SEARCH · Search NASA

Results for “Structural health monitoring”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data

Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Artificial Intelligence for improved facilities operation in the FNAL LINAC

The energy consumption in accelerator structures during beam downtimes is a significant fraction of the overall energy budget. Accurate prediction of downtime duration could inform actions to reduce this energy consumption. The LCAPE project started in 2020 and develops artificial intelligence to improve operations in the FNAL control room by reducing the time to identify the cause of a beam outage, improving the reproducibility of labeling it, predicting their duration and forecasting their occurrence. We present our solution for incorporating information from ~2.5k monitored devices in near-real time to distinguish between dozens of different causes of down time. We discuss the performance of different techniques for modeling the state of health of the facility and we compare unsupervised clustering techniques to distinguish between different causes of down time.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Stretchable Photodiodes with Polymer-Engineered Semiconductor Nanowires for Wearable Photoplethysmography

Healthcare systems worldwide have been stressed to provide sufficient resources to serve the increasing and aging population in our society. The situation became more challenging at the time of pandemic. Technology advancement, especially the adoption of wearable health monitoring devices, has provided an important supplement to current clinical equipment. Most health monitoring devices are rigid, however, human tissues are soft. Such a difference has prohibited intimate contact between the two and jeopardized wearing comfortableness, which hurdles measurement accuracy especially during longtime usage. Here, in this work, we report a soft and stretchable photodiode that can conformally adhere onto the human body without any pressure and measure cardiovascular variables for an extended period with higher reliability than commercial devices. The photodiode used a composite light absorber consisting of an organic bulk heterojunction embedded into an elastic polymer matrix. It is discovered that the elastic polymer matrix not only improves the morphology of the bulk heterojunction for obtaining the desired mechanical properties but also alters its electronic band structure and improves the electrical properties that lead to a reduced dark current and enhanced photovoltage in the stretchable photodiode. The work has demonstrated high fidelity measurements and longtime monitoring of heat rate variability and oxygen saturation, potentially enabling next-generation wearable photoplethysmography devices for point-of-care diagnosis of cardiovascular diseases in a more accessible and affordable way.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

Radiation-induced transients on solid and molten Li and K iodides

The study, quantification, and monitoring of iodine in nuclear power generation systems have been paramount due to its environmental and health implications. Thorough speciation and transport studies strengthened the development and deployment of water reactors, which are now required for the new generation of Molten Salt Reactors (MSR), where the fuel and coolant are a complex liquid system of suitable halides. The speciation, radiation-induced chemistry, and transport of iodine (I-127, I-129 and I-131) under extreme conditions of temperature and ionizing radiation are among the challenges for the future implementation of MSR’s. In aqueous systems, the triiodide-iodine-iodide (I3--I2-I-) equilibrium is strongly dependent on the conditions of the medium. In molten iodides and chlorides, the triiodide detection (and its disproportionation) poses challenges due to the extreme conditions of temperature and radiation, but studies have shown a dependence on temperature, absorbed dose and salt composition. Through absorption spectroscopy techniques (diffuse reflectance and high-temperature UV-Vis), as well as resonance (Electron Paramagnetic Resonance) it is possible to identify primary transients induced by ionizing radiation trapped in the solid phase (Solid-state radiolysis), and steady-state main absorption components with a fast-acquisition real-time spectroscopy. The presence of heterogeneous phase (colloids), viscosity changes, and gas evolution are among the observed processes. A specific case of study is speciation in the presence of Ni. A corrosion product with magnetic properties due to unpaired electrons in its electronic structure. Ferromagnetic materials are monitored in solidified salts to identify aggregation and phase separation. Comparative studies of eutectic mixtures of LiI-KI and LiCl-KCl with known addition of dopants will be presented, with a perspective of radiation chemistry and its possible implications in complex systems.

36 - MATERIALS SCIENCE↗

DOE OSTI2022

Marine Renewable Energy Applications for Restorative Ocean Farming: Kelp

Kelp farming and kelp forest restoration have both been proposed as a solution to locally decrease the impacts of ocean acidification and eutrophication, often with co-benefits to other forms of aquaculture and mariculture. Compared to global markets, the kelp industry in the United States is still in its early phases, with the first commercial kelp farm founded in Casco Bay, Maine in 2010. Since then, interest and effort in kelp production has been increasing, with farms now present in Maine, New Hampshire, Connecticut, Rhode Island, Massachusetts, New York, Washington, and Alaska. Many research projects are underway in the United States to explore benefits of 3D ocean farming, tackle logistical problems of working in the ocean, autonomous farming, and explore viable end uses for kelp products. In seaweed farming, to remove the stored carbon or excess nutrients from the system, the biomass needs to be harvested at the optimal time to avoid the release of CO 2 that comes with decomposition. Timing of the harvest is also important for maximum crop yield, which can vary based on the final product. Additional monitoring needs can include a variety of water quality metrics, growth measurements, and visuals to ensure the health of the farm, comply with permits, support operations and maintenance functions. The variables measured may vary by desired end use of the product, location of farm, and operational design. Monitoring all of these parameters requires specialized devices that can be costly and challenging to maintain. Monitoring devices often face power and logistical constraints that could prevent kelp farmers from adopting these technologies or receiving accurate, efficient monitoring to assess ecosystem benefits and valuation. Marine energy has been identified as a possible power source for these devices. This project investigates the power needs for conducting kelp farm environmental monitoring compared with the available marine energy resource to evaluate if locally generated ocean energy could provide a solution to these monitoring challenges and benefit kelp farmers. This process was structured as follows: 1. Define what data is needed for farmers and their communities through desk research and interviews with end users. 2. Identify sensors and power requirements currently in use or available for commercial purchase. 3. Analyze current kelp and other mariculture farm locations for the potential marine energy resource. 4. Analyze farm designs and associated structures to make recommendations for marine energy design. 5. Quantify value that investment in sensors could provide in terms of carbon credit possibilities.

09 BIOMASS FUELS↗

DOE OSTI2020

Distribution Development for Residual Inventory at the New York West Valley Site - 20400

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351 ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into Agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States. NFS, a private company, built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations ended in 1972 and never reopened, leaving behind radioactive and chemical wastes. Operations led to contamination in a number of facilities and locations. Some of that contamination has migrated from waste disposal zones to other layers, formations, and features on and off the WNYNSC. Phase I decommissioning activities are ongoing and involve the removal of a number of areas and structures that have been associated with contamination. The purpose of this work is to outline the approach for characterizing contamination not associated with disposed wastes, contaminated structures, or specific releases. In this work, the term, residual radiological activity, is used to describe environmental contamination that exists subsequent to the completion of Phase I decommissioning activities, that is not associated with disposed wastes, contaminated structures, or specific releases. Contamination from the Site was quantified relative to data that characterize the concentrations of radionuclides that exist in background. Background concentrations are those present in the area but having no influence from Site related activities. The existence of residual radiological activity that is elevated relative to background has the potential to contribute to future risks to human health and the environment. As a consequence, the residual inventory information is used to inform the West Valley Probabilistic Performance Assessment (PPA) model to characterize potential future risks to human health and the environment. The centralized West Valley Data Management System (DMS) was the source of information for the data assembled in this analysis. The DMS is a fairly large compilation consisting of thousands of records from investigation studies, with sample dates ranging from 1990 to present. Samples from monitoring wells, boreholes, geoprobe studies, surface water, surface soils, storm water outfalls, ventilation stack filters, plant and animal tissues, and more are included in the DMS. Results are typically reported in units of activity per unit volume. For the purpose of the analyses presented here, all results were converted into consistent units of pCi per unit volume. Since 1990, data have been collected from various locations across the WNYNSC at different times with varying frequency over the course of several decades. As a consequence, a number of potential issues can arise with respect to the assembly of a dataset that is deemed adequate for the characterization of residual radiological activity. These issues were assessed and resolved to the extent possible through careful consideration of the properties of the distributions. The intent was to use data which characterize the current state of the Site. Radionuclides can be designated to one of several groups depending on their origin. In this work the groups considered were 1) Naturally Occurring Radioactive Material (NORM), 2) fallout, and 3) Other (including power plant, medical research, etc). This grouping is a useful construct with respect to the interpretation of fixed laboratory results. For example, NORM radionuclides that exist within a decay chain should have approximately equivalent distributions of concentrations if they are representative of background conditions. Insights such as these can be used as a check to identify sample results that need to be further investigated or omitted due to issues associated with reported results from fixed laboratory analyses. This type of analysis provided a foundation for the assessment of the adequacy of sample results for use in subsequent components of an assessment. The general process for the assessment of residual radiological contamination at the Site consists of a sequence of several steps. First, for each analyte, several statistical tests were performed to assess the weight of evidence against the null hypothesis that the mean of the distribution of concentrations was equal to zero. If the mean of the distribution of concentrations for a given radionuclide was not found to be greater than zero, then it was removed from consideration as a component of the residual radiological contamination. If there was significant evidence to reject the hypothesis of the mean being equal to zero, the second step was to compare the distribution of the data from the Site to that of the corresponding background. A suite of tests was used to compare the distributions of the site and background data. The results of these tests were collectively used to determine if site data are elevated relative to background. The third step was to develop distributions using a Bayesian framework to characterize the distribution of mean of the increment present above background for each of the radionuclides. The Bayesian model implemented allowed for the comparison of site-specific records to background concentrations to better approximate contamination attributed to the Site. A final screening step was employed for radionuclides that exceed background. This screening step compared 95% upper confidence limits (UCLs) from the increment distribution developed in the previous step to the risk screening levels. This approach yields a list of analytes that were determined to be elevated relative to background.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Detecting Thermally-Induced Spinodal Decomposition with Picosecond Ultrasonics in Cast Austenitic Stainless Steels

Destructive techniques to monitor nuclear reactor component health may not always be available during service, as they are time-consuming and often require pre-installed inspection coupons. Non-destructive evaluation (NDE) techniques can bridge this gap by rapidly identifying the state of mission-critical reactor components, via inference between NDE-measurable material properties and those of ultimate interest, such as ductility and toughness. Here, we demonstrate one such inference about the health of thermally aged cast austenitic stainless steels. Observations of surface acoustic wave peak (SAW) splitting correlate with spinodal decomposition-induced embrittlement as destructively measured by Charpy impact energy. Elastodynamic calculations and molecular dynamics simulations of the effects of spinodal decomposition on elastic moduli support that the new acoustic modes present are due to stiffening in the δ-ferrite domains. Finally, this discovery enables one to probe structure-property relationships in materials in a greatly accelerated manner, suggesting that similar inference methods can be used to determine material fitness-for-service, or to quickly uncover new structure-property relationships.

304-type stainless steel↗

DOE OSTI2026

Reducing Deferrals by Integrating Health Homes with Weatherization

The U.S. Department of Energy’s Weatherization Assistance Program (WAP) improves energy efficiency and household health for low-income families, yet a substantial number of otherwise eligible homes are deferred from due to health and safety concerns in their homes, including mold, moisture damage, or structural deficiencies. These deferred homes are often occupied by marginalized or otherwise vulnerable residents who may be exposed to elevated indoor air pollutant concentration. Integrating Healthy Homes (HH) interventions with weatherization has been proposed as a strategy to reduce deferrals, address environmental justice concerns, and improve health outcomes. However, limited data on the health and economic implications of such integration exist. This study aimed to assess the potential health benefits and savings-to-investment ratio (SIR) associated with integrating Healthy Homes interventions into weatherization programs for homes typically deferred from WAP services. We collected indoor air pollutant data from homes undergoing health home renovations, including fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), carbon monoxide (CO), and formaldehyde, with sampling times up to one month. Except for fomaldehyde, which was measured using passive UMEx badges, the other metrics were measured using the airQ Pro indoor air quality monitor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI1989

Nuclear Safety [Vol. 30, No. 1, January-March 1989]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 1 International Conference on Thermal Reactor Safety: NUCSAFE 88 by A. P. Malinauskas and J. G. Pruett; ACCIDENT ANALYSIS: 18 Chernobyl Today: State of Research by A. Yu. Gagarinskii; CONTROL AND INSTRUMENTATION: 23 Problems Associated with Routine In-Plant Radioactive Effluent Monitoring Systems at U.S. Light-Water Reactors by Barry G. Wahlig, David M. Walker, Mahmoud R. Ghavi, and John M. Palms; DESIGN FEATURES: 34 Twentieth DOE/NRC Nuclear Air-Cleaning Conference by R. R. Bellamy, D. W. Moeller, and M. W. First, 46 Design Options for the Core Support Structure for Liquid-Metal-Cooled Reactor Plants by J. P. Burelbach, W. J. Kann, J. G. Saiveau, and R. W. Seidensticker; ENVIRONMENTAL EFFECTS: 53 The Radiological Consequences of the Chernobyl Accident by L. V. Konstantinov and A. J. González; WASTE AND SPENT FUEL MANAGEMENT: 70 Activities Related to Waste Management Compiled by E. G. Silver; OPERATING EXPERIENCES: 80 Fuel Performance Annual Report for 1986 by W. J. Bailey, 103 Safety Considerations Related to 12-Hour Shift Schedules by S. Gould, 105 Reactor Shutdown Experience Compiled by J. W. Cletcher, 108 Operating U.S. Power Reactors Compiled by E. G. Silver; RECENT DEVELOPMENTS: 130 General Administrative Activities Compiled by E. G. Silver, 140 Reports, Standards, and Safety Guides by D. S. Queener, 145 Status of Power-Reactor Licensing Activities Compiled by E. G. Silver, 153 Proposed Rule Changes as of Sept. 30, 1988; ANNOUNCEMENTS: 69 Northwestern University Short Course on Radiation Safety, 79 International Seminar on Fission Product Transport Processes in Reactor Accidents, 129 Harvard School of Public Health Offers Short Courses, 152 MIT Offers Summer Short Courses on Reactor Safety and Nodal Analysis, 152 Seminar on Use of PCs in Probabilistic Safety Analysis, 157 The Authors, 160 Indexes to Nuclear Safety, Volume 29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Bio‐Imaging quorum sensing signal molecules in a soil‐mimic gel

Rhizosphere, the narrow region surrounding plant roots directly influenced by root exudates and the root associated microbiome, plays an important role in plant productivity and the rhizosphere is well known for stimulating microbial metabolic activities. How microbial communities interact to form stable, metabolically interconnected functional communities is an area of intense interest. The question remains on how microbially produced secreted molecules that function as intercellular communication signals shape the structure and function of microbial communities. Our goal is to detect and quantify signal molecules produced by microbes or plants in the root‐soil environment, spatially and temporarily. As a proof‐of‐concept, we are imaging diffusible extracellular microbial metabolites involved in a bacteria‐bacteria communication process called quorum‐sensing. Quorum‐sensing relies on the accumulation of high concentrations of signal molecules in the environment to control bacterial gene expression, influencing rhizosphere colonization and plant health. Local concentration of quorum sensing molecules are determined using aptamer based sensors. Aptamers that can specifically bind the desired signal molecules are selected through SELEX and immobilized on the surface of nano‐porous membranes. Binding of the signal molecules and aptamer covered surface results in changes in surface charge distribution and steric hinderance and thus modifying the transmembrane ionic transport. Changes in transmembrane impedance can be measured through electrochemical impedance spectroscopy methods to monitor local concentrations of signal molecules. Sensor responses were determined for different concentrations of signal molecules and results showed detection of C4‐HSL in a soil‐mimic solution with K D of 10 nM. We demonstrate that the quorum‐sensing signal molecule C4‐homoserine lactone and (C4‐HSL) can rapidly diffuse in a soil‐mimic gel, providing evidence for our use of a soil‐mimic for further aptasensor development and validation. The sensors were then inserted into soil mimic gel for monitoring C4‐HSL diffusion and the resulted impedance changes were used to determine the C4‐HSL concentration at different positions in the gel. Measurements of local C4‐HSL concentrations variation and numerical solution of diffusion equation were used to create 4D images of C4‐HSL molecule diffusion in the soil‐mimic gel.

Jiang, Nianyu↗

DOE OSTI2020

A new approach for measuring the carbon and oxygen content of atmospherically relevant compounds and mixtures

Abstract. Due to its complexity, gas- and particle-phase organic carbon in the atmosphere is often classified by its bulk physicochemical properties. However, there is a dearth of robust, moderate-cost approaches to measure the bulk chemical composition of organic carbon in the atmosphere. This is particularly true for the degree of oxygenation, which critically affects the properties and impacts of organic carbon but for which routine measurement approaches are lacking. This gap has limited the understanding of a wide range of atmospheric components, including particulate matter, the mass of which is monitored worldwide due to its health and environmental effects but the chemical characterization of which requires relatively high capital costs and complex operation by highly trained technical personnel. In this work, we demonstrate a new approach to estimate the mass of carbon and oxygen in analytes and mixtures that relies only on robust, moderate-cost detectors designed for use with gas chromatography. Organic compounds entering a flame ionization detector were found to be converted with approximately complete efficiency to CO2, which was analyzed downstream using an infrared detector to measure the mass of carbon analyzed. The ratio of the flame ionization detector (FID) signal generated to CO2 formed (FID∕CO2) was shown to be strongly correlated (R2=0.89) to the oxygen-to-carbon ratio (O∕C) of the analyte. Furthermore, simple mixtures of analytes behaved as the weighted average of their components, indicating that this correlation extends to mixtures. These properties were also observed to correlate well with the sensitivity of the FID estimated by structure activity relationships (quantified as the relative effective carbon number). The relationships between measured FID∕CO2, analyte O∕C, and FID sensitivity allow the estimation of one property from another with <15 % error for mixtures and <20 % error for most individual analytes. The approach opens the possibility of field-deployable, autonomous measurement of the carbon and oxygen content of particulate matter using time-tested, low-maintenance detectors, though such an application would require some additional testing on complex mixtures. With some instrumental modifications, similar measurements on gas-phase species may be feasible. Moreover, the potential expansion to additional gas chromatography detectors may provide concurrent measurement of other elements (e.g., sulfur, nitrogen).

42 ENGINEERING↗

DOE OSTI2020

The Utility of Satellites and Autonomous Remote Sensing Platforms for Monitoring Offshore Aquaculture Farms: A Case Study for Canopy Forming Kelps

The emerging sector of offshore kelp aquaculture represents an opportunity to produce biofuel feedstock to help meet growing energy demand. Giant kelp represents an attractive aquaculture crop due to its rapid growth and production, however precision farming over large scales is required to make this crop economically viable. These demands necessitate high frequency monitoring to ensure outplant success, maximum production, and optimum quality of harvested biomass, while the long distance from shore and large necessary scales of production makes in person monitoring impractical. Remote sensing offers a practical monitoring solution and nascent imaging technologies could be leveraged to provide daily products of the kelp canopy and subsurface structures over unprecedented spatial scales. Here, we evaluate the efficacy of remote sensing from satellites and aerial and underwater autonomous vehicles as potential monitoring platforms for offshore kelp aquaculture farms. Decadal-scale analyses of the Southern California Bight showed that high offshore summertime cloud cover restricts the ability of satellite sensors to provide high frequency direct monitoring of these farms. By contrast, daily monitoring of offshore farms using sensors mounted to aerial and underwater drones seems promising. Small Unoccupied Aircraft Systems (sUAS) carrying lightweight optical sensors can provide estimates of canopy area, density, and tissue nitrogen content on the time and space scales necessary for observing changes in this highly dynamic species. Underwater color imagery can be rapidly classified using deep learning models to identify kelp outplants on a longline farm and high acoustic returns of kelp pneumatocysts from side scan sonar imagery signal an ability to monitor the subsurface development of kelp fronds. Current sensing technologies can be used to develop additional machine learning and spectral algorithms to monitor outplant health and canopy macromolecular content, however future developments in vehicle and infrastructure technologies are necessary to reduce costs and transcend operational limitations for continuous deployment in an offshore setting.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The P132H mutation in the main protease of Omicron SARS-CoV-2 decreases thermal stability without compromising catalysis or small-molecule drug inhibition

The ongoing SARS-CoV-2 pandemic continues to be a significant threat to global health. First reported in November 2021, the Omicron variant (B.1.1.529) is more transmissible and can evade immunity better than previous SARS-CoV-2 variants, fueling an unprecedented surge in cases. To produce functional proteins from its polyprotein, SARS-CoV-2 relies on the cysteine proteases Nsp3/papain-like protease (PL pro ) and Nsp5/main protease (M pro )/3C-like protease to cleave at three and more than 11 sites, respectively. Therefore, M pro and PL pro inhibitors are considered to be one of the most promising SARS-CoV-2 antivirals. On December 22, 2021, the Food and Drug Administration (FDA) issued an Emergency Use Authorization (EUA) for PAXLOVID, a ritonavir-boosted formulation of nirmatrelvir. Nirmatrelvir is a first-in-class orally bioavailable SARS-CoV-2 M pro inhibitor. Thus, the scientific community must vigilantly monitor potential mechanisms of drug resistance, especially because SARS-CoV-2 is naïve to M pro inhibitors. Mutations have been well identified in variants to this point. Notably, Omicron M pro (OM pro ) harbors a single mutation—P132H. Here, we characterized the enzymatic activity, drug inhibition, and structure of OM pro while evaluating the past and future implications of M pro mutations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

The Corrective Maintenance Paradigm Shift at Hanford's Tank Farms - 20077

Hanford's Tank Farms facilities have been used to safely store waste for over 70 years, with the first single-shell tanks being constructed in 1943. Tank Farm facilities consist of 149 single-shell tanks, 28 double-shell tanks, an evaporator facility, and wastewater treatment facilities. Tank Farm facilities are aging, with a tremendous corrective maintenance burden on the Tank Farm contractor. The mission of Tank Farm facilities is soon changing from waste storage to waste staging for the Hanford Waste Treatment and Immobilization Plant (WTP). WTP operations will demand a significant increase in Tank Farm facility operations, in which corrective maintenance outage windows will shrink drastically. This realization has forced the Tank Farm contractor to consider a paradigm shift in Tank Farm facilities Maintenance planning, and the use of reliability Engineering tools. The Tank Farm Production Operations Engineering Cognizant System Engineering (CSE) organization has led the way in motivating this paradigm shift. This shift has been realized through the use of: 1) technical exchange with other Department of Energy (DOE) contractors to develop improvements in the CSE program, 2) a shift from the use of lagging to leading system health indicators, and 3) a Plant Health Committee to unite Engineering, Operations, and Maintenance personnel toward a productive maintenance strategy. The CSE organization has held several technical exchanges with other DOE contractors to discuss CSE concepts, and how to better maintain aging infrastructure. The technical exchange with other contractors has greatly reduced the time required to make improvements in the Tank Farm CSE program. Other DOE contractors have already faced issues surrounding aging infrastructure, and have vast experience in improving the reliability and usable life of structures and components in nuclear facilities. The past CSE program used lagging health indicators to determine the health of systems. The key lagging indicator used to determine system health was availability, which is the percentage of time that a facility was ready for operation compared to the time the facility was demanded for operation. Availability was a good indicator of health in the waste storage mission of Tank Farms, where safe storage was the most important function of the facility, and where maintenance outage windows were typically long-duration. In current and future operations, outage windows are reducing, resulting in the need for much more reliable systems. Systems that have had high availability may suddenly become inoperable due to a failed component or sub-system. In several instances, the use of availability as an indicator of system health failed to predict system/equipment failure before its occurrence. In discussions with other DOE contractors, a set of reliability tools, including leading indicators of health, has been implemented in the CSE program. This primarily involves the use of failure modes and effects analysis and the study of equipment failure to develop system monitoring plans that focus on trending data to detect oncoming equipment failure ahead of time. In addition, the use of a Plant Health Committee has added significantly to the paradigm shift from a corrective maintenance philosophy to the use of predictive and preventive maintenance. The Plant Health Committee is a chartered team consisting of Engineering, Operations, and Maintenance personnel. CSEs use this forum to present the results of their performance monitoring, including the presentation of health via leading health indicators. The most positive aspect of this committee is the communication that it creates within these critical organizations. The Operations and Maintenance organization benefit from focusing maintenance on the reliability-centered focus provided by Engineering. Engineering benefits from the operational experience of the Operations organization and from the failure data that can be provided by Maintenance personnel. The continued use of the Plant Health Committee is expected to further decrease maintenance outage times, in better support of oncoming 24/7 operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Erosion-Corrosion Detection in Carbon Steel Pipe Loops using SRNLs Thickness and Mass Loss Measurement Coupons - 20464

Structural health of waste transfer infrastructure is of utmost importance to DOE and communities surrounding their active sites. A Fitness-for-Service (FFS) program for the Waste Transfer System has been implemented by the US Department of Energy (DOE) for the purposes of evaluating and quantifying the degradation of critical components. Currently, the method of approach is to section and evaluate pipelines that have been removed at end service. In order to augment data collection methods applied to making lifespan estimates of waste transfer system components, Florida International University (FIU) has been investigating new-technology based strategies for quantifying the rate of degradation. Present research considers the option of a coupon system installed on a section of pipe at points of interest that will provide easy access to high resolution measurements of erosion/corrosion rates during operation. Researchers at Savannah River National Laboratory (SRNL) have developed this novel solution for in situ erosion and corrosion measurements in many applicable locations such as tanks, pipes, ducts, and injection points. The coupons are approximately 12.7 mm (1/2 inch) in diameter and 25.4 mm (1 inch) in length and can be placed in the pipe sections using Swagelok compression fittings. The coupon design allows for monitoring of the total degradation resulting from corrosion and erosion. High-resolution Ultrasonic Thickness (UT) testing allows in-situ monitoring of both degradation mechanisms. When removed from the system mass loss resulting from corrosion and erosion may also be evaluated. Experimental testing at FIU implemented the SRNL coupon system in a 6.10 meter (20 foot) pipe loop system comprised of 50.8 mm (2 inch) and 76.2 mm (3 inch) pipe sections in order to replicate expected use cases at the sites. Operational conditions were emulated by pumping abrasive materials through the pipeline at full capacity and collecting measurements from the SRNL coupons. Initial testing was conducted by circulating water followed by a mixture of sand and water for uniform wear rates. Thickness changes and mass loss were measured, and the surface exposed to the process fluid was observed for visual evidence of characteristic wear patterns resulting from an erosive environment. The test matrix consisted of several hours of operation and using fine, medium and coarse grain sands. Test results were analyzed to check for all three parameters (mass loss/gain, thickness change and surface patters) which could provide estimates of the remaining useful life of the pipe sections. Thus, the research presents the findings of this evaluation of the SRNL coupons as a means for conducting high accuracy, cost effective in-situ analysis of pipeline and waste transfer systems for erosion and corrosion susceptibility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI1989

Nuclear Safety [Vol. 30, No. 1, January-March 1989]

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Genomic analysis of Klebsiella aerogenes circulating in New Mexico

Klebsiella aerogenes is an opportunistic pathogen and a growing cause of healthcare-associated infections, characterized by multidrug resistance and the emergence of global high-risk clones. However, regional genomic surveillance data remain limited. Here, we sought to characterize the population structure, transmission dynamics and resistance mechanisms of clinical K. aerogenes in Albuquerque, New Mexico. We sequenced 177 clinical isolates collected between 2021 and 2023. We also developed a novel, species-specific PopPUNK database to facilitate rapid, high-resolution typing. The New Mexico K. aerogenes population was diverse but dominated by two global pandemic lineages, ST93 (47.5%) and ST4 (7.9%), which were significantly enriched for the virulence factors yersiniabactin and colibactin. Genomic evidence for recent local transmission was rare, with only four putative transmission pairs identified. The resistome was characterized by intrinsic and adaptive mutations. Nearly all isolates possessed gyrA mutations associated with decreased fluoroquinolone susceptibility. Mutations in the AmpC regulator AmpD and the outer membrane porin Omp36 were common, particularly within the dominant ST93 lineage. These mutations have been associated with increased AmpC-mediated carbapenem resistance. Our findings underscore the critical importance of genomic surveillance to monitor the transmission and evolution of adaptive resistance.

59 BASIC BIOLOGICAL SCIENCES↗