Extension of Design Space: Topology Optimization on Two-Dimensional Manifolds for Wave Optics

2022 ◽  
pp. 145-162
Author(s):  
Yongbo Deng
Keyword(s):  
Topology Optimization ◽  
Design Space ◽  
Wave Optics ◽  
Two Dimensional ◽  
Space Topology

scholarly journals Computational Simulation of Bone Remodeling using Design Space Topology Optimization

PAMM ◽  
2011 ◽  
Vol 11 (1) ◽  
pp. 97-98
Author(s):  
Christopher Boyle ◽  
Il Yong Kim
Keyword(s):  
Topology Optimization ◽  
Bone Remodeling ◽  
Design Space ◽  
Computational Simulation ◽  
Space Topology

Level set-based topology optimization for two dimensional turbulent flow using an immersed boundary method

2021 ◽  
pp. 110630
Author(s):  
Seiji Kubo ◽  
Atsushi Koguchi ◽  
Kentaro Yaji ◽  
Takayuki Yamada ◽  
Kazuhiro Izui ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Turbulent Flow ◽  
Level Set ◽  
Immersed Boundary Method ◽  
Immersed Boundary ◽  
Two Dimensional ◽  
Boundary Method

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.

The Impact of Geometric Variation on Compressor Two-Dimensional Incidence Range

2014 ◽  
Vol 137 (2) ◽  
Author(s):  
Martin N. Goodhand ◽  
Robert J. Miller ◽  
Hang W. Lung
Keyword(s):  
Design Process ◽  
Design Space ◽  
Leading Edge ◽  
Critical Value ◽  
Two Dimensional ◽  
Suction Surface ◽  
Design Intent ◽  
Manufacture Process ◽  
The Impact ◽  
Geometric Variation

An important question for a designer is how, in the design process, to deal with the small geometric variations which result from either the manufacture process or in-service deterioration. For some blade designs geometric variations will have little or no effect on the performance of a row of blades, while in others their effects can be significant. This paper shows that blade designs which are most sensitive are those which are susceptible to a distinct switch in the fluid mechanisms responsible for limiting blade performance. To demonstrate this principle, the sensitivity of compressor 2D incidence range to manufacture variations is considered. Only one switch in mechanisms was observed, the onset of flow separation at the leading edge. This switch is only sensitive to geometric variations around the leading edge, 0–3% of the suction surface. The consequence for these manufacture variations was a 10% reduction in the blade's positive incidence range. For this switch, the boundary in the design space is best defined in terms of the blade pressure distribution. Blade designs where the acceleration exceeds a critical value just downstream of the leading edge are shown to be robust to geometric variation. Two historic designs, supercritical blades and blades with sharp leading edges, though superior in design intent, are shown to sit outside this robust region and thus, in practice, perform worse. The improved understanding of the robust, region of the design space is then used to design a blade capable of a robust, 5% increase in operating incidence range.

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