توسعه یک چارچوب بهینه‌سازی طراحی و آنالیز چندموضوعی برای میکروپرنده‌های بال ثابت

نوع مقاله : گرایش دینامیک، ارتعاشات و کنترل

نویسنده

استادیار، گروه مهندسی مکانیک، پردیس شهرضا، دانشگاه اصفهان، شهرضا، ایران

چکیده

از آنجائی که روش معینی برای طراحی میکروپرنده‌ها (برخلاف هواپیماهای با مقیاس بزرگ) وجود ندارد، لذا طراحی این وسایل بسیار پیچیده و مبهم است. به همین دلیل، طراحی میکروپرنده‌ها بسیار پرهزینه (زمان‌بر) است و نهایتاً طرح به‌دست‌آمده نمی‌تواند بهینه باشد. برای حل این چالش‌ها، این تحقیق یک چارچوب برای بهینه‌سازی طراحی چندموضوعی میکروپرنده‌های بال ثابت را توسعه داده است. هدف این چارچوب استفاده از مزایای روش بهینه‌سازی طراحی چندموضوعی (کاهش زمان و دستیابی به طرح بهینه) در فرآیند طراحی میکروپرنده‌ها است. لذا سعی شده است تا مهم‌ترین ماژول‌ها برای آنالیز در نظر گرفته و چارچوب بتواند همه فازهای پروازی در فرآیند بهینه‌سازی طراحی را لحاظ کند. هندسه، وزن، تخمین مرکز جرم، آیرودینامیک و تخمین توان ماژول‌های در نظر گرفته‌شده در این چارچوب می‌باشند. برای نشان دادن عملکرد این چارچوب، بهینه‌سازی طراحی یک میکروپرنده بال ثابت با در نظر گرفتن کاهش وزن برخاست و نیروی پسآ به‌عنوان توابع هدف، انجام‌شده است. قیود در نظر گرفته‌شده نیز از ماژول‌های پایداری و هندسه می‌باشند. شایان‌ذکر است که با توجه به فضای طراحی پیچیده میکروپرنده‌ها و قابلیت الگوریتم ژنتیک، این الگوریتم به‌عنوان الگوریتم بهینه‌سازی در نظر گرفته‌شده است.

تازه های تحقیق

  • ارائه یک چارچوب بهینه‌سازی طراحی چندموضوعی برای میکروپرنده‌ها
  • استفاده از نرم‌افزار XFLR5 جهت اعتبارسنجی ماژول آیرودینامیک
  • در نظر گرفتن کل پروفیل پروازی در آنالیز چندموضوعی

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Developing a Multidisciplinary Analyzing and Design Optimization Framework for Fixed Wing Micro Air Vehicles

نویسنده [English]

  • Seyed Mohammad Reza Setayandeh
Assistant Professor, Department of Mechanical Engineering, Shahreza Campus, University of Isfahan, Shahreza, Iran
چکیده [English]

There is no determined method for Micro Air Vehicles (MAVs) design (unlike full-scale aircraft), so MAVs design is very complex and vague. For this reason, the design of MAVs is very expensive (time-consuming), and finally, the obtained design could not be more optimal. To solve these challenges, this study developed a framework for Multidisciplinary Design Optimization (MDO) of fixed-wing MAVs. This framework aims to use the benefits of MDO (time reduction and achieving optimal design) in the design process of MAVs. So, it is tried to consider the most important modules for analysis, and the framework can consider all flight phases in the design optimization process. Geometry, weight, the center of gravity, aerodynamics, and power are the considered modules in this framework. The analysis of all modules is performed for the entire flight phase. To show the performance of this framework, the design optimization of a fixed-wing MAV has been done by considering take-off weight and drag as objective functions.  The considered constraints for this research are from stability and geometry modules. It is worth noting that with attention to the complex design space of MAVs and the capability of the Genetic Algorithm (GA), this algorithm has been considered as an optimization algorithm in this study. 

کلیدواژه‌ها [English]

  • Multidisciplinary design optimization
  • Multidisciplinary analysis
  • Micro air vehicle
  • Optimal design
  • Genetic algorithm
[1] Aboelezz A, Hassanalian M, Desoki A, Elhadidi B, El-Bayoumi G. Design, experimental investigation, and nonlinear flight dynamics with atmospheric disturbances of a fixed-wing micro air vehicle, Aerospace Science and Technology. 2020; 97:1-31. DOI 10.1016/j.ast.2019.105636##.
[2] Kuo ZS, Soong CY, Chang YS. Dynamic modeling and analysis of a whole-wing micro air vehicle, 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural dynamic, and Materials, Honolulu, Hawaii; 2007. DOI 10.2514/6.2007-2238##.
[3] Hassanalian M, Abdelkefi A. Methodologies for weight estimation of fixed and flapping wing micro air vehicles. Meccanica, 2017; 52: 2047-2068. DOI 10.1007/s11012-016-0568-y##.
[4] Hassanalian M, Abdelkefi A. Design, manufacturing, and flight testing of a fixed wing micro air vehicle with Zimmerman planform. Meccanica, 2017; 52: 1265-1282. DOI 10.1007/s11012-016-0475-2##.
[5] Suhariyono A, Hyun kim J, Seo Goo N. Design of precision balance and aerodynamic characteristic measurement system for micro aerial vehicles. Aerospace Science and Technology, 2006; 10: 92-99. DOI 10.1016/j.ast.2005.10.004##.
[6] Gyllhen D, Mohseni K, Lawrence D. Numerical simulation of flow around the Colorado micro aerial vehicle, 35th AIAA Fluid Dynamics Conference and Exhibit, Toronto, Canada; 2005. DOI 10.2514/6.2005-4757##.
[7] Setayandeh MR. Surrogate model-based robust multidisciplinary design optimization of an unmanned aerial vehicle. Journal of Aerospace Engineering, 2021; 34(4): 1-12. DOI 10.1061/(ASCE)AS.1943-5525.000127##.
[8] Setayandeh MR, Babaei AR. Multidisciplinary design optimization of an aircraft by using knowledge-based systems. Soft Computing, 2020; 24: 12429-12448. DOI 10.1007/s00500-020-04684-3##.
[9] Jeyaraj A, Tabesh N, Liscouet-Hanke S. Connecting model-based systems engineering and multidisciplinary design analysis and optimization for aircraft systems architecting- a case study within AGILE 4 project, AIAA Aviation Forum; 2021. DOI 10.2514/6.2021-3077##.
[10] Allison DL, Morris CC, Schetz JA, Kapania RK, Watson LT, Deaton JD. Development of a multidisciplinary design optimization framework for an efficient supersonic air vehicle. Advances in Aircraft and Spacecraft Science, 2015; 2(1): 17-44. DOI 10.12989/aas.2015.2.1.017##.
[11] Hosseini M, Nosratollahi M, Sadati H. Multidisciplinary design optimization of UAV under uncertainty. Journal of Aerospace Technology and Management, 2017; 9(2): 169-178. DOI 10.5028/jatm.v9i2.725##.
[12] Babaei AR, Setayandeh MR, Farrokhfal H. Aircraft robust multidisciplinary design optimization methodology based on fuzzy preference function. Chinese Journal of Aeronautics, 2018; 31(12): 48-59. DOI 10.1016/j.cja.2018.04.018##.
[13] Dresia K, Jentzsch S, Waxenegger-Wilfing G. Multidisciplinary design optimization of reusable launch vehicles for different propellants and objectives. Journal of Spacecraft and Rockets, 2021; 58(4): 1017-1029. DOI 10.2514/1.A34944##.
[14] Ng TTH, Leng GSB. Application of genetic algorithms to conceptual design of a micro-air vehicle. Engineering Applications of Artificial Intelligence, 2002; 15: 439-445. DOI 10.1016/S0952-1976(02)00072-6##.
[15] Hassanalian M, Khaki H, Khosravani M. A new method for design of fixed wing micro air vehicle. Proc IMechE Part G: Journal of Aerospace Engineering, 2015; 229(5): 837-850. DOI 10.1177/0954410014540621##.
[16] Marek P. Design, optimization and flight testing of a micro air vehicle, Master of Science Thesis, Faculty of Engineering, University of Glascow; 2008##.
[17] Rama Sastry DVA, Ramana KV, Narayana KL. Design optimization of a micro air vehicle fixed wing. Research Journal of Applied Sciences Engineering and Technology, 2015; 10 (3): 262-266. DOI 10.19026/rjaset.10.2486##.
[18] Sriganapathy AJ, Gunasekaran R, Kalaiarasan T, Balabharathi R, Haridas T. Optimization in micro aerial vehicle for higher performance. International Research Journal on Advanced Science Hub, 2020; 2(5): 21-26. DOI 10.47392/IRJASH.2020.27##.
[19] Chard R, Snyder D, Beran PS, Parker GH, Blair M. A design optimization strategy for micro air vehicles, 48th AIAA/ASME/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Honolulu, Hawaii; 2007. DOI 10.2514/6.2007-1853##..
[20] Xia Y, Deng H, Hu K, Yang L, Xiao S, Ding X, Xiong Z, Design and optimization of bionic wings based on leading edge angle for flapping wing micro air vehicle, IEEE International Conference on Robotics and Biomimetics (ROBIO), Jinghong, China, 2022. DOI 10.1109/ROBIO55434.2022.10011821##.
[21] Ng TTH, Leng GSB, Design optimization of rotary-wing micro air vehicles, Proceeding of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2006; 220(6): 865-873. DOI 10.1243/09544062JMES104##.
[22] Hassanalian M, Salazar R, Abdelkefi A. Conceptual design and optimization of a tilt-rotor micro air vehicle. Chinese Journal of Aeronautics, 2019; 32(2): 369-381. DOI 10.1016/j.cja.2018.10.006##.
[23] Ali Shams T, Ali Shah SI, Javed A, Hamdani SHR. Airfoil selection procedure, wind tunnel experimentation and implementation of 6DOF modeling on a flying wing micro aerial vehicle. Micromachines, 2020; 11(6): 1-32. DOI 10.3390/mi11060553##.
[24] Sadraey MH, Aircraft design: a systems engineering approach, 1st edition, Wiley, New York; 2012##.
[25] Roskam J, Airplane flight dynamics and automatic flight controls, Lawrence, KS: DARcorporation; 1998##.
[26] Roskam J, Aiplane design, part 6: preliminary calculation of aerodynamic, thrust, and power characteristics, Ottawa, KS: Roskam Aviation and Engineering Corporation; 1987##.
[27] Mueller TJ, Kellogg JC, Ifju PG, Shkarayev SV. Introduction to the design of fixed-wing micro air vehicles-including three case studies, AIAA education Series; 2007. DOI 10.2514/4.862106##.
[28] Setayandeh MR, Azizi MA, Alem E. A new performance based preliminary design method for electric MAV and UAV aircrafts, International Micro Air Vehicle Conference, Braunschweig, Germany; 2010##.
[29] Azizi MA, Setayandeh MR, Alem E. Using energy method in unmanned aerial vehicle design and presenting of AVA micro air vehicle design method, 8th International Aerospace Conference, Shahinshahr, Iran; 2009##.
دوره 20، شماره 2 - شماره پیاپی 76
شماره پیاپی 76، فصلنامه تابستان
تیر 1403
صفحه 69-85
  • تاریخ دریافت: 20 بهمن 1402
  • تاریخ بازنگری: 24 اسفند 1402
  • تاریخ پذیرش: 06 اردیبهشت 1403
  • تاریخ انتشار: 01 تیر 1403