Train small, model big: Scalable physics simulators via reduced order modeling and domain decomposition.

MLA

Chung, Seung Whan, et al. “Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition.” Computer Methods in Applied Mechanics & Engineering, vol. 427, July 2024, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.cma.2024.117041.

APA

Chung, S. W., Choi, Y., Roy, P., Moore, T., Roy, T., Lin, T. Y., Nguyen, D. T., Hahn, C., Duoss, E. B., & Baker, S. E. (2024). Train small, model big: Scalable physics simulators via reduced order modeling and domain decomposition. Computer Methods in Applied Mechanics & Engineering, 427, N.PAG. https://doi.org/10.1016/j.cma.2024.117041

Chicago

Chung, Seung Whan, Youngsoo Choi, Pratanu Roy, Thomas Moore, Thomas Roy, Tiras Y. Lin, Du T. Nguyen, Christopher Hahn, Eric B. Duoss, and Sarah E. Baker. 2024. “Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition.” Computer Methods in Applied Mechanics & Engineering 427 (July): N.PAG. doi:10.1016/j.cma.2024.117041.