Evolutionary topology optimization using design space adjustment based on fixed grid

2006 ◽  
Vol 66 (11) ◽  
pp. 1817-1840 ◽  
Author(s):  
In Gwun Jang ◽  
Byung Man Kwak
Keyword(s):  
Topology Optimization ◽  
Design Space ◽  
Fixed Grid

scholarly journals A new stress-based topology optimization approach for finding flexible structures

2021 ◽  
Author(s):  
Martin Noack ◽  
Arnold Kühhorn ◽  
Markus Kober ◽  
Matthias Firl
Keyword(s):  
Topology Optimization ◽  
Stress State ◽  
Design Space ◽  
Flexible Structures ◽  
Optimization Approach ◽  
Principal Stresses ◽  
Output Displacement ◽  
Design Concepts ◽  
Flexible Designs ◽  
Gauss Points

AbstractThis paper presents a new FE-based stress-related topology optimization approach for finding bending governed flexible designs. Thereby, the knowledge about an output displacement or force as well as the detailed mounting position is not necessary for the application. The newly developed objective function makes use of the varying stress distribution in the cross section of flexible structures. Hence, each element of the design space must be evaluated with respect to its stress state. Therefore, the method prefers elements experiencing a bending or shear load over elements which are mainly subjected to membrane stresses. In order to determine the stress state of the elements, we use the principal stresses at the Gauss points. For demonstrating the feasibility of the new topology optimization approach, three academic examples are presented and discussed. As a result, the developed sensitivity-based algorithm is able to find usable flexible design concepts with a nearly discrete 0 − 1 density distribution for these examples.

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.

Simultaneous Shape and Topology Optimization of Planar Linkage Mechanisms Based on the Spring-Connected Rigid Block Model

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Jeonghan Yu ◽  
Sang Min Han ◽  
Yoon Young Kim
Keyword(s):  
Topology Optimization ◽  
Simultaneous Optimization ◽  
Optimization Process ◽  
Rigid Block ◽  
Low Resolution ◽  
Block Model ◽  
Shape And Topology Optimization ◽  
Fixed Grid ◽  
Computation Efficiency ◽  
And Topology

Abstract Using the topology optimization can be an effective means of synthesizing planar rigid-body linkage mechanisms to generate desired motion, as it does not require a baseline mechanism for a specific topology. While most earlier studies were mainly concerned with the formulation and implementation of topology optimization-based synthesis in a fixed grid, this study aims to realize the simultaneous shape and topology optimization of planar linkage mechanisms using a low-resolution spring-connected rigid block model. Here, we demonstrate the effectiveness of simultaneous optimization over a higher-resolution fixed-grid rigid block-based topology optimization process. When shape optimization to change the block shapes is combined with topology optimization to synthesize the mechanism, the use of low-resolution discretized models improves the computation efficiency considerably and helps to yield compact mechanisms with less complexity, making them more amenable to fabrication. After verifying the effectiveness of the simultaneous shape and topology optimization process with several benchmark problems, we apply the method to synthesize a mechanism which guides a planar version of a human's gait trajectory.

Investigation of Parameter Spaces for Topology Optimization With Three-Dimensional Orientation Fields for Multi-Axis Additive Manufacturing

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Joseph R. Kubalak ◽  
Alfred L. Wicks ◽  
Christopher B. Williams
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Design Space ◽  
Mechanical Performance ◽  
Unit Length ◽  
Three Dimensions ◽  
Layer By Layer ◽  
Material Distribution ◽  
Orientation Fields ◽  
Material Orientation

Abstract The layer-by-layer deposition process used in material extrusion (ME) additive manufacturing results in inter- and intra-layer bonds that reduce the mechanical performance of printed parts. Multi-axis (MA) ME techniques have shown potential for mitigating this issue by enabling tailored deposition directions based on loading conditions in three dimensions (3D). Planning deposition paths leveraging this capability remains a challenge, as an intelligent method for assigning these directions does not exist. Existing literature has introduced topology optimization (TO) methods that assign material orientations to discrete regions of a part by simultaneously optimizing material distribution and orientation. These methods are insufficient for MA–ME, as the process offers additional freedom in varying material orientation that is not accounted for in the orientation parameterizations used in those methods. Additionally, optimizing orientation design spaces is challenging due to their non-convexity, and this issue is amplified with increased flexibility; the chosen orientation parameterization heavily impacts the algorithm’s performance. Therefore, the authors (i) present a TO method to simultaneously optimize material distribution and orientation with considerations for 3D material orientation variation and (ii) establish a suitable parameterization of the orientation design space. Three parameterizations are explored in this work: Euler angles, explicit quaternions, and natural quaternions. The parameterizations are compared using two benchmark minimum compliance problems, a 2.5D Messerschmitt–Bölkow–Blohm beam and a 3D Wheel, and a multi-loaded structure undergoing (i) pure tension and (ii) three-point bending. For the Wheel, the presented algorithm demonstrated a 38% improvement in compliance over an algorithm that only allowed planar orientation variation. Additionally, natural quaternions maintain the well-shaped design space of explicit quaternions without the need for unit length constraints, which lowers computational costs. Finally, the authors present a path toward integrating optimized geometries and material orientation fields resulting from the presented algorithm with MA–ME processes.

Topology and Free Size Optimization With Manufacturing Constraints for Light Weight Die Cast Automotive Backrest Frame

2009 ◽  
Author(s):  
Sreeram Polavarapu ◽  
Lonny L. Thompson ◽  
Mica Grujicic
Keyword(s):  
Finite Element ◽  
Topology Optimization ◽  
Design Space ◽  
Size Optimization ◽  
Manufacturing Constraints ◽  
Material Distribution ◽  
Front Seat ◽  
Die Cast ◽  
Stiffening Ribs ◽  
Multiple Load

Finite element analysis, together with topology and free-size optimization is used to design a lightweight die cast automotive front seat backrest frame when subjected to loads prescribed by ECE R17 European government regulations and additional loads which are predicted in an event of crash. In particular, an effort is made here to study the characteristics of a die cast automotive front seat backrest frame and develop a method for predicting the optimized material and support rib distribution which provides a lightweight seat which satisfies both strength and deflection requirements in a design space which includes the action of multiple load cases. An existing commercially available die cast backrest frame serves as the reference design space. Both 3D surface and solid models are created for representation as shell and solid finite element models for analysis. The objective function for topology optimization of the 3D solid model is to minimize mass of the component subject to stress and deflection constraints and is used as a guide in determining optimal geometric distribution of stiffening ribs. When the shell model of the reference seat is subjected to free-size optimization with this same constraint and objective given, an optimized material distribution measured by shell element thicknesses is obtained. For the topology optimization, manufacturing constraints of preferred draw direction and symmetry are applied in order to obtain an optimized material distribution which can be manufactured in the die-cast process. The procedure followed in this work generated an optimal material distribution and stiffening ribs in a lightweight die cast automotive seat backrest frame when subjected to multiple load cases. An overall reduction in weight of 13% is achieved over a reference commercially available die cast backrest frame component.

Exploring a Multiscale Topology Optimization Design Space Using a Parametric L-system Approach

2022 ◽  
Author(s):  
Brent Bielefeldt ◽  
Richard Beblo ◽  
Joshua D. Deaton ◽  
Kevin Lawson ◽  
Robert Lowe
Keyword(s):  
Topology Optimization ◽  
System Approach ◽  
Optimization Design ◽  
Design Space ◽  
L System

scholarly journals The quest for stiff, strong and tough hybrid materials: an exhaustive exploration

2013 ◽  
Vol 10 (89) ◽  
pp. 20130711 ◽  
Author(s):  
F. Barthelat ◽  
M. Mirkhalaf
Keyword(s):  
Topology Optimization ◽  
Spider Silk ◽  
Design Space ◽  
Materials Science ◽  
Mechanical Performance ◽  
Soft Materials ◽  
Global Approach ◽  
Structure Property ◽  
Structure Property Relationships ◽  
Global Optima

How to arrange soft materials with strong but brittle reinforcements to achieve attractive combinations of stiffness, strength and toughness is an ongoing and fascinating question in engineering and biological materials science. Recent advances in topology optimization and bioinspiration have brought interesting answers to this question, but they provide only small windows into the vast design space associated with this problem. Here, we take a more global approach in which we assess the mechanical performance of thousands of possible microstructures. This exhaustive exploration gives a global picture of structure–property relationships and guarantees that global optima can be found. Landscapes of optimum solutions for different combinations of desired properties can also be created, revealing the robustness of each of the solutions. Interestingly, while some of the major hybrid designs used in engineering are absent from the set of solutions, the microstructures emerging from this process are reminiscent of materials, such as bone, nacre or spider silk.

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