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Multi-objective Goal Programming for Low Altitude Seat Ejections with Fuzzy Logic–Based Decision-making

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Abstract

Aircraft seat ejection systems are essential lifesaving equipment for pilots. Although seat ejections have improved in terms of success rates over the past few decades, ejections at low altitudes (below 150 m) remain a serious concern. These are time critical events and demand optimal process parameters to improve the odds of successful ejection due to the lack of lifesaving height and various other factors. The study optimizes impulse applied and the angle of ejection of the pilot with a novel Multi-Objective optimization approach to minimize Dynamic Response Index (DRI, used to quantify spinal injury) and to maximize the ejection height. The Pareto-optimal solutions are obtained thereof for different scenarios of aircraft flight. A fuzzy logic system is used to handle the uncertainties due to the objective functions under different ejection scenarios of the aircraft; it is used as a decision-maker to choose the initial parameters for goal programming based on the severity of the ejection scenarios. The results were compared with ideal solutions obtained from Pareto fronts using the same fuzzy logic system as decision-maker. The goal programming gave similar results at a quicker time making it advantageous over the conventional “generate first choose later” methods.

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References

  1. Newman DG (2013) Survival outcomes in low-level ejections from high performance aircraft. Aviation, Space, and Environmental Medicine 84(10):1061

    Article  Google Scholar 

  2. Specker L, Plaga J, Santi V (2001) Ejection seat capabilities to meet agile aircraft requirements. Human Consequences of Agile Aircraft 1

  3. Lewis M (2002) Spinal injuries caused by the acceleration of ejection. J R Army Med Corps 148(1):22

    Article  Google Scholar 

  4. Stech EL, Payne PR (1969) Dynamic models of the human body. Tech. rep., Frost Engineering Development Corp Englewood Co

  5. Ruff S (1950) Brief acceleration: Less than one second. Ger Aviat Med World War II 1:584

    Google Scholar 

  6. Eiband AM (1959) Human tolerance to rapidly applied accelerations: a summary of the literature

  7. Brinkley JW, Shaffer JT (1971) Dynamic simulation techniques for the design of escape systems: current applications and future air force requirements. Tech. rep., AIR FORCE AEROSPACE MEDICAL RESEARCH LAB WRIGHT-PATTERSON AFB OH

  8. USAF (2016) Mil-hdbk-516cn-56. Tech. rep.

  9. Wei Z, Jingheng W, Dongqi M (2015) Optimum research of control law in hty-x of ejection seat

  10. Sadler R, McCauley D (2005) Propulsion’s contribution to the success of aircrew emergency escape systems. In: 39th AIAA/ASME/SAE/ASEE joint propulsion conference and exhibit, p 4966

  11. Carroll J (1983) Control law design for ejection seats. In: Guidance and control conference, p 2204

  12. Wise KA, Brinker JS (1996) Linear quadratic flight control for ejection seats. Journal of Guidance, Control, and Dynamics 19(1):15

    Article  Google Scholar 

  13. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182

    Article  Google Scholar 

  14. Abdullah L (2013) Fuzzy multi criteria decision making and its applications: a brief review of category. Procedia-Social and Behavioral Sciences 97:131

    Article  Google Scholar 

  15. Yang X, Cao X (2015) A new approach to autonomous rendezvous for spacecraft with limited impulsive thrust: based on switching control strategy. Aerosp Sci Technol 43:454

    Article  Google Scholar 

  16. Wang W, Peng H (2017) A fast multi-objective optimization design method for emergency libration point orbits transfer between the sun–earth and the earth–moon systems. Aerosp Sci Technol 63:152

    Article  Google Scholar 

  17. Messac A, Mattson CA (2002) Generating well-distributed sets of Pareto points for engineering design using physical programming. Optim Eng 3(4):431

    Article  Google Scholar 

  18. Charnes A, Cooper WW, Ferguson RO (1955) Optimal estimation of executive compensation by linear programming. Management Sci 1(2):138

    Article  MathSciNet  Google Scholar 

  19. Romero C (2014) Handbook of critical issues in goal programming. Elsevier, Amsterdam

    MATH  Google Scholar 

  20. Gembicki F (1974) Vector optimization for control with performance and parameter sensitivity indices, Ph. D. thesis, Case Western Reserve Univ.

  21. Payne PR (1962) The dynamics of human restraint systems. Impact Acceleration Stress, pp 195–257

  22. Latham WCF (1957) A study in body ballistics: seat ejection. Proceedings of the Royal Society of London. Series B-Biological Sciences 147(926):121

    Google Scholar 

  23. Robinson G, Jovanoski Z (2010) Fighter pilot ejection study as an educational tool. Teaching, Mathematics and its Applications: International Journal of the IMA 29(4):176

    Article  Google Scholar 

  24. MATLAB (2017) version: 7.10.0 (R2017b) (The MathWorks Inc., Natick, Massachusetts

  25. Wang YF, Chen G, Han LL (2014) The comprehensive survey for the numerical simulation of the 4th generation rocket ejection seat thrust vector control system. In: Applied mechanics and materials, vol 551, pp 523–529

  26. Specification P (1996) Seat system, upward ejection, aircraft, general specification for. Tech. rep. MIL-PRF-9479d (USAF)

  27. Raj RN, Shankar K (2019) A multi-objective optimization study of parameters for low-altitude seat ejections. In: Soft computing for problem solving. Springer, pp 311–325

  28. Zadeh LA, et al. (1965) Fuzzy sets. Inform Control 8(3):338

    Article  Google Scholar 

  29. Kalavsky P, Socha V, Socha L, Kutilek P, Gazda J, Kimlickova M (2015) Conditions for abandonment out of a helicopter using personal rescue parachute. In: 2015 International conference on military technologies (ICMT). IEEE, pp 1–5

  30. U.S.O. of the Chief of Naval Operations, U.S.N.A.S. Command, NATOPS Flight Manual: Navy Model AV-8B Aircraft 161573 and Up (The Command, 2008). https://books.google.co.in/books?id=7WguHQAACAAJ

  31. U.S.O. of the Chief of Naval Operations, NATOPS Flight Manual: Navy Model F/A-18E/F 165533 and Up Aircraft (Naval Air Technical Data and Engineering Services Command, Naval Air Station, North Island, 2001). https://books.google.co.in/books?id=Ol2jYgEACAAJ

  32. Kal’avskỳ P, Gazda J, Kimličková M (2015) Emergency bail-out from aircraft landing with personal rescue parachutes. Acta Avionica 17(1)

  33. USAF (2007) Mil-dtl-9479 rev. e. Tech. rep.

  34. Mao XD, Lin GP, Yu J (2011) Predicting ejection velocity of ejection seat via back propagation neural network. J Aircr 48(2):668

    Article  Google Scholar 

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Correspondence to K. Shankar.

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Raj, R.N., Shankar, K. Multi-objective Goal Programming for Low Altitude Seat Ejections with Fuzzy Logic–Based Decision-making. Hum Factors Mech Eng Def Saf 4, 6 (2020). https://doi.org/10.1007/s41314-019-0031-7

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