Experiment and multiobjective optimization design of tape-spring hinges

Experiment and multiobjective optimization design of tape-spring hinges

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Article ID: iaor201526306
Volume: 51
Issue: 6
Start Page Number: 1373
End Page Number: 1384
Publication Date: Jun 2015
Journal: Structural and Multidisciplinary Optimization
Authors: , , , ,
Keywords: optimization, programming: multiple criteria, engineering, manufacturing industries, simulation
Abstract:

Flexible tape‐spring hinges can be folded elastically and are able to self‐deploy by releasing stored strain energy with fewer component parts and slight weights. This study presents a detailed investigation of the folding and deployment of single‐layer tape‐spring (SLTS) hinges and double‐layer tape‐spring (DLTS) hinges under pure bend loading. The material properties of tape‐spring hinges are measured using an INSTRON machine. A DLTS hinge construction is created, and its moment‐rotation relationship during quasi‐static deployment is measured. An experiment is conducted to verify the validation of the numerical models for the DLTS hinges. The quasi‐static deployment behavior of SLTS hinges and DLTS hinges is then analyzed using nonlinear finite element ABAQUS/Explicit solver, starting from the complete folded configuration. The DLTS hinge has good quasi‐static deployment performances with regard to maximum stress (S m ), steady moment (M *) and the peak moment (M d ) during the DLTS hinge quasi‐static deployment. In addition, the sampling designs of the DLTS hinges are created based on a three‐level full factorial design of experiments (DOE) method. The surrogate models of S m , M * and M d of the DLTS hinges are derived using response surface method (RSM) to reduce the computational cost of quasi‐static folding and deployment of numerical simulations. The Multiobjective optimization design (MOD) of the DLTS hinge is performed using modified non‐dominated sorting genetic algorithm (NSGA‐II) algorithm to achieve the optimal design. The finite element models for the optimal design based on numerical method are established to validate the optimization results.

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