What is it about?
This paper presents a computational method able to leverage sensor data to enrich the computational model o a system, enabling actualized feedback and prediction that aid in the decision-making process. This method creates a family of solutions, informed by data, to capture information that is not captured by a deterministic computational model. In this work, we focus on improvements that have made this method more robust and able to be run in near-real time
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This page is a summary of: Multimodal Data-Assimilation using the Nonparametric Probabilistic Method for Model-Form Uncertainty Quantification, Stochastic Model Updating, and Digital Twinning, January 2024, American Institute of Aeronautics and Astronautics (AIAA),
DOI: 10.2514/6.2024-0578.
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