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At least 163 records · Page 9

Technology Maturation of Wireless Harsh Environment Sensors For Improved Condition Based Monitoring Of Coal Fired Power Generation

The overall goal of this project was to demonstrate and develop the usage of high-temperature (HT) harsh-environment (HE) wireless surface acoustic wave resonator (SAWR) sensor technology to promote reliable maintenance through condition-based maintenance (CBM) for field applications in harsh service conditions associated with power plant environments. The project aimed to advance the HT HE wireless SAWR sensor technology from TRL 5 to TRL 7. In addition to HT HE wireless temperature sensing, efforts were dedicated during this project to investigate, develop and increase the TRL from 3 to 5 for the following technologies: (a) HT HE strain sensors to address additional CBM monitoring needs, such as boiler tube mechanical / thermal stresses, which can provide early indications for boiler tube cracking and failure; and (b) HT aluminum nitride (AlN) and scandium aluminum nitride (ScAlN) based piezoelectric thin film fabrication and implementation of SAW sensors, with the goal of releasing the need to use single crystal piezoelectric materials for SAWRs and thus broaden possible technology applications to non-planar and harder to modify surfaces. To achieve the goals mentioned above, UMaine and its partner, Environetix Technologies Corporation, established partnerships with the following power plants: Longview Power (Maidsville, WV), a coal-fired power plant; Penobscot Energy Recovery Corp (PERC, Orrington, ME), a waste-to-energy power plant; and the UMaine Steam Plant (Orono, ME), an oil / natural gas power plant. To realize wireless HT HE SAWR sensor systems in these harsh service conditions, the University of Maine research team worked with Environetix and these power plants to define, design, fabricate, test and validate a mature prototype wireless temperature SAWR sensor system for boiler tube applications within the HT HE of the reheater pass damper chamber to directly and wirelessly monitor the temperature at eighteen independent boiler tube locations. The system included three levels, or “tiers”, of wireless communication to enable remote monitoring: Tier 1, the wireless link in the reheater pass damper chamber directly accessing the sensors on the boilers; Tier 2, the wireless local area network link, transmitting processed sensor information within the power plant to the Tier 3, a commercial wireless signal carrier company for secure remote data monitoring outside of the power plant. Regarding the wireless sensor system installed at Longview Power, temperature information from the boilers was continuously transmitted from the Longview boilers at Maidsville, WV, to Environetix headquarters, Orono, ME, over a 34 month period, when the system was finally decommissioned. Strain sensors and piezoelectric ScAlN thin film sensors were successfully installed on the exhaust duct at the UMaine Steam Power plant. The advances in wireless strain sensors and thin film piezoelectric film fabrication and testing were performed mostly in UMaine laboratories and field tested at the UMaine Steam Plant, due to its close proximity to UMaine/Environetix, access to the plant facility, and due to difficulties in accessing the other power plants during the COVID shut-down period. The project accomplished the TRL level increase of the targeted CBM technologies through the successful fabrication, installation, test, and validation of dedicated and commercial wireless sensor systems, utilizing the three different power plants. The outcomes of this project, including the wireless sensor data capability, are expected to yield an advance for CBM in harsh power plant environments. The reduction of maintenance costs, improved safety during plant operation, and increased power plant efficiency will lead to increased revenues (i.e., fewer forced outages) due to better process monitoring enabled by the wireless HT HE SAWR temperature sensor technology.

20 FOSSIL-FUELED POWER PLANTS↗

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗

Meso-scale magnetic signatures for nuclear reactor steel irradiation embrittlement monitoring

Verifying the structural integrity of passive components in light water and advanced reactors will be necessary to ensure safe, long-term operations of the existing U.S. nuclear fleet. This objective can be achieved through nondestructive condition monitoring techniques, which can be integrated with plant operations to quantify the “state of health” of structural materials in real-time. While nondestructive methods for monitoring many classes of degradation (such as fatigue or stress corrosion cracking) are relatively advanced, this is not the case for degradation caused by irradiation. The development of nondestructive evaluation technologies for these types of degradation will require advanced materials characterization techniques and tools that enable comprehensive understanding of nuclear reactor material microstructural and behavioral changes under extreme operating environments. Irradiation-induced degradation of reactor steels causes changes in their microstructure that impacts their micro-magnetic properties. In this paper, we describe preliminary results of integrating advanced material characterization techniques with meso-scale computational models. In the future, this will help to provide an interpretive understanding of the state of degradation in structural materials. Microstructural data are presented from monocrystalline Fe and are correlated with variable-field magnetic force microscopy and micro-magnetic measurements. Ongoing research is focused on extending the measurements and models on thin films to gain insights into the structural state of irradiated materials and the resulting impact on magnetic properties. Preliminary conclusions from these correlations are presented, and next steps described.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Extended Bandwidth Spread Spectrum Time Domain Reflectometry Cable Test for Thermal Aging, Low Resistance Fault, and Water Detection

In 2022, researchers at Pacific Northwest National Laboratory (PNNL) used the Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed to characterize spread spectrum time domain reflectometry (SSTDR) and compare the responses of an SSTDR instrument to those of a frequency domain reflectometry (FDR) instrument. Results showed both techniques could detect and locate cable anomalies such as phase-to-phase low resistance and shorts, thermal insulation damage, mechanical insulation damage, and the presence or absence of water in some conditions. The SSTDR tests used a commercial instrument provided by LiveWire Innovations Inc. This commercial instrument performed tests at 6, 12, 24, and 48 MHz bandwidth. The results of these tests were compared to FDR tests where bandwidths could be extended up to 1.3 GHz, although the best responses for cable tests were from 100 to 500 MHz. Lower bandwidth signals can propagate better along the cable while higher bandwidths have higher resolution for impedance change reflections allowing more precise indication of location and separation of anomalies. The 2022 research found that FDR responses were clearer than SSTDR and speculated that a higher bandwidth SSTDR could more successfully detect and locate cable anomalies. One advantage of the SSTDR system investigated was that it was designed for energized online use up to 1,000 volts, which may be a significant advantage for nuclear power plant use. The LiveWire SSTDR instrument is an established product in the rail and aircraft industry and updating the SSTDR hardware parameters is difficult to justify without more conclusive testing. Therefore, a software adjustable laboratory SSTDR instrument was developed by PNNL and was used to test extended bandwidth SSTDR cable tests. Within the ARENA test bed, 42 cable conditions were tested with the PNNL SSTDR, FDR, and the LiveWire SSTDR—each operating at four different bandwidths. Observations and conclusions regarding the relative performance of the three instruments over different bandwidths are note below. Responses of the PNNL SSTDR (at 50 MHz) and the LiveWire SSTDR (at 48 MHz) were similar. The PNNL SSTDR higher frequency bandwidths behaved as expected showing sharper peaks and higher noise. This validated the PNNL SSTDR as a reasonable implementation of the SSTDR technology. Lower bandwidth SSTDR responses (particularly 6 and 12 MHz) may have increased value for use within longer cables but were not particularly effective at identifying anomalous cable behavior in the 100 ft cables tested here. The higher bandwidths of the PNNL SSTDR (50, 100, 200, and 400 MHz) did not provide substantially clearer cable reflectometry responses, but having the higher frequency responses available did add to the cable test evaluation. Strong responses to shorts and low impedance faults between phases were particularly evident in the higher bandwidth PNNL SSTDR and the FDR data. Measurements were repeatable, with similar responses obtained from a thermally aged cable for tests taken a month apart. Signal noise was affected in the unshielded cable by the local in-tray cable arrangement including proximity to metal edges and rungs of the cable tray. Foam isolation of the cable from the tray metal reduced in both FDR and SSTDR responses. Cable condition monitoring in nuclear power plants will likely benefit from both more informative off-line testing methods and from the development of on-line methods for continuous monitoring of cables in use. The LWRS-funded ARENA test bed was a valuable resource for this development and direct comparison of nuclear electrical cable condition monitoring technologies. Test results are targeted to guide industry advancement of testing and monitoring tools for cable aging management.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Monitor weather conditions for cloud seeding control

The author has identified the following significant results. The near real-time DCS platform data transfer to the time-share compare is a working reality. Six stations are now being automatically monitored and displayed with a system delay of 3 to 8 hours from time of data transmission to time of data accessibility on the computer. The DCS platform system has proven itself a valuable tool for near real-time monitoring of mountain precipitation. Data from Wolf Creek Pass were an important input in making the decision when to suspend seeding operations to avoid exceeding suspension criteria in that area. The DCS platforms, as deployed in this investigation, have proven themselves to be reliable weather resistant systems for winter mountain environments in the southern Colorado mountains.

Kahan, A. M.↗

Monitoring Drought Conditions in the Navajo Nation Using NASA Earth Observations

The Navajo Nation, a 65,700 sq km Native American territory located in the southwestern United States, has been increasingly impacted by severe drought events and changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring drought are dependent on state-based monthly Standardized Precipitation Index value maps calculated by the Western Regional Climate Center. However, these maps do not provide the spatial resolution needed to illustrate differences in drought severity across the vast Nation. To better understand and monitor drought events and drought regime changes in the Navajo Nation, this project created a geodatabase of historical climate information specific to the area, and a decision support tool to calculate average Standardized Precipitation Index values for user-specified areas. The tool and geodatabase use Tropical Rainfall Monitoring Mission (TRMM) and Global Precipitation Monitor (GPM) observed precipitation data and Parameter-elevation Relationships on Independent Slopes Model modeled historical precipitation data, as well as NASA's modeled Land Data Assimilation Systems deep soil moisture, evaporation, and transpiration data products. The geodatabase and decision support tool will allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

Ly, Vickie↗

Methods for the Automated Determination of Sustained Maximum Amplitudes in Oscillating Signals

Machine condition monitoring has been proven to reduce machine downtime and increase productivity. The state-of-the-art research uses vibration monitoring for tasks such as maintenance and tool wear prediction. A less explored aspect is how vibration monitoring might be used to monitor equipment sensitive to vibration. In a manufacturing environment, one example of where this might be needed is in monitoring the vibration of optical linear encoders used in high-precision machine tools and coordinate measuring machines. Monitoring the vibration of sensitive equipment presents a unique case for vibration monitoring because an accurate calculation of the maximum sustained vibration is needed, as opposed to extracting trends from the data. To do this, techniques for determining sustained peaks in vibration signals are needed. Here, this work fills this gap by formalizing and testing methods for determining sustained vibration amplitudes. The methods are tested on simulated signals based on experimental data. Results show that processing the signal directly with the novel Expire Timer method produces the smallest amounts of error on average under various test conditions. Additionally, this method can operate in real-time on streaming vibration data.

Industrial Internet of Things↗

Vehicle Integrated Prognostic Reasoner (VIPR) 2010 Annual Final Report

Honeywell's Central Maintenance Computer Function (CMCF) and Aircraft Condition Monitoring Function (ACMF) represent the state-of-the art in integrated vehicle health management (IVHM). Underlying these technologies is a fault propagation modeling system that provides nose-to-tail coverage and root cause diagnostics. The Vehicle Integrated Prognostic Reasoner (VIPR) extends this technology to interpret evidence generated by advanced diagnostic and prognostic monitors provided by component suppliers to detect, isolate, and predict adverse events that affect flight safety. This report describes year one work that included defining the architecture and communication protocols and establishing the user requirements for such a system. Based on these and a set of ConOps scenarios, we designed and implemented a demonstration of communication pathways and associated three-tiered health management architecture. A series of scripted scenarios showed how VIPR would detect adverse events before they escalate as safety incidents through a combination of advanced reasoning and additional aircraft data collected from an aircraft condition monitoring system. Demonstrating VIPR capability for cases recorded in the ASIAS database and cross linking them with historical aircraft data is planned for year two.

Hadden, George D.↗

Compressional wave velocity and effective stress in unsaturated soil: Potential application for monitoring moisture conditions in vadose zone sediments

Compressional seismic (P-wave) velocities were measured experimentally at different water potentials and confining pressure states using a variety of sediments collected from the US Department of Energy Hanford Site in southeastern Washington State. P-wave velocity was measured in variably saturated sediments using ultrasonic piezoelectric transducers and water potential was measured with a heat dissipation sensor. We propose a model to relate changes in P-wave velocity to soil stress conditions using an effective stress formulation that includes capillary stress as well as adsorptive stress. We show that compressional wave velocities can be related to water potential and confining stress using a model with five fitted parameters. A single set of parameters provides an excellent fit to data acquired from all of the sediment samples. Under very dry conditions, corresponding to low water potentials, water flow occurs in adsorptive thin films associated with very low unsaturated hydraulic conductivities. The results presented here suggest the utility of seismic methods for establishing low water potential and flow conditions within variably saturated Hanford formation sediments and providing feedback on the performance of mitigation efforts such as soil desiccation and surface infiltration barriers. Seismic methods can provide minimally invasive, three-dimensional information on relevant flow conditions in vadose zone sediments as well as changes that occur over time.

Linneman, Dorothy C.↗

Augmented Monitoring and Condition Assessment Program (AMCAP) Material Test Reactor (MTR) (Fuel Inspection Program Report)

The AMCAP MTR Fuel Inspection Program, a special inspection program comprised of four inspection campaigns, examined a total of ten (10) pre-selected aluminum-clad, aluminum-based fuel core spent nuclear fuel assemblies (ASNF) stored in the L Area Disassembly Basin (L Basin) at the Savannah River Site. A full description of the inspections and the results are reported. The fuel had been stored in bundled-tube storage (Vertical Tube Storage) for periods of 18 to 21 years. The prior service experience of the individual 10 assemblies varies, but all included irradiation followed by wet storage at international research reactor sites prior to shipment to the US and storage in L Basin. The 10 assemblies were expected to be among the “worst"’ in terms of prior corrosion damage of the entire inventory of the direct-bundle-stored ASNF in L Basin. The inventory of MTR ASNF in L Basin will continue to be stored in the bundled-tube configuration or in slug-storage buckets with inserts pending retrieval for ultimate disposition. The MTR fuel inspections focused on collecting information for characterization of the material condition of the ASNF considering various types of aluminum fuel corrosion degradation of its assembled materials in water storage. A custom-designed Fuel Inspection Table was used to stage the fuel for remote, enhanced visual examination (close-up video imaging & recording) with controlled lighting and positioning that enables reproducibility of imaging conditions. The inspections were conducted by fuel subject matter expert staff from Spent Fuel Project Engineering (SFPE) and the Savannah River National Laboratory (SRNL). Stills captured from the video records were used to compare the corrosion evolution from previous records, as available. This evaluation of the inspection results including the comparison to the previous inspection results demonstrate that the water quality and the storage configuration of ASNF in L Basin do not cause aggressive corrosion degradation of the fuel; mitigation of the prior corrosion degradation of the fuel also appears to have been achieved with the good water quality conditions of L Basin. Recommendations are made for future inspection of the fuel to trend corrosion degradation and demonstrate continued safe wet storage of the ASNF in L Basin. The next fuel examination is recommended to be performed in 5 years.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗