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2020 – today
- 2024
[j6]Longcong Wang
, Linyu Lin, Nam Dinh:
Trustworthiness modeling and evaluation for a nearly autonomous management and control system. Reliab. Eng. Syst. Saf. 245: 110008 (2024)- [j5]Edward Chen, Han Bao, Nam Dinh:
Evaluating the reliability of machine-learning-based predictions used in nuclear power plant instrumentation and control systems. Reliab. Eng. Syst. Saf. 250: 110266 (2024) - 2023
- [i11]Edward Chen, Han Bao, Nam Dinh:
Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Methods Integrated in Instrumentation & Control Systems. CoRR abs/2308.05120 (2023) - 2022
- [i10]Edward Chen, Han Bao, Tate Shorthill, Carl R. Elks, Nam Dinh:
Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA. CoRR abs/2205.12075 (2022) - [i9]Edward Chen, Han Bao, Tate Shorthill, Carl R. Elks, Athira Varma Jayakumar, Nam Dinh:
Application of Orthogonal Defect Classification for Software Reliability Analysis. CoRR abs/2205.12080 (2022) - [i8]Edward Chen, Han Bao, Tate Shorthill, Hongbin Zhang, Nam Dinh:
Systems-theoretic Hazard Analysis of Digital Human-System Interface Relevant to Reactor Trip. CoRR abs/2209.05480 (2022) - 2021
- [j4]Yang Liu, Dewei Wang, Xiaodong Sun, Yang Liu, Nam Dinh, Rui Hu:
Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments. Reliab. Eng. Syst. Saf. 212: 107636 (2021) - [i7]Linyu Lin, Han Bao, Nam Dinh:
Uncertainty Quantification and Software Risk Analysis for Digital Twins in the Nearly Autonomous Management and Control Systems: A Review. CoRR abs/2103.03680 (2021) - [i6]Linyu Lin, Paridhi Athe, Pascal Rouxelin, Maria Avramova, Abhinav Gupta, Robert Youngblood, Nam Dinh:
Digital-Twin-Based Improvements to Diagnosis, Prognosis, Strategy Assessment, and Discrepancy Checking in a Nearly Autonomous Management and Control System. CoRR abs/2105.11039 (2021) - 2020
- [j3]Saran Srikanth Bodda, Abhinav Gupta, Nam Dinh:
Enhancement of risk informed validation framework for external hazard scenario. Reliab. Eng. Syst. Saf. 204: 107140 (2020) - [i5]Han Bao, Nam Dinh, Linyu Lin, Robert Youngblood, Jeffrey Lane, Hongbin Zhang:
Using Deep Learning to Explore Local Physical Similarity for Global-scale Bridging in Thermal-hydraulic Simulation. CoRR abs/2001.04298 (2020) - [i4]Han Bao, Jinyong Feng, Nam Dinh, Hongbin Zhang:
Deep Learning Interfacial Momentum Closures in Coarse-Mesh CFD Two-Phase Flow Simulation Using Validation Data. CoRR abs/2005.03767 (2020) - [i3]Linyu Lin, Nam Dinh:
Predictive Capability Maturity Quantification using Bayesian Network. CoRR abs/2010.03373 (2020)
2010 – 2019
- 2019
- [i2]Han Bao, Jinyong Feng, Nam Dinh, Hongbin Zhang:
Computationally Efficient CFD Prediction of Bubbly Flow using Physics-Guided Deep Learning. CoRR abs/1910.08037 (2019) - 2018
- [j2]Shinyoung Kwag, Abhinav Gupta, Nam Dinh:
Probabilistic risk assessment based model validation method using Bayesian network. Reliab. Eng. Syst. Saf. 169: 380-393 (2018) - [i1]Yang Liu, Nam Dinh, Yohei Sato, Bojan Niceno:
Data-driven modeling for boiling heat transfer: using deep neural networks and high-fidelity simulation results. CoRR abs/1808.01859 (2018) - 2010
- [j1]Hong Luo, Luqing Luo, Robert R. Nourgaliev, Vincent Mousseau, Nam Dinh:
A reconstructed discontinuous Galerkin method for the compressible Navier-Stokes equations on arbitrary grids. J. Comput. Phys. 229(19): 6961-6978 (2010)
Coauthor Index
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