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Embedding Model-form Uncertainty in Probabilistic Calibration of Digital Twins for Bridges

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Digital twins of bridges rely on physics-based models to infer full-field structural responses from sparse monitoring data. The reliability of these predictions depends on the calibration of model parameters while accounting for discrepancies between the model and the physical system.

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Original headline: Embedding Model-form Uncertainty in Probabilistic Calibration of Digital Twins for Bridges

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Embedding Model-form Uncertainty in Probabilistic Calibration of Digital Twins for Bridges

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Опубликованы итоги форсайт-сессии «Будущее безопасности киберфизических систем в России. Перспективы и векторы развития»

From State Synchronization to Cognitive Self-Evolution: An Operational Architecture for Cognitive Digital Twins

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