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Found 6 papers, 2 papers with code
A digital twin framework for civil engineering structures
This work proposes a predictive digital twin approach to the health monitoring, maintenance, and management planning of civil engineering structures.
A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale
The formal definition of this coupled system as a probabilistic graphical model enables us to draw upon well-established theory and methods from Bayesian statistics, dynamical systems, and control theory.
From Physics-Based Models to Predictive Digital Twins via Interpretable Machine Learning
In operation, the classifier uses observational data from the asset to infer which physics-based models in the model library are the best candidates for the updated digital twin.
mfEGRA: Multifidelity Efficient Global Reliability Analysis through Active Learning for Failure Boundary Location
The method builds on the Efficient Global Reliability Analysis (EGRA) method, which is a surrogate-based method that uses adaptive sampling for refining Gaussian process surrogates for failure boundary location using a single-fidelity model.
Contour location via entropy reduction leveraging multiple information sources
We introduce an algorithm to locate contours of functions that are expensive to evaluate.
Should You Derive, Or Let the Data Drive? An Optimization Framework for Hybrid First-Principles Data-Driven Modeling
This work takes a different perspective and targets the construction of a correction model operator with implicit attributes.
