Parametric Optimization for a Tapered Deployable Mast in an Integrated Design Environment

Abstract:

Deployable mast has a wide range of applications in aerospace industry. As lower weight of deployable mast can greatly save the cost of launching and higher stiffness can improve the loading capacity. This paper aims at designing a tapered deployable truss with lower weight and higher stiffness. The conceptual design and mobility analysis of tapered deployable module are first introduced. Then finite element model is then presented. The proposed structure is optimized towards the goal of maximizing the fundamental frequency and minimizing the structural weight to enhance its stiffness. In the integrated design environment of iSIGHT, Non-dominated Sorting Genetic Algorithm (NSGA-II) is chosen as the optimum tool for this dual objectives optimization issue with four constraints. The Pareto optimal solutions of this optimum problem are found after optimization. Simulation shows that the optimum value of design variables have the capability of enhancing the fundamental frequency by 17% and reducing structure weight by 8%.

• Periodical: Advanced Materials Research (Volume 346)
• Pages: 426-432
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.346.426
• Online since: September 2011
• Authors: Zong Quan Deng, Yang Zhang, Hai Lin Huang, Bing Li
• Keywords: Deployable Mast, Optimization, Screw Theory

References

[1] Gunnar Tibert. Deployable Tensegrity Structures for Space Applications. Royal Institute of Technology, Doctoral Dissertation. pp.1-6, (2002).

[2] Pellegrino S. Large Retractable Appendages in Spacecraft,. J. of Spacecraft and Rockets, 1995, 32(6), pp.1006-1014.

DOI: 10.2514/3.26722

[3] K. Miura, H. Furuya, K. Suzuki. Variable Geometry Truss and Its Application to Deployable Truss and Space Crane Arm,. Acta Astronautica. 1985, 12(7-8), pp.599-607.

DOI: 10.1016/0094-5765(85)90131-6

[4] Christoph Sickinger, Lars Herbeck, Elmar Breitbach. Structural engineering on deployable CFRP booms for a solar propelled sailcraft,. Acta Astron., 2006, 58, pp.185-196.

DOI: 10.1016/j.actaastro.2005.09.011

[5] Yezid Donoso and Ramon Fabregat. Multi-Objective Optimization in Computer Networks Using Metaheuristics, Auerbach Publications, Boca Raton, Florida, 2007, ISBN 0-8493-8084-7.

DOI: 10.1201/9781420013627-2

[6] Engenious Software, Inc. iSight Reference Guide 9. 0. http: /www. engineous. com. (2004).

[7] Wei Liu, Yuying Yang, Multi-objective optimization of an auto panel drawing die face design by mesh morphing,. Computer-Aided Design 39(10), pp.863-869, (2007).

DOI: 10.1016/j.cad.2007.05.009

[8] Akin Keskin and Dieter Bestle, Application of multi-objective optimization to axial compressor preliminary design, Aerospace Science and Technology,  2006, vol. 10, no7, pp.581-589.

DOI: 10.1016/j.ast.2006.03.007

[9] Kalyanmoy Deb, An efficient constraint handling method for genetic algorithms,. Comput. Meth. Appl. Mech. Eng. 186(2-4), pp.311-338, (2000).