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RISS 인기검색어
- 검색키워드
- 저자 : J. WESLEY HINES (검색결과 6 건)
- 무료
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MSET Performance Optimization Through Regularization
J. WESLEY HINES,ALEXANDER USYNIN 한국원자력학회 2005 Nuclear Engineering and Technology Vol.37 No.2
The Multivariate State Estimation Technique (MSET) is being used in Nuclear Power Plants for sensor and equipment condition monitoring. This paper presents the use of regularization methods for optimizing MSET’s predictive performance. The techniques are applied to a simulated data set and a data set obtained from a nuclear power plant currently implementing empirical, on-line, equipment condition monitoring techniques. The results show that regularization greatly enhances the predictive performance. Additionally, the selection of prototype vectors is investigated and a local modeling method is presented that can be applied when computational speed is desired.
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MSET PERFORMANCE OPTIMIZATION THROUGH REGULARIZATION
HINES J. WESLEY,USYNIN ALEXANDER Korean Nuclear Society 2005 Nuclear Engineering and Technology Vol.37 No.2
The Multivariate State Estimation Technique (MSET) is being used in Nuclear Power Plants for sensor and equipment condition monitoring. This paper presents the use of regularization methods for optimizing MSET's predictive performance. The techniques are applied to a simulated data set and a data set obtained from a nuclear power plant currently implementing empirical, on-line, equipment condition monitoring techniques. The results show that regularization greatly enhances the predictive performance. Additionally, the selection of prototype vectors is investigated and a local modeling method is presented that can be applied when computational speed is desired.
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COMPUTATIONAL INTELLIGENCE IN NUCLEAR ENGINEERING
UHRIG ROBERT E.,HINES J. WESLEY Korean Nuclear Society 2005 Nuclear Engineering and Technology Vol.37 No.2
Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.
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Computational Intelligence in Nuclear Engineering
ROBERT E. UHRIG,J. WESLEY HINES 한국원자력학회 2005 Nuclear Engineering and Technology Vol.37 No.2
Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.
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VALIDATION OF ON-LINE MONITORING TECHNIQUES TO NUCLEAR PLANT DATA
Garvey, Jamie,Garvey, Dustin,Seibert, Rebecca,Hines, J. Wesley Korean Nuclear Society 2007 Nuclear Engineering and Technology Vol.39 No.2
The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection
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INSTRUMENTATION AND CONTROL STRATEGIES FOR AN INTEGRAL PRESSURIZED WATER REACTOR
BELLE R. UPADHYAYA,MATTHEW R. LISH,J. WESLEY HINES,RYAN A. TARVER 한국원자력학회 2015 Nuclear Engineering and Technology Vol.47 No.2
Several vendors have recently been actively pursuing the development of integral pressurizedwater reactors (iPWRs) that range in power levels from small to large reactors. Integral reactors have the features of minimum vessel penetrations, passive heat removalafter reactor shutdown, and modular construction that allow fast plant integration and asecure fuel cycle. The features of an integral reactor limit the options for placing controland safety system instruments. The development of instrumentation and control (I&C)strategies for a large 1,000 MWe iPWR is described. Reactor system modelingdwhich includesreactor core dynamics, primary heat exchanger, and the steam flashing drumdis animportant part of I&C development and validation, and thereby consolidates the overallimplementation for a large iPWR. The results of simulation models, control development,and instrumentation features illustrate the systematic approach that is applicable to integrallight water reactors
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