TY - GEN
T1 - Applications of multifidelity reduced order modeling to single and multiphysics problems
AU - Wang, X. Q.
AU - Song, P.
AU - Mignolet, M. P.
N1 - Funding Information:
The financial support of this work by the Air Force Multi University Research Initiative contract FA9550-15-1-0038 with Dr. Jean-Luc Cambier as Technical Monitor is gratefully acknowledged.
Publisher Copyright:
© 2020, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2020
Y1 - 2020
N2 - The focus of the present investigation is on assessing the applicability and performance of the recently introduced Multifidelity Monte Carlo (MFMC) for the computationally efficient prediction of the statistics of the random response of uncertain structures especially those undergoing large deformations and modeled within nonlinear reduced order models. Three such nonlinear applications are considered the first of which is a purely structural problem, a panel subjected to a large loads inducing nonlinear geometric effects. Reduced order models with different fidelities are then generated by reducing the size of the basis from a given set of basis functions. The second nonlinear application is a multiphysics problem, a panel undergoing a simulated high speed trajectory with aerodynamic-structural-thermal coupling. The third application is also multiphysics and focuses on the limit cycle oscillation behavior of a wing past flutter due to structural nonlinearity. In addition, a preliminary validation of the methodology was also carried out that focuses on the linear response of a structure modeled in finite elements where different fidelities are obtained by varying the mesh size. In all of these applications, the MFMC performed very well leading to accurate predictions of the statistics of the response at a reduced/much reduced computational cost.
AB - The focus of the present investigation is on assessing the applicability and performance of the recently introduced Multifidelity Monte Carlo (MFMC) for the computationally efficient prediction of the statistics of the random response of uncertain structures especially those undergoing large deformations and modeled within nonlinear reduced order models. Three such nonlinear applications are considered the first of which is a purely structural problem, a panel subjected to a large loads inducing nonlinear geometric effects. Reduced order models with different fidelities are then generated by reducing the size of the basis from a given set of basis functions. The second nonlinear application is a multiphysics problem, a panel undergoing a simulated high speed trajectory with aerodynamic-structural-thermal coupling. The third application is also multiphysics and focuses on the limit cycle oscillation behavior of a wing past flutter due to structural nonlinearity. In addition, a preliminary validation of the methodology was also carried out that focuses on the linear response of a structure modeled in finite elements where different fidelities are obtained by varying the mesh size. In all of these applications, the MFMC performed very well leading to accurate predictions of the statistics of the response at a reduced/much reduced computational cost.
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U2 - 10.2514/6.2020-2131.c1
DO - 10.2514/6.2020-2131.c1
M3 - Conference contribution
AN - SCOPUS:85092389737
SN - 9781624105951
T3 - AIAA Scitech 2020 Forum
BT - AIAA Scitech 2020 Forum
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - AIAA Scitech Forum, 2020
Y2 - 6 January 2020 through 10 January 2020
ER -