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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 433 records · Page 24

ARM Data as A Resource for Validation of NASA PACE Cloud Retrievals

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will launch in January 2024 and continue and improve upon satellite data records in its eponymous domains. PACE will carry a broad-swath hyperspectral imager, OCI, which will provide MODIS/VIIRS-type cloud data products (i.e. a cloud mask, top height, visible optical thickness, droplet effective radius, phase, and derived water path). It will also carry two multi-angle polarimeters (HARP2 and SPEXone) which will not only provide the above but also enable retrievals of additional cloud properties (e.g. droplet effective variance, ice crystal asymmetry parameter). Validating satellite-based cloud retrievals is challenging. We plan to use several ARM data streams to evaluate PACE cloud data products and are prototyping our analyses using retrievals from MODIS on the Aqua satellite and OLCI on the Sentinel-3A satellite. This poster shows how we plan to use ARM data to evaluate liquid water path (via MWRRET) and cloud top height retrievals (via KARZASRCL), with example results from these proxy sensors and ARM data from the SGP, ENA, and NSA sites. We seek comments from and collaborations with the ARM community to get the most out of our respective data streams.

ARM↗

Predict ephemeral and perennial range quantity and quality during normal grazing season

The author has identified the following significant results. Collection and update of resource inventory data has historically been a difficult, time consuming task. Accurate resource data is necessary as a basis for wise management decisions made by a resource management agency such as the Bureau of Land Management. Black and white and color infrared composites of ERTS satellite imagery at 1:1,000,000 and enlarged scales can be used as data gathering tools. No investment in expensive sophisticated equipment is necessary. A photointerpreter can map boundaries of soils, plant communities, levels of forage production, areas revegetated by man, and areas burned by wildlife directly from satellite imagery. The ERTS system of producing and distributing imagery must be improved greatly before satellite imagery can be useful to the resource manager.

Bentley, R. G., Jr.↗

Use of LANDSAT data for natural resources investigation in the lower basin of Danube and Danube Delta

The author has identified the following significant results. Monitoring of excess humidity was possible at the Baragan test site. Qualitative improvements of 20-50% were obtained in regards to soil inventory in the eastern Danube Delta, comparing data with conventional maps. The pedological situation was observed after drainage in impounded enclosures. The appearance of stagnate water was surveyed due to difference in color shades on LANDSAT imagery. Areas with gluey soils, such as lake bottoms rich in CaCO3 and shell grist, were clearly represented. Sediment discharges into the sea at the Danube mouth and plumes over 100 km at sea could be easily distinguished on LANDSAT MSS 4 and 5.

Oprescu, N.↗

Resource Management in the Microgravity Science Division

In the Microgravity Science Division, the primary responsibilities of the Business Management Office are resource management and data collection. Resource management involves working with a budget to do a number of specific projects, while data collection involves collecting information such as the status of projects and workforce hours. This summer in the Business Management Office I assisted Margie Allen with resource planning and the implementation of specific microgravity projects. One of the main duties of a Project Control Specialists, such as my mentor, is to monitor and analyze project manager s financial plans. Project managers work from the bottom up to determine how much money their project will cost. They then set up a twelve month operating plan which shows when money will be spent. I assisted my mentor in checking for variances in her data against those of the project managers. In order to successfully check for those variances, we had to understand: where the project is including plans vs. actual performance, why it is in its present condition, and what the future impact will be based on known budgetary parameters. Our objective was to make sure that the plan, or estimated resources input, are a valid reflection of the actual cost. To help with my understanding of the process, over the course of my tenure I had to obtain skills in Microsoft Excel and Microsoft Access.

Casselle, Justine↗

Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Processed Data, Cook Inlet, AK, 2021

This submission contains processed datasets from a long-term deployment of 3 moorings and a transect survey of the proposed tidal energy site off the East Forelands in Cook Inlet, AK. The long-term mooring datasets were created from 8 instruments mounted on a Terrasond High Energy Oceanographic Mooring (THEOM) bottom lander and two Mid-Water Mooring (MWM) Stablemoor buoys from 1 July 2021 to 31 August 2021 (60 days). The west-most mooring (MWM1) was deployed at 60.720225 N, 151.436196 W in ~50 m of water. The middle mooring (THEOM) was deployed at 60.720703 N, 151.429500 W in ~52 m of water. The east-most buoy (MWM2) was deployed at 60.720081 N, 151.420896 W in ~50 m of water. Each Stablemoor carried three instruments: 1. A Nortek Vector acoustic Doppler velocimeter (ADV) mounted at the Stablemoor's nose. Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was motion-corrected using the internal IMU and external ADCP bottom-track data and then bin-averaged into 4 minute bins and converted to the Principal (streamwise, cross-stream, vertical) coordinate system. (Note: 30 seconds were trimmed from the beginning and end of each 5 minute duty cycle to account for the filter end-effects from turning on and turning off the IMU.) 2. A down-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the first Stablemoor instrument well. Data were recorded in 2 Hz with 5-beam burst and bottom-track enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. 3. An up-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the second Stablemoor instrument well. Data were recorded at 4 Hz with 5 beam burst enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. Note: the down-facing ADCP on MWM1 failed on July 10th, 2021, only recording 9 days of data. Because ADV motion-correction required bottom track, the ADV from MWM1 also only has 9 days processed. Additionally, only 25 days of data were processed from the MWM2 ADV because it appeared to have been impacted by debris on 7/25. Two instruments were mounted on the THEOM (see MHKDR link further below for THEOM raw data): 4. A Nortek Vector acoustic Doppler velocimeter (ADV). Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was bin-averaged into 5 minute bins, and converted to the Principal coordinate system. 5. A Nortek Signature 500 kHz acoustic Doppler current profiler (ADCP). Data were recorded in 4 Hz in the beam coordinate system from all 5 beams. Processed data has been averaged into 10 minutes bins and converted to the Principal coordinate system.

16 TIDAL AND WAVE POWER↗

Hawthorne Nevada Deep Direct-Use Feasibility Study - Data Used for Geothermal Resource Conceptual Modeling and Power Capacity Estimates

This data submission includes several data components that were used to develop a conceptual model and power capacity-estimates of two low-temperature geothermal resources that define geothermal prospect A at Hawthorne, Nevada. Data are sourced from a combination of legacy publicly-available data and more recent data acquisition conducted by the US Navy Geothermal Program Office (2008-2013) and the Great Basin Center for Geothermal Energy at the University of Nevada, Reno (2008-2010). Data sets include compiled fluid geochemistry data, down-hole temperature logs for wells in the vicinity of prospect A, 2 meter temperature survey data, temperature-spinner logs acquired in well HWAAD-2A, fracture picks from image log data acquired in wells HWAAD-2 and HWAAD-3, and X-Ray Diffraction (XRD) analyses on cuttings from wells HWAAD-2A and HWAAD-3. These data have been reviewed for errors and inconsistencies, but it is possible that few errors could still remain. The resource conceptual model and power capacity estimates are included in the final report to the US Department of Energy, and are presented in a manuscript by Ayling and Hinz. A link to the manuscript published in Geothermics is linked below in this submission.

15 GEOTHERMAL ENERGY↗

Development of a digital geographic data base for resource planning in a wildland environment

Multiple resource planning requires the ability to access information for several parameters in a coordinated way. Attempts to do this manually, through the use of multiple transparent overlays or similar techniques can become awkward if there are more than a few parameters under consideration. One solution to this problem is to use a computer system to collect and organize the information into a data base that will make access and analysis easier, even for large numbers of parameters. The increase in the types and forms of remote sensing data and the decrease in costs for computer systems in the last decade has made this approach more popular than in the past. This paper describes the development of one such data base for the Big Basin Redwoods State Park in the Santa Cruz Mountains in California. The data base contains information for satellite spectral data, soil type, vegetation type, and hypsographic data and was developed for use in a cooperative project being conducted by personnel from the Remote Sensing Research Program and the California Department of Parks and Recreation

Ritter, P. R.↗

NASA Data for Water Resources Applications

Water Management Applications is one of twelve elements in the Earth Science Enterprise National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of: 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies including the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. This includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being eliminated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems WAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification validation. Water Management Applications is one of twelve elements in the Earth Science Enterprise s National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. T us includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being evaluated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems (LDAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification and validation.

Toll, David↗

Development of the data base for near-Earth resources

Development of the data base for near-Earth resources was begun. Specific items accomplished were: (1) Definition of data base contents via discussions among the PSI staff and outside scientist such as Lucy McFadden and Mark Skyes; (2) Discussion/demonstration of dBase capabilities and possible organization of file(s) with L. Alvarez, Steward Observatory; (3) Data base entries for near-Earth asteroids consisting of data from the Russian ephemeris, a forthcoming review chapter for the Asteroids 2 book, and other literature; and (4) Development of a list of asteroid observers worldwide to be contacted during the coordinated phase of the project. A copy of the data base as it now exists is included.

Davis, D. R.↗

Correlation signatures of wet soils and snows

Interpretation, analysis, and development of algorithms have provided the necessary computational programming tools for soil data processing, data handling and analysis. Algorithms that have been developed thus far, are adequate and have been proven successful for several preliminary and fundamental applications such as software interfacing capabilities, probability distributions, grey level print plotting, contour plotting, isometric data displays, joint probability distributions, boundary mapping, channel registration and ground scene classification. A description of an Earth Resources Flight Data Processor, (ERFDP), which handles and processes earth resources data under a users control is provided.

Phillips, M. R.↗

Simulating competition in the US bioeconomy to produce hard‐to‐electrify transportation fuels using limited biomass resources

This study presents a novel bioeconomy optimization framework, BiOpt, designed to address critical questions regarding the strategic use of limited US biomass resources for biofuel production. By integrating detailed techno-economic analyses, life cycle assessments, and resource assessment data, BiOpt optimizes resource distributions across competing technologies to maximize economic performance and/or minimize greenhouse gas emissions. Using feedstock scenarios from the 2023 Billion Ton Study, the analysis explores optimal biomass allocations across sustainable aviation fuel, diesel, and marine biofuel conversion pathways given varying production targets and policy incentives. Results demonstrate distinct feedstock preferences and pathway utilizations when prioritizing economic returns vs. emissions reductions. For instance, fats, oils, and greases were highly favored in cost-optimized scenarios, while low-carbon feedstocks such as wet waste dominated greenhouse gas-minimized strategies. The findings underscore the pivotal role of policy incentives and technological advances in shaping biofuel supply chains and provide actionable insights for scaling sustainable biofuel production to decarbonize hard-to-electrify sectors. This framework offers a robust tool for policymakers and stakeholders to evaluate biofuel strategies that balance energy output, economic viability, and environmental impact.

09 BIOMASS FUELS↗