Digital-Twin-Based Improvements to Diagnosis, Prognosis, Strategy Assessment, and Discrepancy Checking in a Nearly Autonomous Management and Control System

no code implementations • 23 May 2021 • Linyu Lin, Paridhi Athe, Pascal Rouxelin, Maria Avramova, Abhinav Gupta, Robert Youngblood, Nam Dinh

The Nearly Autonomous Management and Control System (NAMAC) is a comprehensive control system that assists plant operations by furnishing control recommendations to operators in a broad class of situations.

Attribute BIG-bench Machine Learning +2

Development and Assessment of a Nearly Autonomous Management and Control System for Advanced Reactors

no code implementations • 29 Aug 2020 • Linyu Lin, Paridhi Athe, Pascal Rouxelin, Robert Youngblood, Abhinav Gupta, Jeffrey Lane, Maria Avramova, Nam Dinh

This paper develops a Nearly Autonomous Management and Control (NAMAC) system for advanced reactors.

Management

Using Deep Learning to Explore Local Physical Similarity for Global-scale Bridging in Thermal-hydraulic Simulation

no code implementations • 6 Jan 2020 • Han Bao, Nam Dinh, Linyu Lin, Robert Youngblood, Jeffrey Lane, Hongbin Zhang

Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities.