Výsledky vyhledávání - "Todd, Michael D"

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Damage detection in an uncertain nonlinear beam based on stochastic Volterra series: an experimental application

Autor: Villani, Luis Gustavo Gioacon, da Silva, Samuel, Cunha Jr, Americo, Todd, Michael D.

Publikováno v: Mechanical Systems and Signal Processing, vol. 128, pp. 463-478, 2019

The damage detection problem becomes a more difficult task when the intrinsically nonlinear behavior of the structures and the natural data variation are considered in the analysis because both phenomena can be confused with damage if linear and dete

Externí odkaz: http://arxiv.org/abs/2409.16305

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Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems

Autor: Sharma, Harsh, Najera-Flores, David A., Todd, Michael D., Kramer, Boris

Complex mechanical systems often exhibit strongly nonlinear behavior due to the presence of nonlinearities in the energy dissipation mechanisms, material constitutive relationships, or geometric/connectivity mechanics. Numerical modeling of these sys

Externí odkaz: http://arxiv.org/abs/2404.05040

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A Comprehensive Review of Digital Twin -- Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives

Autor: Thelen, Adam, Zhang, Xiaoge, Fink, Olga, Lu, Yan, Ghosh, Sayan, Youn, Byeng D., Todd, Michael D., Mahadevan, Sankaran, Hu, Chao, Hu, Zhen

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensiv

Externí odkaz: http://arxiv.org/abs/2208.12904

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