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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.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees or reliability block diagrams) can effectively propagate reliability data from the asset to the system level in order to identify system critical points. However, employed asset reliability data are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers on the most critical assets. In addition, the propagation of quantitative health data from the asset to the system level is a challenge given the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, expected failure time). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating available health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Here, this paper is directly addressing these two goals by proposing a different approach for reliability modeling that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. The propagation of health data from the asset to the system level is performed through fault tree models not in probability terms, but in terms of margin where margin is the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of an undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical assets.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Health outcomes among offspring of US Coast Guard responders to the Deepwater Horizon oil spill, 2010–2011

To evaluate the potential for adverse health outcomes among infants born to US Coast Guard (USCG) responders to the Deepwater Horizon (DWH) oil spill disaster. Department of Defense Birth and Infant Health Research programme data identified a cohort of singleton infants born 2010–2011 to USCG personnel in the DWH Oil Spill Coast Guard Cohort study. Infants were included if their military parent (‘sponsor’) responded to the oil spill during a selected reproductive exposure window (ie, 3 months preconception for male sponsors and periconception through pregnancy for female sponsors), or if their sponsor was a non-responder. χ 2 tests and multivariable log-binomial regression were used to compare the demographic and health characteristics of infants born to spill responders and non-responders. Altogether, 1974 infants with a male sponsor (n=182 responder, n=1792 non-responder) and 628 infants with a female sponsor (n=35 responder, n=593 non-responder) in the DWH Oil Spill Coast Guard Cohort were identified. Health outcomes were similar among the offspring of male responders and non-responders. The frequency of any poor live birth outcome (ie, low birth weight, preterm birth or birth defect) was higher among infants born to female responders (17.1%, n=6) than non-responders (8.9%, n=53); the maternal age-adjusted association was suggestively elevated (risk ratio 1.93, 95% CI 0.89 to 4.16). Infant health outcomes were comparable between the offspring of male USCG oil spill responders and non-responders. Findings were limited by the small number of infants identified, particularly among female responders, and should be interpreted with caution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Marine energy converters: Potential acoustic effects on fishes and aquatic invertebrates

The potential effects of underwater anthropogenic sound and substrate vibration from offshore renewable energy development on the behavior, fitness, and health of aquatic animals is a continuing concern with increased deployments and installation of these devices. Initial focus of related studies concerned offshore wind. However, over the past decade, marine energy devices, such as a tidal turbines and wave energy converters, have begun to emerge as additional, scalable renewable energy sources. Because marine energy converters (MECs) are not as well-known as other anthropogenic sources of potential disturbance, their general function and what is known about the sounds and substrate vibrations that they produce are introduced. Furthermore, while most previous studies focused on MECs and marine mammals, this paper considers the potential of MECs to cause acoustic disturbances affecting nearshore and tidal fishes and invertebrates. In particular, the focus is on particle motion and substrate vibration from MECs because these effects are the most likely to be detected by these animals. Finally, an analysis of major data gaps in understanding the acoustics of MECs and their potential impacts on fishes and aquatic invertebrates and recommendations for research needed over the next several years to improve understanding of these potential impacts are provided.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Trace elements and heavy metals in black vultures ( Coragyps atratus ) and turkey vultures ( Cathartes aura ) in the southeastern United States

Many vulture species worldwide are declining at alarming rates due to a variety of anthropogenic causes, including exposure to pollutants and pharmaceuticals through consumption of contaminated carrion. However, little is known about the extent to which vultures are exposed to various contaminants as well as toxicity thresholds for trace elements and heavy metals. Our objective was to quantify levels of trace elements and heavy metals within black vulture (Coragyps atratus) and turkey vulture (Cathartes aura) tissues to determine the extent to which populations in the southeastern United States are exposed to carrion that contains high levels of contaminants. We collected black vulture liver samples and examined differences in trace element and heavy metal concentrations between sexes and age classes (adult and juvenile). Further, we collected 81 blood and 42 feather samples from additional black and turkey vultures and compared differences between species and age classes. We found similar element concentrations between juvenile and adult black vultures with the exception of Cu, where levels 40 were higher in juveniles compared to adults. However, we did observe substantial differences in element concentrations between species for both blood and feather samples, with black vultures generally having higher concentrations of most elements. Our data revealed higher element levels in both species compared to toxicity thresholds found in other bird of prey species, such as blood and liver toxicity threshold suggestions for Pb poisoning in Falconiformes. Further, while average contaminant levels were generally low, extreme outliers were observed for some elements, including Pb, suggesting some individuals were exposed to high levels of potentially toxic elements. In conclusion, more research is needed to better understand contaminant exposure in black and turkey vultures across a broader geographic region, as well as elucidate toxicity thresholds and non-lethal impacts of contaminant exposure in these species.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

The Oral CXCR4 Inhibitor X4-136 Improves Tumor Control and Reduces Toxicity in Cervical Cancer Treated With Radiation Therapy and Concurrent Chemotherapy

Cervical cancer is a global health problem. Despite the growth of prevention programs, there is an important need to improve the effectiveness of treatment for patients with invasive, locally advanced disease. In this study we examined (1) the efficacy of radiation therapy (RT) with cisplatin (RTCT) and an orally administered CXCR4 inhibitor suitable for clinical use, X4-136; (2) biomarkers of response to RTCT and X4-136; and (3) intestinal toxicity from RTCT and X4-136.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Short term treatment with a cocktail of rapamycin, acarbose and phenylbutyrate delays aging phenotypes in mice

Pharmaceutical intervention of aging requires targeting multiple pathways, thus there is rationale to test combinations of drugs targeting different but overlapping processes. In order to determine if combining drugs shown to extend lifespan and healthy aging in mice would have greater impact than any individual drug, a cocktail diet containing 14 ppm rapamycin, 1000 ppm acarbose, and 1000 ppm phenylbutyrate was fed to 20-month-old C57BL/6 and HET3 4-way cross mice of both sexes for three months. Mice treated with the cocktail showed a sex and strain-dependent phenotype consistent with healthy aging including decreased body fat, improved cognition, increased strength and endurance, and decreased age-related pathology compared to mice treated with individual drugs or control. The severity of age-related lesions in heart, lungs, liver, and kidney was consistently decreased in mice treated with the cocktail compared to mice treated with individual drugs or control, suggesting an interactive advantage of the three drugs. This study shows that a combination of three drugs, each previously shown to enhance lifespan and health span in mice, is able to delay aging phenotypes in middle-aged mice more effectively than any individual drug in the cocktail over a 3-month treatment period.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Review—Thermal Safety Management in Li-Ion Batteries: Current Issues and Perspectives

Approaches for thermal management of lithium-ion (Li-ion) batteries do not always keep pace with advances in energy storage and power delivering capabilities. Root-cause analysis and empirical evidence indicate that thermal runaway (TR) in cells and cell-to-cell thermal propagation are due to adverse changes in physical and chemical characteristics internal to the cell. However, industry widely uses battery management systems (BMS) originally designed for aqueous-based batteries to manage Li-ion batteries. Even the "best" BMS that monitor both voltage and outside-surface temperature of each cell are not capable of preventing TR or TR propagation, because voltage and surface-mounted temperature sensors do not track fast-emerging adverse events inside a cell. Most BMS typically include a few thermistors mounted on select cells to monitor their surface temperature. Technology to track intra-cell changes that are TR precursors is becoming available. Simultaneously, the complex pathways resulting in cell-to-cell TR propagation are being successfully modelled and mapped. Innovative solutions to prevent TR and thermal propagation are being advanced. These include modern BMS for rapid monitoring the internal health of each individual cell and physical as well as chemical methods to reduce the deleterious effects of rapid cell-to-cell heat and material transport in case of TR.

25 ENERGY STORAGE↗
DOE OSTI2022

Editorial: Particulate Matter Emissions From Conventional and Reformulated Fuel Combustion: Advances in Experiments and Simulations

Particulate matter (PM or soot) emissions generated by combustion of conventional and reformulated fuels adversely impact the environment and human health (Bond et al., 2013; Landrigan et al., 2018; World Health Organization (WHO), 2016), generating public awareness and motivating efforts towards the mitigation of their harmful effects. Soot formation is one of the most complex phenomena in combustion, involving interactions between combustion chemistry, fluid mechanics, mass/heat transport, and particle dynamics, spanning different spatial and temporal scales. A fundamental understanding of soot formation process is thus necessary to achieve a strong reduction of PM emissions and design cleaner and more efficient combustion systems. This has motivated a longstanding and ongoing research activity aimed at improving our understanding of the physical and chemical processes involved in soot formation, well reviewed in these recent works (Wang and Chung, 2019; Michelsen et al., 2020; Martin et al., 2022). Despite the wide interest, the transition from gas-phase molecules to incipient soot particles is still elusive and the successive particle growth and oxidation processes are far from being fully understood, especially in conditions relevant to real-world applications. Recent advances in combustion PM emission diagnostic and computational capabilities helped in improving the predictability of fundamental chemical and aerosol models for practical applications, thus tackling some of the above-mentioned challenges. The aim of this research topic is to display the ongoing research efforts in addressing the existing gaps on particulate formation from various fuel sources and in conditions typical of practical combustion applications (e.g. flames, engines, pool fires), through both experimental and numerical approaches.

42 ENGINEERING↗
DOE OSTI2024

Technical Language Processing of Nuclear Power Plants Equipment Reliability Data

Operating nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) element data that contain information about the status of components, assets, and systems. Some of this information is in textual form where the occurrence of abnormal events or maintenance activities are described. Analyses of NPP textual data via natural language processing (NLP) methods have expanded in the last decade, and only recently the true potential of such analyses has emerged. So far, applications of NLP methods have been mostly limited to classification and prediction in order to identify the nature of the given textual element (e.g., safety or non-safety relevant). In this paper, we target a more complex problem: the automatic generation of knowledge based on a textual element in order to assist system engineers in assessing an asset’s historical health performance. The goal is to assist system engineers in the identification of anomalous behaviors, cause–effect relations between events, and their potential consequences, and to support decision-making such as the planning and scheduling of maintenance activities. “Knowledge extraction” is a very broad concept whose definition may vary depending on the application context. In our particular context, it refers to the process of examining an ER textual element to identify the systems or assets it mentions and the type of event it describes (e.g., component failure or maintenance activity). In addition, we wish to identify details such as measured quantities and temporal or cause–effect relations between events. This paper describes how ER textual data elements are first preprocessed to handle typos, acronyms, and abbreviations, then machine learning (ML) and rule-based algorithms are employed to identify physical entities (e.g., systems, assets, and components) and specific phenomena (e.g., failure or degradation). A few applications relevant from an NPP ER point of view are presented as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Machine Learning Models for Mapping Groundwater Pollution Risk: Advancing Water Security and Sustainable Development Goals in Georgia, USA

The widespread use of pesticides, such as atrazine and malathion, in agricultural systems raises significant concerns regarding the contamination of groundwater, which serves as a critical resource for drinking water. This study applies machine learning techniques to predict the concentrations of atrazine and malathion in groundwater across Georgia, USA, using 2019 data. A Random Forest classifier was employed to integrate various environmental and demographic factors, including pesticide application rates, precipitation, lithology, and population density, to predict pesticide contamination in groundwater. The models demonstrated high training accuracies of 100% and moderate average testing accuracy of 55% for atrazine and 60% for malathion across five iterations. The low test accuracy of the model, ranging from 50% to 75%, is likely due to overfitting, which can be attributed to the small dataset size and the complex nature of pesticide-contamination patterns, making it challenging for the model to generalize to unseen data. Feature importance analysis revealed that average pesticide usage emerged as the most influential factor for atrazine, while aquifer lithology and precipitation played crucial roles in both models. These results provide valuable insights into the dynamics of pesticide contamination, highlighting areas at greater risk of contamination. The findings underscore the importance of integrating environmental, geological, and agricultural variables for more effective groundwater management and sustainable agricultural practices, contributing to the protection of water resources and public health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dose Rate Effects on Degradation of Nuclear Power Plant Electrical Cable Insulation at a Common Dose

The intent of this report is to address an identified knowledge gap in relating accelerated aging of nuclear electrical cables to service aging: dose rate effects (DRE). Here, DRE refer to gamma radiation-induced polymer degradation being a function of dose rate in addition to total absorbed dose. The concern raised is that historical qualification conducted at higher dose rates to simulate service lifetime may underestimate insulation degradation that occurs at lower dose rates in service. In the work described herein, common nuclear cable insulation materials—cross-linked polyethylene (XLPE) and ethylene propylene diene elastomer (EPDM)—were subjected to accelerated aging at ambient temperature (26°C) at different gamma dose rates of 100, 200 and 1800 Gy/h for select exposure durations to achieve constant total doses of 170, 210 and 300 kGy to evaluate DRE. First, the cable insulation material types investigated are described. Then, the accelerated aging experimental process involving gamma irradiation applied to the insulation specimens at room temperature and different dose rates is discussed. Then, the experimental characterization techniques used to perform this work are elucidated. These include elongation at break (EAB), mass change, yellowness index (YI), carbonyl index (CI), density, indenter modulus (IM), and relaxation constant (t). Theory of polymer degradation is discussed, and characterization results and discussion are provided. Finally, concluding remarks are made. The findings from this work and cited prior work reveal that DRE are material dependent, even between similar material categories (e.g., XLPE). In the case of the EPDM studied, degradation of ductility was observed to be greater at higher dose rate for the same total dose, indicating accelerated gamma aging to be more conservative than extended aging. Thus, conclusions regarding the conservatism of historical qualification likely require additional consideration for specific materials and conditions in question. The results of this study support the contention that, due to inherent limitations and uncertainties associated with prediction of cable remaining useful life from accelerated aging experiments, trending of installed cable insulation health status will be more practical and useful for safe and efficient cable aging management repair and replace decisions than lifetime prediction from historical qualification. The combination of material robustness demonstrated by the qualification process and ongoing monitoring of cable health status combine to provide confidence in continued safe use of existing nuclear cables. Additional research into effective and efficient condition monitoring methods for non-destructive evaluation of installed cables is needed to support aging cable management, including material studies to inform interpretation of measured results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.

Nazaralizadeh, Solmaz (ORCID:0009000737004039)↗
DOE OSTI2021

Effects of a Layered Morphology on Drip Suppression in Burning Polymers

Fire safety in polymers is critically important with products such as textiles and consumer goods, as well as materials used in construction, aerospace, transportation, and furniture. Additives used as anti-dripping and flame-retardant agents impose acute human health issues and have negative environmental impacts. With a focus on developing additive-free solutions, here we used multilayer coextrusion to fabricate layered polyethylene/polypropylene (PE/PP) films and investigated the effect of a layered morphology on dripping and burning rates. The experimental results for multilayered PE/PP samples were compared to control groups of melt blended PE/PP samples. The multilayer configuration provides two significant advantages: 154% delay in the time to the first drip and up to 87% reduction in the number of drips compared to the value for the melt blended samples with no additives. PE/PP blends with up to 2 wt % polytetrafluoroethylene, a commonly used anti-dripping agent in the industry, showed only 85% delay in the time to the first drip and about 60% reduction in the number of drips. We discovered a linear relationship between film thickness and burning rate, which allows for the use of the volumetric burning rate to normalize the effect of film thickness. No benefit in the burning rate was observed when comparing multilayered structures and conventional melt blended architectures or blends with PTFE. Annealing studies and transmission electron microscopy at areas close to the combustion zones confirmed that higher extensional viscosities induced by the layered structures and morphological changes due to the layer breakup play an important role in reducing dripping. By combining the first drip time and overall drip numbers, a parameter, “dripping index”, was defined to establish a fire safety map to simplify material comparisons. This study demonstrates that a multilayer film geometry can provide an additive-free solution to yield control over fire safety parameters in polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gut microbiome partially mediates and coordinates the effects of genetics on anxiety-like behavior in Collaborative Cross mice

Abstract Growing evidence suggests that the gut microbiome (GM) plays a critical role in health and disease. However, the contribution of GM to psychiatric disorders, especially anxiety, remains unclear. We used the Collaborative Cross (CC) mouse population-based model to identify anxiety associated host genetic and GM factors. Anxiety-like behavior of 445 mice across 30 CC strains was measured using the light/dark box assay and documented by video. A custom tracking system was developed to quantify seven anxiety-related phenotypes based on video. Mice were assigned to a low or high anxiety group by consensus clustering using seven anxiety-related phenotypes. Genome-wide association analysis (GWAS) identified 141 genes (264 SNPs) significantly enriched for anxiety and depression related functions. In the same CC cohort, we measured GM composition and identified five families that differ between high and low anxiety mice. Anxiety level was predicted with 79% accuracy and an AUC of 0.81. Mediation analyses revealed that the genetic contribution to anxiety was partially mediated by the GM. Our findings indicate that GM partially mediates and coordinates the effects of genetics on anxiety.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Rice Bran Stabilisation and Oil Extraction Using the Microwave-Assisted Method and Its Effects on GABA and Gamma-Oryzanol Compounds

Rice bran oil (RBO) is a valuable ingredient extracted from rice bran (RB), a side stream of polishing rice grain in the milling process. RBO is rich in bioactive ingredients with potential health benefits, such as gamma-oryzanol (GO) and gamma-aminobutyric acid (GABA). Despite its benefits, the quality of RBO depends on the degree of stabilisation of the RB, which is easily affected by lipase enzymes, and thus needs an effective treatment prior to RBO production. To assess the potential of the microwave-assisted method for RB stabilisation and RBO extraction, three Carolino rice varieties (Ariete, Teti, Luna) were tested. The effect of RB stabilisation was evaluated via acid value, water absorption, and GO and GABA levels. The RBO yield was optimised by solvent, temperature, and solvent-to-sample ratio, and the GO and fatty acid levels were determined. The RB stabilisation for the Luna variety did not affect the GO and GABA; for the Ariete and Teti varieties, the GO decreased by 34.4% and 24.2%, and the GABA increased by 26.5% and 47.0%, respectively. The GO levels in RBO samples were not affected by RB stabilisation. The RBO nutritional value was confirmed by the suitable ratio (>2) between polyunsaturated (PUFA) and saturated fatty acids (SFA), with the Teti variety presenting the highest ratio.

Reis, Núria (ORCID:0000000194339109)↗
DOE OSTI2025

National serosurvey and risk mapping reveal widespread distribution of Coxiella burnetii in Kenya

Coxiella burnetii, the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

60 APPLIED LIFE SCIENCES↗