Zhu Mao - Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics 2021

The Conference Proceedings of the Society for Experimental Mechanics Series presents early findings and case studies from a wide range of fundamental and applied work across the broad range of fields that comprise Experimental Mechanics. Series volumes follow the principle tracks or focus topics featured in each of the Societys two annual conferences: IMAC, A Conference and Exposition on Structural Dynamics, and the Societys Annual Conference & Exposition and will address critical areas of interest to researchers and design engineers working in all areas of Structural Dynamics, Solid Mechanics and Materials Research.

More information about this series at http://www.springer.com/series/8922

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Model Validation and Uncertainty Quantification represents one of nine volumes of technical papers presented at the 39th IMAC, A Conference and Exposition on Structural Dynamics, organized by the Society for Experimental Mechanics, and held between February 8 and 11, 2021. The full proceedings also include volumes on nonlinear structures and systems; dynamics of civil structures; dynamic substructures; special topics in structural dynamics and experimental techniques; rotating machinery, optical methods, and scanning ldv methods; sensors and instrumentation, aircraft/aerospace, energy harvesting, and dynamic environments testing; topics in modal analysis and parameter identification; and data science in engineering.

Each collection presents early findings from experimental and computational investigations on an important area within structural dynamics. Model validation and uncertainty quantification (MVUQ) is one of these areas.

Modeling and simulation are routinely implemented to predict the behavior of complex dynamical systems. These tools powerfully unite theoretical foundations, numerical models, and experimental data, which include associated uncertainties and errors. The field of MVUQ research entails the development of methods and metrics to test model prediction accuracy and robustness while considering all relevant sources of uncertainties and errors through systematic comparisons against experimental observations.

The organizers would like to thank the authors, presenters, session organizers, and session chairs for their participation in this track.