113
Views
0
CrossRef citations to date
0
Altmetric
Original Articles

The multi-objective reliability-based design optimisation of buffering characteristics of airbag seat in manned airdrop

, , , , &
Pages 391-401 | Received 27 Aug 2021, Accepted 22 Aug 2023, Published online: 29 Aug 2023

References

  • Liu X, Zhang ZY. Optimization of astronaut landing position based on micro multi-objective genetic algorithms. Aerosp Sci Technol. 2013;29(1):321–329. doi: 10.1016/j.ast.2013.04.003.
  • Dančuo ZZ, Rašuo BP, Bengin AČ, et al. Flight to mars: envelope simulation in a ground based high-performance human centrifuge. FME Trans. 2018;46(1):1–9. doi: 10.5937/fmet1801001D.
  • Ilić Z, Rašuo B, Jovanović M, et al. The efficiency of passive vibration damping on the pilot seat of piston propeller aircraft. Measurement. 2017;95:21–32. doi: 10.1016/j.measurement.2016.09.042.
  • Lawrence C, Carney KS, Littell J. Astronaut risk levels during crew module (CM) land landing. NASA/TM. 2007;214669:15803.
  • Lawrence C, Fasanella EL, Tabiei A, et al. The use of a vehicle acceleration exposure limit model and a finite element crash test dummy model to evaluate the risk of injuries during orion crew module landings. NASA/TM. 2008;215198:16469.
  • Ma HL, Liu BK, Jiang SZ, et al. Simulation analysis for the safety protection of cervical vertebra under unusual landing impact. Int J Crashworthines. 2011;16(5):469–473. doi: 10.1080/13588265.2011.593977.
  • Chiba M, Yasui T, Nambu Y, et al. Airbag application to passenger seat for aircraft: impact tests. Int J Crashworthiness. 2020;25(3):242–251. doi: 10.1080/13588265.2019.1573488.
  • Tan J, Han X, Liu X. Optimal design of airbag chair for manned airdrop protection. J Vib Shock China. 2011;30(2):222–225.
  • Liu X, Zhang ZY, Zhao ZH. The uncertain optimisation of buffering characteristics of landing airbag in manned airdrop. Int J Crashworthiness. 2013;18(3):225–236. doi: 10.1080/13588265.2013.775738.
  • Do S, Weck OL. A personal airbag system for the orion crew exploration vehicle. Acta Astronaut. 2012;81(1):239–255. doi: 10.1016/j.actaastro.2012.06.022.
  • Chiba M, Shimizu K, Yasui T, et al. Airbag models for aircraft passenger seats. Int J Crashworthiness. 2021;26(6):636–650.
  • Li MY, Wang ZQ. Surrogate model uncertainty quantification for reliability-based design optimization. Reliab Eng Syst Safe. 2019;192:106432. doi: 10.1016/j.ress.2019.03.039.
  • Hu L, Hu XT, Kuang A, et al. Casualty risk of e-bike rider struck by passenger vehicle using China in-depth accident data. Traffic Inj Prev. 2020;21(4):283–287. doi: 10.1080/15389588.2020.1747614.
  • Xu MH, Huang JH, Wang C, et al. Fuzzy identification of dynamic loads in presence of structural epistemic uncertainties. Comput Method Appl M. 2020;360:112718. doi: 10.1016/j.cma.2019.112718.
  • Xiao Z, Han X, Jiang C, et al. An efficient uncertainty propagation method for parameterized probability boxes. Acta Mech. 2016;227(3):633–649. doi: 10.1007/s00707-015-1492-2.
  • Zhou ZH, Chen SH, Liu X. The design of linear magnetic negative stiffness element for engineering application using rectangular permanent magnets. JMAG. 2020;25(2):172–180. doi: 10.4283/JMAG.2020.25.2.172.
  • Peng X, Ye T, Li JQ, et al. Multi-scale uncertainty quantification of composite laminated plate considering random and interval variables with data driven PCE method. Mech. Adv. Mater. Struct. 2021;28(23):2429–2439. doi: 10.1080/15376494.2020.1741749.
  • Meng DB, Yang SY, He C, et al. Multidisciplinary design optimization of engineering systems under uncertainty: a review. IJSI. 2022;13(4):565–593. doi: 10.1108/IJSI-05-2022-0076.
  • Peng X, Guo YL, Qiu C, et al. Reliability optimization design for composite laminated plate considering multiple types of uncertain parameters. Eng Optimiz. 2021;53(2):221–236. doi: 10.1080/0305215X.2019.1705289.
  • Meng DB, Hu ZG, Wu P, et al. Reliability-based optimization for offshore structures using saddlepoint approximation. P I Civil Eng-Mar En. 2020;173(2):33–42.
  • Shi L, Lin SP. A new RBDO method using adaptive response surface and first-order score function for crashworthiness design. Reliab Eng Syst Safe. 2016;156:125–133. doi: 10.1016/j.ress.2016.07.007.
  • Liu X, Gong M, Zhou ZH, et al. An improved first order approximate reliability analysis method for uncertain structures based on evidence theory. Mech Based Des Struc. 2023;51(7):4137–4154. doi: 10.1080/15397734.2021.1956324.
  • Ben-Haim Y, Elishakoff I. Discussion on: a non-probabilistic concept of reliability. Struct Saf. 1995;17(3):195–199. doi: 10.1016/0167-4730(95)00010-2.
  • Zaeimi M, Ghoddosain A. System reliability based design optimization of truss structures with interval variables. Period Polytech-Civ. 2020;64(1):42–59.
  • Du X. Reliability-based design optimization with dependent interval variables. Int J Numer Meth Eng. 2012;91(2):218–228. doi: 10.1002/nme.4275.
  • Zhang JH, Gao L, Xiao M, et al. An active learning kriging-assisted method for reliability-based design optimization under distributional probability-box model. Struct Multidisc Optim. 2020;62(5):2341–2356. doi: 10.1007/s00158-020-02604-5.
  • Dey S, Zaman K. Dimension reduction method-based RBDO for dependent interval variables. Int J Comp Meth-Sing. 2020;17(10):1–40.
  • Jiang C, Han X, Li WX, et al. A hybrid reliability approach based on probability and interval for uncertain structures. J Mech Design. 2012;134(3):031001.
  • Wang J, Qiu ZP. The reliability analysis of probabilistic and interval hybrid structural system. Appl Math Model. 2010;34(11):3648–3658. doi: 10.1016/j.apm.2010.03.015.
  • Meng DB, Xie TW, Wu P, et al. An uncertainty-based design optimization strategy with random and interval variables for multidisciplinary engineering systems. Struct. 2021;32:997–1004. doi: 10.1016/j.istruc.2021.03.020.
  • Jiang C, Lu GY, Han X, et al. A new reliability analysis method for uncertain structures with random and interval variables. Int J Mech Mater Des. 2012;8(2):169–182. doi: 10.1007/s10999-012-9184-8.
  • Zaman K, Mahadevan S. Reliability-based design optimization of multidisciplinary system under aleatory and epistemic uncertainty. Struct Multidisc Optim. 2017;55(2):681–699. doi: 10.1007/s00158-016-1532-0.
  • Xia B, Lü H, Yu D, et al. Reliability-based design optimization of structural systems under hybrid probabilistic and interval model. Comput Struct. 2015;160:126–134. doi: 10.1016/j.compstruc.2015.08.009.
  • Huang ZL, Jiang C, Zhou YS, et al. Reliability-based design optimization for problems with interval distribution parameters. Struct Multidisc Optim. 2017;55(2):513–528. doi: 10.1007/s00158-016-1505-3.
  • Liu X, Fu Q, Ye NH, et al. The multi-objective reliability-based design optimization for structure based on probability and ellipsoidal convex hybrid model. Struct Saf. 2019;77:48–56. doi: 10.1016/j.strusafe.2018.11.004.
  • Liu X, Li TR, Zhou ZH, et al. An efficient multi-objective reliability-based design optimization method for structure based on probability and interval hybrid model. Comput. Methods Appl. Mech. Eng. 2022;392:114682. doi: 10.1016/j.cma.2022.114682.
  • Hu L, Tian QT, Zou CF, et al. A study on energy distribution strategy of electric vehicle hybrid energy storage system considering driving style based on real urban driving data. Renew. Sust. Energ. Rev. 2022;162(7):112416. doi: 10.1016/j.rser.2022.112416.
  • Zhang JH, Xiao M, Gao L, et al. A novel projection outline based active learning method and its combination with kriging metamodel for hybrid reliability analysis with random and interval variables. Comput Method Appl M. 2018;341(1):32–52. doi: 10.1016/j.cma.2018.06.032.
  • Jing Z, Chen JQ, Li X. RBF-GA: an adaptive radial basis function metamodeling with genetic algorithm for structural reliability analysis. Reliab Eng Syst Safe. 2019;189:42–57. doi: 10.1016/j.ress.2019.03.005.
  • Li X, Gong CL, Gu LX, et al. A sequential surrogate method for reliability analysis based on radial basis function. Struct Saf. 2018;73:42–53. doi: 10.1016/j.strusafe.2018.02.005.
  • Liu X, Chen ZH, Liu X, et al. Structural optimisation of transportation equipment using an adaptive approximation model. P I Civil Eng-Transp. 2023;1–12. doi: 10.1680/jtran.22.00100.
  • Bostrom O, Svennson MY, Aldman B, et al. A new neck injury criterion candidate-based on injury findings in the cervical spine ganglia after experimental neck extension trauma Ireland. Proceedings of the International IRCOBI Conference on the Biomechanics of Impact; 1996.
  • TNO Automotive China. Madymo theory manuals 6.2.1. The Netherlands: Tass; 2006.
  • Mertz JH, Prasad P, Nusholtz G. Head injury risks assessment for forehead impacts. Warrendale: Sae International Congress; 1996.
  • Hasofer AM, Lind NC. Exact and invariant second-moment code format. J Eng Mech. 1974;100(1):111–121.
  • Zhang M. Structural reliability analysis: methods and procedures. Beijing: Science Press; 2009.
  • Liu X, Wang XY, Xie J, et al. Construction of probability box model based on maximum entropy principle and corresponding hybrid reliability analysis approach. Struct Multidisc Optim. 2020;61(2):599–617. doi: 10.1007/s00158-019-02382-9.
  • Amouzgar K, Strömberg N. Radial basis functions as surrogate models with a priori bias in comparison with a posteriori bias. Struct Multidisc Optim. 2017;55(4):1453–1469. doi: 10.1007/s00158-016-1569-0.
  • Zhang DQ, Zhang N, Ye N, et al. Hybrid learning algorithm of radial basis function networks for reliability analysis. IEEE T Reliab. 2020;99:1–14.
  • Liu X, Liu X, Zhou ZH, et al. An efficient multi-objective optimization method based on the adaptive approximation model of the radial basis function. Struct Multidisc Optim. 2021;63(3):1385–1403. doi: 10.1007/s00158-020-02766-2.
  • Liu X, Wang XY, Sun L, et al. An efficient multi-objective optimization method for uncertain structures based on ellipsoidal convex model. Struct Multidisc Optim. 2019;59(6):2189–2203. doi: 10.1007/s00158-018-2185-y.
  • Husslage B, Rennen G, Dam E, et al. Space-filling latin hypercube designs for computer experiments. Optim Eng. 2011;12(4):611–630. doi: 10.1007/s11081-010-9129-8.
  • Deb K. Multi-objective optimization using evolutionary algorithms. England: Wiley; 2001.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.