scholarly journals Computational design of finite strain auxetic metamaterials via topology optimization and nonlinear homogenization

2019 ◽  
Vol 356 ◽  
pp. 490-527 ◽  
Author(s):  
Guodong Zhang ◽  
Kapil Khandelwal
Keyword(s):  
Topology Optimization ◽  
Finite Strain ◽  
Computational Design ◽  
Nonlinear Homogenization

scholarly journals Computational design of thermo-mechanical metadevices using topology optimization

2021 ◽  
Vol 90 ◽  
pp. 758-776
Author(s):  
Juan C. Álvarez Hostos ◽  
Víctor D. Fachinotti ◽  
Ignacio Peralta
Keyword(s):  
Topology Optimization ◽  
Computational Design

Topology Optimization of Rigid-Body Systems Considering Collision Avoidance

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Fritz Stöckli ◽  
Kristina Shea
Keyword(s):  
Topology Optimization ◽  
Rigid Body ◽  
Collision Avoidance ◽  
Optimization Problems ◽  
Computational Design ◽  
Optimization Method ◽  
The Body ◽  
Graph Grammar ◽  
Automated Synthesis ◽  
Inertia Properties

Abstract Passive dynamic mechanisms can perform simple robotic tasks without requiring actuators and control. In previous research, a computational design method was introduced that integrates dynamic simulation to evaluate and evolve configurations of such mechanisms. It was shown to find multiple solutions of passive dynamic brachiating robots (Stöckli and Shea, 2017, “Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method,” J. Mech. Des. 139(9), p. 092301). However, these solutions are limited, since bodies are modeled only by their inertia properties and thus lack a shape embodiment. This paper presents a method to generate rigid-body topologies based on given inertia properties. The rule-based topology optimization method presented guarantees that the topology is manifold, meaning that it has no disconnected parts, while still connecting all joints that need to be part of the body. Furthermore, collisions with the environment, as well as with other bodies, during their predefined motion trajectories are avoided. A collision matrix enables efficient collision detection as well as the calculation of the swept area of one body in the design space of another body by only one matrix–vector multiplication. The presented collision avoidance method proves to be computationally efficient and can be adopted for other topology optimization problems. The method is shown to solve different tasks, including a reference problem as well as passive dynamic brachiating mechanisms. Combining the presented methods with the simulation-driven method from Stöckli and Shea (2017, “Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method,” J. Mech. Des. 139(9), p. 092301), the computational design-to-fabrication of passive dynamic systems is now possible and solutions are provided as STL files ready to be 3D-printed directly.

Checking the Automated Construction of Finite Element Simulations From Dirichlet Boundary Conditions

2019 ◽  
Author(s):  
Kevin N. Chiu ◽  
Mark D. Fuge
Keyword(s):  
Finite Element ◽  
Topology Optimization ◽  
Boundary Conditions ◽  
Dirichlet Boundary ◽  
Fem Simulation ◽  
Computational Design ◽  
Dirichlet Boundary Conditions ◽  
Governing Equations ◽  
Variational Form ◽  
Key Issues

Abstract From engineering analysis and topology optimization to generative design and machine learning, many modern computational design approaches require either large amounts of data or a method to generate that data. This paper addresses key issues with automatically generating such data through automating the construction of Finite Element Method (FEM) simulations from Dirichlet boundary conditions. Most past work on automating FEM assumes prior knowledge of the physics to be run or is limited to a small number of governing equations. In contrast, we propose three improvements to current methods of automating the FEM: (1) completeness labels that guarantee viability of a simulation under specific conditions, (2) type-based labels for solution fields that robustly generate and identify solution fields, and (3) type-based labels for variational forms of governing equations that map the three components of a simulation set — specifically, boundary conditions, solution fields, and a variational form — to each other to form a viable FEM simulation. We implement these improvements using the FEniCS library as an example case. We show that our improvements increase the percent of viable simulations that are run automatically from a given list of boundary conditions. This paper’s procedures ultimately allow for the automatic — i.e., fully computer-controlled — construction of FEM multi-physics simulations and data collection required to run data-driven models of physics phenomena or automate the exploration of topology optimization under many physics.

scholarly journals Eigenfrequency constrained topology optimization of finite strain hyperelastic structures

2020 ◽  
Vol 61 (6) ◽  
pp. 2577-2594 ◽  
Author(s):  
Anna Dalklint ◽  
Mathias Wallin ◽  
Daniel A. Tortorelli
Keyword(s):  
Topology Optimization ◽  
Finite Strain

scholarly journals An Open Source Framework for Integrated Additive Manufacturing and Level-Set-Based Topology Optimization

2017 ◽  
Vol 17 (4) ◽  
Author(s):  
Panagiotis Vogiatzis ◽  
Shikui Chen ◽  
Chi Zhou
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
3D Printing ◽  
Open Source ◽  
Level Set ◽  
Optimization Procedure ◽  
Computational Design ◽  
Standard Format ◽  
Practical Algorithms ◽  
Open Source Framework

Topology optimization has been considered as a promising tool for conceptual design due to its capability of generating innovative design candidates without depending on the designer's intuition and experience. Various optimization methods have been developed through the years, and one of the promising options is the level-set-based topology optimization method. The benefit of this alternative method is that the design is characterized by its clear boundaries. This advantage can avoid postprocessing work in conventional topology optimization process to a large extent and realize direct integration between topology optimization and additive manufacturing (AM). In this paper, practical algorithms and a matlab-based open source framework are developed to seamlessly integrate the level-set-based topology optimization procedure with AM process by converting the design to STereoLithography (STL) files, which is the de facto standard format for three-dimensional (3D) printing. The proposed algorithm and code are evaluated by a proof-of-concept demonstration with 3D printing of both single and multimaterial topology optimization results. The algorithm and the open source framework proposed in this paper will be beneficial to the areas of computational design and AM.

Computational Design and Additive Manufacturing of Conformal Metasurfaces by Combining Topology Optimization With Riemann Mapping Theorem

2017 ◽  
Author(s):  
Panagiotis Vogiatzis ◽  
Ming Ma ◽  
Shikui Chen ◽  
Xianfeng David Gu
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Conformal Mapping ◽  
Level Set ◽  
Computational Design ◽  
Unit Cell ◽  
Free Form ◽  
Computational Framework ◽  
Riemann Mapping Theorem ◽  
Free Form Surfaces

In this paper, we present a computational framework for computational design and additive manufacturing of spatial free-form periodic metasurfaces. The proposed scheme rests on the level-set based topology approach and the conformal mapping theory. A 2D unit cell of metamaterial with tailored effective properties is created using the level-set based topology optimization method. The achieved unit cell is further mapped to the 3D quad meshes on a free-form surface by applying the conformal mapping method which can preserve the local shape and angle when mapping the 2D design to a 3D surface. The proposed level-set based optimization methods not only can act as a motivator for design synthesis, but also can be seamlessly hooked with additive manufacturing with no need of CAD reconstructions. The proposed computational framework provides a solution to increasing applications involving innovative metamaterial designs on free-form surfaces in different fields of interest. The performance of the proposed scheme is illustrated through a benchmark example where a negative-Poisson’s-ratio unit cell pattern is mapped to a 3D human face and fabricated through additive manufacturing.

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