Engineering topics

Dib, Gerges

Publications and source records attributed to Dib, Gerges.

9 records

DOE OSTI2019

In-situ fatigue monitoring procedure using nonlinear ultrasonic surface waves considering the nonlinear effects in the measurement system

Second harmonic generation using nonlinear ultrasonic waves have been shown to be an early indicator of possible fatigue damage in nuclear power plant components. This technique relies on measuring amplitudes, making it highly susceptible to variations in transducer coupling and instrumentation. This paper proposes an experimental procedure for in-situ surface wave nonlinear ultrasound measurements on specimen with permanently mounted transducers under high cycle fatigue loading without interrupting the experiment. It allows continuous monitoring and minimizes variation due to transducer coupling. Moreover, relations describing the effects of the measurement system nonlinearity including the effects of the material transfer function on the measured nonlinearity parameter are derived. An in-situ high cycle fatigue test was conducted using two 304 stainless steel specimens with two different excitation frequencies. A comprehensive analysis of the nonlinear sources, which result in variations in the measured nonlinearity parameters, was performed and the effects of the system nonlinearities are explained and identified. In both specimens, monotonic trend was observed in nonlinear parameter when the value of fundamental amplitude was not changing.

42 ENGINEERING↗

DOE OSTI2019

Investigations of degradation and encapsulation of plastic scintillator

Studies have revealed that plastic scintillators such as polyvinyl toluene and polystyrene can undergo environmentally related material damage (“fogging”) that adversely affects detection performance under certain conditions and histories. A significant decrease in sensitivity has been seen in some gamma-ray detectors as they age as a result of this damage. Performance degradation due to such damage is characterized by a signal change from the detector, which shifts to lower energy, and ultimately a reduction in the ability to detect gamma radiation. This degradation is due to the permeation of water into the plastic, which can then cause temporary fogging and permanent damage to the material. As an example, a 1-mm thick barrier of high-density polyethylene with an area of 1 m 2 would allow 5 g per year of water transmission at 100% relative humidity. Thus, significant amounts of water can penetrate plastics over time and provide the potential for damage to the plastic. Such damage to plastic scintillator can cause problems for radiation detection applications in uncontrolled environments. Mitigation approaches that have been proposed to prevent damage to plastic scintillator include encapsulation of the plastic scintillator to prevent water intrusion that leads to damage during cold cycles. It is concluded that an encapsulation material with a moisture vapor transmission rate on the order of 10 -4 g∙m -2 ∙d -1 or better is needed for protecting large pieces of plastic scintillator from fogging over years of use. This article presents information on testing of bare and encapsulated plastic scintillator samples and on diagnostic approaches to measure the nature and progression of the fogging condition. It is shown that several encapsulation approaches fail to prevent water intrusion, while a couple methods can successfully encapsulate plastic and prevent water from penetrating the plastic and producing fogging.

36 MATERIALS SCIENCE↗

DOE OSTI2018

On the Usage of Ultrasound Computational Models for Decision Making Under Ambiguity

Computer modeling and simulation is becoming pervasive within the non-destructive evaluation (NDE) industry as a convenient tool for designing and assessing inspection techniques. This raises a pressing need for developing quantitative techniques for demonstrating the validity and applicability of the computational models. Computational models provide deterministic results based on deterministic and well-defined input, or stochastic results based on inputs defined by probability distributions. However, computational models cannot account for the effects of personnel, procedures, and equipment, resulting in ambiguity about the efficacy of inspections based on guidance from computational models only. In addition ambiguity arises when model inputs, such as the representation of realistic cracks, cannot be defined deterministically, probabilistically, or by intervals. In this work, Pacific Northwest National Laboratory demonstrates the ability of computational models to represent field measurements under known variabilities, and quantify the differences using maximum amplitude and power spectrum density metrics. Sensitivity studies are also conducted to quantify the effects of different input parameters on the simulation results.

Dib, Gerges↗

DOE OSTI2017

Integration and Assessment of Component Health Prognostics in Supervisory Control Systems

Enhanced risk monitors (ERMs) for active components in advanced reactor concepts use predictive estimates of component failure to update, in real time, predictive safety and economic risk metrics. These metrics have been shown to be capable of use in optimizing maintenance scheduling and managing plant maintenance costs. Integrating this information with plant supervisory control systems increases the potential for making control decisions that utilize real-time information on component conditions. Such decision making would limit the possibility of plant operations that increase the likelihood of degrading the functionality of one or more components while maintaining the overall functionality of the plant. ERM uses sensor data for providing real-time information about equipment condition for deriving risk monitors. This information is used to estimate the remaining useful life and probability of failure of these components. By combining this information with plant probabilistic risk assessment models, predictive estimates of risk posed by continued plant operation in the presence of detected degradation may be estimated. In this paper, we describe this methodology in greater detail, and discuss its integration with a prototypic software-based plant supervisory control platform. In order to integrate these two technologies and evaluate the integrated system, software to simulate the sensor data was developed, prognostic models for feedwater valves were developed, and several use cases defined. The full paper will describe these use cases, and the results of the initial evaluation.

Ramuhalli, Pradeep↗

DOE OSTI2017

Integration and assessment of component health prognostics in supervisory control systems - 291

Enhanced risk monitors (ERMs) for active components in advanced reactor concepts use predictive estimates of component failure to update, in real time, predictive safety and economic risk metrics. These metrics have been shown to be capable of use in optimizing maintenance scheduling and managing plant maintenance costs. Integrating this information with plant supervisory control systems increases the potential for making control decisions that utilize realtime information on component conditions. Such decision making would limit the possibility of plant operations that increase the likelihood of degrading the functionality of one or more components while maintaining the overall functionality of the plant. ERM uses sensor data for providing real-time information about equipment condition for deriving risk monitors. This information is used to estimate the remaining useful life and probability of failure of these components. By combining this information with plant probabilistic risk assessment models, predictive estimates of risk posed by continued plant operation in the presence of detected degradation may be estimated. In this paper, we describe this methodology in greater detail, and discuss its integration with a prototypic software-based plant supervisory control platform. In order to integrate these two technologies and evaluate the integrated system, software to simulate the sensor data was developed, prognostic models for feedwater valves were developed, and several use cases defined. The full paper will describe these use cases, and the results of the initial evaluation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

PVT Degradation Studies: Acoustic Diagnostics

Under certain environmental conditions, polyvinyl toluene (PVT) plastic scintillator has been observed to undergo internal fogging. This document reports on a study of acoustic techniques to determine whether they can provide a diagnostic for the fogging of PVT. Different ultrasound techniques were employed for detecting the level of internal fogging in PVT, including wave velocity measurements, attenuation, nonlinear acoustics, and acoustic microscopy. The results indicate that there are linear relations between the wave velocity and wave attenuation with the level of internal fogging. The effects of fogging on ultrasound wave attenuation is further verified by acoustic microscopy imaging, where regions with fog in the specimen demonstration higher levels of attenuation compared to clear regions. Results from the nonlinear ultrasound measurements were inconclusive due to high sensitivities to transducer coupling and fixture variabilities.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Supervisory Control System for Multi-Modular Advanced Reactors

The proposed supervisory control system (SCS) may provide considerable benefits to advanced small modular reactors, including reduced plant staffing, optimized maintenance activities, greater plant availability, and higher operating efficiency. The SCS makes risk-informed decisions based on (1) a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and (2) a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety system—one measure of SCS success. The probabilistic portion of the decision-making engine of the SCS is based on the control actions associated with an advanced liquid-metal reactor (ALMR) Power Reactor, Innovative, Small Module (PRISM). Within the SCS, the probabilistic assessment provides a ranking of viable control actions; however, certain instructions generated by the probabilistic model only include an abstract notion of action without specifications. For instance, one instruction may be to reduce power without specifying how much reduction is needed. The prognostic/diagnostic models incorporate the health of components into the decision-making process. Once the control options are identified and ranked based on the likelihood of success, the SCS transmits the options to the deterministic portion of the platform. The performance-based system models assess and rank each of the probabilistically identified control actions by taking into account the physical behavior (current and projected) of the system. The performance-based decision making module receives inputs from the probabilistic decision-making module and the ERM module to generate a single solution. Interfaces to these modules are defined later in the section. A utility theory algorithm factors into the decision making by estimating the distance from and approach to a trip setpoint for each control option. If the magnitude of a negative utility value increases rapidly as the system approaches the trip setpoint, that option is not likely to be the preferred option. This can lead to a re-ranking of the control options. The SCS then transmits a control signal(s) to a component or system and informs the operator of actions taken based on the action chosen. The SCS successfully coupled probabilistic and performance-based system models to arrive at optimal control decisions based on the actual status of the plant and components. The automatic, autonomous, and real-time performance requirements for a control system were met by the SCS. The value of coupling probabilistic and performance-based system models was demonstrated by the re-ranking of control options based on the use of a utility algorithm. The use of ERM monitors provides added value to the SCS as demonstrated by the re-ranking of control options based on a components degraded state.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Summary Describing Integration of ERM Methodology into Supervisory Control Framework with Software Package Documentation; Advanced Reactor Technology Milestone: M4AT-16PN2301052

This project involved the development of enhanced risk monitors (ERMs) for active components in Advanced Reactor (AdvRx) designs by integrating real-time information about equipment condition with risk monitors. Health monitoring techniques in combination with predictive estimates of component failure based on condition and risk monitors can serve to indicate the risk posed by continued operation in the presence of detected degradation. This combination of predictive health monitoring based on equipment condition assessment and risk monitors can also enable optimization of maintenance scheduling with respect to the economics of plant operation. This report summarizes PNNL’s multi-year project on the development and evaluation of an ERM concept for active components while highlighting FY2016 accomplishments. Specifically, this report provides a status summary of the integration and demonstration of the prototypic ERM framework with the plant supervisory control algorithms being developed at Oak Ridge National Laboratory (ORNL), and describes additional case studies conducted to assess sensitivity of the technology to different quantities. Supporting documentation on the software package to be provided to ONRL is incorporated in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Nondestructive Measurements for Diagnostics of Advanced Reactor Passive Components

Information on advanced reactor (AdvRx) component condition and failure probability is necessary to maintaining adequate safety margins and avoiding unplanned shutdowns, both of which have regulatory and economic consequences. Prognostic health management (PHM) technologies provide one approach to addressing these needs by providing the technical means for lifetime management of significant passive components and reactor internals. However, such systems require measurement data that are sensitive to degradation of the component. This paper describes results to date of ongoing research on nondestructive measurements of component condition for degradation mechanisms of relevance to AdvRx concepts. The focus of this paper is on in-situ ultrasonic measurements during high-temperature creep degradation. The data were analyzed to assess the sensitivity of the measurements to creep degradation, with the specific objective of assessing the suitability of the resulting correlations for remaining life prediction. The details of the measurements, results of data analysis, and ongoing research in this area are discussed.

advanced reactors↗