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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 OSTI2024

Scaling Individual Tree Transpiration With Thermal Cameras Reveals Interspecies Differences to Drought Vulnerability

Abstract Understanding tree transpiration variability is vital for assessing ecosystem water‐use efficiency and forest health amid climate change, yet most landscape‐level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard Forest and Niwot Ridge. PT‐JPL model was used to derive latent heat flux from thermal images at the canopy‐level, showing strong agreement with tower measurements ( R 2 = 0.70–0.96 at Niwot, 0.59–0.78 at Harvard at half‐hourly to monthly scales) and daily RMSE of 33.5 W/m 2 (Niwot) and 52.8 W/m 2 (Harvard). Tree‐level analysis revealed species‐specific responses to drought, with lodgepole pine exhibiting greater tolerance than Engelmann spruce at Niwot and red oak showing heightened resistance than red maple at Harvard. These findings show how ecophysiological differences between species result in varying responses to drought and demonstrate that these responses can be characterized by deriving transpiration from crown temperature measurements.

Javadian, Mostafa↗
NASA NTRS1975

Passenger comfort response times as a function of aircraft motion

The relationship between a passenger's response time of changes in level of comfort experienced as a function of aircraft motion was examined. The aircraft used in this investigation was capable of providing a wide range of vertical and transverse accelerations by means of direct lift flap control surfaces and side force generator surfaces in addition to normal control surfaces. Response times to changes in comfort were recorded along with the passenger's rating of comfort on a five point scale. In addition, a number of aircraft motion variables including vertical and transverse accelerations were also recorded. Results indicate some relationship between human comfort response times to reaction time data.

Rinalducci, E. J.↗
NASA NTRS1984

Description of sunspot cycles by orthogonal functions

Based on the principal component analysis technique and evidence for a 22-yr double-sunspot cycle periodicity. The time series of sunspot numbers is represented as a sum of mutually orthogonal eigenvectors in the time domain. It is shown that the first two eigenvectors account for about 90 percent of the cumulative 'signal power,' and that this is sufficient for reconstruction of the raw data curve. It is also noted that the second eigenvector behaves as the time derivative of the first, and that a phase-plane plot of these eigenvectors (i.e. a plot of a variable vs. its rate of change) suggests that the sun's sunspot cycle is driven by an oscillator; the implication is that, embedded within the sun, a chronometer is at work (e.g. Dicke, 1979).

Teuber, D. L.↗
NASA NTRS1990

A model for the production of cosmogenic nuclides in chondrites

A model is presented for calculating the production rates of cosmic-ray-produced He, Ne, and Ar as well as Be-10, Al-26, and Mn-53 in chondrites of variable size and shape. The predictions of this model are compared with published data for the meteorites ALH78084, St. Severin, and Keyes. The agreement is found to be about 5 percent for the concentrations of Be-10, Ne-21, Ne-22, Ar-38, and Mn-53, and to be better than 1 percent for the Ne-22/Ne-21 ratios. The correlation between P(Be-10)/P(Ne-21) and Ne-22/Ne-21 ratios is experimentally verified over a wide range of irradiation conditions.

Graf, TH.↗
NASA NTRS2002

Science Goal Driven Observing: A Step Towards Maximizing Science Returns and Spacecraft Autonomy

While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. Also, the new generation of space-based telescopes will generate data at an unprecedented rate. Yet, while on-board data processing and storage capability will increase rapidly, bandwidth for downloading data will not increase as fast and can become a significant cost of a science program. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will not meet the science goals, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the observatory can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download them at a reduced resolution its overall efficiency will be dramatically increased. We are investigating and developing tools for a science goal monitoring (SGM) system. The SGM will have an interface to help capture higher-level science goals from the scientists and translate them into a flexible observing strategy that SGM can execute and monitor. SGM will then monitor the incoming data stream and interface with data processing systems to recognize significant events. When an event occurs, the system will use the science goals given it to reprioritize observations, and react appropriately and/or communicate with ground systems - both human and machine - for confirmation and/or further high priority analyses.

Jones, Jeremy↗
NASA NTRS2002

Science Goal Driven Observing: A Step Towards Maximizing Science Returns and Spacecraft Autonomy

In the coming decade, the drive to increase the scientific returns on capital investment and to reduce costs will force automation to be implemented in many of the scientific tasks that have traditionally been manually overseen. Thus, spacecraft autonomy will become an even greater part of mission operations. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. The new generation of space-based telescopes/observatories will see deeper, with greater clarity, and they will generate data at an unprecedented rate. Yet, while onboard data processing and storage capability will increase rapidly, bandwidth for downloading data will not increase as fast and can become a significant bottleneck and cost of a science program. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will not meet the science goals of variability or minimum brightness, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the observatory can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download them at a reduced resolution its overall efficiency will be dramatically increased. We are investigating and developing tools for a science goal monitoring (SGM) system. The SGM will have an interface to help capture higher-level science goals from scientists and translate them into a flexible observing strategy that SGM can execute and monitor. SGM will then monitor the incoming data stream and interface with data processing systems to recognize significant events. When an event occurs, the system will use the science goals given it to reprioritize observations, and react appropriately and/or communicate with ground systems - both human and machine - for confirmation and/or further high priority analyses.

Koratkar, Anuradha↗
NASA NTRS2018

Using Concurrent Cardiovascular Information to Augment Survival Time Data for Evaluating Orthostatic Tilt Test Performance

Head-up tilt (HUT) tests often are used in research to measure orthostatic intolerance (OI) (inability to appropriately control blood pressure while upright) in clinical populations and otherwise healthy individuals after interventions. Post-space flight orthostatic intolerance is a well-known phenomenon, and countermeasures to its development has been an active area of research at NASA. In the NASA HUT protocol, subjects lie horizontally on an automatic tilt table for baseline measurements before being raised to 80deg head-up tilt for a defined period of time or until signs or symptoms of presyncope ensues (light-headedness, nausea, dizziness, sweating, weakness or fainting). Multiple measures are collected to evaluate the cardiovascular system's ability to respond appropriately to the orthostatic challenge. However if the intended duration of the HUT is short, the ability to detect changes in OI due to an intervention or its prevention by a countermeasure may be limited by a small number of failures to permit comparisons based on survival time alone. Thus, the time-trajectory of the cardiovascular data becomes an important additional source of information. In particular, we will show how various measures of trajectory variability can effectively augment survival analysis for the assessment of OI in a joint model when high censoring rates are present.

Feiveson, Alan H.↗
NASA NTRS2019

A Multidisciplinary Modeling Approach of Plant Gas Exchange in Reduced Gravity Environments

In-situ food production is a necessary step for human exploration of the solar system and requires a deep understanding of plant growth in reduced gravity environments. In particular, the lack of buoyancy-driven convection changes the gas exchange at the leaf surface, which decreases photosynthesis and transpiration rates, and ultimately biomass production. To understand the intricate relations between physical, chemical, and biochemical processes, the following methodology combines the development of a mechanistic model of plant growth in reduced gravity environments, computational fluid dynamics (CFD) simulations, and experiments in different time frames.The model presented here is a coupled mass and energy balance using the single round leaf assumption, including gravity as an entry parameter, and the leaf surface temperature as an output variable. Measures of the leaf surface temperature using infra-red cameras allow for a computation of the transpiration rate. This approach was followed to design a parabolic flight experiment, which performed 7 flights, and enabled data collection for model validation in different gravity and ventilation settings on a short time frame. Current measures of carbon assimilation and transpiration rate at the leaf and canopy level using an infra-red gas analyzer (Li-6800) in 1g lab conditions on several species will enable a validation on longer time frames and further calibration of the model. CFD studies both on the parabolic flight and on the lab experimental set-up allow the precise assessment of ventilation above the canopy and plants' leaves.Ultimately, this work will provide recommendations for the design of future plant growth hardware, especially on the lowest adequate ventilation for optimal plant growth in reduced gravity environments, as well as assessing biomass and oxygen production rates on planetary surfaces and space stations. This work was funded by CNES, CNRS, Clermont Auvergne Metropole, and NASA Space Biology through NASA postdoctoral program / USRA.

Poulet, Lucie↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
NASA NTRS2021

Data-driven landslide nowcasting at the global scale

Landslides affect nearly every country in the world each year. To better understand this global hazard, the Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed previously. LHASA version 1 combines satellite precipitation estimates with a global landslide susceptibility map to produce a gridded map of potentially hazardous areas from 60° North-South every 3 h. LHASA version 1 categorizes the world’s land surface into three ratings: high, moderate, and low hazard with a single decision tree that first determines if the last seven days of rainfall were intense, then evaluates landslide susceptibility. LHASA version 2 has been developed with a data-driven approach. The global susceptibility map was replaced with a collection of explanatory variables, and two new dynamically varying quantities were added: snow and soil moisture. Along with antecedent rainfall, these variables modulated the response to current daily rainfall. In addition, the Global Landslide Catalog (GLC) was supplemented with several inventories of rainfall-triggered landslide events. These factors were incorporated into the machine-learning framework XGBoost, which was trained to predict the presence or absence of landslides over the period 2015–2018, with the years 2019–2020 reserved for model evaluation. As a result of these improvements, the new global landslide nowcast was twice as likely to predict the occurrence of historical landslides as LHASA version 1, given the same global false positive rate. Furthermore, the shift to probabilistic outputs allows users to directly manage the trade-off between false negatives and false positives, which should make the nowcast useful for a greater variety of geographic settings and applications. In a retrospective analysis, the trained model ran over a global domain for 5 years, and results for LHASA version 1 and version 2 were compared. Due to the importance of rainfall and faults in LHASA version 2, nowcasts would be issued more frequently in some tropical countries, such as Colombia and Papua New Guinea; at the same time, the new version placed less emphasis on arid regions and areas far from the Pacific Rim. LHASA version 2 provides a nearly real-time view of global landslide hazard for a variety of stakeholders.

XGBoos↗
NASA NTRS1999

Interpreting Aircraft-Derived Ice Sheet Elevation Change Using Climate Station Data

This year repeat elevation surveys in the southern half of Greenland were made using the Airborne Topographic Mapper (ATM). The intent of these surveys is to compare present elevations to those measured in 1993 and determine the magnitude and spatial distributions of thickening and thinning rates. In order to effectively interpret any observed changes, it is important to understand the processes that affect these changes. Moreover, because the surveys are made over a brief period (2-4 weeks) during the spring or summer, it is also important to understand the effects of seasonal and interannual elevation variability, in relation to the timing of these surveys. Toward that end we are examining data from weather stations along the coast of Greenland along with data from GC-Net automatic weather stations (AWS's) on the ice sheet. The objectives are to assess: a) the importance of the timing of the flights in relation to natural processes that affect surface heights, namely accumulation and melt, and b) the temperature characteristics of the region in the five years that separated the two sets of surveys (1993-1998), in relation to the past 19 years.

Abdalati, Waleed↗
NASA NTRS2012

Seismic Rate Changes Associated with Seasonal, Annual, and Decadal Changes in the Cryosphere

Near the Bering Glacier Global Fiducial site in southern Alaska large cryospheric fluctuations occur in a region of upper crustal faulting and folding associated with collision and accretion of the Yakutat terrane. In this study we report constraints on seasonal, annual and decadal cryospheric changes estimated over the last decade from field, aircraft and satellite measurements, and we evaluate the influence of cryospheric changes on the background seismic rate. Multi-year images from the Bering Glacier global fiducial site are available since mid-2003 to constrain changes in extent of the Bering Glacier and to discern feature changes in the glacial surface. Starting around the same time, satellite gravimetric measurements from the Gravity Recovery and Climate experiment (GRACE) commenced. Large spatial-scale mass change calculated from the GRACE 1deg x 1deg mascon solution of Luthcke et al. [2012] indicate a general trend of annual ice mass loss for southern Alaska but with large, variable seasonal mass fluctuations. Since 2007, the station position of a continuous GPS site near Cape Yakataga (Alaska EarthScope PBO site, AB35) has been available as well. In addition to changes in the geodetic position due to tectonic motion, this GPS station shows large seasonal excursions in the detrended vertical and horizontal position components consistent with snow loading in the fall and winter and melt onset/mass decrease in the spring/summer. To better understand the timing of processes responsible for the onset of cryospheric mass loss documented in the GRACE data, we examined changes in the snow cover extent and the onset of melt in the spring. We calculated the surface displacements of the solid Earth and theoretical earthquake failure criteria associated with these annual and seasonal ice and snow changes using layered elastic half-space. Additionally, we compared the seismic rate (M>1.8) from a reference background time period against other time periods with variable ice or tectonic change characteristics to test the significance of seismic rate changes. Our earlier results suggest statistically significant changes in the background seismic rate associated with large seasonal mass changes. INDEX

Sauber-Rosenberg, Jeanne↗
DOE OSTI2026

Opportunities for bioenergy crops to support transitions from irrigated agriculture and conserve the U.S. High Plains Aquifer

This study investigates potential economic and groundwater driven transitions from irrigated maize production—the dominant irrigated cropping system in the High Plains Aquifer (HPA) region—to alternative crops such as sorghum and switchgrass, two common bioenergy feedstocks. Unsustainable groundwater extraction in the U.S. High Plains presents critical challenges including reduced irrigation capacities, diminished crop yields, lower land values, and escalating energy costs. Using a spatially explicit optimization framework combined with comprehensive economic and hydrogeological data, we evaluate optimal land-use strategies and irrigation system investments over a 30-year planning period. Results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions. Nebraska and parts of northern Texas can sustain irrigated maize profitability due to relatively favorable groundwater conditions and lower land rents, respectively. In contrast, many portions of Kansas and southern Texas are more likely to transition to dryland agriculture within two decades. Colorado and New Mexico show potential for significant adoption of switchgrass production as an alternative biomass-based energy crop. Overall, over the 30-year horizon, our model implies that approximately 23% of currently irrigated maize area across the HPA region may transition to dryland farming under business-as-usual conditions. This transition is complemented by a threefold increase in non-irrigated sorghum production, from 0.20 to 0.77 Mt yr−1, indicating that groundwater-driven shifts in agricultural production may support a larger regional base for bioenergy feedstocks. The study also reveals opportunities for producers to optimize economic returns and biomass production potential.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1972

Liquid propellant thermal conditioning system test program

Results are presented from more than 1500 hours of testing on a liquid hydrogen thermal conditioning unit. Test parameters included: mixer and vent flow rates; tank size; ullage volume; pressurant gas; pressurant temperature; pressure level; and heat rate. Gaseous hydrogen and helium were used as pressurants. Analytical models were developed to correlate the test data and relate the performance to that anticipated in zero gravity. Experimental and theoretical results are presented which relate the variables controlling vapor condensation at a moving interface.

Bullard, B. R.↗
NASA NTRS1985

Experimental aerodynamic heating to simulated space shuttle tiles in laminar and turbulent boundary layers with variable flow angles at a nominal Mach number of 7

The heat transfer to simulated shuttle thermal protection system tiles was investigated experimentally by using a highly instrumented metallic thin wall tile arranged with other metal tiles in a staggered tile array. Cold wall heating rate data for laminar and turbulent flow were obtained in the Langley 8 foot high Temperature Tunnel at a nominal Mach number of 7, a nominal total temperature of 3300R, a free stream unit Reynolds number from 3.4 x 10 sup 5 to 2.2 10 sup 6 per foot, and a free stream dynamic pressure from 2.1 to 9.0 psia. Experimental data are presented to illustrate the effects of flow angularity and gap width on both local peak heating and overall heating loads. For the conditions of the present study, the results show that localized and total heating are sensitive to changes in flow angle only for the test conditions of turbulent boundary layer flow with high kinetic energy and that a flow angle from 30 deg to 50 deg will minimize the local heating.

Avery, D. E.↗
NASA NTRS1994

The selective use of functional optical variables in the control of forward speed

Previous work on the perception and control of simulated vehicle speed has examined the contributions of optical flow rate (angular visual speed) and texture, or edge rate (frequency of passing terrain objects or markings) on the perception and control of forward speed. However, these studies have not examined the ability to selectively use edge rate or flow rate. The two studies presented here show that this ability is far greater for pilots than non-pilots, as would be expected since pilots must control vehicular speed over a variety of altitudes where flow rates change independently of forward speed. These studies also show that this ability to selectively use these variables is linked to the visual contextual information about the relative validity (linkage with speed) of the two variables. Subjective judgment data also indicated that awareness of altitude and ground texture density did not mediate ground speed awareness.

Johnson, Walter W.↗
NASA NTRS1997

Prediction of Crack Growth under Variable-Amplitude Loading in Thin-Sheet 2024-T3 Aluminum Alloys

The present paper is concerned with the application of a "plasticity-induced" crack closure model to study fatigue crack growth under various load histories. The model was based on the Dugdale model but modified to leave plastically deformed material in the wake of the advancing crack. The model was used to correlate crack growth rates under constant-amplitude loading and then used to predict crack growth under variable-amplitude and spectrum loading on thin-sheet 2024- T3 aluminum alloys. Predicted crack-opening stresses agreed well with test data from the literature. The crack-growth lives agreed within a factor of two for single and repeated spike overloads/underloads and within 20 percent for spectrum loading. Differences were attributed to fretting-product-debris-induced closure and three-dimensional affects not included in the model.

Newman, J. C., Jr.↗
NASA NTRSDate not supplied

GeoNEX-ML: A Machine Learning System for Geostationary Satellite Imagery

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), Himawari-8/9 (JAXA), and GK-2A (Korea), we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary satellites↗