Physics-Informed Machine Learning Surrogates with Optimization-Based Guarantees: Applications to AC Power Flow.
Abstract not provided.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- NA0003525;
- OSTI ID:
- 1897922
- Report Number(s):
- SAND2021-14467C; 701553
- Resource Type:
- Conference presentation
- Conference Information:
- Proposed for presentation at the AIChE Annual Meeting held November 8-12, 2021 in Bostom, MA United States
- Country of Publication:
- United States
- Language:
- English
Similar Records
Physics-informed machine learning with optimization-based guarantees: Applications to AC power flow
Physics-informed machine learning of flow and reactive transport in porous media.
Journal Article
·
2024
· International Journal of Electrical Power and Energy Systems
·
OSTI ID:2283480
Physics-informed machine learning of flow and reactive transport in porous media.
Conference
·
2021
·
OSTI ID:1876606