TY - GEN
T1 - Probabilistic failure analysis for icme using an adjoint-based lattice particle method
AU - Gao, Yi
AU - Liu, Yongming
N1 - Publisher Copyright:
© 2019, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2019
Y1 - 2019
N2 - The discontinuous model has the benefits that spatial singularities or even discontinuities can be avoided compared with the conventional continuum-based computation models. For that reason, an adjoint-based lattice particle method is developed for probabilistic failure analysis of ICME. The performance function value is estimated by Lattice Particle Model (LPM) and the model can be equivalent to solving the system of linear equations consistent with the finite element analysis. The response of the LPM model is regarded as the additional constraints in the probabilistic analysis. And the reliability analysis will be converted to a constrained optimization problem based on FORM. Then, the failure probability is calculated by the efficient gradient-based optimization approach, in which the gradient information is evaluated by the dimension-unrelated adjoint method. The method can overcome the difficulty of “curse of dimensionality” and can be used to solve the extremely large-dimensional problems with a very low computational cost. The demonstrated example shows the good feasibility and efficiency of the method. Finally, several potential future research works are discussed following the conclusions.
AB - The discontinuous model has the benefits that spatial singularities or even discontinuities can be avoided compared with the conventional continuum-based computation models. For that reason, an adjoint-based lattice particle method is developed for probabilistic failure analysis of ICME. The performance function value is estimated by Lattice Particle Model (LPM) and the model can be equivalent to solving the system of linear equations consistent with the finite element analysis. The response of the LPM model is regarded as the additional constraints in the probabilistic analysis. And the reliability analysis will be converted to a constrained optimization problem based on FORM. Then, the failure probability is calculated by the efficient gradient-based optimization approach, in which the gradient information is evaluated by the dimension-unrelated adjoint method. The method can overcome the difficulty of “curse of dimensionality” and can be used to solve the extremely large-dimensional problems with a very low computational cost. The demonstrated example shows the good feasibility and efficiency of the method. Finally, several potential future research works are discussed following the conclusions.
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U2 - 10.2514/6.2019-0970
DO - 10.2514/6.2019-0970
M3 - Conference contribution
AN - SCOPUS:85083942262
SN - 9781624105784
T3 - AIAA Scitech 2019 Forum
BT - AIAA Scitech 2019 Forum
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - AIAA Scitech Forum, 2019
Y2 - 7 January 2019 through 11 January 2019
ER -