Xu, Y., Kohtz, S., Boakye, J., Gardoni, P., & Wang, P. (2023). Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges. Reliability engineering & system safety, 230, 108900. https://doi.org/10.1016/j.ress.2022.108900
Chicago Style (17th ed.) CitationXu, Yanwen, Sara Kohtz, Jessica Boakye, Paolo Gardoni, and Pingfeng Wang. "Physics-informed Machine Learning for Reliability and Systems Safety Applications: State of the Art and Challenges." Reliability Engineering & System Safety 230 (2023): 108900. https://doi.org/10.1016/j.ress.2022.108900.
MLA (9th ed.) CitationXu, Yanwen, et al. "Physics-informed Machine Learning for Reliability and Systems Safety Applications: State of the Art and Challenges." Reliability Engineering & System Safety, vol. 230, 2023, p. 108900, https://doi.org/10.1016/j.ress.2022.108900.