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Extension of the NEAMS workbench to parallel sensitivity and uncertainty analysis of thermal hydraulic parameters using Dakota and Nek5000

Authors :
Marc-Olivier G. Delchini
Laura P. Swiler
Robert A. Lefebvre
Source :
Nuclear Engineering and Technology, Vol 53, Iss 10, Pp 3449-3459 (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

With the increasing availability of high-performance computing (HPC) platforms, uncertainty quantification (UQ) and sensitivity analyses (SA) can be efficiently leveraged to optimize design parameters of complex engineering problems using modeling and simulation tools. The workflow involved in such studies heavily relies on HPC resources and hence requires pre-processing and post-processing capabilities of large amounts of data along with remote submission capabilities. The NEAMS Workbench addresses all aspects of the workflows involved in these studies by relying on a user-friendly graphical user interface and a python application program interface.This paper highlights the NEAMS Workbench capabilities by presenting a semiautomated coupling scheme between Dakota and any given package integrated with the NEAMS Workbench, yielding a simplified workflow for users. This new capability is demonstrated by running a SA of a turbulent flow in a pipe using the open-source Nek5000 CFD code. A total of 54 jobs were run on a HPC platform using the remote capabilities of the NEAMS Workbench. The results demonstrate that the semiautomated coupling scheme involving Dakota can be efficiently used for UQ and SA while keeping scripting tasks to a minimum for users. All input and output files used in this work are available in https://code.ornl.gov/neams-workbench/dakota-nek5000-study.

Details

Language :
English
ISSN :
17385733
Volume :
53
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Nuclear Engineering and Technology
Publication Type :
Academic Journal
Accession number :
edsdoj.5125aa8d19f44a4b4fba1908589cbba
Document Type :
article
Full Text :
https://doi.org/10.1016/j.net.2021.04.005