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Nam Dinh

North Carolina State University

SCHOLARLY PAPERS

5

DOWNLOADS

235

TOTAL CITATIONS

1

Scholarly Papers (5)

1.

Data Coverage Assessment on Neural Network Based Digital Twins for Autonomous Control System

Number of pages: 51 Posted: 28 Jun 2022
Longcong Wang, Linyu Lin and Nam Dinh
affiliation not provided to SSRN, Government of the United States of America - Idaho National Laboratory and North Carolina State University
Downloads 67 (899,324)

Abstract:

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Machine Learning, Neural Network, Digital Twin, Data Coverage Assessment

2.

Machine Learning from Rans And Les to Inform Coarse Grid Simulations

Number of pages: 23 Posted: 11 Apr 2023
North Carolina State University, Pennsylvania State University, Pennsylvania State University and North Carolina State University
Downloads 57 (989,921)

Abstract:

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Machine Learning, Coarse grid RANS, Mixing in upper plenum, Turbulence modeling, Error correction

3.

High-Resolution Flow Boiling Simulations with Multiple Nucleation Sites in Mini-Channels with Offset Strip Fins

Number of pages: 59 Posted: 09 Jul 2024
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, North Carolina State University and North Carolina State University - Department of Nuclear Engineering
Downloads 44 (1,133,231)

Abstract:

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flow boiling, level-set method, direct numerical simulations

4.

Generative AI-based Agentic Framework for the Formulation of Phenomena Identification and Ranking Table for Advanced Reactor Application

Number of pages: 23 Posted: 28 Apr 2026
Paridhi Athe and Nam Dinh
affiliation not provided to SSRN and North Carolina State University
Downloads 36 (1,436,435)

Abstract:

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PIRT, generative AI, knowledge transfer, decision analysis, agentic AI

5.

Development and Assessment of a Reactor System Prognosis Model with Physics-Guided Machine Learning

Number of pages: 18 Posted: 04 Aug 2022
Anil Gurgen and Nam Dinh
University of Maryland, College Park and North Carolina State University
Downloads 31 (1,304,549)
Citation 1

Abstract:

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Nuclear power plant, autonomous control, prognosis, physics-guided machine learning