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 …
Physics-informed machine learning model for battery state of health prognostics using partial charging segments
The accurate and efficient estimation of battery state-of-health (SoH) is an ever-significant
issue for applications of lithium-ion batteries (LIBs). Physics-of-failure (PoF) and machine …
issue for applications of lithium-ion batteries (LIBs). Physics-of-failure (PoF) and machine …
[HTML][HTML] A surrogate-assisted uncertainty quantification and sensitivity analysis on a coupled electrochemical–thermal battery aging model
M Alipour, L Yin, SS Tavallaey, AM Andersson… - Journal of Power …, 2023 - Elsevier
High-fidelity physics-based models are required to comprehend battery behavior at various
operating conditions. This paper proposes an uncertainty quantification analysis on a …
operating conditions. This paper proposes an uncertainty quantification analysis on a …
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 …
[HTML][HTML] Machine learning enhanced control co-design optimization of an immersion cooled battery thermal management system
The development of lithium-ion battery technology has ensured that battery thermal
management systems are an essential component of the battery pack for next-generation …
management systems are an essential component of the battery pack for next-generation …
Polyethylene terephthalate-based cathode current collectors coated by ultrathin aluminum metal layers for commercial lithium-ion batteries with high security and long …
W Yao, Z Zheng, G Zhong, Y Lin, D Liu, J Song… - Journal of Alloys and …, 2023 - Elsevier
With the rapidly increasing market demand of lithium-ion batteries (LIBs), safety has become
the main focus and challenge in realizing high-energy and high-safety LIBs. In this paper, a …
the main focus and challenge in realizing high-energy and high-safety LIBs. In this paper, a …
[HTML][HTML] Physics-informed machine learning for system reliability analysis and design with partially observed information
Constructing a high-fidelity predictive model is crucial for analyzing complex systems,
optimizing system design, and enhancing system reliability. Although Gaussian Process …
optimizing system design, and enhancing system reliability. Although Gaussian Process …
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 …
Adaptive surrogate models for uncertainty quantification with partially observed information
View Video Presentation: https://doi. org/10.2514/6.2022-1439. vid Surrogate models are
commonly used to reduce computational cost by replacing expensive physical models with …
commonly used to reduce computational cost by replacing expensive physical models with …
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 …