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Results for “Environmental variabilities”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

NWSC nickel cadmium spacecraft cell accelerated life test program data analysis

An analysis of the data leading to a proposed accelerated life test scheme to test a nickel cadmium cell under spacecraft usage conditions is described. The amount and concentration of electrolyte and the amount of precharge in the cell are discussed in relation to the design of the cell and the accelerated test design. A failure analysis of the cell is summarized. The analysis included such environmental test variables as the depth of discharge, the temperature, the amount of recharge and the charge and discharge rate.

Lander, J.↗
NASA NTRS1982

The structure and dynamics of mesoscale systems influencing severe thunderstorm development during AVE/SESAME 1

Relationships between meso-beta scale systems and thunderstorm formation were examined as part of the NASA atmospheric variability experiment/severe environmental storms and mesoscale experiment 1979. The McIdas program was employed for meso-beta scale analyses of atmospheric structure and dynamics in kinematic computations of the Abilene Triangle on a grid mesh of 100 km for station spacing of 275 km. Mesoscale short wave systems were detected imbedded and propagating cyclonically around upper-level vortex circulation and creating environmental conditions conducive to thunderstorm development. TIROS-N and GOES satellite data served to connect the systems with two convective storms which developed. The necessity to use spaceborne instrumentation carried on the Shuttle or on free-flying satellites for enhancing the data-base on storm development is noted.

Wilson, G. S.↗
NASA NTRS1995

Empirical modeling of environment-enhanced fatigue crack propagation in structural alloys for component life prediction

This research aims to develop the methods and understanding needed to incorporate time and loading variable dependent environmental effects on fatigue crack propagation (FCP) into computerized fatigue life prediction codes such as NASA FLAGRO (NASGRO). In particular, the effect of loading frequency on FCP rates in alpha + beta titanium alloys exposed to an aqueous chloride solution is investigated. The approach couples empirical modeling of environmental FCP with corrosion fatigue experiments. Three different computer models have been developed and incorporated in the DOS executable program. UVAFAS. A multiple power law model is available, and can fit a set of fatigue data to a multiple power law equation. A model has also been developed which implements the Wei and Landes linear superposition model, as well as an interpolative model which can be utilized to interpolate trends in fatigue behavior based on changes in loading characteristics (stress ratio, frequency, and hold times).

Richey, Edward, III↗
NASA NTRS1998

Remotely-Sensed Regional-Scale Evapotranspiration of a Semi-Arid Great Basin Desert and its Relationship to Geomorphology, Soils, and Vegetation

Landsat thematic mapper data are used to estimate instantaneous regional-scale surface water and energy fluxes in a semi-arid Great Basin desert of the western United States. Results suggest that it is possible to scale from point measurements of environmental state variables to regional estimates of water and energy exchange. This research characterizes the unifying thread in the classical climate-topography-soil-vegetation relation -the surface water and energy balance-through maps of the partitioning of energy throughout the landscape. The study was conducted in Goshute Valley of northeastern Nevada, which is characteristic of most faulted graben valleys of the Basin and Range Province of the western United States. The valley comprises a central playa and lake plain bordered by alluvial fans emanating from the surrounding mountains. The distribution of evapotranspiration (ET) is lowest in the middle reaches of the fans where the water table is deep and plants are small, resulting in low evaporation and transpiration. Highest ET occurs in the center of the valley, particularly in the playa, where limited to no vegetation occurs, but evaporation is relatively high because of a shallow water table and silty clay soil capable of large capillary movement. Intermediate values of ET are associated with large shrubs and is dominated by transpiration.

Laymon, C.↗
NASA NTRS1997

Remotely-Sensed Regional-Scale Evapotranspiration of a Semi-Arid Great Basin Desert and its Relationship to Geomorphology, Soils, and Vegetation

Landsat Thematic Mapper data is used to estimate instantaneous regional-scale surface water and energy fluxes in a semi-arid Great Basin desert of the western United States. Results suggest that it is possible to scale from point measurements of environmental state variables to regional estimates of water and energy exchange. This research characterizes the unifying thread in the classical climate-topography-soil-vegetation relation-the surface water and energy balance-through maps of the partitioning of energy throughout the landscape. The study was conducted in Goshute Valley of northeastern Nevada, which is characteristic of most faulted graben valleys of the Basin and Range Province of the western United States. The valley comprises a central playa and lake plain bordered by alluvial fans emanating from the surrounding mountains. The distribution of evapotranspiration (ET) is lowest in the middle reaches of the fans where the water table is deep and plants are small, resulting in low evaporation and transpiration. Highest ET occurs in the center of the valley, particularly in the playa, where limited to no vegetation occurs, but evaporation is relatively high because of a shallow water table and silty clay soil capable of large capillary movement. Intermediate values of ET are associated with large shrubs and is dominated by transpiration.

Laymon, C.↗
NASA NTRS2004

Estimating Spatially-distributed Surface Fluxes in a Semi-arid Great Basin Desert Using Landsat TM Thermal Data

The research described in this chapter demonstrates a method for using Landsat Thematic Mapper data to estimate instantaneous regional-scale energy fluxes over an arid valley in eastern Nevada, U.S.A. Here point-based models of surface energy and water balance fluxes were applied to individual pixels of a Landsat Thematic Mapper scene over the study area. Although the method used to estimate these instantaneous fluxes requires certain assumptions be made about the spatial distribution of several physical parameters, the results from this analysis and modeling suggest that it is possible to scale from point measurements of environmental state variables (i.e., net radiation flux, surface heat flux, sensible heat flux, and latent heat flux) to regional estimates of energy exchange to obtain an understanding of the spatial relationship between these fluxes and landscape variables.

Quattrochi, Dale A.↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Molthan, Andrew L.↗
NASA NTRS2017

Synchronization of Human Autonomic Nervous System Rhythms with Geomagnetic Activity in Human Subjects

A coupling between geomagnetic activity and the human nervous system's function was identified by virtue of continuous monitoring of heart rate variability (HRV) and the time-varying geomagnetic field over a 31-day period in a group of 10 individuals who went about their normal day-to-day lives. A time series correlation analysis identified a response of the group's autonomic nervous systems to various dynamic changes in the solar, cosmic ray, and ambient magnetic field. Correlation coefficients and p values were calculated between the HRV variables and environmental measures during three distinct time periods of environmental activity. There were significant correlations between the group's HRV and solar wind speed, Kp, Ap, solar radio flux, cosmic ray counts, Schumann resonance power, and the total variations in the magnetic field. In addition, the time series data were time synchronized and normalized, after which all circadian rhythms were removed. It was found that the participants' HRV rhythms synchronized across the 31-day period at a period of approximately 2.5 days, even though all participants were in separate locations. Overall, this suggests that daily autonomic nervous system activity not only responds to changes in solar and geomagnetic activity, but is synchronized with the time-varying magnetic fields associated with geomagnetic field-line resonances and Schumann resonances.

Magnetic Fields↗
NASA NTRSDate not supplied

Determining the Cause of Reduced Concurrent Flame Spread over Thin Solid Fuels in Low Pressure and Low Gravity

The spread of flames over the surface of solid combustible materials is affected by the environmental conditions. Variables such as flow velocity, oxygen concentration, ambient pressure, partial gravity or microgravity, may change the material flammability and influence the fire dynamics. This is an important fire safety issue for space exploration vehicles and space habitats which will very likely have different environments than those currently used on the International Space Station, such as reduced pressure and enriched oxygen concentration (SEA). However, testing experimentally the materials to be used and qualified for space exploration under these conditions is a difficult and expensive task. Here, numerical modeling is used to understand the dominant physico-chemical processes on the concurrent flame spread over thin fabrics under reduced ambient pressure (and in turn, buoyancy) and variable gravitational conditions. The numerical model uses the Fire Dynamics Simulator (FDS6) code with a single-step Arrhenius reaction rate for the solid phase decomposition. Different models are tested for the gas phase combustion kinetics. The model results are validated with experimental results obtained at similar reduced ambient pressure and flow conditions at 1 g. It is shown that as ambient pressure is reduced the flame spread rate over a thin fabric is also reduced, both experimentally and numerically. Numerical results are compared to an analytical approach previously developed to explain the experimental trends. Further interpretation of the model results provides information regarding the physics of the process and how they are affected by the lower pressure environments and gravity conditions. The results of this work provide guidance for potential on-earth testing for fire safety design in spacecraft and space habitats.

Fire Safety↗
NASA NTRSDate not supplied

Determining the Cause of Reduced Concurrent Flame Spread over Thin Solid Fuels in Low Pressure and Low Gravity

The spread of flames over the surface of solid combustible materials is affected by the environmental conditions. Variables such as flow velocity, oxygen concentration, ambient pressure, partial gravity or microgravity, may change the material flammability and influence the fire dynamics. This is an important fire safety issue for space exploration vehicles and space habitats which will very likely have different environments than those currently used on the International Space Station, such as reduced pressure and enriched oxygen concentration (SEA). However, testing experimentally the materials to be used and qualified for space exploration under these conditions is a difficult and expensive task. Here, numerical modeling is used to understand the dominant physico-chemical processes on the concurrent flame spread over thin fabrics under reduced ambient pressure (and in turn, buoyancy) and variable gravitational conditions. The numerical model uses the Fire Dynamics Simulator (FDS6) code with a single-step Arrhenius reaction rate for the solid phase decomposition. Different models are tested for the gas phase combustion kinetics. The model results are validated with experimental results obtained at similar reduced ambient pressure and flow conditions at 1 g. It is shown that as ambient pressure is reduced the flame spread rate over a thin fabric is also reduced, both experimentally and numerically. Numerical results are compared to an analytical approach previously developed to explain the experimental trends. Further interpretation of the model results provides information regarding the physics of the process and how they are affected by the lower pressure environments and gravity conditions. The results of this work provide guidance for potential on-earth testing for fire safety design in spacecraft and space habitats.

microgravity↗
NASA NTRS2022

Northeast US Ecological Forecasting: Modeling Invasive Plant Habitat Suitability to Support Management Efforts in the American Northeast

Invasive plant species threaten environmental and economic interests when they spread into new areas, outcompete native species, and disrupt ecosystem services. If the spread is not controlled early, species can become well-established and increasingly difficult to manage. The National Park Service (NPS) Invasive Plant Management Teams (IPMTs) strive for an “early detection, rapid response” approach to reducing invasive species spread. Management teams can better prioritize their work with the help of species distribution models (SDMs), which map habitat suitability by combining species occurrences with environmental predictor variables. Scarce invaded range data for newly arrived invasive species presents a particular challenge for producing accurate models. To improve future modeling efforts, this project compared SDM methods using different spatial scales to model two plant species invasive to the Northeast US: the well-established Japanese stiltgrass (Microstegium vimineum) and newer invasive species wavyleaf basketgrass (Oplismenus undulatifolius). The team used NASA Earth observations and climate datasets to model occurrence data and predictor layers at a US-specific extent (90m2 spatial resolution) and global extent (1 km2 spatial resolution). Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) provided data for US Normalized Difference Moisture Indices (NDMI), while global NDMI and topographic predictor layers were derived from Shuttle Radar Topography Mission (SRTM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting models indicated important predictor variables for each species and explored the benefits and tradeoffs of using global data to model habitat suitability for new-arrival invasive species.

Rebecca Ohman↗
NASA NTRSDate not supplied

Informing Dionaea muscipula (Venus Flytrap) Conservation Through Habitat Modeling and Forecasted Land Cover Change

The carnivorous Dionaea muscipula (Venus flytrap, Droseraceae) is threatened by habitat loss, fire suppression, and poaching. For rare plant species like D. muscipula with specialized habitat requirements and fragmented distribution, habitat suitability modeling is an important method for guiding conservation efforts. To support the D. muscipula conservation, this study: 1) modeled suitable habitat across the extent of the species’ known range and 2) forecasted land cover change due to development in the study area to the year 2050. Habitat modeling was conducted by overlaying high-confidence presence data observed since 1980 (n=292) with environmental predictor variables (n=23). Suitable habitats were then compared with land cover change to identify areas at risk of habitat loss due to human development. According to those models, nearly half (107.1km2) of modeled highly suitable D. muscipula habitat outside of protected lands are likely to face development pressure. On the other hand, 39.4% (139.9km2) of highly suitable habitats overlap with protected lands and may serve as lasting D. muscipula habitat. Results from this study can inform D. muscipula conservation, including targeted seed banking of populations at risk of extirpation, prioritization of habitats for protection and management, and reintroduction to suitable habitats within protected areas.

Kathryn Caruso↗
DOE OSTI2026

Multi-Agent Control Planes for Quantum Networks: A Scalable Architecture for Autonomous Quantum Internet Management

Quantum networks are expected to enable distributed quantum computing, secure communication, and global entanglement distribution. However, operating such networks presents significant challenges, including stochastic quantum processes, fragile entanglement resources, dynamic topology, and cross-layer control requirements. Current quantum network control architectures largely rely on centralized or hierarchical controllers inspired by classical software-defined networking (SDN). While effective for small testbeds, these approaches face scalability, latency, and reliability limitations as quantum networks grow. This paper proposes a multi-agent control plane architecture for quantum networks. In this design, intelligent software agents operate at quantum nodes, repeaters, and orchestration layers, collectively managing entanglement generation, routing, purification, and scheduling. The distributed intelligence of the agent system allows the network to adapt dynamically to quantum hardware variability and environmental noise. We argue that multi-agent systems provide significant advantages over centralized control approaches, including scalability, resilience, local autonomy, and real-time adaptation. The paper discusses architectural design principles, agent coordination mechanisms, and research challenges in deploying multi-agent control planes for the emerging quantum Internet.

Alnajjar, Anees [ORNL] (ORCID:0000000237101601)↗
NASA NTRS2001

Crops Models for Varying Environmental Conditions

New variable environment Modified Energy Cascade (MEC) crop models were developed for all the Advanced Life Support (ALS) candidate crops and implemented in SIMULINK. The MEC models are based on the Volk, Bugbee, and Wheeler Energy Cascade (EC) model and are derived from more recent Top-Level Energy Cascade (TLEC) models. The MEC models simulate crop plant responses to day-to-day changes in photosynthetic photon flux, photoperiod, carbon dioxide level, temperature, and relative humidity. The original EC model allows changes in light energy but uses a less accurate linear approximation. The simulation outputs of the new MEC models for constant nominal environmental conditions are very similar to those of earlier EC models that use parameters produced by the TLEC models. There are a few differences. The new MEC models allow setting the time for seed emergence, have realistic exponential canopy growth, and have corrected harvest dates for potato and tomato. The new MEC models indicate that the maximum edible biomass per meter squared per day is produced at the maximum allowed carbon dioxide level, the nominal temperatures, and the maximum light input. Reducing the carbon dioxide level from the maximum to the minimum allowed in the model reduces crop production significantly. Increasing temperature decreases production more than it decreases the time to harvest, so productivity in edible biomass per meter squared per day is greater at nominal than maximum temperatures, The productivity in edible biomass per meter squared per day is greatest at the maximum light energy input allowed in the model, but the edible biomass produced per light energy input unit is lower than at nominal light levels. Reducing light levels increases light and power use efficiency. The MEC models suggest we can adjust the light energy day-to- day to accommodate power shortages or Lise excess power while monitoring and controlling edible biomass production.

Jones, Harry↗
NASA NTRS2014

Environmental Risk Factors and Child Nutritional Status and Survival in a Context of Climate Variability and Change

Much of the population in the developing world resides in rural areas, is dependent on local agriculture for survival, and thus directly subject to increasingly volatile and variable climatic patterns. Poverty limits options for adaptation to unpredictable weather and resultant food insecurity; these concerns are particularly salient in an era of climate change, which threatens to roll back years of development gains. Examining the association between the growing environment and child survival and nutrition is important in this context. Using NASA's satellite remote sensing data with Demographic and Health Surveys (DHS) data from four West African countries (Mali, Burkina Faso, Guinea and Benin), we assess the association between a climate-related environmental variable (vegetation index - NDVI) and child survival and nutrition. NDVI had a positive association with child survival and nutrition in countries with a wide distribution of NDVI values. NDVI was more likely to be positively associated with wasting rather than stunting. We find that environmental factors can be important for child survival and nutrition outcomes in specific contexts. Additional research is needed to further explore the ways NDVI can be used to inform our understanding of the environment's impact on child survival and nutrition.

Environment↗
DOE OSTI2022

Key environmental and production factors for understanding variation in switchgrass chemical attributes

Abstract Switchgrass ( Panicum virgatum L.) is a promising feedstock for bioenergy and bioproducts; however, its inherent variability in chemical attributes creates challenges for uniform conversion efficiencies and product quality. It is necessary to understand the range of variation and factors (i.e., field management, environmental) influencing chemical attributes for process improvement and risk assessment. The objectives of this study were to (1) examine the impact of nitrogen fertilizer application rate, year, and location on switchgrass chemical attributes, (2) examine the relationships among chemical attributes, weather and soil data, and (3) develop models to predict chemical attributes using environmental factors. Switchgrass samples from a field study spanning four locations including upland cultivars, one location including a lowland cultivar, and between three and six harvest years were assessed for glucan, xylan, lignin, volatiles, carbon, nitrogen, and ash concentrations. Using variance estimation, location/cultivar, nitrogen application rate, and year explained 65%–96% of the variation for switchgrass chemical attributes. Location/cultivar × year interaction was a significant factor for all chemical attributes indicating environmental‐based influences. Nitrogen rate was less influential. Production variables and environmental conditions occurring during the switchgrass field trials were used to successfully predict chemical attributes using linear regression models. Upland switchgrass results highlight the complexity in plant responses to growing conditions because all production and environmental variables had strong relationships with one or more chemical attributes. Lowland switchgrass was limited to observations of year‐to‐year environmental variability and nitrogen application rate. All explanatory variable categories were important for lowland switchgrass models but stand age and precipitation relationships were particularly strong. The relationships found in this study can be used to understand spatial and temporal variation in switchgrass chemical attributes. The ability to predict chemical attributes critical for conversion processes in a geospatial/temporal manner would provide state‐of‐the‐art knowledge for risk assessment in the bioenergy and bioproducts industry.

09 BIOMASS FUELS↗
DOE OSTI2025

Exploring the environmental drivers of human blastomycosis cases in the Midwestern United States

Blastomycosis is a fungal infection endemic to the eastern United States (US) and Canada caused by the inhalation of the fungi Blastomyces spp. Currently, the environmental drivers of disease dynamics are poorly understood. The goal of our work was to explore what environmental conditions are associated with the annual presence of blastomycosis cases, and therefore are potentially explanatory of the ecological niche of Blastomyces. We examined the relationships between reported cases of blastomycosis in three Midwestern US states (Michigan, Minnesota, and Wisconsin) from 2007–2017 in relation to eleven hypothesized environmental conditions, including climate, stream and soil mineral content, and land cover variables. Then, we fit logistic regression models to explore the relationships between the environmental variables and yearly blastomycosis case occurrence. Mean soil moisture, stream sediment mercury content, percent of water within the county, and woody wetlands land cover were all positively associated with the presence of annual cases, with woody wetlands having the most consistent signal across the three states. We also found significant differences in the likelihood of case presence between US states that were not explained by the variables in our model, suggesting state-level differences in case reporting and disease awareness. Our results provide a perspective on potential biological hypotheses to further test regarding environmental controls on the life cycle and ecological niche of Blastomyces.

54 ENVIRONMENTAL SCIENCES↗