[en] The overall purpose of this Nuclear Engineering Education Research (NEER) project was to integrate new, innovative, and existing technologies to develop a fault diagnostics and characterization system for nuclear plant steam generators (SG) and heat exchangers (HX). Issues related to system level degradation of SG and HX tubing, including tube fouling, performance under reduced heat transfer area, and the damage caused by stress corrosion cracking, are the important factors that influence overall plant operation, maintenance, and economic viability of nuclear power systems. The research at The University of Tennessee focused on the development of techniques for monitoring process and structural integrity of steam generators and heat exchangers. The objectives of the project were accomplished by the completion of the following tasks. All the objectives were accomplished during the project period. This report summarizes the research and development activities, results, and accomplishments during June 2001-September 2004. (1) Development and testing of a high-fidelity nodal model of a U-tube steam generator (UTSG) to simulate the effects of fouling and to generate a database representing normal and degraded process conditions. Application of the group method of data handling (GMDH) method for process variable prediction. (2) Development of a laboratory test module to simulate particulate fouling of HX tubes and its effect on overall thermal resistance. Application of the GMDH technique to predict HX fluid temperatures, and to compare with the calculated thermal resistance. (3) Development of a hybrid modeling technique for process diagnosis and its evaluation using laboratory heat exchanger test data. (4) Development and testing of a sensor suite using piezo-electric devices for monitoring structural integrity of both flat plates (beams) and tubing. Experiments were performed in air, and in water with and without bubbly flow. (5) Development of advanced signal processing methods using wavelet transforms and image processing techniques for isolating flaw types. (6) Development and implementation of a new nonlinear and non-stationary signal processing method, called the Hilbert-Huang transform (HHT), for flaw detection and location. This is a more robust and adaptive approach compared to the wavelet transform. (7) Implementation of a moving-window technique in the time domain for detecting and quantifying flaw types in tubular structures. A window zooming technique was also developed for flaw location in tubes. (8) Theoretical study of elastic wave propagation (longitudinal and shear waves) in metallic flat plates and tubing with and without flaws. (9) Simulation of the Lamb wave propagation using the finite-element code ABAQUS. This enabled the verification of the experimental results. The research tasks included both analytical research and experimental studies. The experimental results helped to enhance the robustness of fault monitoring methods and to provide a systematic verification of the analytical results. The results of this research were disseminated in scientific meetings. A journal manuscript was submitted for publication. The new findings of this research have potential applications in aerospace and civil structures. The report contains a complete bibliography that was developed during the course of the project

[en] Integrity monitoring and flaw diagnostics of flat beams and tubular structures was investigated in this research task using guided acoustic signals. A piezo-sensor suite was deployed to activate and collect Lamb wave signals that propagate along metallic specimens. The dispersion curves of Lamb waves along plate and tubular structures are generated through numerical analysis. Several advanced techniques were explored to extract representative features from acoustic time series. Among them, the Hilbert-Huang transform (HHT) is a recently developed technique for the analysis of non-linear and transient signals. A moving window method was introduced to generate the local peak characters from acoustic time series, and a zooming window technique was developed to localize the structural flaws. The time-frequency analysis and pattern recognition techniques were combined for classifying structural defects in brass tubes. Several types of flaws in brass tubes were tested, both in the air and in water. The techniques also proved to be effective under background/process noise. A detailed theoretical analysis of Lamb wave propagation was performed and simulations were carried out using the finite element software system ABAQUS. This analytical study confirmed the behavior of the acoustic signals acquired from the experimental studies. The report presents the background the analysis of acoustic signals acquired from piezo-electric transducers for structural defect monitoring. A comparison of the use of time-frequency techniques, including the Hilbert-Huang transform, is presented. The report presents the theoretical study of Lamb wave propagation in flat beams and tubular structures, and the need for mode separation in order to effectively perform defect diagnosis. The results of an extensive experimental study of detection, location, and isolation of structural defects in flat aluminum beams and brass tubes are presented. The results of this research show the feasibility of on-line monitoring of small structural flaws by the use of transient and nonlinear acoustic signal analysis, and its implementation by the proper design of a piezo-electric transducer suite

[en] An integrated method for the detection and isolation of incipient faults in common field devices, such as sensors and actuators, using plant operational data is presented. The approach is based on the premise that data for normal operation lie on a surface and abnormal situations lead to deviations from the surface in a particular way. Statistically significant deviations from the surface result in the detection of faults, and the characteristic directions of deviations are used for isolation of one or more faults from the set of typical faults. Principal component analysis (PCA), a multivariate data-driven technique, is used to capture the relationships in the data and fit a hyperplane to the data. The fault direction for each of the scenarios is obtained using the singular value decomposition on the state and control function prediction errors, and fault isolation is then accomplished from projections on the fault directions. This approach is demonstrated for a simulated pressurized water reactor steam generator system and for a laboratory process control system under single device fault conditions. Enhanced fault isolation capability is also illustrated by incorporating realistic nonlinear terms in the PCA data matrix

[en] This paper presents a reactor-monitoring algorithm using the group method of data handling (GMDH) that creates nonlinear algebraic models for system characterization. The monitoring system was applied to the IEA-R1 experimental reactor at the Instituto de Pesquisas Energeticas e Nucleares (IPEN). The IEA-R1 is a 5-MW pool-type research reactor that uses light water as coolant and moderator and graphite as reflector. The GMDH provides a general framework for characterizing the relationships among a set of state variables of a process system and is used for generating estimates of critical variables in an optimal data-driven model form. The monitoring system developed in this work was used to predict the IEA-R1 reactor environment, using nuclear power, rod position, and coolant temperatures, by combining two variables at a time. The results obtained using the GMDH models agreed very well with the dose rate measurements, with prediction errors of less than 5%. The error was minimal when the dose rate prediction was made using reactor power and coolant temperature

[en] Highlights: • Integral Inherently Safe Light Water Reactor instrumentation is discussed. • Ultrasonic primary flow monitoring for integral reactors is proposed. • In-vessel instrument cable strategies are discussed and paths proposed. - Abstract: The Integral Inherently Safe Light Water Reactor (I"2S-LWR) is a novel pressurized water reactor (PWR) concept being developed by a multi-institutional team led by Georgia Institute of Technology, under the Department of Energy’s Nuclear Energy University Programs Integrated Research Projects (DOE NEUP IRP). The I"2S-LWR aims to deliver approximately 1 GWe power output, comparable to other large scale LWRs, while simultaneously delivering improved safety over other Generation III+ LWRs. This reactor concept aims to achieve these goals by incorporating inherent safety features in the design. These features include an integral design of the primary coolant and control rod drive systems which eliminate the possibility of large break loss of coolant and control rod ejection accidents. It also features a fully passive decay heat removal system (DHRS) designed to providing indefinite core cooling as long as the core remains submerged in coolant. These features impact the design of the instrumentation system in a variety of ways. The University of Tennessee is developing instrumentation and control design concepts for the I"2S-LWR. The development of instrumentation systems in the I"2S-LWR, and the challenges and technology gaps to be addressed, are presented.

[en] The University of Tennessee is engaged in research and development projects related to instrumentation and controls for small modular reactors (SMR) and integral pressurized water reactors (iPWR). The approach incorporates the deployment of physics-based models for control design and parameter estimation, development of noncontact sensors for flow monitoring, and placement of sensors to maximize fault detection and isolation. The results of research and development illustrate the feasibility of sensor location in space-constrained environment. Major issues and challenges in I and C design are addressed

[en] Development and deployment of small-scale nuclear power reactors and their maintenance, monitoring, and control are part of the mission under the Small Modular Reactor (SMR) program. The objectives of this NERI-consortium research project are to investigate, develop, and validate advanced methods for sensing, controlling, monitoring, diagnosis, and prognosis of these reactors, and to demonstrate the methods with application to one of the proposed integral pressurized water reactors (IPWR). For this project, the IPWR design by Westinghouse, the International Reactor Secure and Innovative (IRIS), has been used to demonstrate the techniques developed under this project. The research focuses on three topical areas with the following objectives. Objective 1 - Develop and apply simulation capabilities and sensitivity/uncertainty analysis methods to address sensor deployment analysis and small grid stability issues. Objective 2 - Develop and test an autonomous and fault-tolerant control architecture and apply to the IRIS system and an experimental flow control loop, with extensions to multiple reactor modules, nuclear desalination, and optimal sensor placement strategy. Objective 3 - Develop and test an integrated monitoring, diagnosis, and prognosis system for SMRs using the IRIS as a test platform, and integrate process and equipment monitoring (PEM) and process and equipment prognostics (PEP) toolboxes. The research tasks are focused on meeting the unique needs of reactors that may be deployed to remote locations or to developing countries with limited support infrastructure. These applications will require smaller, robust reactor designs with advanced technologies for sensors, instrumentation, and control. An excellent overview of SMRs is described in an article by Ingersoll (2009). The article refers to these as deliberately small reactors. Most of these have modular characteristics, with multiple units deployed at the same plant site. Additionally, the topics focus on meeting two of the eight needs outlined in the recently published 'Technology Roadmap on Instrumentation, Control, and Human-Machine Interface (ICHMI) to Support DOE Advanced Nuclear Energy Programs' which was created 'to provide a systematic path forward for the integration of new ICHMI technologies in both near-term and future nuclear power plants and the reinvigoration of the U.S. nuclear ICHMI community and capabilities.' The research consortium is led by The University of Tennessee (UT) and is focused on three interrelated topics: Topic 1 (simulator development and measurement sensitivity analysis) is led by Dr. Mike Doster with Dr. Paul Turinsky of North Carolina State University (NCSU). Topic 2 (multivariate autonomous control of modular reactors) is led by Dr. Belle Upadhyaya of the University of Tennessee (UT) and Dr. Robert Edwards of Penn State University (PSU). Topic 3 (monitoring, diagnostics, and prognostics system development) is led by Dr. Wes Hines of UT. Additionally, South Carolina State University (SCSU, Dr. Ken Lewis) participated in this research through summer interns, visiting faculty, and on-campus research projects identified throughout the grant period. Lastly, Westinghouse Science and Technology Center (Dr. Mario Carelli) was a no-cost collaborator and provided design information related to the IRIS demonstration platform and defining needs that may be common to other SMR designs. The results of this research are reported in a six-volume Final Report (including the Executive Summary, Volume 1). Volumes 2 through 6 of the report describe in detail the research and development under the topical areas. This volume serves to introduce the overall NERI-C project and to summarize the key results. Section 2 provides a summary of the significant contributions of this project. A list of all the publications under this project is also given in Section 2. Section 3 provides a brief summary of each of the five volumes (2-6) of the report. The contributions of SCSU are described in Section 4, including a summary of undergraduate research experience. The project management organizational chart is provided as Figure 1. Appendices A, B, and C contain the reports on the summer research performed at the University of Tennessee by undergraduate students from South Carolina State University.

[en] In this paper, a reconfigurable controller consisting of a normal controller and a standby controller is designed to control the ThermoElectric (TE) power in the SP-100 space reactor. The normal controller uses a Model Predictive Control (MPC) method where the future TE power is predicted by using support vector regression. A genetic algorithm that can effectively accomplish multiple objectives is used to optimize the normal controller. The performance of the normal controller depends on the capability of predicting the future TE power. Therefore, if the prediction performance is degraded, the Proportional-Integral (PI) controller of the standby controller begins to work instead of the normal controller. Performance deterioration is detected by a Sequential Probability Ratio Test (SPRT). A lumped parameter simulation model of the SP-100 nuclear space reactor is used to verify the proposed reconfigurable controller. The results of numerical simulations to assess the performance of the proposed controller show that the TE generator power level controlled by the proposed reconfigurable controller could track the target power level effectively, satisfying all control constraints. Furthermore, the normal controller is automatically switched to the standby controller when the performance of the normal controller degrades

[en] Several Generation IV nuclear reactor concepts have goals for optimizing investment recovery through phased introduction of multiple units on a common site with shared facilities and/or reconfigurable energy conversion systems. Additionally, small modular reactors are suitable for remote deployment to support highly localized microgrids in isolated, underdeveloped regions. The long-term economic viability of these advanced reactor plants depends on significant reductions in plant operations and maintenance costs. To accomplish these goals, intelligent control and diagnostic capabilities are needed to provide nearly autonomous operations with anticipatory maintenance. A nearly autonomous control system should enable automatic operation of a nuclear power plant while adapting to equipment faults and other upsets. It needs to have many intelligent capabilities, such as diagnosis, simulation, analysis, planning, reconfigurability, self-validation, and decision. These capabilities have been the subject of research for many years, but an autonomous control system for nuclear power generation remains as-yet an unrealized goal. This article describes a functional framework for intelligent, autonomous control that can facilitate the integration of control, diagnostic, and decision-making capabilities to satisfy the operational and performance goals of power plants based on multimodular advanced reactors

[en] Preliminary results of the dynamic analysis of a two-fluid molten-salt breeder reactor (MSBR) system are presented. Based on an earlier work on the preliminary dynamic model of the concept, the model presented here is nonlinear and has been revised to accurately reflect the design exemplified in ORNL-4528. A brief overview of the model followed by results from simulations performed to validate the model is presented. Simulations illustrate stable behavior of the reactor dynamics and temperature feedback effects to reactivity excursions. Stable and smooth changes at various nodal temperatures are also observed. Control strategies for molten-salt reactor operation are discussed, followed by an illustration of the open-loop load-following capability of the molten-salt breeder reactor system. It is observed that the molten-salt breeder reactor system exhibits “self-regulating” behavior, minimizing the need for external controller action for load-following maneuvers