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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

COVID-19 Lead Time: Evaluating the timeliness and reliability of reported COVID-19 cases and hospitalizations as leading indicators of hospitalizations and death in the US

The COVID-19 pandemic prompted a reliance on real-time data sources to understand the global spread and impact of the SARS-CoV-2 virus. Reported cases were presumed leading indicators for hospitalizations, while hospitalizations were considered predictive of deaths. However, studies have questioned the consistency of reported cases as leading indicators. This study systematically assesses the reliability of United States (US) reported cases and hospitalizations as leading indicators for hospitalizations and deaths respectively, examining the first 2.5 years of the pandemic (January 2020 - June 2022) across different phases of the pandemic and states. Using correlation analysis, population data, and forecasting accuracy measures, we investigate the temporal relationships and identify possible determinants of lead time variability. Notably, we found that the average lead time between reported cases and hospitalizations across US states is relatively short at 1.76 days, implying that reported cases might not be as effective a leading indicator for hospitalizations as previously believed. Populations with higher comorbidity burdens, such as proportion of smokers, are expected on average to have shorter lead times, possibly due to shorter time to hospitalization among these vulnerable populations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

NASA Perspective on Leading Indicators and Dashboarding

To convey information about NASA shares information to programs, projects, Centers on the status of certain activities/requirements via dashboards. in addition, how we use leading indicators to anticipate and mitigate problems prior to an accident.

leading indicators↗
NASA NTRS2012

Monitoring of International Space Station Telemetry Using Shewhart Control Charts

Shewhart control charts have been established as an expedient method for analyzing dynamic, trending data in order to identify anomalous subsystem performance as soon as such performance would exceed a statistically established baseline. Additionally, this leading indicator tool integrates a selection methodology that reduces false positive indications, optimizes true leading indicator events, minimizes computer processor unit duty cycles, and addresses human factor concerns (i.e., the potential for flight-controller data overload). This innovation leverages statistical process control, and provides a relatively simple way to allow flight controllers to focus their attention on subtle system changes that could lead to dramatic off-nominal system performance. Finally, this capability improves response time to potential hardware damage and/or crew injury, thereby improving space flight safety. Shewhart control charts require normalized data. However, the telemetry from the ISS Early External Thermal Control System (EETCS) was not normally distributed. A method for normalizing the data was implemented, as was a means of selecting data windows, the number of standard deviations (Sigma Level), the number of consecutive points out of limits (Sequence), and direction (increasing or decreasing trend data). By varying these options, and treating them like dial settings, the number of nuisance alerts and leading indicators were optimized. The goal was to capture all leading indicators while minimizing the number of nuisances. Lean Six Sigma (L6S) design of experiment methodologies were employed. To optimize the results, Perl programming language was used to automate the massive amounts of telemetry data, control chart plots, and the data analysis.

Fitch, Jeffery T.↗
DOE OSTI2024

Challenges of COVID-19 Case Forecasting in the US, 2020–2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub ( https://covid19forecasthub.org ). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1–4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

Accelerated Aging System for Prognostics of Power Semiconductor Devices

Prognostics is an engineering discipline that focuses on estimation of the health state of a component and the prediction of its remaining useful life (RUL) before failure. Health state estimation is based on actual conditions and it is fundamental for the prediction of RUL under anticipated future usage. Failure of electronic devices is of great concern as future aircraft will see an increase of electronics to drive and control safety-critical equipment throughout the aircraft. Therefore, development of prognostics solutions for electronics is of key importance. This paper presents an accelerated aging system for gate-controlled power transistors. This system allows for the understanding of the effects of failure mechanisms, and the identification of leading indicators of failure which are essential in the development of physics-based degradation models and RUL prediction. In particular, this system isolates electrical overstress from thermal overstress. Also, this system allows for a precise control of internal temperatures, enabling the exploration of intrinsic failure mechanisms not related to the device packaging. By controlling the temperature within safe operation levels of the device, accelerated aging is induced by electrical overstress only, avoiding the generation of thermal cycles. The temperature is controlled by active thermal-electric units. Several electrical and thermal signals are measured in-situ and recorded for further analysis in the identification of leading indicators of failures. This system, therefore, provides a unique capability in the exploration of different failure mechanisms and the identification of precursors of failure that can be used to provide a health management solution for electronic devices.

Celaya, Jose R.↗
DOE OSTI2021

Impact of n -Butylammonium Bromide on the Chemical and Electronic Structure of Double-Cation Perovskite Thin Films

2D/3D perovskite heterostructures have emerged as a promising material composition to reduce nonradiative recombination in perovskite-based LEDs and solar cells. Such heterostructures can be created by a surface treatment with large organic cations, for example, n-butylammonium bromide (BABr). To understand the impact of the BABr surface treatment on the double-cation (Cs 0.17 FA 0.83 Pb(I 0.6 Br 0.4 ) 3 ) (FA = formamidinium) perovskite thin film and further optimize the corresponding structures, an in-depth understanding of the chemical and electronic properties of the involved surfaces, interfaces, and bulk is required. We study the impact of the BABr treatment with a combination of surface-sensitive X-ray photoelectron spectroscopy and bulk-sensitive resonant inelastic soft X-ray scattering (RIXS). A quantitative analysis of the BABr-treated perovskite thin film shows a modified chemical perovskite surface environment of carbon, nitrogen, bromine, iodine, and lead, indicating that the treatment leads to a perovskite surface with a modified composition and bonding structure. With K-edge RIXS, the local environment at the nitrogen and carbon atoms is probed, allowing us to identify the presence of BABr in the perovskite bulk albeit with a modified bonding environment. This, in turn, identifies a "hidden parameter" for the optimization of the BABr treatment and overall performance of 2D/3D perovskite solar cell absorbers.

2D/3D perovskite heterostructure↗
NASA NTRS1973

Excess lead in 'rusty rock' 66095 and implications for an early lunar differentiation

Apollo 16 breccia 66095 contains a remarkably high amount of lead (15 parts per million), 85 percent of which is not supported by uranium and thorium in the rock. An acid leach experiment coupled with separate analyses of the whole rock and mineral fractions for uranium, thorium, and lead indicate that the excess lead has a lunar source and was apparently introduced about 4.0 b.y. ago. The data also suggest that a major lunar crustal differentiation occurred about 4.47 b.y. ago.

Nunes, P. D.↗
NASA NTRS1998

Precipitation-Based ENSO Indices

In this study gridded observed precipitation data sets are used to construct rainfall-based ENSO indices. The monthly El Nino and La Nina Indices (EI and LI) measure the steepest zonal gradient of precipitation anomalies between the equatorial Pacific and the Maritime Continent. This is accomplished by spatially averaging precipitation anomalies using a spatial boxcar filter, finding the maximum and minimum averages within a Pacific and Maritime Continent domain for each month, and taking differences. EI and LI can be examined separately or combined to produce one ENSO Precipitation Index (ESPI). ESPI is well correlated with traditional sea surface temperature and pressure indices, leading Nino 3.4. One advantage precipitation indices have over more conventional indices, is describing the strength and position of the Walker circulation. Examples are given of tracking the impact of ENSO events on the tropical precipitation fields.

Adler, Robert↗
DOE OSTI2024

A modeling pipeline to relate municipal wastewater surveillance and regional public health data

As COVID-19 becomes endemic, public health departments require improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging. We have developed a generalized methodology to improve the predictive power of wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but all model estimates of prevalence significantly improved correlation compared to doing no correction. We also investigate the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We do this in a rolling manner for corrected wastewater data and for other prevalence indicators, and statistically compare the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We find that wastewater trends often lead other COVID-19 indicators in predicting new surges.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2008

Achieving Workplace Health through Application of Wellness Strategies

Purpose: 1) Understand and measure JSC workplace health: a) levels, sources, indicators & effects of negative, work-related stress; b) define leading indicators of emerging issues. 2 Provide linkage to outcomes: a) Focus application of wellness strategies & HR tools; b) Increase quality of work life and productivity. 3) Current effort will result in: a) Online assessment tool; b) Assessment of total JSC population (civil service & contractors); c) Application of mitigation tools and strategies. 4) Product of the JSC Employee Wellness Program. 5) Collaboration with Corporate Health Improvement Program/University of Arizona.

Robinson, Judith L.↗
NASA NTRS2007

Using Satellite Remote Sensing Data in a Spatially Explicit Price Model

Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.

Brown, Molly E.↗
NASA NTRS1974

Lead isotope systematics of some Apollo 17 soils and some separated components from 76501

Isotopic lead data from bulk samples of Apollo 17 soils were analyzed, and they define a chord in a concordia diagram, showing the presence of a component or components containing excess radiogenic lead with Pb-207/Pb-206 equal to about 1.32. The chord is distinctly different from the cataclysm chord, for which Pb-207/Pb-206 is approximately 1.45. Nitric acid analysis of plagioclase indicates lead ages of around 4.35 AE, in agreement with previous findings. Agglutinates from soil 76501,34 show loss of approximately 15% of lead.

Church, S. E.↗
DOE OSTI2021

Investigating the relation between instantaneous driving decisions and safety critical events in naturalistic driving environment

The availability of large-scale naturalistic driving data provides enormous opportunities for studying relationships between instantaneous driving decisions prior to involvement in safety critical events (SCEs). This study investigates the role of driving instability prior to involvement in SCEs. While past research has studied crash types and their contributing factors, the role of pre-crash behavior in such events has not been explored as extensively. The research demonstrates how measures and analysis of driving volatility can be leading indicators of crashes and contribute to enhancing safety. Highly detailed microscopic data from naturalistic driving are used to provide the analytic framework to rigorously analyze the behavioral dimensions and driving instability that can lead to different types of SCEs such as roadway departures, rear end collisions, and sideswipes. Modeling results reveal a positive association between volatility and involvement in SCEs. Specifically, increases in both lateral and longitudinal volatilities represented by Bollinger bands and vehicular jerk lead to higher likelihoods of involvement in SCEs. Further, driver behavior related factors such as aggressive driving and lane changing also increases the likelihood of involvement in SCEs. Driver distraction, as represented by the duration of secondary tasks, also increases the risk of SCEs. Likewise, traffic flow parameters play a critical role in safety risk. The risk of involvement in SCEs decreases under free flow traffic conditions and increases under unstable traffic flow. Further, the model shows prediction accuracy of 88.1 % and 85.7 % for training and validation data. These results have implications for proactive safety and providing in-vehicle warnings and alerts to prevent the occurrence of such SCEs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

The Hanford Lead Canister Collaboration

The Hanford Site, Management of the Cesium and Strontium Capsules (MCSC) Project is preparing to place cesium and strontium material into dry storage using stainless steel canisters that are housed inside vertical concrete casks. Part of the site’s aging management program is to use a spare canister system as a leading indicator canister to provide advance warning for signs of chloride induced stress corrosion cracking (CISCC) or any other kind of canister degradation that might take place over the system’s 300-year design life. The Hanford Lead Canister (HLC) will use electric heaters to simulate the decay heat of cesium and strontium to ensure the HLC simulates the environment and conditions the capsule-loaded systems will experience. In addition to being part of the site’s aging management program, the HLC is being made available for research and development that advances the industry regarding canister mitigation and repair (M&R). The HLC system closely resembles current spent nuclear fuel (SNF) dry storage systems, making the HLC useful for demonstrating technologies or performing research that is relevant to SNF canisters . Several organizations are collaborating to prepare the HLC, along with technical strategy, to perform the needed research and development activities, to include the Pacific Northwest National Laboratory (PNNL), Central Plateau Cleanup Company (CPCCo), and the Electric Power Research Institute (EPRI). In one example of this collaborative research, EPRI is planning to use the HLC to demonstrate in-situ M&R technologies under controlled conditions before the HLC is deployed at Hanford. There is a period of several years when the HLC will be available for canister M&R activity before it is deployed. This paper describes the development of the HLC, its role in the Hanford site’s MCSC Project aging management program, and some of the research activities that are planned for the HLC.

Klymyshyn, Nicholas A.↗
DOE OSTI2021

Mechanical Properties of Nominally Ductile and Brittle Zones within the Caney Shale Formation

We present a case study from the Caney Shale, which is an emerging hydrocarbon-bearing formation in Oklahoma. Open hole logs lead to a nominal distinction of five zones in an exploration well, two of which are designated “ductile” and three of which are designated as less ductile “reservoir” zones. Subsequently, a detailed mechanical characterization was carried out on core plugs taken from each of these zones. Results show nominally “ductile” zones are weaker in terms of UCS, tensile strength, fracture toughness, and confined compressive strength. However, by a variety of brittleness indices, it is found the nominal “ductile” regions do not behave as expected. They are weaker, but not consistently more ductile. Furthermore, some brittleness indices lead to contradictory conclusions. For example, zones which would be considered the most brittle according to the proportion of nonlinear stress-strain behavior prior to failure and/or by indices based on elastic properties would be considered the least brittle according to their internal friction angle.

Benge, Margaret↗
DOE OSTI2025

Integrating Contaminant Source Indicators, Water Quality Measures, and Ecotoxicity to Characterize Contaminant Mixtures and Per- and Polyfluoroalkyl Substance (PFAS) Variability in an Urban Watershed

Thousands of chemical contaminants threaten watersheds but are time and cost prohibitive to monitor. Identifying their sources, transport, and ecological risk is limited in heterogeneous urban watersheds. We present an integrative watershed approach using source-specific indicator compounds, common water quality measures, and ecotoxicity assays to examine the distribution of contaminant mixtures in an urbanized watershed. Indicator compound concentrations were temporally and spatially distributed for treated/untreated sewage (sucralose, artificial sweetener), road runoff (diphenyl-guanidine [DPG] and 6PPD-quinone [6PPD-Q], automobile tire additives), and lawncare runoff (aminomethanephosphonic acid (AMPA), major degradant of the herbicide glyphosate). Sucralose was predominately sourced from treated wastewater; measurable concentrations in tributaries indicated raw sewage inputs. DPG and 6PPD-Q concentrations correlated to road density during base flow and were elevated during stormflow. AMPA was measurable spring through fall, especially where lawns were dense. When specific sources dominated flow, water quality measures correlated with wastewater (sulfate, potassium, chloride, and sodium) and road runoff (chromium and lead) indicators. The limited behavioral toxicity observed in exposed zebrafish (Danio rerio) (18%) was not well explained by source-indicators. PFAS concentrations were highly variable spatially but not well explained by our source-specific indicator compounds. Here, more costly compound-specific monitoring may be necessary when multiple sources exist or when unexpected toxicity trends occur.

computer simulations↗
NASA NTRS2021

Leveraging NASA Soil Moisture Active Passive for Assessing Fire Susceptibility and Potential Impacts over Australia and California

Wildfires are a major concern around the globe because of the immediate impact they have on people's lives, local ecosystems, and the environment. Soil moisture is one of the most important factors that influences wildfire occurrences and spread. However, it is also one of the most challenging hydrological variables to measure routinely and accurately. Therefore, soil moisture is significantly underutilized in operational wildfire risk applications. Thus, the aim here is to use a well-established operational soil moisture product to isolate the soil moisture-fire relationship and assess the utility of using soil moisture as a leading indicator of potential fire risk. We evaluated the value of remotely-sensed soil moisture observations from the Soil Moisture Active Passive (SMAP) sensor for monitoring and predicting fire risk in Australia and California. We quantified the relationship between observed fire activity and soil moisture conditions and analyzed the soil moisture conditions for two extreme fire events. Our findings show that fire activity is strongly associated with soil moisture anomalies. Lagged correlation analysis demonstrated that a remote-sensing based soil moisture product could predict fire activity with a 1-2 month lead-time. Soil moisture anomalies consistently decreased in the months preceding fire occurrence, often from normal to drier conditions, according to a spatiotemporal analysis of soil moisture in two extreme fire events. Overall, our findings indicate that soil moisture conditions prior to large wildfires can aid in their prediction and operational satellite-based soil moisture products such as the one used here have real value for supporting wildfire susceptibility and impacts.

Nazmus Sazib↗
DOE OSTI2024

A multi-ancestry GWAS of Fuchs corneal dystrophy highlights the contributions of laminins, collagen, and endothelial cell regulation

Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular etiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program followed by multi-ancestry meta-analysis with the previous largest FECD GWAS, for a total of 3970 cases and 333,794 controls. We confirm the previous four loci, and identify eight novel loci: SSBP3, THSD7A, LAMB1, PIDD1, RORA, HS3ST3B1, LAMA5, and COL18A1. We further confirm the TCF4 locus in GWAS for admixed African and Hispanic/Latino ancestries and show an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling, validated through homology, suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and colocalization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.

59 BASIC BIOLOGICAL SCIENCES↗