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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Advanced Chemical Propulsion Study

A study was performed of advanced chemical propulsion technology application to space science (Code S) missions. The purpose was to begin the process of selecting chemical propulsion technology advancement activities that would provide greatest benefits to Code S missions. Several missions were selected from Code S planning data, and a range of advanced chemical propulsion options was analyzed to assess capabilities and benefits re these missions. Selected beneficial applications were found for higher-performing bipropellants, gelled propellants, and cryogenic propellants. Technology advancement recommendations included cryocoolers and small turbopump engines for cryogenic propellants; space storable propellants such as LOX-hydrazine; and advanced monopropellants. It was noted that fluorine-bearing oxidizers offer performance gains over more benign oxidizers. Potential benefits were observed for gelled propellants that could be allowed to freeze, then thawed for use.

Woodcock, Gordon↗
NASA NTRS1997

Winter and Spring Thaw as Observed with Imaging Radar at BOREAS

In the boreal forest region and for coniferous forest species, the summer frost free period bounds the growing season length (Walter et Breckle 1993). For both coniferous and deciduous trees, their grown potential is further limited by their mineral and water uptake.

BOREARS Thaw Freez Boreal Forest↗
NASA NTRS2006

Effects of Vegetation and of Heat and Vapor Fluxes from Soil on Snowpack Evolution and Radiobrightness

The radiobrightness of a snowpack is strongly linked to the snow moisture content profile, to the point that the only operational inversion algorithms require dry snow. Forward dynamic models do not include the effects of freezing and thawing of the soil beneath the snowpack and the effect of vegetation within the snow or above the snow. To get a more realistic description of the evolution of the snowpack, we reported an addition to the Snow-Soil-Vegetation-Atmosphere- Transfer (SSVAT) model, wherein we coupled soil processes of the Land Surface Process (LSP) model with the snow model SNTHERM. In the near future we will be adding a radiobrightness prediction based on the modeled moisture, temperature and snow grain size profiles. The initial investigations with this SSVAT for a late winter and early spring snow pack indicate that soil processes warm the snowpack and the soil. Vapor diffusion needs to be considered whenever the ground is thawed. In the early spring, heat flow from the ground into a snow and a strong temperature gradient across the snow lead to thermal convection. The buried vegetation can be ignored for a late winter snow pack. The warmer surface snow temperature will affect radiobrightness since it is most sensitive to snow surface characteristics. Comparison to data shows that SSVAT provides a more realistic representation of the temperature and moisture profiles in the snowpack and its underlying soil than SNTHERM. The radiobrightness module will be optimized for the prediction of brightness when the snow is moist. The liquid water content of snow causes considerable absorption compared to dry snow, and so longer wavelengths are likely to be most revealing as to the state of a moist snowpack. For volumetric moisture contents below about 7% (the pendular regime), the water forms rings around the contact points between snow grains. Electrostatic modeling of these pendular rings shows that the absorption of these rings is significantly higher than a sphere of the same volume. The first implementation of the radiobrightness module will therefore be a simple radiative transfer model without scattering.

soil↗
NASA NTRS2004

The HYDROS Radiometer/Radar Instrument

The science objectives of the HYDROS mission are to provide frequent, global measurements of surface soil moisture and surface freeze/thaw state. In order to adequately measure these geophysical quantities, the key instrument requirements were determined by the HYDROS science team to be: 1) Dual-polarization L-Band passive radiometer measurements at 40 km resolution, 2) Dual-polarization L-Band active radar measurements at 3 km resolution, and 3) A wide swath to insure global three day refresh time for these measurements (1000 km swath at the selected orbit altitude of 670 km). As a solution to this challenging set of instrument requirements, a relatively large, 6 meter, conically-scanning reflector antenna architecture was selected for the instrument design. The deployable mesh antenna is shared by both the radiometer and radar electronics by employing a single L-Band feed.

freeze thaw↗
NASA NTRS2008

GFSSP Training Course Lectures

GFSSP has been extended to model conjugate heat transfer Fluid Solid Network Elements include: a) Fluid nodes and Flow Branches; b) Solid Nodes and Ambient Nodes; c) Conductors connecting Fluid-Solid, Solid-Solid and Solid-Ambient Nodes. Heat Conduction Equations are solved simultaneously with Fluid Conservation Equations for Mass, Momentum, Energy and Equation of State. The extended code was verified by comparing with analytical solution for simple conduction-convection problem The code was applied to model: a) Pressurization of Cryogenic Tank; b) Freezing and Thawing of Metal; c) Chilldown of Cryogenic Transfer Line; d) Boil-off from Cryogenic Tank.

Majumdar, Alok K.↗
NASA NTRS2006

Integrated System for Autonomous Science

The New Millennium Program Space Technology 6 Project Autonomous Sciencecraft software implements an integrated system for autonomous planning and execution of scientific, engineering, and spacecraft-coordination actions. A prior version of this software was reported in "The TechSat 21 Autonomous Sciencecraft Experiment" (NPO-30784), NASA Tech Briefs, Vol. 28, No. 3 (March 2004), page 33. This software is now in continuous use aboard the Earth Orbiter 1 (EO-1) spacecraft mission and is being adapted for use in the Mars Odyssey and Mars Exploration Rovers missions. This software enables EO-1 to detect and respond to such events of scientific interest as volcanic activity, flooding, and freezing and thawing of water. It uses classification algorithms to analyze imagery onboard to detect changes, including events of scientific interest. Detection of such events triggers acquisition of follow-up imagery. The mission-planning component of the software develops a response plan that accounts for visibility of targets and operational constraints. The plan is then executed under control by a task-execution component of the software that is capable of responding to anomalies.

Chien, Steve↗
NASA NTRS2010

Freezable Radiator Model Correlation and Full Scale Design

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the space craft s surroundings and because of different thermal loads during different mission phases. However, freezing and thawing (recovering) a radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. This paper summarizes efforts made to correlate a Thermal Desktop (TM) model with empirical testing data from two test articles. A 50-50 mixture of DowFrost HD and water is used as the working fluid. Efforts to scale this model to a full scale design, as well as efforts to characterize various thermal control fluids at low temperatures are also discussed.

Lillibridge, Sean T.↗
NASA NTRS2009

Preliminary Evaluation of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

The Air Force Weather Agency (AFWA) - NASA (ANSA) blended-snow product utilizes EOS standard snow products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE. with SWE values calculated from snow depths reported at approx.1500 National Climatic Data Center (NCDC) coop stations in the Lower Great Lakes basin. Our preliminary results show that conversion of snow depth to SWE is very sensitive to the choice of snow density (we used either 0.2 or 03 as conversion factors). We found overall better agreement between the ANSA-derived SWE and the co-op station data when we use a snow density of 0.3 to convert the snow depths to SWE. In addition, we show that the ANSA underestimates SWE in densely-forested areas, using January and February 2008 ANSA and co-op data. Furthermore, apparent large SWE changes from one day to the next may be caused by thaw-re-freeze events, and do not always represent a real change in SWE. In the near future we will continue the analysis in the 2006-07 and 2007-08 snow seasons.

Hall, Dorothy K.↗
NASA NTRS2011

Freezable Radiator Model Correlation Improvements and Fluids Study

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the space craft s surroundings and because of different thermal rejection requirements during different mission phases. However, freezing and thawing (recovering) a radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. To attempt to improve this, tests were conducted in 2009 to determine whether the behavior of a simple stagnating radiator could be predicted or emulated in a Thermal Desktop(trademark) numerical model. A 50-50 mixture of DowFrost HD and water was used as the working fluid. Efforts to scale this model to a full scale design, as well as efforts to characterize various thermal control fluids at low temperatures are also discussed. Previous testing and modeling efforts showed that freezable radiators could be operated as intended, and be fairly, if not perfectly predicted by numerical models. This paper documents the improvements made to the numerical model, and outcomes of fluid studies that were determined necessary to go forward with further radiator testing.

Lillibridge, Sean↗
NASA NTRS2004

Improved Method of Purifying Carbon Nanotubes

An improved method of removing the residues of fabrication from carbon nanotubes has been invented. These residues comprise amorphous carbon and metal particles that are produced during the growth process. Prior methods of removing the residues include a variety of processes that involved the use of halogens, oxygen, or air in both thermal and plasma processes. Each of the prior methods entails one or more disadvantages, including non-selectivity (removal or damage of nanotubes in addition to removal of the residues), the need to dispose of toxic wastes, and/or processing times as long as 24 hours or more. In contrast, the process described here does not include the use of toxic chemicals, the generation of toxic wastes, causes little or no damage to the carbon nanotubes, and involves processing times of less than 1 hour. In the improved method, purification is accomplished by flowing water vapor through the reaction chamber at elevated temperatures and ambient pressures. The impurities are converted to gaseous waste products by the selective hydrogenation and hydroxylation by the water in a reaction chamber. This process could be performed either immediately after growth or in a post-growth purification process. The water used needs to be substantially free of oxygen and can be obtained by a repeated freeze-pump-thaw process. The presence of oxygen will non-selectively attach the carbon nanotubes in addition to the amorphous carbon.

Delzeit, Lance D.↗
NASA NTRS2011

Six-Tube Freezable Radiator Testing and Model Correlation

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recovering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TradeMark) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested, namely MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Lillibridge, Sean↗
NASA NTRS2012

Six-Tube Freezable Radiator Testing and Model Correlation

Freezable Radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft?s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recov ering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TM) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested: MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Lilibridge, Sean T.↗
NASA NTRS2011

The NASA Soil Moisture Active Passive (SMAP) Mission Formulation

The Soil Moisture Active Passive (SMAP) mission is one of the first-tier projects recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission is in formulation phase and it is scheduled for launch in 2014. The SMAP mission is designed to produce high-resolution and accurate global mapping of soil moisture and its freeze/thaw state using an instrument architecture that incorporates an L-band (1.26 GHz) radar and an L-band (1.41 GHz) radiometer. The simultaneous radar and radiometer measurements will be combined to derive global soil moisture mapping at 9 [km] resolution with a 2 to 3 days revisit and 0.04 [cm3 cm-3] (1 sigma) soil water content accuracy. The radar measurements also allow the binary detection of surface freeze/thaw state. The project science goals address in water, energy and carbon cycle science as well as provide improved capabilities in natural hazards applications.

microwave↗
NASA NTRS2016

SLAPex Freeze/Thaw 2015: The First Dedicated Soil Freeze/Thaw Airborne Campaign

Soil freezing and thawing is an important process in the terrestrial water, energy, and carbon cycles, marking the change between two very different hydraulic, thermal, and biological regimes. NASA's Soil Moisture Active/Passive (SMAP) mission includes a binary freeze/thaw data product. While there have been ground-based remote sensing field measurements observing soil freeze/thaw at the point scale, and airborne campaigns that observed some frozen soil areas (e.g., BOREAS), the recently-completed SLAPex Freeze/Thaw (F/T) campaign is the first airborne campaign dedicated solely to observing frozen/thawed soil with both passive and active microwave sensors and dedicated ground truth, in order to enable detailed process-level exploration of the remote sensing signatures and in situ soil conditions. SLAPex F/T utilized the Scanning L-band Active/Passive (SLAP) instrument, an airborne simulator of SMAP developed at NASA's Goddard Space Flight Center, and was conducted near Winnipeg, Manitoba, Canada, in October/November, 2015. Future soil moisture missions are also expected to include soil freeze/thaw products, and the loss of the radar on SMAP means that airborne radar-radiometer observations like those that SLAP provides are unique assets for freeze/thaw algorithm development. This paper will present an overview of SLAPex F/T, including descriptions of the site, airborne and ground-based remote sensing, ground truth, as well as preliminary results.

BOREAS↗
NASA NTRS2016

Instrumentation for Examining Microbial Response to Changes In Environmental Pressures

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to selection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation.The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber.Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations.

Environment↗
NASA NTRSDate not supplied

HydroSAR: A Cloud-based SAR Data Analysis Service to Monitor Hydrological Disasters and their Impact on Population and Agriculture

Weather-related hazards are ubiquitous around the world including: 1) hurricane storm surges, 2) rapid snowmelt and heavy rainfall, 3) severe weather leading to flash floods, and 4) seasonal freeze and thaw of rivers that may lead to ice jams. Each of these hazards affects human settlements and has the potential to impact agricultural productivity. In each setting, end-users in disaster management need access to data processing tools helpful in mapping past and current disasters. Analysis of past events supports risk mitigation by understanding what has already occurred and how to alleviate those impacts in the future. Having capabilities to generate the same products in a response setting means that lessons learned from risk analysis will carry forward to event response. Synthetic aperture radar (SAR) data are particularly useful for these activities due to their all-weather 24/7 monitoring capabilities. In this effort we present HydroSAR, a cloud-based SAR data analysis service for the mapping of meteorological and hydrological disasters as well as their impact on population and agriculture. As part of this project we have developed a series of SAR-based value added products for the monitoring of surface hydrology (image time series, change detection, flood extent, flood depth) and the assessment of impacts on population (flood depth) and agriculture (active agriculture, inundated agriculture, flood duration). We also developed a cloud-based platform for generating these products over affected areas and are working with end-users to integrate derived product into decision-making workflows The paper will briefly introduce the SAR-based products that were developed for this effort. We describe the cloud-based production pipeline that was built to automatically generate these products in near-real time over extended regions. The integration of SAR-based information into hazard preparation and response activities is described for a number of recent disasters including the 2019 forest fires in Alaska, 2019 flooding in the U.S. Midwest, the 2020 U.S. severe weather easter outbreak, 2020 tropical storm Christobal, 2020 cyclone Amphan, 2020, Alaska Spring breakup flooding, and the 2020 flood season in Eastern India, Bangladesh, and Nepal.

Franz Josef Meyer↗
NASA NTRS2022

A New Snow Module Improves Predictions of the Isotope-Enabled MAIDENiso Forest Growth Model

The representation of snow processes in forest growth models is necessary to accurately predict the hydrological cycle in boreal ecosystems and the isotopic signature of soil water extracted by trees, photosynthates and tree-ring cellulose. Yet, most process-based models do not include a snow module; consequently, their simulations may be biased in cold environments. Here, we modified the MAIDENiso model to incorporate a new snow module that simulates snow accumulation, melting and sublimation, as well as thermal exchanges driving freezing and thawing of the snow and the soil. We tested these implementations in two sites in eastern and western Canada for black spruce (Picea mariana (Mill.) B.S.P.) and white spruce (Picea glauca (Moench) Voss) forests, respectively. The new snow module improves the skills of the model to predict components of the hydrological cycle. The MAIDENiso model is now able to reproduce the spring discharge peak and to simulate stable oxygen isotopes in tree-ring cellulose more realistically than in the original snow-free version of the model. The new implementation also results in simulations with a higher contribution from the source water on the oxygen isotopic composition of the simulated cellulose, leading to more accurate estimates of cellulose isotopic composition. Future work may include the development of inverse modelling with this new version of MAIDENiso to produce robust reconstructions of the hydrological cycle and isotope processes in cold environments.

Snow processes↗