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

AbstractConsidering the influence of multi-source uncertainties on buffering characteristics of airbag seat in manned airdrop, a reliability-based design optimisation (RBDO) method based on probability and interval models is proposed for optimising buffering characteristics of airbag seat. Firstly, the numerical model of the airbag seat is established and the validity is tested by the real equipment airdrop experiment. Secondly, the uncertainties are described by the probability model and the interval model. The multi-objective reliability-based design optimisation problem based on probability and interval hybrid model is also constructed. Thirdly, an efficient decoupling strategy is developed to transform original three-layer RBDO problem to single-layer optimisation problem based on Karush-Kuhn-Tucker (KKT) necessary condition and the second-order fourth moment method. Finally, in order to further improve the efficiency, the approximate models for the airbag seat are established based on radial basis function and the approximate reliability-based design optimisation problem is constructed which is solved by multi-objective genetic algorithm (MOGA). The results show that the proposed method not only obtains the best design parameters for the airbag seat, but also upgrade the safety of astronauts.Keywords: Airbag seatmanned airdropmulti-objective reliability-based design optimisationhybrid modeladaptive approximation model AcknowledgementsThe authors would also like to thank anonymous reviewers for their valuable comments.Disclosure statementOn behalf of all authors, the corresponding author states that there is no conflict of interest.Additional informationFundingThis work is supported by the National Natural Science Foundation of China (52275235, 51775057), the Hunan Provincial Natural Science Foundation of China for distinguished young scholars (No.2021JJ10040), the Hunan Provincial Natural Science Foundation of China (2021JJ30731), the Research Foundation of Education Department of Hunan Province (No.20K008, No.21B0353) and the Science Foundation of State Key Laboratory of Mechanical Transmissions (No.SKLMT-MSKFKT-202001).