Linyu Lin

Works (5)

Updated: April 11th, 2023 10:13

2022 journal article

Data coverage assessment on neural network based digital twins for autonomous control system

ANNALS OF NUCLEAR ENERGY, 182.

By: L. Wang n, L. Lin* & N. Dinh n 

author keywords: Machine learning; Neural network; Digital twin; Data coverage assessment
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Sources: Web Of Science, NC State University Libraries
Added: January 17, 2023

2021 journal article

Development of the Machine Learning-based Safety Significant Factor Inference Model for Diagnosis in Autonomous Control System

ANNALS OF NUCLEAR ENERGY, 162.

By: J. Lee n, L. Lin n, P. Athe n  & N. Dinh n 

Contributors: J. Lee n, L. Lin n, P. Athe n  & N. Dinh n 

author keywords: Diagnosis; Digital twin; Recurrent Neural Network; Safety significant factor; Machine Learning
TL;DR: A machine learning (ML) based SSF inference model (SSFIM) using the Recurrent Neural Network (RNN) with acceptable accuracy, generalization capability, effectiveness, and robustness against sensor errors is developed. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: August 23, 2021

2021 journal article

Digital-twin-based improvements to diagnosis, prognosis, strategy assessment, and discrepancy checking in a nearly autonomous management and control system

ANNALS OF NUCLEAR ENERGY, 166.

By: L. Lin n, P. Athe n , P. Rouxelin n, M. Avramova n, A. Gupta n, R. Youngblood*, J. Lane*, N. Dinh n 

Contributors: L. Lin n, P. Athe n , P. Rouxelin n, M. Avramova n, A. Gupta n, R. Youngblood*, J. Lane*, N. Dinh n 

author keywords: autonomous control; digital twin; diagnosis; prognosis
TL;DR: This study refines a NAMAC system for making reasonable recommendations during complex loss-of-flow scenarios with a validated Experimental Breeder Reactor II simulator, digital twins improved by machine-learning algorithms, a multi-attribute decision-making scheme, and a discrepancy checker for identifying unexpected recommendation effects. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: November 1, 2021

2021 article

Enhancing the Operational Resilience of Advanced Reactors with Digital Twins by Recurrent Neural Networks

2021 RESILIENCE WEEK (RWS).

By: L. Lin*, J. Lee n, B. Poudel *, T. McJunkin *, N. Dinh n  & V. Agarwal *

author keywords: digital twin; diagnosis; prognosis; resilience
TL;DR: This paper develops and assesses both the diagnosis and prognosis DTs in a nearly autonomous management and control system for an Experimental Breeder Reactor-II simulator during different loss-of-flow scenarios. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: May 10, 2022

2021 review

Uncertainty quantification and software risk analysis for digital twins in the nearly autonomous management and control systems: A review

[Review of ]. ANNALS OF NUCLEAR ENERGY, 160.

By: L. Lin n, H. Bao* & N. Dinh n 

author keywords: Digital twin; Autonomous control; Uncertainty quantification; Software risk analysis
TL;DR: This study selects and reviews relevant UQ techniques and software hazard and software risk analysis methods that may be suitable for DTs in the NAMAC system and evaluates the uncertainty of DTs and its impacts on the reactor digital instrumentation and control systems. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: July 6, 2021

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