Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges
The computerized simulations of physical and socio-economic systems have proliferated in
the past decade, at the same time, the capability to develop high-fidelity system predictive …
the past decade, at the same time, the capability to develop high-fidelity system predictive …
A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications
Z Azarhoosh, MI Ghazaan - Computer Methods in Applied Mechanics and …, 2025 - Elsevier
In fields where predictions may have vital consequences, uncertainty quantification (UQ)
plays a crucial role, as it enables more accurate forecasts and mitigates the potential risks …
plays a crucial role, as it enables more accurate forecasts and mitigates the potential risks …
Hall-effect sensor design with physics-informed Gaussian process modeling
Magnetic field sensor devices have been widely used to track changes in magnetic flux
concentration, and the Hall sensors are promising in many engineering applications. Design …
concentration, and the Hall sensors are promising in many engineering applications. Design …
Multi-Task Learning for Design Under Uncertainty With Multi-Fidelity Partially Observed Information
The assessment of system performance and identification of failure mechanisms in complex
engineering systems often requires the use of computation-intensive finite element software …
engineering systems often requires the use of computation-intensive finite element software …
Hall Effect Sensor Design Optimization With Multi-Physics Informed Gaussian Process Modeling
Magnetic field sensor devices have been widely used to track changes in magnetic flux
concentration, and the Hall sensors are promising in many engineering applications. Design …
concentration, and the Hall sensors are promising in many engineering applications. Design …
Multi-Task Multi-Fidelity Machine Learning for Reliability-Based Design With Partially Observed Information
In complex engineering systems, assessing system performance and underlying failure
mechanisms with respect to uncertain variables requires repeated testing, which is often …
mechanisms with respect to uncertain variables requires repeated testing, which is often …
Hierarchical surrogate modeling with multiple order partially observed information
Understanding the input and output relationship of a complex engineering system is an
essential task that attracts widespread interests in engineering design fields. To investigate …
essential task that attracts widespread interests in engineering design fields. To investigate …
Reliability-Based Optimization of Offshore Salt Caverns for CO2 Abatement
In recent years, projects have been proposed to utilize salt caverns as a storage method for
supercritical CO2 (s-CO2) and have been carried out around the world, which can effectively …
supercritical CO2 (s-CO2) and have been carried out around the world, which can effectively …
High-Dimensional Statistical Inference: Phase Transition, Power Enhancement, and Sampling
Y He - 2021 - search.proquest.com
Abstract The``Big Data''era features large amounts of high-dimensional data, in which the
number of characteristics per subject is large. The high dimensionality of such big data can …
number of characteristics per subject is large. The high dimensionality of such big data can …