Discovering Origami Fold Patterns With Optimal Actuation Through Nonlinear Mechanics Analysis

2017 ◽  
Author(s):  
Andrew Gillman ◽  
Kazuko Fuchi ◽  
Giorgio Bazzan ◽  
Edward J. Alyanak ◽  
Philip R. Buskohl
Keyword(s):  
Topology Optimization ◽  
Optimization Algorithms ◽  
Three Dimensional ◽  
Nonlinear Mechanics ◽  
Optimization Framework ◽  
Mechanics Model ◽  
Truss Model ◽  
Gradient Optimization ◽  
Large Rotations ◽  
Mechanical Actuation

The ability of origami fold patterns to transform two-dimensional sheets into complex three-dimensional structures provides utility for design and development of multifunctional devices. Recently, a topology optimization framework has been developed to discover fold patterns that realize optimal performance including mechanical actuation. This work incorporates an efficient nonlinear mechanics model into the topology optimization framework that accurately captures the geometric non-linearities associated with large rotations of origami facets. A nonlinear truss model, with accommodation for fold stiffness and large rotations, is implemented in both gradient and non-gradient optimization algorithms in this study. The ability of this framework to discover fold topology maximizing actuation motion is verified for the well known “Chomper” and “Square Twist” patterns. In particular, the performance of various optimization algorithms is discussed, and genetic algorithms consistently yield solutions with better performance.

Discovering Sequenced Origami Folding Through Nonlinear Mechanics and Topology Optimization

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Andrew S. Gillman ◽  
Kazuko Fuchi ◽  
Philip R. Buskohl
Keyword(s):  
Topology Optimization ◽  
Design Space ◽  
Optimization Algorithms ◽  
Element Model ◽  
Evolutionary Optimization ◽  
Nonlinear Mechanics ◽  
Design Problems ◽  
Mechanics Model ◽  
Highly Nonlinear ◽  
Evolutionary Optimization Algorithms

Origami folding provides a novel method to transform two-dimensional (2D) sheets into complex functional structures. However, the enormity of the foldable design space necessitates development of algorithms to efficiently discover new origami fold patterns with specific performance objectives. To address this challenge, this work combines a recently developed efficient modified truss finite element model with a ground structure-based topology optimization framework. A nonlinear mechanics model is required to model the sequenced motion and large folding common in the actuation of origami structures. These highly nonlinear motions limit the ability to define convex objective functions, and parallelizable evolutionary optimization algorithms for traversing nonconvex origami design problems are developed and considered. The ability of this framework to discover fold topologies that maximize targeted actuation is verified for the well-known “Chomper” and “Square Twist” patterns. A simple twist-based design is also discovered using the verified framework. Through these case studies, the role of critical points and bifurcations emanating from sequenced deformation mechanisms (including interplay of folding, facet bending, and stretching) on design optimization is analyzed. In addition, the performance of both gradient and evolutionary optimization algorithms are explored, and genetic algorithms (GAs) consistently yield solutions with better performance given the apparent nonconvexity of the response-design space.

scholarly journals Two view NURBS reconstruction based on GACO model

2021 ◽  
Author(s):  
Deepika Saini ◽  
Sanoj Kumar ◽  
Manoj K. Singh ◽  
Musrrat Ali
Keyword(s):  
Optimization Algorithms ◽  
Three Dimensional ◽  
Optimization Procedure ◽  
Least Square ◽  
Ant Colony ◽  
Free Form ◽  
Reconstruction Process ◽  
Nurbs Curve ◽  
Data Points ◽  
Ant Colony Optimization Algorithms

AbstractThe key job here in the presented work is to investigate the performance of Generalized Ant Colony Optimizer (GACO) model in order to evolve the shape of three dimensional free-form Non Uniform Rational B-Spline (NURBS) curve using stereo (two) views. GACO model is a blend of two well known meta-heuristic optimization algorithms known as Simple Ant Colony and Global Ant Colony Optimization algorithms. Basically, the work talks about the solution of NURBS-fitting based reconstruction process. Therefore, GACO model is used to optimize the NURBS parameters (control points and weights) by minimizing the weighted least-square errors between the data points and the fitted NURBS curve. The algorithm is applied by first assuming some pre-fixed values of NURBS parameters. The experiments clearly show that the optimization procedure is a better option in a case where good initial locations of parameters are selected. A detailed experimental analysis is given in support of our algorithm. The implemented error analysis shows that the proposed methodology perform better as compared to the conventional methods.

scholarly journals Three-dimensional fluid topology optimization for heat transfer

2018 ◽  
Vol 59 (3) ◽  
pp. 801-812 ◽  
Author(s):  
M. Pietropaoli ◽  
F. Montomoli ◽  
A. Gaymann
Keyword(s):  
Heat Transfer ◽  
Topology Optimization ◽  
Three Dimensional

scholarly journals Multiscale, thermomechanical topology optimization of self-supporting cellular structures for porous injection molds

2019 ◽  
Vol 25 (9) ◽  
pp. 1482-1492
Author(s):  
Tong Wu ◽  
Andres Tovar
Keyword(s):  
Topology Optimization ◽  
Mechanical Performance ◽  
Mechanical Load ◽  
Design Method ◽  
Three Dimensional ◽  
Optimization Method ◽  
Cellular Structures ◽  
Injection Mold ◽  
Computationally Efficient ◽  
Content Type

Purpose This paper aims to establish a multiscale topology optimization method for the optimal design of non-periodic, self-supporting cellular structures subjected to thermo-mechanical loads. The result is a hierarchically complex design that is thermally efficient, mechanically stable and suitable for additive manufacturing (AM). Design/methodology/approach The proposed method seeks to maximize thermo-mechanical performance at the macroscale in a conceptual design while obtaining maximum shear modulus for each unit cell at the mesoscale. Then, the macroscale performance is re-estimated, and the mesoscale design is updated until the macroscale performance is satisfied. Findings A two-dimensional Messerschmitt Bolkow Bolhm (MBB) beam withstanding thermo-mechanical load is presented to illustrate the proposed design method. Furthermore, the method is implemented to optimize a three-dimensional injection mold, which is successfully prototyped using 420 stainless steel infiltrated with bronze. Originality/value By developing a computationally efficient and manufacturing friendly inverse homogenization approach, the novel multiscale design could generate porous molds which can save up to 30 per cent material compared to their solid counterpart without decreasing thermo-mechanical performance. Practical implications This study is a useful tool for the designer in molding industries to reduce the cost of the injection mold and take full advantage of AM.

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