Digital twin, physics-based model, and machine learning applied to damage detection in structures

Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health Monitoring

(2020) Caterina Bigoni et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Deep digital twins for detection, diagnostics and prognostics

(2020) Wihan Booyse et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Uncertainty quantification in deep convolutional neural network diagnostics of journal bearings with ovalization fault

(2020) Diogo Stuani Alves et al.   MECHANISM AND MACHINE THEORY

Machine learning based digital twin for dynamical systems with multiple time-scales

(2020) S. Chakraborty et al.   COMPUTERS & STRUCTURES

The role of surrogate models in the development of digital twins of dynamic systems

(2020) S. Chakraborty et al.   APPLIED MATHEMATICAL MODELLING

A high-bias, low-variance introduction to Machine Learning for physicists

(2019) Pankaj Mehta et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

The digital twin of discrete dynamic systems: Initial approaches and future challenges

(2019) R. Ganguli et al.   APPLIED MATHEMATICAL MODELLING

Investigation of random matrix applications on structural dynamics using a tensor decomposition

(2019) Thiago G. Ritto et al.   Journal of the Brazilian Society of Mechanical Sciences and Engineering

Digital twin approach for damage-tolerant mission planning under uncertainty

(2019) Pranav M. Karve et al.   ENGINEERING FRACTURE MECHANICS

Solving high-dimensional partial differential equations using deep learning

(2018) Jiequn Han et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Optimal classification trees

(2017) Dimitris Bertsimas et al.   MACHINE LEARNING

Simulation-Based Classification; a Model-Order-Reduction Approach for Structural Health Monitoring

(2016) T. Taddei et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

Data-driven probability concentration and sampling on manifold

(2016) C. Soize et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems

(2015) Peter Benner et al.   SIAM REVIEW

A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing

(2011) Christopher J. Roy et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A new measure of efficiency for model reduction: Application to a vibroimpact system

(2010) T.G. Ritto et al.   JOURNAL OF SOUND AND VIBRATION