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Linearly structured quadratic model updating using partial incomplete eigendata

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  • Saha, Tanay
  • Rakshit, Suman
  • Khare, Swanand R.

Abstract

This paper presents a new method for linearly structured quadratic model updating problem for the second order damped system. This problem is concerned with updating the quadratic model with minimum adjustment preserving the linear structure of the original damped model using partially measured incomplete eigendata. It is worthwhile to note that partially measured incomplete eigendata refers to a small number of incomplete measured modal data, that is, a few natural frequencies along with some specific coordinates of the corresponding mode shapes of the model are measured. In this paper, we have proposed an optimization based approach to find the solution of the problem. Towards the end, some numerical experiments have been presented to demonstrate the efficiency and usefulness of our proposed approach.

Suggested Citation

  • Saha, Tanay & Rakshit, Suman & Khare, Swanand R., 2023. "Linearly structured quadratic model updating using partial incomplete eigendata," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    • Handle: RePEc:eee:apmaco:v:446:y:2023:i:c:s0096300323000607
    DOI: 10.1016/j.amc.2023.127891
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    References listed on IDEAS

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    1. Wenyu Sun & Ya-Xiang Yuan, 2006. "Optimization Theory and Methods," Springer Optimization and Its Applications, Springer, number 978-0-387-24976-6, September.
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