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Modeling Efforts to Gain Insight into Historical Leak Events from the Single-Shell Tank A-105 in the Hanford 241-A Tank Farm - 20113
The 241-A Tank Farm is a single-shell tank (SST) farm constructed to store process waste from Hanford nuclear operations. Millions of gallons of nuclear waste were stored in the 241-A Tank Farm SSTs and some of the SSTs leaked in the past. In addition, spills and pipeline leaks during transfers and storage and intentional discharges to cribs and trenches resulted in releasing waste to the ground. Tank liner leaks are referred to as 'leaks' and all other discharges to the soil are referred to as 'releases.' Liquid waste that could be removed by pumping has been removed from all of the SSTs to reduce the potential for future leaks. The most significant historical leak event in 241-A Tank Farm occurred in 1965 when tank A-105 experienced a pressurized steam event. This event resulted in damage to the inner steel liner flooring of A-105, which was separated from the sidewalls over part of its circumference and buckled up to 2.5 m, vertically. During this event up to 7,570 L of contaminated liquid may have leaked to the adjacent soil. This leak occurred under extreme temperature and pressure conditions. Modeling efforts to better understand the nature and extent of historical leaks from subsurface SSTs that were used to store highly radioactive, self-boiling liquid wastes at 241-A Tank Farm have recently been undertaken. These efforts have compiled the available historical information to support a preliminary non-isothermal, multiphase flow and chemical transport modeling effort to re-create the conditions under which the leaks occurred and to formulate a conceptual model as to the extent and distribution of leaked radioactive contaminants in the adjacent soil material. The focus of this work was on developing an understanding of the key features, processes and bounding conditions related to tank A-105 leak events that occurred in the 1960's. The activities include estimation of leak composition, non-isothermal multiphase flow and transport modeling, and geochemical modeling. The STOMP{sup C} Water-Air-Energy modeling code was utilized to implement the three-dimensional representation of the subsurface tank and the surrounding flow field. Once constructed, the model was used to evaluate the conceptual understanding of leaks originating from different parts of the tank under the elevated temperature boundary conditions that were imposed by surrounding tanks at the time of the historical leaks. The chemical evolution of the liquid waste was also evaluated as it leaked from the tank under transient pressure and temperature gradients. The results of the preliminary evaluation suggested the presence of a heat-pipe effect beneath tank A-105 in which water vapor at an elevated temperature is driven away from the base of the tank to a position where water vapor cools, condenses and is then drawn back toward the tank by the strong capillary attraction of the dry soil. A non-sorbing contaminant (Tc-99) was introduced into this flow field to better understand the potential distribution patterns of leaked contaminants that may have occurred during the historical leak events. (authors)
Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases
Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.
Experimental Evaluation of Refrigerant Leak Characteristics for Different HVAC&R Equipment Types–Phase 2
The US Department of Energy (DOE) Building Technology Office (BTO) and the Air-conditioning, Heating & Refrigeration Technology Institute (AHRTI) collaborated to sponsor an experimental study of refrigerant leak characteristics at Oak Ridge National Laboratory (ORNL); AHRTI project 9012. The project has been conducted in two phases with objectives to conduct refrigerant leak tests on several heating, ventilating, air-conditioning and refrigeration (HVAC&R) systems under operating conditions representative of actual applications to document the pressure decay rate and the mass flow rate of leaked refrigerant as a function of time. Phase 1 of the project ran from late 2017 to late 2018 with refrigerant leaks imposed on five systems and the collection of data to meet the project objectives. Systems chosen covered three air-conditioning (AC) applications (packaged terminal AC or PTAC, 3-ton residential split system AC, and 5-ton packaged rooftop AC) and two refrigeration applications (split system unit cooler, and standalone display case). AHRTI members donated the test systems used for the project. The systems were tested at two different leak rates (catastrophic high rate simulating full line break and a lower flow rate), two leak locations (high-pressure side and low-pressure side), and two operating conditions (compressor ON or OFF). Phase 1 results were summarized in a project report by Baxter, et al. (2019)1. The leak rates imposed in Phase 1 led to much more rapid charge releases than the more typical much slower rates seen in practice that would take days, weeks, or months to empty a system of its entire charge. For Phase 2, the project sponsors asked that the “higher” leak rate target a total charge release time of about 4 min. This was intended to represent a “reasonable” worst case release scenario to match the refrigerant leak rate assumption used in the International Electrotechnical Commission (IEC) standard IEC 60335-2-40 (2016 version [IEC 2016]. A charge release time of about 20–40 min (leak release rate 5 to 10 times lower than higher rate) was targeted for the “lower” leak rate. This report provides a summary of the Phase 2 effort. Two additional HVAC systems were selected for testing in this phase. First was a multi-split air-conditioning (MS-AC) system with one outdoor section and two indoor units and a nameplate refrigerant charge of 1.75 kg (3.86 lb.) of R-410A. The MS-AC was tested in cooling only or AC operation. Second was a split system heat pump coupled to two different representative supply duct systems (HP-duct) and a nameplate charge of 3.83 kg (8.44 lb.) of R-410A. This system was tested in both space heating and AC modes. As in Phase 1 of the project, all tests were conducted using R-410A.
Heuristic based analytics for gas leak source identification
Heuristic-based techniques for gas leak source identification are provided. In one aspect, a method for identifying a location of a gas leak source includes: obtaining gas sensor data and wind data synchronously from a gas leak detection system having a network of interconnected motes comprising gas sensors and wind sensors, with the gas sensors arranged around possible gas leak sources in a given area of interest; identifying the location of the gas leak source using the gas sensor data and wind data; and determining a magnitude of gas leak from the gas leak source using the location of the gas leak source and a distance d between the location of the gas leak source and a select one of the gas sensors from which the gas sensor data was obtained. A gas leak detection system is also provided.
Evaluating Acoustic vs. AI-Based Satellite Leak Detection in Aging US Water Infrastructure: A Cost and Energy Savings Analysis
The aging water distribution system in the United States, constructed mainly during the 1970s with some pipes dating back 125 years, is experiencing significant deterioration leading to substantial water losses. Along with the potential for water loss savings, improvements in the distribution system by using leak detection technologies can create net energy and cost savings. In this work, a new framework has been presented to calculate the economic level of leakage within water supply and distribution systems for two primary leak detection technologies (acoustic vs. satellite). In this work, a new framework is presented to calculate the economic level of leakage (ELL) within water supply and distribution systems to support smart infrastructure in smart cities. A case study focused using water audit data from Atlanta, Georgia, compared the costs of two leak mitigation technologies: conventional acoustic leak detection and artificial intelligence–assisted satellite leak detection technology, which employs machine learning algorithms to identify potential leak signatures from satellite imagery. The ELL results revealed that conducting one survey would be optimum for an acoustic survey, whereas the method suggested that it would be expensive to utilize satellite-based leak detection technology. However, results for cumulative financial analysis over a 3-year period for both technologies revealed both to be economically favorable with conventional acoustic leak detection technology generating higher net economic benefits of USD 2.4 million, surpassing satellite detection by 50%. A broader national analysis was conducted to explore the potential benefits of US water infrastructure mirroring the exemplary conditions of Germany and The Netherlands. Achieving similar infrastructure leakage index (ILI) values could result in annual cost savings of $\$4$–$\$4.8$ billion and primary energy savings of 1.6–1.9 TWh. These results demonstrate the value of combining economic modeling with advanced leak detection technologies to support sustainable, cost-efficient water infrastructure strategies in urban environments, contributing to more sustainable smart living outcomes.
Nondestructive Modular Leak Detection in 3D Printed 316L Stainless Steel Pipes via Laser Powder Bed Fusion
This research investigates the leak detection features of 316L Stainless Steel pipe structures manufactured via Laser Powder Bed Fusion (LPBF). This work involves the design of a modular sensor system integrating nondestructive evaluation (NDE) methods, including thermal imaging and ultrasonic frequency detection to detect and characterize leaks in components. This aims to improve leak detection sensitivity within medium-pressure gas systems, during continuous operation without halting flow or introducing safety risks. The system could be adaptable for use on unmanned aerial vehicles (UAVs), enabling remote leak detection in active environments. A custom pneumatic system incorporating temperature and pressure sensors was assembled to detect leaks in LPBF-printed 316L SS tee pipes. Experimental results and simulations confirm the system’s effectiveness in leak detection and material evaluation. This research program also integrated a Python-based image recognition platform based on a metallography and optical microscopy to assess the porosity and complement the leak detection data on the printed structures. This allows a detailed analysis of pore distribution and internal leak paths, which could compromise structural integrity, critical for quality control during manufacturing. Findings suggest that the investigated approach holds potential for enhancing leak detection technologies and adapt them for advanced manufactured parts.
FY2025 Status Report: Model 9975 O Ring Fixture Long-Term Leak Performance
Leak testing experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the model 9975 shipping package have been ongoing since 2004 at Savannah River National Laboratory. Seventy tests using mock-up 9975 primary containment vessels (PCVs) with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 °F. Due to material substitution, fourteen tests with GLT-S O-rings were initiated in 2008 and heated to temperatures ranging from 200 to 400 °F. The conditioning temperatures are elevated compared to the calculated maximum O-ring temperature in a 9975 package in storage, 158 °F, to accelerate aging and enable observations of O-ring failures in a reasonable time frame. The mock-up PCV fixtures are leak tested periodically, and all GLT O-ring fixtures aged at 350 °F or above have failed to maintain a leak-tight seal. Eight GLT O-ring fixtures aged at 300 °F have failed after 2.8 to 5.7 years at temperature while the remaining fixtures at 300 °F were retired from testing following more than five years of aging without failure. Two of these retired fixtures were returned to testing and heated to 350 °F to evaluate the impact of additional heating at higher temperature for aged O-rings. Fixture #20 failed after 3 months while fixture #18 failed after 9 months at 350 °F. These O-rings demonstrated that aged and in-service O-rings can continue to be used, even at higher temperatures, after being in storage, and their leak performance are consistent with other samples at 350 °F. There has been one GLT O-ring fixture which failed after 13.4 years of aging at 200 °F. However, 20 other GLT O-rings aging at 200 °F have remained leak-tight for over 16.9 years and remain in test. There are two GLT O-ring fixtures at 270 °F; one fixture has failed after 12.9 years while the other fixture remains in test after 12.5 years. All GLT-S O-ring fixtures aged at 300 °F or above have failed their leak test. No failures have yet been observed in GLT-S O-ring fixtures aging at 250 °F for 14.9 years, while one GLT-S O-ring fixture failed after 12.4 years at 200 °F. The leak testing data to date suggest the GLT and GLT-S O-rings aging in the K-Area Complex (KAC) storage at temperatures of 158 °F might maintain a leak-tight seal for up to 59 years. Data from the O-ring fixtures are generally consistent with results from compression stress-relaxation testing and provide confidence in the predictive models based on those results. However, uncertainty exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in KAC. The collective data from these test efforts suggest the minimum O-ring service life at KAC normal storage conditions should be at least 34 years for GLT and GLT-S O-rings. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicate significant margin remains for O-rings still in service in 9975 packages in KAC. Aging and periodic leak testing will continue for the remaining 24 mock-up PCV fixtures.
Data Analytics Applied to Coal Fired Boilers for Detecting Leaks
Data analytics were used to detect boiler leaks from five different coal-fired boilers including both subcritical and supercritical systems. Discriminant functions were developed that detected leaks up to two weeks prior to forced plant shutdowns for repairs. The leaks were identified to occur at different sections of the boiler for each plant, including waterwalls, economizer and superheater using conventional process measurement data. Leaking conditions were detected with a high degree of confidence (≪ 1% misclassified observations) and were able to distinguish normal operations from those time periods with steam leaks even while operating the power plants in power cycling mode.Multivariable statistical analyses, including Principal Component (PCA), cluster, and Fischer Discriminant Analysis (FDA) were used to characterize the leak occurrence. Normal and operational states with steam leaks were provided in the original process datasets. These datasets were split into two different groups for training and validation purposes. The data were sorted chronologically, and every third observation was assigned to training the Discriminant Function Model (DFM) while the rest were reserved for validation. PCA was used to reduce dimensionality of the original datasets. Canonical and FDA analyses were used to investigate the relationship between process variables. The outcome of the analyses revealed that nearly 35,000 observations were classified correctly; less than 0.05% of total observations were misclassified to be leaking, i.e. both false positives and false negatives.
Using Bayesian Methodology to Estimate Liquefied Natural Gas Leak Frequencies
This analysis provides estimates on the leak frequencies of nine components found in liquefied natural gas (LNG) facilities. Data was taken from a variety of sources, with 25 different data sets included in the analysis. A hierarchical Bayesian model was used that assumes that the log leak frequency follows a normal distribution and the logarithm of the mean of this normal distribution is a linear function of the logarithm of the fractional leak area. This type of model uses uninformed prior distributions that are updated with applicable data. Separate models are fit for each component listed. Five order-of-magnitude fractional leak areas are considered, based on the flow area of the component. Three types of supporting analyses were performed: sensitivity of the model to the data set used, sensitivity of the leak frequency estimates to differences in the model structure or prior distributions, and sufficiency of sample sized used for convergence. Recommended leak frequency distributions for all component types and leak sizes are given. These leak frequency predictions can be used for quantitative risk assessments in the future.
Hydrogen Component Leak Rate Quantification for System Risk and Reliability Assessment through QRA and PHM Frameworks: Preprint
The National Renewable Energy Laboratory's (NREL) Hydrogen Safety Research and Development (HSR&D) program in collaboration with the University of Maryland's Systems Risk and Reliability Analysis Laboratory (SyRRA) are working to improve reliability and reduce risk in hydrogen systems. This approach strives to use quantitative data on component leaks and failures, together with Prognosis and Health Management (PHM), and Quantitative Risk Assessment (QRA) to identify at-risk components, reduce component failures and downtime, and predict when components require maintenance. Hydrogen component failures increase facility maintenance cost, facility downtime, and reduce public acceptance of hydrogen technologies, ultimately increasing facility size and cost because of potentially overly conservative requirements. Leaks are a predominant failure mode for hydrogen components. However, uncertainties in the amount of hydrogen emitted from leaking components and the frequency of those failure events limit the understanding of the risks that they present under real-world operational conditions. NREL has deployed a test fixture, the Leak Rate Quantification Apparatus (LRQA), to quantify the mass flow rate of leaking gases from medium and high-pressure components that have failed while in service. Quantitative hydrogen leak rate data from this system could ultimately be used to better inform risk assessment and Regulation Codes and Standards (RCS). Parallel activity explores the use of PHM and QRA techniques to assess and reduce risk, thereby improving safety and reliability of hydrogen systems. The results of QRAs could further provide a systematic and science-based foundation for the design and implementation of RCS, as in the latest versions of the NFPA 2 code for gaseous hydrogen stations. Alternatively, data-driven techniques of PHM could provide new damage diagnosis and health-state prognosis tools. This research will help end users, station owners and operators, and regulatory bodies move towards risk-informed preventative maintenance versus emergency corrective maintenance, reducing cost and improving reliability. Predictive modelling of failures could improve safety and affect RCS requirements such as setback distances at liquid refuelling sites. The combination of leak rate quantification research, PHM, and QRA can lead to better informed models enabling data-based decision to be made for hydrogen system safety improvements.
Data analytics for leak detection in a subcritical boiler
For decades, boiler leaks have been the leading cause of forced outages in the coal-fired unit. The leak occurrences are currently escalating since the existing plants must satisfy faster-ramping rates to support grid operation. Data analytics including Principal Component Analysis, Canonical Variate, and Fisher Discriminant Analysis were combined for detecting and characterizing the leak in a commercial 650 MW subcritical coal-fired power plant. The combined approach was shown to be highly effective in the fault investigation that would not have been easily achieved by an individual technique. The variability in both training and validation datasets was first evaluated using PCA. Then, the CV-FDA was employed to discriminate among faults, and to categorize the processed data into two main groups: no-leak (0) and leak (1), providing the timeframe and location of the leak occurrence. Furthermore, about 8,014 observations from 81 process variables were initially included in the calculation, while the variable count was reduced to 4 with less than 1% misclassification rate in total observations. Finally, the leak was isolated in the waterwall section. Thus, the outcome of this research may provide early detection and isolation of faulty operations in the coal-fired power plant that involves a considerable number of process variables.
HELIUM LEAK TEST MODELING OF A SPENT NUCLEAR FUEL CANISTER
The U.S. Department of Energy (DOE) is considering the development of one or more federal consolidated interim storage facilities (CISFs) to be used to store commercial spent nuclear fuel (SNF) at locations in the U.S. One of the first technical challenges of a CISF is performing an inspection of SNF canisters upon their receipt to confirm they can be placed into the CISF’s licensed storage configuration. The canister receipt inspection is critical to CISF site operations. The test is conceived as being a helium (He) leak check, intended to confirm that the confinement boundary of a SNF canister is intact. SNF canisters are filled with He when they are sealed, so detection of a He leak indicates that a through-wall flaw has occurred in the canister confinement boundary. Other measurements are planned to occur upon canister receipt in addition to the He leak check such as krypton-85 measurements, which would indicate confinement breaches of one or more fuel rods in addition to a breach of the SNF canister. However, the He leak check has been identified as one of such high importance and has such significant technical challenges that a full-scale demonstration is needed to confirm the He leak test’s viability and to assist in planning relative to its operational requirements. A modeling methodology for simulating the He detection test was developed to help inform the test plan and the design of the test vessels. To develop the modeling methodology a detailed computational fluid dynamics (CFD) benchmark model was constructed to compare against leak rate test data from a transportation package for radioactive material. This report is focused on modeling efforts to simulate the benchmark leak test.
Updated Filter Leak Frequencies for Use in Risk Assessments
Quantitative risk assessment (QRA) is highly dependent on data, leading to more robust models as new and updated data is acquired. The Hydrogen Plus Other Alternative Fuels Risk Assessment (HyRAM+) QRA capabilities include calculations of individual risk from leaks in a gaseous hydrogen facility due to the potential effects of jet fires and explosions. Leak frequencies are acquired through statistical analysis of published data from a variety of sources and industries. The filter leak frequencies in previous versions of the HyRAM+ software are substantially greater than the leak frequencies of other components, leading to QRA results for gaseous hydrogen in which filters consistently dominate the overall risk. Data that were previously used to derive the filter leak frequencies were reevaluated for applicability and additional data points were added to update the filter leak frequencies. The new frequencies are more comparable to leak frequencies for other components.
Model 9975 O Ring Fixture LongTerm Leak Performance (FY2021 Status Report)
Leak testing experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the model 9975 shipping package has been ongoing since 2004 at Savannah River National Laboratory. Seventy tests using mock-up 9975 primary containment vessels (PCVs) with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 °F. Due to material substitution, fourteen tests with GLT-S O-rings were initiated in 2008 and heated to temperatures ranging from 200 to 400 °F. The conditioning temperatures are elevated compared to the calculated maximum O-ring temperature in a 9975 package in storage, 158 °F, to accelerate aging and enable observations of O-ring failures in a reasonable time frame. The fixtures are leak tested periodically and all GLT O-ring fixtures aging at 350 °F or above have failed to maintain a leak-tight seal. Eight GLT O-ring fixtures aging at 300 °F have failed after 2.8 to 5.7 years at temperature while the remaining fixtures at 300 °F were retired from testing following more than five years without failure. There has been one GLT O-ring fixture which failed after 13.4 years aging at 200 °F. However, 19 other GLT O-rings aging at 200 °F have remained leak-tight for over 14 years and remain in test. No failures have yet been observed in GLT O-ring fixtures aging at 270 °F for 9.5 years. All GLT-S O-ring fixtures aging at 300 °F or above have failed their leak test. No failures have yet been observed in GLT-S O-ring fixtures aging at 200 and 250 °F for 11.5 years. Data from the O-ring fixtures are generally consistent with results from compression stress-relaxation testing, and provide confidence in the predictive models based on those results. However, uncertainty exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in K-Area Complex (KAC). Oxygen consumption testing, which includes results from temperatures near KAC normal storage temperatures, is ongoing to provide further confidence and corroborate these extrapolations. The collective data from these test efforts suggest the minimum O-ring service life at KAC normal storage conditions should be at least 34 years for GLT and GLT-S O-rings. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicate significant margin remains for O-rings still in service in 9975 packages in KAC. Aging and periodic leak testing will continue for the remaining 26 mock-up PCV fixtures.
Model 9975 O-Ring Fixture Long-Term Leak Performance (FY2022 Status Report)
Leak testing experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the model 9975 shipping package has been ongoing since 2004 at Savannah River National Laboratory. Seventy tests using mock-up 9975 primary containment vessels (PCVs) with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 °F. Due to material substitution, fourteen tests with GLT-S O-rings were initiated in 2008 and heated to temperatures ranging from 200 to 400 °F. The conditioning temperatures are elevated compared to the calculated maximum O-ring temperature in a 9975 package in storage, 158 °F, to accelerate aging and enable observations of O-ring failures in a reasonable time frame. The fixtures are leak tested periodically and all GLT O-ring fixtures aging at 350 °F or above have failed to maintain a leak-tight seal. Eight GLT O-ring fixtures aging at 300 °F have failed after 2.8 to 5.7 years at temperature while the remaining fixtures at 300 °F were retired from testing following more than five years without failure. There has been one GLT O-ring fixture which failed after 13.4 years aging at 200 °F. However, 20 other GLT O-rings aging at 200 °F have remained leak-tight for over 14 years and remain in test. No failures have yet been observed in GLT O-ring fixtures aging at 270 °F for 10.4 years. All GLT-S O-ring fixtures aging at 300 °F or above have failed their leak test. No failures have yet been observed in GLT-S O-ring fixtures aging at 250 °F for 12.5 years. This year, one GLT-S O-ring fixture failed after 12.4 years aging at 200 °F. Data from the O-ring fixtures are generally consistent with results from compression stress-relaxation testing, and provide confidence in the predictive models based on those results. However, uncertainty exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in K-Area Complex (KAC). Oxygen consumption testing, which includes results from temperatures near KAC normal storage temperatures, is ongoing to provide further confidence and corroborate these extrapolations. The collective data from these test efforts suggest the minimum O-ring service life at KAC normal storage conditions should be at least 34 years for GLT and GLT-S O-rings. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicate significant margin remains for O-rings still in service in 9975 packages in KAC. Aging and periodic leak testing will continue for the remaining 25 mock-up PCV fixtures.
Gaining Real-Time Water Leak Detection
Devens Reserve Forces Training Area is a United States Army Reserve (USAR) Installation that struggles with severe water leaks, often causing significant damage to the facility and requiring major renovation. Traditional water use is highly dependent on occupancy, so it can be difficult to benchmark a facility’s water use. It can be exceptionally difficult when occupancy is transient and/or varies. Pacific Northwest National Laboratory (PNNL) collaborated with Devens to implement real-time monitoring of their water consumption by utilizing the smart meter data from their existing 23 water meters. PNNL created a simple algorithm to calculate hourly water consumption and trigger an alert to be instantly emailed to Devens’ personnel when there appears to be a water leak in any building with a smart water meter. Here, this approach is expected to save hundreds of thousands of dollars in unnecessary water consumption costs and damages from leaks and was implemented with little-to-no costs or service disruptions. Next steps for this project include slow leak detection through nighttime monitoring and to extrapolate this water leak approach to the remainder 360 water meters on USAR’s Enterprise Building Control System so USAR sites across the country can be instantly notified of potential water leaks.
Leak detection in a subcritical boiler
Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Furthermore, because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coalfired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.