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 …
Adaptive surrogate models with partially observed information
Surrogate models have been developed to replace expensive physical models and reduce
the computational cost in various engineering applications, such as reliability analysis and …
the computational cost in various engineering applications, such as reliability analysis and …
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 …
Alleviating expansion-induced mechanical degradation in lithium-ion battery silicon anodes via morphological design
The mechanics of films undergoing volume expansion on curved substrates plays a key role
in a variety of technologies including biomedical implants, thermal and environmental …
in a variety of technologies including biomedical implants, thermal and environmental …
Numerical modeling on the delamination-induced capacity degradation of silicon anode
Silicon is a promising candidate for the negative electrode in lithium-ion battery. However,
silicon-based electrodes experience large volume changes during the lithiation-delithiation …
silicon-based electrodes experience large volume changes during the lithiation-delithiation …
Uncertainty quantification analysis on mechanical properties of the structured silicon anode via surrogate models
Silicon anode is the most promising candidate for next generation lithium ion batteries. A
major drawback limiting its application is the significant volume change during lithiation …
major drawback limiting its application is the significant volume change during lithiation …
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 …
Design of three-dimensional bi-continuous silicon based electrode materials for high energy density batteries
Silicon-based anode is a promising candidate for next generation lithium-ion batteries (LIBs)
with improved energy and power density. However, the practical application of Si anode is …
with improved energy and power density. However, the practical application of Si anode is …
Mean Time to Failure Prediction for Complex Systems With Adaptive Surrogate Modeling
Abstract The Mean Time to Failure (MTTF) is a critical metric for assessing the reliability of
non-repairable systems, and it plays a significant role in incident management. However …
non-repairable systems, and it plays a significant role in incident management. However …