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Full-Text Articles in Nuclear Engineering
Development Of A Data Driven Multiple Observer And Causal Graph Approach For Fault Diagnosis Of Nuclear Power Plant Sensors And Field Devices, Ke Zhao
Data driven multiple observer and causal graph approach to fault detection and isolation is developed for nuclear power plant sensors and actuators. It can be integrated into the advanced instrumentation and control system for the next generation nuclear power plants.
The developed approach is based on analytical redundancy principle of fault diagnosis. Some analytical models are built to generate the residuals between measured values and expected values. Any significant residuals are used for fault detection and the residual patterns are analyzed for fault isolation.
Advanced data driven modeling methods such as Principal Component Analysis and Adaptive Network Fuzzy Inference System ...
An Information Approach To Regularization Parameter Selection For The Solution Of Ill-Posed Inverse Problems Under Model Misspecification, Aleksey M. Urmanov
Engineering problems are often ill-posed, i.e. cannot be solved by conventional data-driven methods such as parametric linear and nonlinear regression or neural networks. A method of regularization that is used for the solution of ill-posed problems requires an a priori choice of the regularization parameter. Several regularization parameter selection methods have been proposed in the literature, yet, none is resistant to model misspecification. Since almost all models are incorrectly or approximately specified, misspecification resistance is a valuable option for engineering applications.
Each data-driven method is based on a statistical procedure which can perform well on one data set and ...