Evolutionary topology optimization for structures made of multiple materials with different properties in tension and compression

Yu, Li; Xie, Yi Min

doi:10.1016/j.compstruct.2020.113497

Cited by 45 publications

(11 citation statements)

References 26 publications

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“…Most of the early works on topology optimization focused on maximizing structural stiffness (Bendsøe and Kikuchi 1988;Rozvany et al 1992;Xie and Steven 1993). Later, other effects have also been considered by researchers, such as natural frequencies , multiple materials (Huang and Xie 2009;Li and Xie 2021), structural complexity (He et al 2020(He et al , 2022, additive manufacturability (Bi et al 2020(Bi et al , 2022, and principal stress (Amir 2017;Chen et al 2021). In addition, topology optimization under buckling constraints is regarded as a challenging and important topic.…”

Section: Introductionmentioning

confidence: 99%

Bi-directional evolutionary structural optimization with buckling constraints

Lin

Xie

2023

Struct Multidisc Optim

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Buckling is a critical phenomenon in structural members under compression, which could cause catastrophic failure of a structure. To increase the buckling resistance in structural design, a novel topology optimization approach based on the bi-directional evolutionary structural optimization (BESO) method is proposed in this study with the consideration of buckling constraints. The BESO method benefits from using only two discrete statuses (solid and void) for design variables, thereby alleviating numerical issues associated with pseudo buckling modes. The Kreisselmeier-Steinhauser aggregation function is introduced to aggregate multiple buckling constraints into a differentiable one. An augmented Lagrangian multiplier is developed to integrate buckling constraints into the objective function to ensure computational stability. Besides, a modified design variable update scheme is proposed to control the evolutionary rate after the target volume fraction is reached. Four topology optimization design examples are investigated to demonstrate the effectiveness of the buckling-constrained BESO method. The numerical results show that the developed optimization algorithm with buckling constraints can significantly improve structural stability with a slight increase in compliance.

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Section: Introductionmentioning

confidence: 99%

Bi-directional evolutionary structural optimization with buckling constraints

Lin

Xie

2023

Struct Multidisc Optim

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“…These designs have numerous applications in various industries, including aerospace, automotive, and construction. [22][23][24][25][26] As such, this research aims, to implement concurrent multiscale and multiphysics topology optimization for attaining the optimal design of lightweight, and stiff porous composite structures that have high sustainability toward hygro and thermal loading. This goal is attained by utilizing two engineering aspects which are: hygro-thermo-elastic coupling structural analysis, and concurrent multiscale optimization for the multiphysics problem.…”

Section: Introductionmentioning

confidence: 99%

“…As a result of this development, the production of extremely efficient and lightweight structures has become possible, which would have been difficult to achieve with conventional manufacturing techniques. These designs have numerous applications in various industries, including aerospace, automotive, and construction 22–26 …”

Section: Introductionmentioning

confidence: 99%

On concurrent multiscale topology optimization for porous structures under hygro‐thermo‐elastic multiphysics with considering evaporation

Ali

Shimoda

2023

Numerical Meth Engineering

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Lightweight polymeric and natural composite materials are extensively used in modern structures, especially with the demands for environmentally friendly products as well as lowering energy consumption. Furthermore, a high performance‐to‐weight ratio can be attained by utilizing porous composites. However, hygral and thermally induced loads are limiting the robustness of polymeric and natural composite materials, therefore; in this research, concurrent multiscale multiphysics topology optimization is used to design lightweight porous composite structures that have resilience toward mechanical as well as hygral and thermal loads. By establishing two independent representations of the design problem, that is, macro and microscale domains, a concurrent topology optimization framework is implemented, and the effective properties of the microscale (i.e., elastic, thermal conductivity, moisture diffusivity tensors, and hygral as well as thermal expansion coefficients) are calculated and used as the hygro‐thermo‐elastic properties of the macroscale using in‐house MATLAB codes. For hygral physics, moisture transport, as well as evaporation, are simultaneously considered in this study. A sensitivity analysis was conducted on the multiphysics concurrent optimization scheme in order to account for the coupling of macro and microstructure, as well as hygro‐thermo‐elastic physics. Multiple numerical cases were examined, which included different loading and boundary conditions, as well as various spatial configurations. The results showed attaining a high stiffness‐to‐weight ratio for the multiscale optimized porous structure compared to the single‐scale solid structure. Furthermore, a study was conducted on multiple microstructure subsystems to examine the impact of microstructure systems on macrostructure dependence. By combining several microstructures into a single macro design domain, design flexibility was enhanced and the performance‐to‐weight ratio was improved. The study was expanded to include the evaluation of hygro‐thermo‐elastic multiscale multiphysics with an evaporation problem, which was demonstrated through several numerical examples. The introduced formulations showed a successful application of the concurrent multiscale optimization formulations and good coupling on the macro and microscale. Also, the formulations demonstrated a strong influence between the macro and the microscale of the design problem for the topology optimization methods. The successful application of the concurrent multiscale optimization method in this research highlights its potential for designing more efficient and effective structures in the future.

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“…The most examined design case is that considering structural mean compliance minimization, subjected to a volume constraint 7 . Moreover, the latest versions of BESO method have effectively shown a promising performance when considering it for different topology design problems such as geometrically nonlinear 8 , 9 , composite materials 10 , 11 , and elasto-plastic analysis 12 .…”

Section: Introductionmentioning

confidence: 99%

Reliability based geometrically nonlinear bi-directional evolutionary structural optimization of elasto-plastic material

Habashneh

Rad

2022

Sci Rep

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The aim of this paper is to integrate the reliability-based analysis into topology optimization problems. Consequently, reliability-based topology optimization (RBTO) of geometrically nonlinear elasto-plastic models is presented. For purpose of performing (RBTO), the volume fraction is considered reliable since that the application of (RBTO) gives different topology in comparison to the deterministic topology optimization. The effects of changing the prescribed total structural volume constraint for deterministic designs and changing the reliability index for probabilistic designs are considered. Reliability index works as a constraint which is related to reliability condition added into the volume fraction and it is calculated using the Monte-Carlo simulation approach in the case of probabilistic design. In addition, bi-directional evolutionary structural optimization (BESO) method is utilized to study the effect of geometrically nonlinear elasto-plastic design. The plastic behavior can be controlled by defining a limit on the plastic limit load multipliers. The suggested work's efficiency is demonstrated via a 2D benchmark problem. In case of elastic material, a 2D model of U-shape plate is used for probabilistic design of linear and geometrically nonlinear topology optimizations. Furthermore, a 2D elasto-plastic model is considered for reliability-based design to demonstrate that the suggested approach can determine the best topological solution.

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Evolutionary topology optimization for structures made of multiple materials with different properties in tension and compression

Cited by 45 publications

References 26 publications

Bi-directional evolutionary structural optimization with buckling constraints

Bi-directional evolutionary structural optimization with buckling constraints

On concurrent multiscale topology optimization for porous structures under hygro‐thermo‐elastic multiphysics with considering evaporation

Reliability based geometrically nonlinear bi-directional evolutionary structural optimization of elasto-plastic material

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