مقایسة چارچوب‌های بهینه‌سازی چندموضوعی در طراحی حامل‌ فضایی

نوع مقاله: مقاله پژوهشی

نویسنده

عضو هیات علمی / پژوهشگاه هوافضا، وزارت علوم، تحقیقات و فناوری

چکیده

در این مقاله، ضمن معرفی چارچوب‌های جدید طراحی بهینة چندموضوعی حامل‌های فضایی، کارآیی چارچوب‌های بهینة چندموضوعی نیز بررسی شده است. طی سالیان اخیر، دو چارچوب اصلی طراحی بهینة چندموضوعی به‌کار رفته در طراحی حامل‌های فضایی، طراحی بهینة چندموضوعی و طراحی همزمان جامع بوده است. مورد نخست براساس روش‌های بهینه‌سازی در قالب روش‌های بهینه‌سازی چندموضوعی، امکان طراحی چندموضوعی توسعه یافته و مورد دوم با بهره‌گیری از منطق فازی و تبدیل مسئلة بهینه‌سازی چندهدفی مقید به بهینه‌سازی تک‌هدفی نامقید توسعه یافته است. در این مقاله دو چارچوب مورد اشاره برای طراحی بهینة چندموضوعی حامل‌های فضایی پیاده‌سازی شده است. برای ارزیابی کارآیی چارچوب‌های طراحی از منظر زمان اجرا و دقت نتایج، از نتایج حاصل از پیاده‌سازی دو چارچوب برای یک حامل فضایی موجود استفاده شده است. نتایج حاکی از دقت بالاتر چارچوب طراحی بهینة چندموضوعی و زمان اجرای کمتر چارچوب طراحی همزمان جامع است. گفتنی است چارچوب طراحی بهینة چندموضوعی در مجامع علمی توسعة چشمگیری یافته است، این در حالی است که طراحی همزمان جامع در ابتدای راه توسعة بهینه‌سازی چندموضوعی قرار دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Comparing the launch vehicle multidisciplinary design optimization frameworks

نویسنده [English]

  • Hassan Naseh
چکیده [English]

The main aim of this paper is introducing the launch vehicle multidisciplinary design optimization frameworks and also considering the performance of them (aspects of processing time and accuracy). Recently, two multidisciplinary design optimization frameworks are applied for optimizing launch vehicles are Multidisciplinary Design Optimization (MDO) and Holistic Concurrent Design (HCD). The first framework is developed based on Multidisciplinary Design Feasible (MDF) and the second one is established the fuzzy rule set based on designer's expert knowledge with a holistic approach. For assessment of performance the frameworks from time and accuracy aspects utilized the result of applying the frameworks on existing launch. The achieved results have shown the more accuracy in MDO and less processing time in HCD frameworks. That is noticed the MDO framework is developed in scientific literature and the HCD framework has not developed yet. Finally, the MDO and HCD methodologies are recommended to apply the multidisciplinary problems.

کلیدواژه‌ها [English]

  • optimal design
  • multidisciplinary
  • launch vehicle
  • MDO
  • HCD

[1] M. Mirshams, H Karimi, H. Naseh, Multi-stage liquid propellant launch vehicle conceptual design based on combinatorial optimization of major design parameters, Journal of Space Science & Technology (JSST), Vol. 1, No. 1, pp. 21-36, 2008. (in Persian فارسی)

[2] M. Mirshams, H Karimi, H. Naseh, Multi-stage liquid propellant launch vehicle conceptual design (LVCD) software based on combinatorial optimization of major design parameters, Journal of Space Science & Technology (JSST), Vol. 1, No. 2, pp. 17-25, 2009. (in Persian فارسی)

[3] M. Mirshams, H. Naseh, A. R. Novinzadeh, Low Thrust Space Propulsion Design Methodology, Journal of Space Science & Technology (JSST), Vol. 7, No. 3, 2014. (in Persian فارسی)

[4] J. Sobieszczanski-Sobieski, J. F. Barthelemy, K. M. Riley, Sensitivity of optimum solutions to problem parameters, AIAA J, Vol. 2, No. 9, pp. 1291-1299, 1982.

[5] R.T, Haftka, Simultaneous Analysis and Design (SAND), AIAA J, Vol. 23, No. 7, pp. 1099-1103, 1985.

[6] R. D. Braun, I. M. Kroo, Development and application of the collaborative optimization architecture in a multidisciplinary design environment, In: Alexandrov N, Hussaini MY (eds) Multidisciplinary design optimization: state of the art. SIAM, Philadelphia, pp. 98-116, 1997.

[7] W. Hammond, Space Transportation: A Systems Approach to Analysis and Design, Reston, VA: AIAA, 1999.

[8] C. Geethaikrishnan, Multidisciplinary Design Optimization Strategy in Multi-Stage  Launch Vehicle Conceptual Design, 1st Progress Seminar Report, Department of Aerospace Engineering Indian Institute of Technology, Bombay, August 2003.

[9] J. Jodei, M. Ebrahimi, J. Roshanian, Multidisciplinary design optimization of a small solid propellant launch vehicle using system sensitivity analysis, Journal of Structural and Multidisciplinary Optimization, Vol. 38, No. 1, pp. 93–100, 2009.

[10] H. R. Fazeley, H. Taei, H. Naseh, M. Mirsham, A multi-objective, multidisciplinary design optimization, methodology for the conceptual design of a spacecraft bi-propellant propulsion system, Journal of Structural and Multidisciplinary Optimization, Vol. 53, No. 1, pp 145-160, 2016.

[11] N. M. Alexandrov, S. Kodiyalam, Initial results of an MDO evaluation survey, AIAA Paper 4884, 1998.

[12] N. M. Alexandrov, R. M. Lewis, Analytical and computational aspects of collaborative optimization for multidisciplinary design, AIAA J, Vol. 40, No. 2, pp. 301-309, 2002.

[13] N. P. Tedford, J. R. R. A. Martins, Benchmarking multidisciplinary design optimization algorithms, Optimal Engineering Journal, Vol. 11, No. 1, pp. 159-183, 2010.

[14] S. I. Yi, J. K. Shin, G. J. Park, Comparison of MDO methods with mathematical examples, Journal of Structural and Multidisciplinary Optimization, Vol. 35, No. 5, pp. 391-402, 2008.

[15] R. Chhabra, M. R. Emami, Linguistic Mechatronics, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, China, 2008.

[16] V. Ragusila, M. R. Emami, A Mechatronics Approach to Legged Locomotion, Canada, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, July 6-9, 2010.

[17] M. R. Emami, R. Chhabra, Concurrent Engineering of Robot Manipulators, University of Toronto Institute for Aerospace Studies Canada, Book chapter, 2010.

[18] I. M. Chen, J. W. Burdick, Determining Task Optimal Modular Robot Assembly Configurations, IEEE International Conference on Robotics and Automation, pp. 132-137, 1995.

[19] Z. M. Bi, W. A. Gruver, S. Y. T. Lang, Analysis and Synthesis of Reconfigurable Robotic Systems, Concurrent Engineering: Research and Applications, Vol. 12, No. 2, pp. 145-153, 2004.

[20] Z. M. Bi, W. J. Zhang, Concurrent Optimal Design of Modular Robotic Configuration, Journal of Robotic Systems, Vol. 18, No. 2, pp. 77-87, 2001.

[21] N. P. Suh, Axiomatic Design Theory for Systems, Research in Engineering Design, Vol. 10, No. 4, pp. 189-209, 1998.

[22] G. S. Chirikjian, Kinematics of a Metamorphic System, IEEE International Conference on Robotics and Automation, pp. 449-455, 1994.

[23] D. Rus, C. Mc Gray, Self-Reconfigurable Modular As 3-D Metamorphic Robots, IEEE International Conference on Intelligent Robots and Systems, pp.837-842, 1998.

[24] E. Yoshida, S. Kokaji, S. Murata, H. Kurokawa, K. Tomita, Miniaturized Self-Reconfigurable System Using Shape Memory Alloy, IEEE International Conference on Intelligent Robots and Systems, pp. 1579-1585, 1999.

[25] D. Rus, M. Vona, A Physical Implementation of Self-Reconfigurable Crystalline Robot, IEEE International Conference on Robotics and Automation, pp. 1726-1733, 2000.

[26] S. Murata, E. Yoshida, K. Tomita, H. Kurokawa, Kamimura and S. Kokaji, Hardware Design of Modular Robotic System, IEEE International Conference on Intelligent Robots and Systems, pp. 2210-2217, 2000.

[27] K. N. Otto, E. K. Antonsson, Imprecision in Engineering Design, ASME Journal of Mechanical Design, Vol. 117, No. B, pp. 25-32, 1995.

[28] R. R. Yager, D. P. Filev, Essentials of Fuzzy Modeling and Control, New York: John Wiley & Sons, 1994.

[29] M. R. Emami, I. B. Turksen, A. A. Goldenberg, A Unified Parameterized Formulation of Reasoning in Fuzzy Modeling and Control, Fuzzy sets and Systems, Vol. 108, No. 1, pp. 59-81, 1999.

[30] K. N. Otto, E. K. Antonsson, Trade-off Strategics in engineering design, Research in Engineering Design, Volume 3, No. 2, pp. 87-103, 1991.

[31] M. Sugeno, T. Yasukawa, A Fuzzy-logic based Approach to Qualitative Modeling, IEEE Transactions on Fuzzy Systems, Vol. 1, pp. 7-31, 1993.

[32] R. Chhabra, M. R. Emami, Holistic System Modeling in Mechatronics, Mechtronics, Vol. 21, No. 1, pp. 166-175, 2011.

[33] M. Mirshams, H. Naseh, H. Taei, H. R. Fazeley, Liquid propellant engine conceptual design by using a fuzzy-multi-objective genetic algorithm (MOGA) optimization method, Journal of Aerospace Engineering, Vol. 228 No. 14, pp. 2587-2603, 2014.

[34] M. Mirshams, H. Naseh, H. R. Fazeley, Multi-objective Multidisciplinary design of Space Launch System using Holistic Concurrent Design, Journal of Aerospace, Science and Technology, Volume 33, Issue 1, pp. 40–54, 2014.

[35] M. Mirdamadian, M. Mirshams, Structural Design of Liquid propellant Space Launch System, Master of Science Thesis, K. N. Toosi University of Technology, 2013. (in Persian فارسی)