Online autonomous calibration of digital twins using machine learning with application to nuclear power plants

Data-Enabled Physics-Informed Machine Learning for Reduced-Order Modeling Digital Twin: Application to Nuclear Reactor Physics

(2022) Helin Gong et al.   NUCLEAR SCIENCE AND ENGINEERING

Policies toward net-zero: Benchmarking the economic competitiveness of nuclear against wind and solar energy

(2022) Victor Nian et al.   APPLIED ENERGY

Physics-informed machine learning-aided framework for prediction of minimum film boiling temperature

(2022) Kyung Mo Kim et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems

(2022) Ahmad K. Sleiti et al.   Energy Reports

Online Learning: A Comprehensive Survey

(2021) Steven C. H. Hoi et al.   NEUROCOMPUTING

Improved departure from nucleate boiling prediction in rod bundles using a physics-informed machine learning-aided framework

(2021) Xingang Zhao et al.   NUCLEAR ENGINEERING AND DESIGN

The role of current and emerging technologies in meeting Japan’s mid- to long-term carbon reduction goals

(2021) Anshuman Chaube et al.   APPLIED ENERGY

Economic solution for low carbon process heat: A horizontal, compact high temperature gas reactor

(2021) W.R. Stewart et al.   APPLIED ENERGY

Application of the best-estimate model calibration and prediction through experimental data assimilation methodology to the tests performed on a helium cooled First Wall Mock-up

(2020) Bruno Gonfiotti et al.   FUSION ENGINEERING AND DESIGN

The k-means Algorithm: A Comprehensive Survey and Performance Evaluation

(2020) Mohiuddin Ahmed et al.   Electronics

Development and assessment of a nearly autonomous management and control system for advanced reactors

(2020) Linyu Lin et al.   ANNALS OF NUCLEAR ENERGY

A data-driven framework for error estimation and mesh-model optimization in system-level thermal-hydraulic simulation

(2019) Han Bao et al.   NUCLEAR ENGINEERING AND DESIGN

Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system

(2019) Zhe Dong et al.   APPLIED ENERGY

On the prediction of critical heat flux using a physics-informed machine learning-aided framework

(2019) Xingang Zhao et al.   APPLIED THERMAL ENGINEERING

Autonomous operation algorithm for safety systems of nuclear power plants by using long-short term memory and function-based hierarchical framework

(2018) Daeil Lee et al.   ANNALS OF NUCLEAR ENERGY

Discovering relationships and forecasting PM 10 and PM 2.5 concentrations in Bogotá, Colombia, using Artificial Neural Networks, Principal Component Analysis, and k-means clustering

(2018) Fabiana Franceschi et al.   Atmospheric Pollution Research

Short-term power prediction for photovoltaic power plants using a hybrid improved Kmeans-GRA-Elman model based on multivariate meteorological factors and historical power datasets

(2018) Peijie Lin et al.   ENERGY CONVERSION AND MANAGEMENT

A Data Mining Approach Combining $K$ -Means Clustering With Bagging Neural Network for Short-Term Wind Power Forecasting

(2017) Wenbin Wu et al.   IEEE Internet of Things Journal

Day-ahead electricity price forecasting via the application of artificial neural network based models

(2016) Ioannis P. Panapakidis et al.   APPLIED ENERGY

Future prospects for nuclear power in France

(2014) Nadia Maïzi et al.   APPLIED ENERGY

Nuclear power can reduce emissions and maintain a strong economy: Rating Australia’s optimal future electricity-generation mix by technologies and policies

(2014) Sanghyun Hong et al.   APPLIED ENERGY

Improvement of ATHLET modelling capability for asymmetric natural circulation phenomenon using uncertainty and sensitivity measures

(2013) X.J. Liu et al.   ANNALS OF NUCLEAR ENERGY

Forecasting hourly global solar radiation using hybrid k-means and nonlinear autoregressive neural network models

(2013) Khalil Benmouiza et al.   ENERGY CONVERSION AND MANAGEMENT

A review of online learning in supervised neural networks

(2013) Lakhmi C. Jain et al.   NEURAL COMPUTING & APPLICATIONS

Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach

(2013) Derong Liu et al.   IEEE Transactions on Neural Networks and Learning Systems

Using statistical sensitivities for adaptation of a best-estimate thermo-hydraulic simulation model

(2010) X.J. Liu et al.   NUCLEAR ENGINEERING AND DESIGN

Control Experiment of a Wheel-Driven Mobile Inverted Pendulum Using Neural Network

(2008) Seul Jung et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY