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08/02/2023
A digital twin framework for civil engineering structures
The digital twin concept represents an appealing opportunity to advance ...
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04/22/2022
Bayesian operator inference for data-driven reduced-order modeling
This work proposes a Bayesian inference method for the reduced-order mod...
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10/14/2021
Non-intrusive reduced-order models for parametric partial differential equations via data-driven operator inference
This work formulates a new approach to reduced modeling of parameterized...
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12/10/2020
A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale
A unifying mathematical formulation is needed to move from one-off digit...
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04/23/2020
From Physics-Based Models to Predictive Digital Twins via Interpretable Machine Learning
This work develops a methodology for creating a data-driven digital twin...
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10/06/2019
mfEGRA: Multifidelity Efficient Global Reliability Analysis
This paper develops mfEGRA, a multifidelity active learning method using...
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07/28/2019
Balanced Truncation Model Reduction for Lifted Nonlinear Systems
We present a balanced truncation model reduction approach for a class of...
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05/19/2018
Contour location via entropy reduction leveraging multiple information sources
We introduce an algorithm to locate contours of functions that are expen...
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11/12/2017