Towards an integrated and efficient framework for leveraging reduced order models for multifidelity Uncertainty Quantification.
Abstract not provided.
- Research Organization:
- Sandia National Lab. (SNL-CA), Livermore, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1761000
- Report Number(s):
- SAND2020-0046C; 681919
- Resource Relation:
- Conference: Proposed for presentation at the AIAA SciTech 2020.
- Country of Publication:
- United States
- Language:
- English
Similar Records
Towards an integrated and efficient framework for leveraging reduced order models for multifidelity Uncertainty Quantification.
An integrated and efficient framework for embedded Reduced Order Models for multifidelity Uncertainty Quantification.
Performance and Capability Improvements Towards Industrial Grade Open-Source DEM Simulation Framework with Integrated and Easy-To-Use Uncertainty Quantification.
Conference
·
Wed Jan 01 00:00:00 EST 2020
·
OSTI ID:1761000
+1 more
An integrated and efficient framework for embedded Reduced Order Models for multifidelity Uncertainty Quantification.
Conference
·
Fri Nov 01 00:00:00 EDT 2019
·
OSTI ID:1761000
+3 more
Performance and Capability Improvements Towards Industrial Grade Open-Source DEM Simulation Framework with Integrated and Easy-To-Use Uncertainty Quantification.
Conference
·
Mon Aug 01 00:00:00 EDT 2016
·
OSTI ID:1761000
+7 more