101 citations · 264 across the 32 of their papers we have counts for
33 papers
Modelling Irrational Behaviour of Residential End Users using Non-Stationary Gaussian Processes
Nam Trong Dinh, Sahand Karimi-Arpanahi, Rui Yuan +4
Demand response (DR) plays a critical role in ensuring efficient electricity consumption and optimal use of network assets. Yet, existing DR models often overlook a crucial element…
Predict+Optimize Problem in Renewable Energy Scheduling
Christoph Bergmeir, Frits de Nijs, Evgenii Genov +25
Predict+Optimize frameworks integrate forecasting and optimization to address real-world challenges such as renewable energy scheduling, where variability and uncertainty are criti…
Interface Capturing Flow Boiling Simulations in a Compact Heat Exchanger
Anna Iskhakova, Yoshiyuki Kondo, Koichi Tanimoto +2
High-fidelity flow boiling simulations are conducted in a vertical minichannel with offset strip fins (OSF) using R113 as a working fluid. Finite-element code PHASTA coupled with l…
Optimal activity and battery scheduling algorithm using load and solar generation forecasts
Yogesh Pipada Sunil Kumar, Rui Yuan, Nam Trong Dinh +1
Energy usage optimal scheduling has attracted great attention in the power system community, where various methodologies have been proposed. However, in real-world applications, th…
Systems-theoretic Hazard Analysis of Digital Human-System Interface Relevant to Reactor Trip
Edward Chen, Han Bao, Tate Shorthill +2
Human-system interface is one of the key advanced design features applied to modern digital instrumentation and control systems of nuclear power plants. The conventional design is…
Application of Orthogonal Defect Classification for Software Reliability Analysis
Edward Chen, Han Bao, Tate Shorthill +3
The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks stron…
Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA
Edward Chen, Han Bao, Tate Shorthill +2
In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems. However, there has also bee…
Advanced Transient Diagnostic with Ensemble Digital Twin Modeling
Edward Chen, Linyu Lin, Nam T. Dinh
The use of machine learning (ML) model as digital-twins for reduced-order-modeling (ROM) in lieu of system codes has grown traction over the past few years. However, due to the com…
Direct Numerical Simulation of Low and Unitary Prandtl Number Fluids in Reactor Downcomer Geometry
Cheng-Kai Tai, Tri Nguyen, Arsen S. Iskhakov +3
Buoyancy effect on low-flow condition convective heat transfer of non-conventional coolants, such as liquid metal and molten salts, is a crucial safety factor to advanced reactors…
Data-driven Hi2Lo for Coarse-grid System Thermal Hydraulic Modeling
Arsen S. Iskhakov, Nam T. Dinh, Victor Coppo Leite +1
Traditional 1D system thermal hydraulic analysis has been widely applied in nuclear industry for licensing purposes due to its numerical efficiency. However, such codes are inheren…
Optimal activity and battery scheduling algorithm using load and solar generation forecast
Rui Yuan, Nam Trong Dinh, Yogesh Pipada +1
In this report, we provide a technical sequence on tackling the solar PV and demand forecast as well as optimal scheduling problem proposed by the IEEE-CIS 3rd technical challenge…
Digital-Twin-Based Improvements to Diagnosis, Prognosis, Strategy Assessment, and Discrepancy Checking in a Nearly Autonomous Management and Control System
Linyu Lin, Paridhi Athe, Pascal Rouxelin +4
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…
Uncertainty Quantification and Software Risk Analysis for Digital Twins in the Nearly Autonomous Management and Control Systems: A Review
Linyu Lin, Han Bao, Nam Dinh
A nearly autonomous management and control (NAMAC) system is designed to furnish recommendations to operators for achieving particular goals based on NAMAC's knowledge base. As a c…
Review of Physics-based and Data-driven Multiscale Simulation Methods for Computational Fluid Dynamics and Nuclear Thermal Hydraulics
Arsen S. Iskhakov, Nam T. Dinh
Modeling of fluid flows requires corresponding adequate and effective approaches that would account for multiscale nature of the considered physics. Despite the tremendous growth o…
Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments
Yang Liu, Dewei Wang, Xiaodong Sun +2
In this paper, we develop a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of the two-fluid model-based multiphase computational fluid…
Physics-integrated machine learning: embedding a neural network in the Navier-Stokes equations. Part II
Arsen S. Iskhakov, Nam T. Dinh
The work is a continuation of a paper by Iskhakov A.S. and Dinh N.T. "Physics-integrated machine learning: embedding a neural network in the Navier-Stokes equations". Part I // arX…
Physics-integrated machine learning: embedding a neural network in the Navier-Stokes equations. Part I
Arsen S. Iskhakov, Nam T. Dinh
In this paper the physics- (or PDE-) integrated machine learning (ML) framework is investigated. The Navier-Stokes (NS) equations are solved using Tensorflow library for Python via…
Predictive Capability Maturity Quantification using Bayesian Network
Linyu Lin, Nam Dinh
In nuclear engineering, modeling and simulations (M&Ss) are widely applied to support risk-informed safety analysis. Since nuclear safety analysis has important implications, a con…
Development and Assessment of a Nearly Autonomous Management and Control System for Advanced Reactors
Linyu Lin, Paridhi Athe, Pascal Rouxelin +5
This paper develops a Nearly Autonomous Management and Control (NAMAC) system for advanced reactors. The development process of NAMAC is characterized by a three layer-layer archit…
An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario
B. N. Hanna, L. T. Trieu, T. C. Son +1
The paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagno…
Deep Learning Interfacial Momentum Closures in Coarse-Mesh CFD Two-Phase Flow Simulation Using Validation Data
Han Bao, Jinyong Feng, Nam Dinh +1
Multiphase flow phenomena have been widely observed in the industrial applications, yet it remains a challenging unsolved problem. Three-dimensional computational fluid dynamics (C…
A Data-driven Approach for Turbulence Modeling
Yangmo Zhu, Nam Dinh
Data-driven turbulence modeling is a newly emerged research area in thermal hydraulics simulation of nuclear power plant (NPP). The most common CFD method used in NPP thermal hydra…
Development of a Data-driven Turbulence Model for 3d Thermal Stratification Simulation during Reactor Transients
Yangmo Zhu, Nam Dinh, Rui Hu +1
SAM, a plant-level system analysis tool for advanced reactors (SFR, LFR, MSR/FHR) is under development at Argonne. As a modern system code, SAM aims to improve the predictions of 3…
Using Deep Learning to Explore Local Physical Similarity for Global-scale Bridging in Thermal-hydraulic Simulation
Han Bao, Nam Dinh, Linyu Lin +3
Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond th…