تدوین نرم‌افزار بهینه سازی طراحی برای یک نوع هواپیمای هوانوردی عمومی با نگرش چندموضوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضو هیات علمی / دانشکده مهندسی هوا فضا، دانشگاه صنعتی خواجه نصیر الدین طوسی

2 دانشجوی دکتری / دانشکده مهندسی هوا فضا، دانشگاه صنعتی خواجه نصیر الدین طوسی

3 دانشجوی کارشناسی ارشد / دانشکده مهندسی هوا فضا، دانشگاه صنعتی خواجه نصیر الدین طوسی

چکیده

در این مقاله به ارائه یک نرم­افزار طراحی چندموضوعی به‌منظور طراحی هواپیمای هوانوردی عمومی پرداخته شده است. در این نرم­افزار در ابتدای فرایند طراحی، پیکره­بندی اولیه­ی هواپیما بر‌مبنای یک سری الزامات از پیش تعیین شده و مطالعات آماری تعیین می­گردد. سپس حلقه امکان‌پذیری طراحی چندموضوعی بر‌اساس انجام یک تحلیل چندموضوعی طرح را در حضور قیود عملکردی و مأموریتی ارزیابی می­نماید. قیود و الگوریتم­های لحاظ شده در طراحی برمبنای روش طراحی گودمانسون پیاده­سازی شده است. متغیرهای طراحی با دقت و برمبنای تحلیل حساسیت روی اهداف بهینه­سازی (کاهش وزن کل و افزایش برد) انتخاب شده‌اند. قیود پایداری استاتیکی نیز به‌منظور دست­یافتن به یک طرح امکان­پذیر در طراحی لحاظ شده است. نهایتاً با استفاده از یک الگوریتم بهینه­سازی تکاملی چندهدفی (NSGA-II)، مجموعه پاسخ­های ممکن در قالب جبهه پرتو ارائه می­گردد. این نرم­افزار با قابلیت افزودن انواع موتورها و ایرفویل­ها، گستره­ی جامعی از طرح­های بهینه را پوشش خواهد داد. جبهه پرتوی حاصل از فرایند بهینه­سازی، امکان­پذیری و سودمندی این نرم­افزار طراحی مفهومی را نشان می­دهد.

کلیدواژه‌ها


عنوان مقاله [English]

Design optimization software for a type of general aviation aircraft: a multidisciplinary approach

نویسندگان [English]

  • Jafar Roshanian 1
  • Ali Asghar Bataleblu 2
  • Benyamin Ebrahimi 3
  • Mohammad Hossein Farghadani 3
1 Professor / Aerospace Engineering Department, K. N. Toosi University of Technology
2 Ph.D. Student / Aerospace Engineering Department, K. N. Toosi University of Technology
3 M.Sc. Student / Aerospace Engineering Department, K. N. Toosi University of Technology
چکیده [English]

This article provides comprehensive multidisciplinary design software for the design of a class of General Aviation Aircrafts (GAAs). At the beginning of the design process of this software, preliminary aircraft configuration will be determined based on a preset series of requirements and statistical study. Afterward, the MDF loop assesses the design in the presence of performance and mission constraints by implementing a multidisciplinary analysis. The constraints and algorithms which are considered in the design process are based on the Gudmundsson design approach. Design variables are selected carefully using sensitivity analysis on design objectives (i.e. reducing the gross weight and increasing the range). The static stability constraints are considered to obtain a feasible design. Eventually, the NSGA-II multi-objective evolutionary optimization algorithm is utilized to demonstrate a set of possible answers in the form of the Pareto front. This software can add a variety of engines and airfoils, will cover a comprehensive range of optimal designs. The Pareto front resulted from the optimization process illustrates the feasibility and effectiveness of this conceptual design software.

کلیدواژه‌ها [English]

  • general aviation aircraft
  • multidisciplinary design optimization
  • multi-objective optimization
  • pareto front
[1] S. Gudmundsson, General aviation aircraft design: Applied Methods and Procedures, First Edittion, pp. 133-924, Massachusetts: Butterworth-Heinemann, 2013.
[2] J. Sobieszczanski-Sobieski, Multidisciplinary design optimization: an emerging new engineering discipline, J. Herskovits (Eds.), Advances in Structural Optimization, pp. 483-496, Ontario: Springer, 1995.
[3] D. Raymer, Enhancing aircraft conceptual design using multidisciplinary optimization, PhD Thesis, Department of Aeronautics Royal Institute of Technology, Stockholm, 2002.
[4] J. Sobieszczanski-Sobieski, Multidisciplinary optimization for engineering systems: Achievements and potential,  in: Optimization: Methods and applications, possibilities and limitations, Eds., pp. 42-62: Springer, 1989.
[5] E. J. Cramer, J. Dennis, John E, P. D. Frank, R. M. Lewis, G. R. Shubin, Problem formulation for multidisciplinary optimization, SIAM Journal on Optimization, Vol. 4, No. 4, pp. 754-776, 1994.
[6] C. L. Bloebaum, P. Hajela, J. Sobieszczanski
Sobieski, Non-hierarchic system decomposition in structural optimization, Engineering Optimization A35, Vol. 19, No. 3, pp. 171-186, 1992.
[7] R. Sellar, S. Batill, J. Renaud, Response surface based, concurrent subspace optimization for multidisciplinary system design, Proceeding of The 34th Aerospace Sciences Meeting and Exhibit, pp. 714, 1996.
[8] B. A. Wujek, J. E. Renaud, S. M. Batill, J. B. Brockman, Concurrent subspace optimization using design variable sharing in a distributed computing environment, Concurrent Engineering, Vol. 4, No. 4, pp. 361-377, 1996.
[9] I. Kroo, I. Kroo, Multidisciplinary optimization applications in preliminary design-status and directions, Proceeding of The 38th Structures, Structural Dynamics, and Materials Conference, pp. 1408,1997.
[10] A.V. DeMiguel, W. Murray, An analysis of collaborative optimization methods, Proceeding of The 8th Symposium on Multidisciplinary Analysis and Optimization,pp. 4720, 2000.
[11] B. D. Roth, Aircraft family design using enhanced collaborative optimization: ProQuest, 2008.
[12] J. Sobieszczanski-Sobieski, J. S. Agte, R. R. Sandusky, Bilevel integrated system synthesis, AIAA journal, Vol. 38, No. 1, pp. 164-172, 2000.
[13] J. Sobieszczanski-Sobieski, T. D. Altus, M. Phillips, R. Sandusky, Bilevel integrated system synthesis for concurrent and distributed processing, AIAA journal, Vol. 41, No. 10, pp. 1996-2003, 2003.
[14] S. Kodiyalam, J. Sobieszczanski-Sobieski, Bilevel integrated system synthesis with response surfaces, AIAA journal, Vol. 38, No. 8, pp. 1479-1485, 2000.
[15] B. Malone, W. Mason, Multidisciplinary optimization in aircraft design using analytic technology models, Journal of Aircraft, Vol. 32, No. 2, pp. 431-438, 1995.
[16] A. Dovi, G. Wrenn, J.-F. Barthelemy, P. Coen, L. Hall, Multidisciplinary design integration methodology for a supersonic transport aircraft, Journal of aircraft, Vol. 32, No. 2, pp. 290-296, 1995.
[17] M. Anderson, W. Mason, An MDO approach to controlconfigured-vehicle design, Proceedings of The 6th Symposium on Multidisciplinary Analysis and Optimization, Bellevue: AIAA, pp. 1-10, 1996.
[18] S. Wakayama, Multidisciplinary design optimization of the blended-wing-body, Proceedings of The 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, California: AIAA, pp. 1-9 , 1998.
[19] R. Perez, H. Liu, K. Behdinan, Flight Dynamics and Control Multidisciplinary Integration in Aircraft Conceptual Design Optimization, Proceedings of The 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, New York: AIAA, pp. 1-10, 2004.
[20] S. M. B. Malaek, A. Ghorbani, Aircraft conceptual design based on genetic algorithm, Aerospace Mechanics Journal, Vol. 1, No. 1, pp. 101-114, 2005. (in Persian)
[21] J. Cavalcanti, B. Mattos, P. Paglione, Optimal Conceptual Design of Transport Aircraft, Proceedings of The 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Virginia: AIAA, pp. 1-22, 2006.
[22] M. A. Azizi, H. Salehipour, S. Farazi, Aircraft conceptual design methods based on Raskam method and its application for designing an unmanned aircraft, Mechanical Engineering Majlesi, Vol. 1, No. 3, pp. 64-74, 2008. (in Persian)
[23] L. Cavagna, L. Riccobene, S. Ricci, A. Bérard, A. Rizzi, A fast MDO tool for aeroelastic optimization in aircraft conceptual design, Proceedings of The 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, British Columbia: AIAA, pp. 1-17, 2008.
[24] C. Park, C.-Y. Joh, Y.-S. Kim, Multidisciplinary design optimization of a structurally nonlinear aircraft wing via parametric modeling, International Journal of Precision Engineering and Manufacturing, Vol. 10, No. 2, pp. 87-96, 2009.
[25] R. Ramanna, M. Kumar, K. Sudhakar, K. Harinarayana, Multidisciplinary Design Optimization of Transport Class Aircraft, Chakrabarti, Amaresh, Prakash, Raghu V (Eds.), ICoRD'13 Global Product Development, pp. 125 135, India: Springer, 2013.
[26] J. Yoon, N.-V. Nguyen, S.-M. Choi, J.-W. Lee, S. Kim, Y.-H. Byun, Multidisciplinary General Aviation Aircraft Design Optimizations Incorporating Airworthiness Constraints, Proceedings of the 10th AIAA aviation technology, integration, and operations (ATIO) conference, Fort Worth: AIAA, pp. 1-12, 2010.
[27] J. Roshanian, A. A. Bataleblu, M. H Farghadani, B. Ebrahimi, Multi-Objective Multidisciplinary Design Optimization of a General Aviation Aircraft, Journal of Modares Mechanical Engineering, 2017. (in Persian)
[28] K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp. 182-197, 2002.
[29] D. A. Van Veldhuizen, G. B. Lamont, Evolutionary computation and convergence to a pareto front, pp. 221-228, 1998.
[30] A. M. D. O. T. Committee, Current state of the art on multidisciplinary design optimization (MDO), An AIAA White Paper. AIAA, 1991.
[31] J. Blair, R. Ryan, L. Schutzenhofer, W. Humphries, Launch vehicle design process: characterization, technical integration, and lessons learned, 2001.
[32] D. P. Raymer, Aircraft design: A conceptual approach, Second Edittion, pp. 395-407, Washington: AIAA, 2006.
[33] L. M. Nicolai, G. Carichner, L. Malcolm, Fundamentals of aircraft and airship design, First Edittion, pp. 551-574, Washington: AIAA, 2010.
[34] E. Torenbeek, advanced aircraft design conceptual design, analysis and optimization of subsonic civil airplanes, First Edittion, pp. 229 261, Chichester: Springer Science & Business Media, 2013.
[35] I. H. Abbott, A. E. Von Doenhoff, Theory of wing sections, including a summary of airfoil data, First Edittion, pp. 111-124, New York: Dover publications, 1959.