Conceptual Remote Sensing Satellite Design Optimization under uncertainty

Abstract This paper focuses upon the development of an efficient method for the conceptual design optimization of Remote Sensing Satellites (RSS) under uncertainty. There are many acceptable optimal solutions for implementation of satellite subsystems in a space system mission. Every solution should be assessed based on the different criteria such as cost, mass, reliability and payload resolution. In the present paper satellite mass and imaging payload resolution were considered as system level objective functions to obtain the system optimal solution during the conceptual design phase. Furthermore, two Multidisciplinary Design Optimization (MDO) frameworks; Multidisciplinary Design Feasible (MDF) and distributed Collaborative Optimization (CO) were applied to the multi-objective design optimization problem under uncertainty. Also, various uncertainties involving environment, operation, geometry, subsystems, etc. were considered in the Reliability Based Multidisciplinary Design Optimization (RBMDO) frameworks. In the present study, MDF, CO, Reliability Based Multi-disciplinary Design Feasible (RB-MDF) and Reliability Based Collaborative Optimization (RB-CO) frameworks were evaluated and compared. The methodology was based on the utilization of Monte Carlo simulation method for accounting uncertainties in design process and applying genetic algorithms and sequential quadratic programming to system level and discipline level optimizers. Results obtained in this study, have shown that the introduced method provides an effective way of accounting uncertainty in a complex space system design such as the conceptual design optimization of a spacecraft.

[1]  Young-Keun Chang,et al.  SEDT (System Engineering Design Tool) development and its application to small satellite conceptual design , 2007 .

[2]  Carlos A. Coello Coello,et al.  Multiobjective Evolutionary Algorithms in Aeronautical and Aerospace Engineering , 2012, IEEE Transactions on Evolutionary Computation.

[3]  Joaquim R. R. A. Martins,et al.  Large-scale MDO of a small satellite using a novel framework for the solution of coupled systems and their derivatives , 2013 .

[4]  Christina Bloebaum,et al.  NON-HIERARCHIC SYSTEM DECOMPOSITION IN STRUCTURAL OPTIMIZATION , 1992 .

[5]  Timothy K. Hasselman,et al.  Reliability based structural design optimization for practical applications , 1997 .

[6]  I. A. Budianto,et al.  A collaborative optimization approach to design and deployment of a space based infrared system constellation , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[7]  Bernhard Sendhoff,et al.  Robust Optimization - A Comprehensive Survey , 2007 .

[8]  ZhiQun Liu,et al.  Fatigue life reliability based design optimization for the missile suspension structure , 2012 .

[9]  R. Haftka,et al.  Sensitivity Analysis of Discrete Structural Systems , 1986 .

[10]  Henri P. Gavin,et al.  High-order limit state functions in the response surface method for structural reliability analysis , 2008 .

[11]  Dario Izzo,et al.  Robust and Automated Space System Design , 2008 .

[12]  George W. Morgenthaler,et al.  Conceptual space Systems Design using Meta-Heuristic Algorithms , 2002 .

[13]  Mehran Mirshams,et al.  A multi-objective, multidisciplinary design optimization methodology for the conceptual design of a spacecraft bi-propellant propulsion system , 2016 .

[14]  Jeremy S. Agte,et al.  Bi-Level Integrated System Synthesis , 1998 .

[15]  Mitsuo Gen,et al.  Genetic algorithms and engineering optimization , 1999 .

[16]  Hong-Fei Teng,et al.  Optimal Layout Design of a Satellite Module Using a Coevolutionary Method with Heuristic Rules , 2009 .

[17]  Zhao-wei Sun,et al.  The satellite optimization design using collaborative optimization method based on normal cloud model , 2011, Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology.

[18]  Rania Hassan,et al.  Spacecraft Reliability-Based Design Optimization Under Uncertainty Including Discrete Variables , 2008 .

[19]  Paul T. Boggs,et al.  Sequential Quadratic Programming , 1995, Acta Numerica.

[20]  Ilan Kroo,et al.  Implementation and Performance Issues in Collaborative Optimization , 1996 .

[21]  Andrew Santangelo.  OpenSAT(TM) and SATBuilder: A Satellite Design Automation Environment for Responsive Space , 2008 .

[22]  Scott Alan Uebelhart,et al.  Non-deterministic design and analysis of parameterized optical structures during conceptual design , 2006 .

[23]  J. C. Ziegert,et al.  Multi‐Disciplinary Design Optimization of a Composite Car Door for Structural Performance, NVH, Crashworthiness, Durability and Manufacturability , 2009 .

[24]  Rania Hassan,et al.  Genetic algorithm approaches for conceptual design of spacecraft systems including multi-objective optimization and design under uncertainty , 2004 .

[25]  Deyu Wang,et al.  A Framework of Multiobjective Collaborative Optimization , 2009 .

[26]  Roger Förstner,et al.  Quantification of the Influence between Satellite Design Parameters for the Support of System Design Decisions , 2013 .

[27]  Natalia Alexandrov,et al.  Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design , 2002 .

[28]  Achintya Haldar,et al.  First-Order and Second-Order Reliability Methods , 1995 .

[29]  S. C. Dixon,et al.  Comparison of Two Types of Structural Optimization Procedures for Flutter Requirements , 1975 .

[30]  Zhenzhou Lu,et al.  The applications of an importance sampling method to reliability analysis of the inside flap of an aircraft , 2013 .

[31]  John E. Dennis,et al.  Problem Formulation for Multidisciplinary Optimization , 1994, SIAM J. Optim..

[32]  Hong-Fei Teng,et al.  Optimal layout design of a satellite module , 2003 .

[33]  Zhao-wei Sun,et al.  The Satellite Optimization Design Using Normal Cloud Model Method , 2011, 2011 International Conference on Network Computing and Information Security.

[34]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[35]  Jan Roupec,et al.  ADVANCED GENETIC ALGORITHMS FOR ENGINEERING DESIGN PROBLEMS , 2010 .

[36]  John E. Renaud,et al.  A study using Monte Carlo Simulation for failure probability calculation in Reliability-Based Optimization , 2006 .

[37]  Natalia Alexandrov,et al.  Multidisciplinary design optimization : state of the art , 1997 .

[38]  Tao Jiang,et al.  Target Cascading in Optimal System Design , 2003, DAC 2000.

[39]  Michel van Tooren,et al.  Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles , 2011 .

[40]  Andrew Santangelo.  OpenSAT(TM), a framework for satellite design automation for responsive space , 2007 .

[41]  Sharon L. Padula,et al.  Aerospace applications of optimization under uncertainty , 2006 .

[42]  Xiaoqian Chen,et al.  Utilizing Uncertainty Multidisciplinary Design Optimization for Conceptual Design of Space Systems , 2010 .

[43]  Nickolas Vlahopoulos,et al.  An integrated multidisciplinary particle swarm optimization approach to conceptual ship design , 2010 .

[44]  Kyung K. Choi,et al.  Selecting probabilistic approaches for reliability-based design optimization , 2004 .

[45]  Luis G. Crespo,et al.  Reliability-Based Control Design for Uncertain Systems , 2005 .

[46]  W. Manners.  A first-order reliability method for certain system and load combination calculations , 1989 .

[47]  R. Haftka.  Simultaneous analysis and design , 1985 .

[48]  Kyung K. Choi,et al.  Reliability-based design optimization for crashworthiness of vehicle side impact , 2004 .

[49]  Dimitri N. Mavris,et al.  Uncertainty Modeling and Management in Multidisciplinary Analysis and Synthesis , 2000 .

[50]  John R. Olds,et al.  Evaluation of Multidisciplinary Optimization Techniques Applied to a Reusable Launch Vehicle , 2006 .

[51]  James R. Wertz,et al.  Space Mission Analysis and Design , 1992 .

[52]  Andrew Santangelo.  Design Under the step_SATdb and QuickSAT: A Web-Based and Open Source Satellite Design Automation Environment , 2011 .

[53]  Yan-Gang Zhao,et al.  Moment methods for structural reliability , 2001 .

[54]  R. Melchers.  Importance sampling in structural systems , 1989 .

[55]  L. A. Schmit,et al.  Structural synthesis - Its genesis and development , 1981 .

[56]  Hong-Zhong Huang,et al.  System Reliability Based Design Optimization with Monte Carlo simulation , 2012, 2012 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering.

[57]  Joaquim R. R. A. Martins,et al.  Benchmarking multidisciplinary design optimization algorithms , 2010 .

[58]  Abdelhamid Chriette,et al.  A survey of multidisciplinary design optimization methods in launch vehicle design , 2012 .

[59]  Enrique F. Castillo,et al.  An alternative approach for addressing the failure probability-safety factor method with sensitivity analysis , 2003, Reliab. Eng. Syst. Saf..

[60]  Liang Gao,et al.  A local adaptive sampling method for reliability-based design optimization using Kriging model , 2014 .