Topology optimization applied to the design of actuators driven by pressure loads

Moscatelli, Eduardo; Silva, Emilío Carlos Nelli

doi:10.1007/s00158-019-02421-5

Cited by 27 publications

(15 citation statements)

References 39 publications

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“…Vasista and Tong [20] employed the solid isotropic material with penalization (SIMP) and the moving isosurface threshold methods in their approach. de Souza and Silva [21] also employed the method proposed by Sigmund and Clausen [16]. In our previous study [9], the authors presented a design method using Darcy's law in conjunction with a drainage term.…”

Section: Background and Approachmentioning

confidence: 99%

Topological synthesis of fluidic pressure-actuated robust compliant mechanisms

Kumar

Langelaar

2022

Mechanism and Machine Theory

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Section: Background and Approachmentioning

confidence: 99%

Topological synthesis of fluidic pressure-actuated robust compliant mechanisms

Kumar

Langelaar

2022

Mechanism and Machine Theory

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“…The problem of topology optimizing a soft actuator while maintaining a variable sized, closed actuation chamber is addressed using a mixed formulation SIMP approach. [ 119 ] A projection technique is developed which avoids the formation of holes in the solid material layer by forming a solid boundary between interior and exterior regions. In both cases, linear materials and deformations were assumed in the FEA solver resulting in physically unrealizable or undesirable solutions.…”

Section: Topology Optimizationmentioning

confidence: 99%

From Bioinspiration to Computer Generation: Developments in Autonomous Soft Robot Design

Pinskier

Howard

2021

Advanced Intelligent Systems

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The emerging field of soft robotics presents a new paradigm for robot design in which “precision through rigidity” is replaced by “cognition through compliance.” Lightweight and flexible, soft robots have vast potential to interact with fragile objects and navigate unstructured environments. Like octopuses and worms in nature, soft robots’ flexible bodies conform to hard objects and reconfigure for different tasks, delegating the burden of control from brain to body through embodied cognition. However, because of the lack of efficient modeling and simulation tools, soft robots are primarily designed by hand. Typically, hard components from rigid robots or living creatures are heuristically substituted for comparable soft ones. Autonomous design and manufacturing methodologies are urgently required to produce bespoke, high‐performing robots. Currently, design methodologies exist between simple but realistic parametric optimizations, and evolutionary algorithms which simulate morphology and control coevolution. To find high‐performing designs, novel high‐fidelity simulators and high‐throughput manufacturing and testing processes are required to explore the complex soft material, morphology and control landscape, blending simulation, and experimental data. This article reviews the state of the art in autonomous soft robotic design. Existing manual and automated designs are surveyed and future directions to automate soft robot design and manufacturing are presented.

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“…Since, parallelization in FEniCS works by splitting the mesh into 'n' parts -where 'n' is the number of processorsand then passing only a portion of the mesh to a single processor, the information required for computation of the filter is not available with each processor. Thus, to make the code compatible for parallel computation we have to change the filter to the Helmholtz filter as described in [41,27]. Parallel computation can then be performed on 16 cores by running the command:…”

Section: Parallel Implementation Of Topology Optimizationmentioning

confidence: 99%

A 55-line code for large-scale parallel topology optimization in 2D and 3D

Gupta,

Chowdhury,

Chakrabarti

et al. 2020

Preprint

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This paper presents a 55-line code written in python for 2D and 3D topology optimization (TO) based on the open-source finite element computing software (FEniCS), equipped with various finite element tools and solvers. PETSc is used as the linear algebra back-end, which results in significantly less computational time than standard python libraries. The code is designed based on the popular solid isotropic material with penalization (SIMP) methodology. Extensions to multiple load cases, different boundary conditions, and incorporation of passive elements are also presented. Thus, this implementation is the most compact implementation of SIMP based topology optimization for 3D as well as 2D problems.Utilizing the concept of Euclidean distance matrix to vectorize the computation of the weight matrix for the filter, we have achieved a substantial reduction in the computational time and have also made it possible for the code to work with complex ground structure configurations. We have also presented the code's extension to large-scale topology optimization problems with support for parallel computations on complex structural configuration, which could help students and researchers explore novel insights into the TO problem with dense meshes. Appendix A contains the complete code, and the website: https: //github.com/iitrabhi/topo-fenics also contains the complete code.

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Topology optimization applied to the design of actuators driven by pressure loads

Cited by 27 publications

References 39 publications

Topological synthesis of fluidic pressure-actuated robust compliant mechanisms

Topological synthesis of fluidic pressure-actuated robust compliant mechanisms

From Bioinspiration to Computer Generation: Developments in Autonomous Soft Robot Design

A 55-line code for large-scale parallel topology optimization in 2D and 3D

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