multi-objective optimization design method was proposed to optimize the parameters of the direct laser engraving of the cell structure. In this paper, based on the characteristics of the cell structure and the analysis of the contact force, the ANSYS parametric design language (APDL) was used to conduct a finite element analysis on the microstructure of the regular hexagonal cell. We found that there is a certain optimization space. Then, a response surface (RSM) method optimization model, using a central composite design (CCD), was established to obtain, and then analyze, the sensitivity of each design variable to the objective functions. Finally, a multi-objective genetic algorithm (MOGA) was used to solve the model. The optimization results show that the maximum deformation was reduced by 44.4%, and the total volume was reduced by 46.3%. By comparing with the model before optimization, the rationality and effectiveness of this method were verified. This shows that the method can be effectively applied to the design optimization of gravure cell microstructure, and it provides theoretical support for new cell design.

Adaptively Allocating Constraint-Handling Techniques for Constrained Multi-objective Optimization Problems

2021 ◽  
pp. 2159032
Author(s):  
Ning Yang ◽  
Hai-Lin Liu
Keyword(s):  
Optimization Problems ◽  
Performance Measure ◽  
Experimental Results ◽  
The Other ◽  
Constraint Handling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Selection Operators ◽  
Handling Technique ◽  
Feasible Solutions

For solving constrained multi-objective optimization problems (CMOPs), an effective constraint-handling technique (CHT) is of great importance. Recently, many CHTs have been proposed for solving CMOPs. However, no single CHT can outperform all kinds of CMOPs. This paper proposes an algorithm, namely, ACHT-M2M, which adaptively allocates the existing CHTs in an M2M framework for solving CMOPs. To be more specific, a CMOP is first decomposed into several constrained multi-objective optimization subproblems by ACHT-M2M. Each subproblem has a subpopulation in a subregion. CHT for each subregion is adaptively allocated according to a proposed composite performance measure. Population for the next generation is selected from subregions by selection operators with different CHTs and the obtained nondominated feasible solutions in each generation are used to update a predefined archive. ACHT-M2M assembles the advantages of different CHTs and makes them cooperate with each other. The proposed ACHT-M2M is finally compared with the other 12 representative algorithms on benchmark CMOPs and the experimental results further confirm the effectiveness of ACHT-M2M for solving CMOPs.

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