Topology Optimization of a Bi-Stable Airfoil Using Nonlinear Elasticity

Bhattacharyya, Anurag; Conlan-Smith, Cian; James, Kai A.

doi:10.2514/6.2017-3656

Cited by 4 publications

(7 citation statements)

References 34 publications

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“…As shown in [9], the MMA is one of the most suitable optimizers which could substitute the Optimality Criteria adopted in the 88-line code by Sigmund [52], in order to accelerate convergence.…”

Section: Optimizer: Methods Of Moving Asympthotesmentioning

confidence: 99%

“…A nonlinear hyperelastic material was investigated: the same methods described in [9] were adopted, but modifying the proposed algorithm in order to achieve the same results as well as a fast convergence. Moreover, far too little attention has been paid to the feasibility of the structure itself: this can be observed by the absence of a constraint related to the maximum stress supportable by the material.…”

Section: New Formulation 31 Materials Descriptionmentioning

confidence: 99%

“…In the literature, several promising applications of TO to classical aerospace structures can be found [9][10][11][12][13]. Recently, researchers have shown an increased interest in alternative architectures presenting wings with a variable geometry, better known as "morphing wings" [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…Work from [24] evidences the differences encountered in a TO problem, according to the choice of a linear or a nonlinear analysis, leading to totally different results. The introduction of Nonlinear Mechanics into the TO of a morphing wing has already been treated by Bhattacharyya et al [9]: in particular, geometric and material nonlinearities have been investigated. In [9], the optimization problem presents the objective of minimizing the actuating force, under constraints of desired volume fraction, compliance and trailing edge displacement.…”

Section: Introductionmentioning

confidence: 99%

“…The introduction of Nonlinear Mechanics into the TO of a morphing wing has already been treated by Bhattacharyya et al [9]: in particular, geometric and material nonlinearities have been investigated. In [9], the optimization problem presents the objective of minimizing the actuating force, under constraints of desired volume fraction, compliance and trailing edge displacement. The obtained structure is, in fact, a compliant mechanism capable of getting a geometric advantage.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Stress-based topology optimization of compliant mechanisms using nonlinear mechanics

Capasso¹,

Morlier²,

Charlotte³

et al. 2020

Mechanics & Industry

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The present work demonstrates how a light structure can be easily designed through Topology Optimization even including complex analysis and sizing criteria such as hyperelastic Neo-Hookean materials for nonlinear analysis and aggregated stress constraints. The SIMP approach was adopted and two different strategies were analysed using an in house versatile MATLAB code. MMA was used as reference optimizer (in structural optimization) whereas a unified aggregation and relaxation method was adopted to deal with stress constraints. Feasibility was analyzed from the viewpoint of allowable stress verification. Two test cases are then studied: a morphing airfoil (for aeronautical applications) and a geometric inverter (for mechanics and bio-medical applications). For both, a hyperelastic Neo-Hookean material was chosen. Finally a complementary study on the effects of constraints and the input force intensity is also presented.

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Section: Optimizer: Methods Of Moving Asympthotesmentioning

confidence: 99%

Section: New Formulation 31 Materials Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Stress-based topology optimization of compliant mechanisms using nonlinear mechanics

Capasso¹,

Morlier²,

Charlotte³

et al. 2020

Mechanics & Industry

View full text Add to dashboard Cite

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Multidisciplinary Topology Optimization Using Generative Adversarial Networks for Physics-Based Design Enhancement

Parrott

Abueidda

James

2023

Journal of Mechanical Design

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The computational cost of traditional gradient-based topology optimization is amplified for multidisciplinary design optimization (MDO) problems, most notably when coupling between physics disciplines is accounted for. To alleviate this, we investigate new methods and applications of generative adversarial networks (GANs) as a surrogate for MDO. Accepting physical fields from each physics discipline as input, the trained network produces an optimal design that closely resembles that of the iterative gradient-based approach. With this model as a baseline, we introduce a novel architecture that performs physics-based design enhancement of optimal single-physics designs to produce multiphysics designs. By providing the network with boundary conditions from a secondary physics discipline, we obtain multiphysics structures while avoiding the need for costly coupled multiphysics analysis, thereby generating significant savings in computational effort. We demonstrate our approach by designing a series of structures optimized for both thermal and elastic performance. With the physics-based design enhancement GAN, we obtain thermoelastic structures that outperform those produced by the baseline multiphysics GAN architecture.

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