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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Sporadic Groundwater Upwelling in Deep Martian Craters: Evidence for Lacustrine Clays and Carbonates

While the surface of Mars may have had an active hydrosphere early in its history [1], it is likely that this water retreated to the subsurface early on due to loss of the magnetic field and early atmosphere [2]. This likely resulted in the formation of two distinct aqueous regimes for Mars from the Late Noachian onward: one dominated by redistribution of surface ice and occasional melting of snow/ice [3], and one dominated by groundwater activity [4]. The excavation of alteration minerals from deep in the crust by impact craters points to an active, ancient, deep hydrothermal system [5]. Putative sapping features [6] may occur where the groundwater breached the surface. Upwelling groundwater may also have played a critical role in the formation of massive, layered, cemented sediments in Sinus Meridiani [7,8], in the Valles Marineris [9], and possibly in Gale Crater [10], where the Curiosity Rover will land later this year. Understanding the past distribution, geochemistry, and significance of groundwater on Mars is critical to untangling the origins of deep alteration minerals, Hesperian sulfate deposits, and crater fill deposits at Gale Crater or in other locations.

Michalski, J. R.↗
DOE OSTI2022

Convolutional neural networks for intra-hour solar forecasting based on sky image sequences

Accurate and timely solar forecasts play an increasingly critical role in power systems. Compared to longer forecasting timescales, very short-term solar forecasting has lagged behind in both research and practice. In this paper, we propose deep convolutional neural networks (CNNs) to provide operational intra-hour (10-minute-ahead to 60-minute-ahead) solar forecasts. We develop two CNN structures inspired by a widely-used CNN architecture. The CNNs are tailored to our solar forecasting regression tasks and rely solely on sky image sequences. Case studies based on six years of data (over 150,000 data points) demonstrate that the best CNN model has forecast skill scores of 20%-39% over the naive persistence of cloudiness benchmark, even at these very short timescales. The CNNs also have consistently superior performance when compared to shallow machine learning models with meteorological predictors, where the improvement averages around 7%. The sensitivity analyses show that the sky image length, resolution, and weather conditions have impacts on the deep learning model accuracy. In our intra-hour problem with specific setups, two sky images with a 10-minute 128 x 128 resolution yield the most accurate forecasts. Current limitations, future work, and deployment challenges and solutions are also discussed.

14 SOLAR ENERGY↗
DOE OSTI2025

SeisLearn

Understanding data amount impact on seismic deep learning

Myren, Samuel↗
NASA NTRS1973

Conjectures about the evolution of the moon.

The principal questions about the derivation of the lunar surface have not yet been settled: is it the surface left over from the process of accumulation of the moon, or is it a surface generated by magmatic processes on the moon and subsequently altered by further infall from outside. The evidence derived from many sources now favors the former. Seismic data suggest an absence of bedrock down to a depth of several kilometers, and instead a compacted powder only. The 'mascon' evidence can be understood as a consequence of major impacts in a deep porous layer. The great abundance of cosmic ray tracks in most soil samples demands a much greater cosmic ray dosage than present rates would cause in the age of the moon, unless the dust represented infallen material previously irradiated.

Gold, T.↗
NASA NTRS1980

Shallow moonquakes - How they compare with earthquakes

Of three types of moonquakes strong enough to be detectable at large distances - deep moonquakes, meteoroid impacts and shallow moonquakes - only shallow moonquakes are similar in nature to earthquakes. A comparison of various characteristics of moonquakes with those of earthquakes indeed shows a remarkable similarity between shallow moonquakes and intraplate earthquakes: (1) their occurrences are not controlled by tides; (2) they appear to occur in locations where there is evidence of structural weaknesses; (3) the relative abundances of small and large quakes (b-values) are similar, suggesting similar mechanisms; and (4) even the levels of activity may be close. The shallow moonquakes may be quite comparable in nature to intraplate earthquakes, and they may be of similar origin.

Nakamura, Y.↗
NASA NTRS1982

Correction of lunar seismograms for instrumental and near-surface effects and constraints on the velocity structure of the lunar interior

Long-period lunar seismograms were studied with the aim of identifying consistent sets of direct shear and secondary wave arrivals, thus constraining the velocities in the lunar mantle and the depths of the velocity discontinuities. Two velocity models were used to locate the natural impacts and the shallow moonquakes and to obtain the travel time residuals. Seismic sections were made of the radial, transverse, and vertical components of ground motion for impacts, shallow, and deep moonquakes in order to search for consistent sets of secondary wave arrivals. No conclusive set of secondary arrivals could be recognized on the seismic sections and thus the velocities and depths of the velocity discontinuities cannot be severely constrained by secondary arrivals. It is likely that the crust is thinner than 50 km and that a first-order discontinuity separates the upper and lower crust at a depth of between 20 and 30 km.

Horvath, P.↗
NASA NTRS2004

Environmental Test Program for the Mars Exploration Rover Project

On June 10 and July 7, 2003 the National Aeronautics and Space Administration (NASA) launched two spacecraft from Cape Canaveral, Florida for a six (6) months flight to the Red Planet, Mars. The two Mars Exploration Rover spacecraft landed safely on the planet in January 2004. Prior to the successful launch, both of the spacecraft were involved in a comprehensive test campaign that included development, qualification, and protoflight test programs. Testing was performed to simulate the environments associated with launch, inter-planetary cruise, landing on the planet and Mars surface operations. Unique test requirements included operating the spacecraft while the chamber pressure was controlled to simulate the decent to the planet from deep space, high impact landing loads and rover operations on the surface of the planet at 8 Torr and -130 C. This paper will present an overview of the test program that included vibration, pyro-shock, landing loads, acoustic noise, thermal vacuum and solar simulation testing at the Jet Propulsion Laboratory (JPL) Environmental Test Laboratory facilities in Pasadena, California.

Fisher, Terry C.↗
NASA NTRS2021

Regolith Adaptive Modification Systems (Rams) - Final Report

Establishing human habitation on the Moon or Mars requires a palette of reaction chemistries for deconstructing extraterrestrial soils to extract structural metals, fuels, and propellants, as well as consolidating the soils into load-bearing forms. This report outlines progress related to the fundamental chemistry of in-situ resource utilization that is the focus of our Regolith Adaptive Modification System (RAMS) NIAC project. The RAMS concept is a breakthrough approach for preparing surfaces for early landing sites–and subsequent settlement operations–on the Lunar and Martian surface, among others. The RAMS concept is aligned with aspirations and capabilities of planned NASA Artemis mission. The approach is predicated on the sequential delivery of microcapsules onto lunar and Martian surfaces, which upon rupture, release payloads that react with regolith to yield geopolymerized subsurface slabs and surface high-strength steel skin and anchors . Through successively more exothermic reactions, we are seeking to build subsurface geopolymer slabs and use thermite reactions to constitute micro-alloyed advanced high-strength steel (AHSS) and Ti—Al—V pads on surfaces of planetary bodies, thereby circumventing the need for energy-intensive sintering technologies. As a precursor delivery system used to constitute landingpads, RAMS can be scaled for robotic, human-class, and more prominent (i.e., Starship) landers and will be configured within pressurized delivery systems that use radio beacons to outline coordinates for precision landings. Microcapsule delivery systems are designed to impel precursors (nanothermite mixtures and organosilanes), which activate in response to stress, heat, or impact to constitute deep geopolymerized slabs and AHSS skins. Dust mitigation is accomplished by reaction/solidification chemistry that yields a subsurface slab and advanced high-strength steel skin and anchors.

2021 NIAC Phase I↗
NASA NTRS2010

Radiation Environment and Surface Radiolytic Interactions at Mimas

Saturn's innermost principal moon Mimas shares the distinction with Europa at Jupiter of being the most irradiated icy moon in its respective planetary system, although the energetic electron energy flux at Mimas is forty times smaller than at Europa. High energy (> 10 MeV) proton fluxes are low in this moon's orbital corridor, likely since slowly diffusing protons from the weak but steady source of cosmic ray albedo neutron decay (CRAND) cannot accumulate without impacting the moon surface. Lower energy proton fluxes are also evidently suppressed in this orbital region. Plasma ion and electron fluxes are also low apparently due to cooling by interaction with E-ring dust and neutral gas from Enceladus. Due to energy-dependent effects of longitudinal gradient-curvature drift for the electrons, the trailing hemisphere is mainly irradiated by electrons at energies below 1 MeV that drift relative to Mimas in the prograde direction of orbital motion around Saturn, while higher energy electrons primarily impact the leading hemisphere. Plasma ions in the inner magnetosphere of Saturn are mainly pickup ions forming from the dissociation products of Enceladus plume water molecules, additionally including some contribution from photosputtering of the main rings, and do not introduce new elemental materials at Mimas via surface implantation from the corotating plasma. Thus the primary interaction at the surface is radiolytic chemistry induced in pure water ice by relatively deep penetration of the energetic electrons to millimeter and greater depths, as compared to the micron depths impacted by the corotating plasma ions. If surface erosion by sputtering from relatively low fluxes of the plasma and more energetic ions is indeed ineffective, then molecular products (OH, H2O2, 02, 03) of the radiolytic interactions may accumulate in the meters-deep impact regolith of the surface ices. An effect of regolith trapped gas accumulation could be to increase porosity and reduce thermal conductivity of the ice, potentially contributing to reported thermal anomalies from Cassini infrared map observations. Low amplitude of trailing-leading asymmetry in optical albedo and color maps at Mimas is suggestive of relative weakness of asymmetrical effects from low-energy ions. Greater induced asymmetries are expected and observed for the moons beyond Enceladus in the middle magnetospheric region of hot plasma ions at much greater fluxes than at Mimas. Low density (1.15 g/cc) of this moon indicates paucity of mineral salts and radiogenic heating to maintain subsurface liquids, so Enceladus-like cryovolcanism as a resurfacing process is unlikely despite closer proximity to Saturn, greater tidal forcing, and more intense surface irradiation than for Enceladus.

Cooper, J. F.↗
DOE OSTI2021

Impacts of cloud microphysics parameterizations on simulated aerosol–cloud interactions for deep convective clouds over Houston

Aerosol–cloud interactions remain largely uncertain with respect to predicting their impacts on weather and climate. Cloud microphysics parameterization is one of the factors leading to large uncertainty. Here, we investigate the impacts of anthropogenic aerosols on the convective intensity and precipitation of a thunderstorm occurring on 19 June 2013 over Houston with the Chemistry version of Weather Research and Forecast model (WRF-Chem) using the Morrison two-moment bulk scheme and spectral bin microphysics (SBM) scheme. We find that the SBM predicts a deep convective cloud that shows better agreement with observations in terms of reflectivity and precipitation compared with the Morrison bulk scheme that has been used in many weather and climate models. With the SBM scheme, we see a significant invigoration effect on convective intensity and precipitation by anthropogenic aerosols, mainly through enhanced condensation latent heating. Such an effect is absent with the Morrison two-moment bulk microphysics, mainly because the saturation adjustment approach for droplet condensation and evaporation calculation limits the enhancement by aerosols in (1) condensation latent heat by removing the dependence of condensation on droplets and aerosols and (2) ice-related processes because the approach leads to stronger warm rain and weaker ice processes than the explicit supersaturation approach.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, to estimate the broadband fluxes between CERES observations. This requires stable imager visible channel calibration, which the CERES project verifies by utilizing deep convective clouds (DCC) as an invariant Earth target. GSICS, which is an international collaboration, is also evaluating the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the Aqua-MODIS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical DCC-identified pixel-level reflectances, which are histogrammed to find the mode reflectance of the probability density function (PDF). The imager stability is monitored by tracking the monthly DCC PDF mode reflectance over time. Radiometric scaling is accomplished by ratioing the GEO and VIIRS DCC mode reflectance values. The PDF shape and mode dependency on sensor pixel resolution, which varies among sensors, is unknown. This study will characterize the impact of pixel resolution on the DCC PDFs by aggregating Landsat 30-m pixel reflectances into various coarser pixel resolutions ranging from 100-m to 4-km, and comparing the corresponding PDF statistics. This analysis will assist in improving the uncertainty in a DCC-based intercalibration between instruments with different pixel resolutions.

Conor Haney↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, are used to estimate the broadband fluxes between CERES observations. This requires stable and consistent cross-platform imager visible channel calibration. The CERES project utilizes deep convective clouds (DCC) as an invariant Earth target to both monitor the stability of sensors and for radiometric scaling. GSICS, an international collaboration, is also evaluating and implementing the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the AquaMODIS or the NOAA-20 VIIRS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical D CC-identified pixel-level reflectances, which are aggregated as probability density functions (PDF). By assuming the monthly PDF shape is otherwise consistent in time excepting shifts in reflectance caused by changes in the sensor calibration, the imager stability is monitored. Radiometric scaling is accomplished by ratioing the sensor pair DCC PDF reflectance values. The success of the DCC methodology relies on consistent PDF distributions. The goal of this study is to determine the impact of pixel resolution on the DCC reflectance distribution. Single SNPP-VIIRS 750-m and Landsat 8 OLI 30-m granules are aggregated to degrade the pixel resolution from the native level. The DCC pixels are identified using a BT threshold. Most of the brightest DCC pixels are also the coldest, although there are exceptions. It was found that increasing the BT threshold exponentially increased the number of darker pixels. The pixel resolution did not seem to impact the DCC reflectance PDF distribution for pixel resolutions less than 3 km, which suggests that imagers of varying pixel resolutions may be radiometrically scaled to each other using DCC targets.

DCC↗
NASA NTRS2001

Exploration of the Eltanin Impact Area (Bellingshausen Sea): Expedition ANT XVIII5a

The impact of the Eltanin asteroid into the Bellingshausen Sea (2.15 Ma) is the only known impact in a deep-ocean (approx. 5 km) basin. On 26 March 2001, the FS Polarstern returned to the impact area during expedition ANT XVIII/5a. Over a period of 14 days, this region was explored by detailed bathymetric mapping, acoustic profiling of sediment deposits, and direct sampling with 18 piston cores and four gravity cores. Preliminary shipboard examination of microfossils showed that sixteen of the piston cores and three gravity cores contained sediments at least as old as the impact event and have a high probability of containing a record of the disturbances caused by the impact. During the expedition, portions of eleven piston cores were opened for preliminary examination of the impact deposits. Visual examination of cores and microscopic identification of suspect impact melt particles were were used to identify ejecta and X-ray radiographs of the opened core segments permitted analysis of sediment structures. Impact deposits were found in nine of the eleven opened cores, and a similar success rate is anticipated in the seven cores remaining to be opened. These preliminary observations indicate that the highest concentrations of meteoritic ejecta and the largest particle sizes appear to occur in the region north of the San Martin seamounts. Recovered debris includes cm-sized melt rocks and a 2.5 cm meteorite. This expedition has confirmed the presence of high concentrations of meteoritic ejecta across a region at least as large as 10(exp 5) sq km. Quantitative analyses of ejecta distribution within this region will require further study, but previous estimates of 1 km for the minimum diameter of the Eltanin asteroid, appear safe.

Gersonde, Rainer↗
NASA NTRSDate not supplied

The Impact of Stable Layers on Downdrafts in Tropical Deep Convection

Previous studies have demonstrated that one pathway by which dry air can interrupt tropical cyclone intensification is by inducing downdrafts that flood the surface inflow layer with low entropy air. While work has been performed examining the relationship between dry air and downdraft intensity, very little has been done to investigate the potential for features of the convective environment, such as stable layers, to inhibit the downward progression of downdrafts. This study aims to understand the role that stable layers have on inhibiting the downward progression of downdrafts and their associated low entropy air in the context of tropical deep convection. Specifically, this study asks two key questions: can a stable layer halt the downward progression of a downdraft or merely slow its velocity and can a stable layer stop the injection of low entropy air into the boundary layer? The present study aims to answer these questions using a combination of high-altitude airborne radar and dropsonde observations, both collected within four tropical cyclones (Gaston, Hermine, Karl, and Matthew) during the 2016 NOAA SHOUT field campaign, as well as idealized simulations of tropical deep convection. Preliminary results suggest that precipitation-free downdrafts can be blocked by a stable layer while precipitation-laden downdrafts are weakened, but not stopped, by the presence of a stable layer. This presentation will primarily focus on the precipitation-laden downdrafts that can be observed via airborne radar. Additionally, the presentation will conclude with a brief discussion of the implications of downdraft/stable-layer interactions for a tropical cyclone ingesting dry environmental air.

Charles N Helms↗
NASA NTRSDate not supplied

The Application of Artificial Intelligence Deep Learning to Visually Identify Micrometeoroid and Orbital Debris Impacts

Recent advances in Artificial Intelligence (AI) are changing the World. Novel approaches to training AI systems have led to dramatic reductions in the amount of time required. Training an AI system could take years and teams of people using traditional methods, but with the advancements of Deep Learning (DL) models this training can now be accomplished by an individual in a matter of minutes. The development of “fast AI” libraries has delivered AI to essentially everyone. Democratization of AI power has inspired many to revisit past problems that will benefit from DL approaches. For example, the application of AI has improved detection of breast cancer by 20% compared to traditional detection methods. Computer vision and machine learning are being used to identify soil deficiencies and provide planting recommendations to farmers. Success stories like these and many others have provided inspiration to see if AI can help improve one of our needed capabilities – that of visually identifying micrometeoroid and orbital debris (MMOD) impact damage to spacecraft from images of the spacecraft exterior. The need to visually locate and characterize spacecraft MMOD impact damage has been present since the early days of space travel. This is often done by either having a crew member take photographs of the spacecraft through a window using a hand-held camera or ground personnel directing externally-mounted cameras. The photographs are then transmitted back to Earth for visual analysis. This method of MMOD damage inspection works well and has been used on various spacecraft including the Space Shuttle and the International Space Station (ISS). One of the issues with the current method that we believe AI could improve is the speed and possibly the accuracy in identifying MMOD impacts. Note that detecting MMOD impacts in images can be very difficult. The visual appearance of an MMOD impact can change dramatically with lighting conditions, size of impact, depth of penetration, material types, surface waviness, fabric coverings, camera & lens, distance to surface, spacecraft orientation, analyst experience, and many other factors. Currently, this takes a team of highly-experienced specialists in both the fields of Image Analysis and MMOD impacts. This paper documents our initial research in training an AI DL model using the fast-AI library to identify actual and simulated MMOD impacts and perforations into exposed flat surfaces. While we recognize that this initial goal seems modest, it must be noted that what we have done would have taken teams of individuals and years of training just ten years ago. Our long-term goal is to add complexity and use-cases to the DL model being trained to expand the capabilities of this model so that it can be used to identify MMOD impacts on all types of spacecraft surfaces.

Cameron M Collins↗
NASA NTRS2021

Impacts of Varying Concentrations of Cloud Condensation Nuclei On Deep Convective Cloud Updrafts – A Multimodel Assessment

This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations amongst seven, state-of-the-art, cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced, updraft changes. The models show several consistent trends. In general, the changes between the High- CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5-15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~-5-0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

deep convective cloud updrafts↗
DOE OSTI2021

Impacts of Varying Concentrations of Cloud Condensation Nuclei on Deep Convective Cloud Updrafts—A Multimodel Assessment

Abstract This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations among seven state-of-the-art cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas, are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced updraft changes. The models show several consistent trends. In general, the changes between the High-CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5%–15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~−5% to 0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Fully Automatic Method for Rapidly Mapping Impacted Area by Natural Disaster

Deep learning based change detection methods have achieved the state-of-the-art performance in several recent studies. However, such methods usually are supervised, and therefore a large number of training samples is often a requisite. Manually preparing those training samples is not only expensive but also time-consuming, which does not fit the need of rapidly mapping the impacted area caused by nature disaster for further rescue mission and damage assessment. In this study, a fully automatic method was proposed to address the issue by automating training sample generation for mapping the impacted area caused by nature disaster. We used the 2011 tornado event in Joplin, Missouri, US, as an example of its application. The generated impacted area map was both visually and quantitatively evaluated against the ground truth data collected by US Federal Emergency Management Agency (FEMA). The results show that the map matches well with the FEMA ground truth data with 86% of major-damaged and destroyed buildings identified by FEMA on the ground also detected by this fully automatic framework using very high resolution (VHR) satellite images.

Liu, Tao↗