Imperial College London
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DrLudovicRenson

Faculty of Engineering, Department of Mechanical Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 7088l.renson

 
 
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Location

 

558City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Song:2022:10.1016/j.ymssp.2021.108337,
author = {Song, M and Renson, L and Moaveni, B and Kerschen, G},
doi = {10.1016/j.ymssp.2021.108337},
journal = {Mechanical Systems and Signal Processing},
pages = {1--15},
title = {Bayesian model updating and class selection of a wing-engine structure with nonlinear connections using nonlinear normal modes},
url = {http://dx.doi.org/10.1016/j.ymssp.2021.108337},
volume = {165},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper presents a Bayesian model updating and model class selection approach based on nonlinear normal modes (NNMs). The performance of the proposed approach is demonstrated on a conceptually simple wing-engine structure. Control-based continuation is exploited to measure experimentally the NNMs of the structure by tracking the phase quadrature condition between the structural response and single input excitation. A two-phase Bayesian model updating framework is implemented to estimate the joint posterior distribution of unknown model parameters: (1) at phase I, the effective Young’s modulus of a detailed linear finite element model and its estimation uncertainty are inferred from the data; (2) at phase II, a reduced-order model is obtained from the updated linear model using Craig-Bampton method, and coefficient parameters of structural nonlinearities are updated using the measured NNMs. Five different model classes representing different nonlinear functions are investigated, and their Bayesian evidence are compared to reveal the most plausible model. The obtained model is used to predict NNMs by propagating uncertainties of parameters and error function. Good agreement is observed between model-predicted and experimentally identified NNMs, which verifies the effectiveness of the proposed approach for nonlinear model updating and model class selection.
AU  - Song,M
AU  - Renson,L
AU  - Moaveni,B
AU  - Kerschen,G
DO  - 10.1016/j.ymssp.2021.108337
EP  - 15
PY  - 2022///
SN  - 0888-3270
SP  - 1
TI  - Bayesian model updating and class selection of a wing-engine structure with nonlinear connections using nonlinear normal modes
T2  - Mechanical Systems and Signal Processing
UR  - http://dx.doi.org/10.1016/j.ymssp.2021.108337
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000704784400005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.sciencedirect.com/science/article/pii/S0888327021006944?via%3Dihub
UR  - http://hdl.handle.net/10044/1/93680
VL  - 165
ER  -
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