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Multi-fidelity analysis and uncertainty quantification of beam vibration using co-kriging interpolation method

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  • Krishnan, K V Vishal
  • Ganguli, Ranjan

Abstract

In this paper, a multi-fidelity surrogate model is created using co-kriging methodology to determine the natural frequencies of beams by combining the fidelities of Euler-Bernoulli (low-fidelity) and Timoshenko (high-fidelity) beam finite element models. This study of free vibration of beams involves uncertainties in material properties. The sampling space for the co-kriging surrogate model is created using an optimal latin hypercube sampling technique. It is shown that the co-kriging surrogate model predicts the natural frequencies with high computational efficiency and accuracy, in the entire design space. The computational efficiency and utility of the multi-fidelity model is demonstrated through its application to a problem of quantifying uncertainties in the natural frequencies of a tapered beam using Monte Carlo Simulation.

Suggested Citation

  • Krishnan, K V Vishal & Ganguli, Ranjan, 2021. "Multi-fidelity analysis and uncertainty quantification of beam vibration using co-kriging interpolation method," Applied Mathematics and Computation, Elsevier, vol. 398(C).
    • Handle: RePEc:eee:apmaco:v:398:y:2021:i:c:s0096300321000357
    DOI: 10.1016/j.amc.2021.125987
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    References listed on IDEAS

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    1. Nobuo Namura & Koji Shimoyama & Shigeru Obayashi, 2017. "Kriging surrogate model with coordinate transformation based on likelihood and gradient," Journal of Global Optimization, Springer, vol. 68(4), pages 827-849, August.
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    Cited by:

    1. Lima, João P.S. & Evangelista, F. & Guedes Soares, C., 2023. "Hyperparameter-optimized multi-fidelity deep neural network model associated with subset simulation for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 239(C).

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