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Proceedings Paper

An automated approach to design shape morphing strategies for reconfigurable surfaces
Author(s): Narayan Srinivasa; Richard Ross
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Paper Abstract

Reconfigurable and morphing structures have attracted attention for potentially providing a range of new functionalities including system optimization over broad operational conditions and multi-mission capability. One promising approach for creating large deformation morphing structures uses variable stiffness components to provide large deformation without large energy input to the system. In this paper, we present an automated approach to design shape morphing strategies for reconfigurable surfaces composed of variable stiffness components. Variable stiffness components create an ill-posed control problem and generally have multiple solutions for any given morphing task. We formulate this problem as an optimization search using genetic algorithms (GA) to efficiently search the design space and rapidly arrive at a family of plausible solutions. Our novel approach can simultaneously satisfy a broad range of design constraints including structural properties, mechanical loading, boundary conditions and shape. Critical to GA searching is an accurate and computationally efficient variable stiffness surface model. Computer simulation of the reconfigurable surface was performed using a physics based model of the variable stiffness surface. The surface is modeled as a thin elastic plate in which the stretching and bending elastic moduli are treated separately and as arbitrary functions defined over the surface. This allows for large deformations including complete foldings. The resulting non-linear difference equations are solved using various preconditioned global search based relaxation algorithms. The results of our simulations show that our approach not only allows us to verify the feasibility of morphing tasks of variable stiffness surfaces, but also enables us to efficiently explore much larger design spaces resulting in unique and non-obvious morphing strategies.

Paper Details

Date Published: 19 May 2005
PDF: 8 pages
Proc. SPIE 5757, Smart Structures and Materials 2005: Modeling, Signal Processing, and Control, (19 May 2005); doi: 10.1117/12.601496
Show Author Affiliations
Narayan Srinivasa, HRL Labs. LLC (United States)
Richard Ross, HRL Labs. LLC (United States)


Published in SPIE Proceedings Vol. 5757:
Smart Structures and Materials 2005: Modeling, Signal Processing, and Control
Ralph C. Smith, Editor(s)

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