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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Ocean alkalinity and the Cretaceous/Tertiary boundary

A biogeochemical cycle model resolving ocean carbon and alkalinity content is applied to the Maestrichtian and Danian. The model computes oceanic concentrations and distributions of Ca(2+), Mg(2+), and Sigma-CO2. From these values an atmospheric pCO2 value is calculated, which is used to estimate rates of terrestrial weathering of calcite, dolomite, and calcium and magnesium silicates. Metamorphism of carbonate rocks and the subsequent outgassing of CO2 to the atmosphere are parameterized in terms of carbonate rock reservoir sizes, total land area, and a measure of overall tectonic activity, the sea-floor generation rate. The ocean carbon reservoir computed by the model is used with Deep Sea Drilling Project (DSDP) C-13 data to estimate organic detrital fluxes under a variety of ocean mixing rate assumptions. Using Redfield ratios, the biogenic detrital flux estimate is used to partition the ocean carbon and alkalinity reservoirs between the mixed layer and deep ocean. The calcite flux estimate and carbonate ion concentrations are used to determine the rate of biologically mediated CaCO3 titration. Oceanic productivity was severely limited for approximately 500 kyr following the K/T boundary resulting in significant increases in total ocean alkalinity. As productivity returned to the ocean, excess carbon and alkalinity was removed from the ocean as CaCO3. Model runs indicate that this resulted in a transient imbalance in the other direction. Ocean chemistry returned to near-equilibrium by about 64 mybp.

Caldeira, K. G.↗
NASA NTRS2005

Evolutionary Computing for Low-thrust Navigation

The development of new mission concepts requires efficient methodologies to analyze, design and simulate the concepts before implementation. New mission concepts are increasingly considering the use of ion thrusters for fuel-efficient navigation in deep space. This paper presents parallel, evolutionary computing methods to design trajectories of spacecraft propelled by ion thrusters and to assess the trade-off between delivered payload mass and required flight time. The developed methods utilize a distributed computing environment in order to speed up computation, and use evolutionary algorithms to find globally Pareto-optimal solutions. The methods are coupled with two main traditional trajectory design approaches, which are called direct and indirect. In the direct approach, thrust control is discretized in either arc time or arc length, and the resulting discrete thrust vectors are optimized. In the indirect approach, a thrust control problem is transformed into a costate control problem, and the initial values of the costate vector are optimized. The developed methods are applied to two problems: 1) an orbit transfer around the Earth and 2) a transfer between two distance retrograde orbits around Europa, the closest to Jupiter of the icy Galilean moons. The optimal solutions found with the present methods are comparable to other state-of-the-art trajectory optimizers and to analytical approximations for optimal transfers, while the required computational time is several orders of magnitude shorter than other optimizers thanks to an intelligent design of control vector discretization, advanced algorithmic parameterization, and parallel computing.

optimization↗
NASA NTRS2000

Atmospheric Dynamics on Venus, Jupiter, and Saturn: An Observational and Analytical Study

Determining the static stability of Jupiter's atmosphere below the visible cloud levels is important for understanding the dynamical modes by which energy and momentum are transported through Jupiter's deep troposphere. The Galileo Probe Atmospheric Structure Investigation (ASI) employed pressure and temperature sensors to directly measure these state variables during the parachute-descent phase, which started at a pressure (p) of 0.4 bars and ended at p= 22 bars. The internal temperature of the probe underwent large temperature fluctuations which significantly exceeded design specifications. Corrections for these anomalous interior temperatures have been evaluated based on laboratory data acquired after the mission using the flight spare hardware. The corrections to the pressure sensor readings was particularly large and the uncertainties in the atmospheric pressures derived from the p sensor measurements may still be significant. We have sought to estimate the formal uncertainties in the static stability derived from the p and T sensor measurements directly and to devise means of assessing the static stability of Jupiter's atmosphere which do not rely on the p sensor data.

Bridger, Alison↗
NASA NTRS2006

Role of Deep Convection in Establishing the Isotopic Composition of Water Vapor in the Tropical Transition Layer

The transport of H2O and HDO within deep convection is investigated with 3-D large eddy simulations (LES) using bin microphysics. The lofting and sublimation of HDO-rich ice invalidate the Rayleigh fractionation model of isotopologue distribution within deep convection. Bootstrapping the correlation of the ratio of HDO to H2O (deltaD) to water vapor mixing ratio (q(sub v)) through a sequence of convective events produced non-Rayleigh correlations resembling observations. These results support two mechanisms for stratospheric entry. Deep convection can inject air with water vapor of stratospheric character directly into the tropical transition layer (TTL). Alternatively, moister air detraining from convection may be dehydrated via cirrus formation n the TTL to produce stratospheric water vapor. Significant production of subsaturated air in the TTL via convective dehydration is not observed in these simulations, nor is it necessary to resolve the stratospheric isotope paradox.

Smith, Jamison A.↗
NASA NTRS2024

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, development of new coating systems is hindered by the large design space and difficulty in predicting properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate accurate prediction of the anisotropy of the CTE in good agreement with diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

rare earth silicates↗
NASA NTRS1971

The energy spectrum of primary cosmic ray electrons from 2 GeV to 200 GeV.

Use of a balloon-borne counter telescope with a gas Cerenkov counter to measure the energy of primary cosmic ray electrons between 2 and 200 GeV. Electrons are identified by the characteristic electron-photon shower which they produce in a 15 radiation length deep stack of high-Z material interleaved with scintillation counters. Calibrations with monoenergetic electrons up to 14 GeV and monoenergetic protons up to 28 GeV from accelerators are used to develop criteria to statistically separate electrons from proton-induced events. The results from six balloon flights (total exposure time 63 hours) are combined to obtain the electron energy spectrum. Up to about 30 GeV, the spectrum measured in this experiment can be directly checked with calibrations and agrees well with results from other experiments. Above this energy, the flux reported in the present work is somewhat higher than the determinations reported by most other authors. An apparent flattening of the energy spectrum above 50 GeV is not regarded as significant. There is no evidence for a steepening of the spectrum at energies below 200 GeV.

Fanselow, J. L.↗
NASA NTRS2007

Direct Measurements of the Convective Recycling of the Upper Troposphere

We present a statistical representation of the aggregate effects of deep convection on the chemistry and dynamics of the Upper Troposphere (UT) based on direct aircraft observations of the chemical composition of the UT over the Eastern United States and Canada during summer. These measurements provide new and unique observational constraints on the chemistry occurring downwind of convection and the rate at which air in the UT is recycled, previously only the province of model analyses. These results provide quantitative measures that can be used to evaluate global climate and chemistry models.

Bertram, Timothy H.↗
NASA NTRS2006

Interfacing with USSTRATCOM and UTTR during Stardust Earth Return

The Stardust Sample Return Capsule separated from the main spacecraft four hours prior to atmospheric entry. Between this time and the time at which the SRC touched down at the Utah Test and Training Range, two organizations external to JPL were involved in tracking the Sample Return Capsule. Orbit determination for the Stardust spacecraft during deep space cruise, the encounters of asteroid Annefrank and comet Wild 2, and the final approach to Earth used X-band radio metric Doppler and range data obtained through the Deep Space Network. The SRC lacked the electronics needed for coherently transponded radio metric tracking, so the DSN was not able to track the SRC after it separated from the main spacecraft. Although the expected delivery accuracy at atmospheric entry was well within the capability needed to target the SRC to the desired ground location, it was still desirable to obtain direct knowledge of the SRC trajectory in case of anomalies. For this reason U.S. Strategic Command was engaged to track the SRC between separation and atmospheric entry. Once the SRC entered the atmosphere, ground sensors at UTTR were tasked to acquire the descending SRC and maintain track during the descent in order to determine the landing location, to which the ground recovery team was then directed. This paper discusses organizational interfaces, data products, and delivery schedules, and the actual tracking operations are described.

Utah Test and Training Range (UTTR)↗
NASA NTRS2012

Two Years of Simultaneous K(sub a)-Band Measurements: Goldstone, CA; White Sands, NM; and Guam, USA

In order to statistically characterize the effect of the Earth's atmosphere on Ka-Band links, site test interferometers (STIs) have been deployed at three of NASA s operational sites to directly measure each site's tropospheric phase stability and rain attenuation. These STIs are composed of two antennas on a short baseline (less than 1km) that observe the same unmodulated beacon signal broadcast from a geostationary satellite (e.g., Anik F2). The STIs are used to measure the differential phase between the two received signals as well as the individual signal attenuation at each terminal. There are currently three NASA sites utilizing STIs; the Goldstone Deep Space Communications Complex near Barstow, California; the White Sands Complex in Las Cruces, New Mexico; and the Guam Remote Ground Terminal on the island of Guam. The first two sites are both located in desert regions that have highly similar climates in terms of their seasonal temperatures, average humidity, and annual rain fall (the primary factors in determining phase stability). In contrast, Guam is in a tropical region with drastically higher annual rainfall and humidity. Five station years of data have been collected in Goldstone, three in White Sands, and two in Guam, yielding two years of simultaneous data collection across all three sites. During this period of simultaneous data collection, the root-mean-square (RMS) of the time delay fluctuations stayed under 2.40 picoseconds for 90% of the time in Goldstone, under 2.07 picoseconds for 90% of the time in White Sands, and under 10.13 picoseconds for 90% of the time in Guam. For the 99th percentile, the statistics were 6.32 ps, 6.03 ps, and 24.85 ps, respectively. These values, as well as various other site quality characteristics, will be used to determine the suitability of these sites for NASA s future communication services at Ka-Band.

Acosta, Roberto J.↗
NASA NTRSDate not supplied

Multi-Wavelength Modeling and Analysis of the Center-to-Limb Effects of Solar Spectroscopy and Helioseismology

An accurate interpretation of observed solar dynamics with different instruments requires modeling solar magnetoconvection indifferent regimes, as well as taking into account center-to-limb effects, magnetic fields, and turbulence. Realistic 3D radiative MHD modeling of the solar magnetoconvection and atmosphere allows us to generate synthetic observables that directly link the physical properties of the solar plasma to spectroscopic and helioseismic observables. In this work, we investigate the influence of the center-to-limb effects for a wide range of wavelengths, which correspond to the operational lines of HMI/SDO, Hinode, DKIST, and other instruments. In particular, we discuss the wavelength-dependency of the center-to-limb helioseismic observations of acoustic travel times that are used for diagnostics of the deep meridional circulation, as well as 'concave' Sun effect. The presented study will support interpretation of helioseismic inversion results by taking into account realistic coupling of subsurface and atmosphere, and geometry-related effects. In particular, it allows us to improve accuracy of solar subsurface measurements from the SoHO and SDO missions, and resolve the long-standing problem of the meridional circulation and evolution with the solar cycle.

SMD↗
NASA NTRS2021

Microbial Food Safety in Space Production Systems

While traveling to deep space is difficult for many reasons, food is a crucial one. Round-trip Mars mission scenarios last 3 years, demanding food with a shelf-life of 5 years; this means that feeding human crew sustainably for long-duration missions beyond low Earth orbit (LEO) will ultimately lead to a paradigm shift away from the current Earth-based food production system, which depends upon storing and transporting prepackaged foods, and toward bio-regenerative production of food in space. Pharmaceuticals and nutritional supplements face similar challenges. Moreover, the methods we currently use to detect dangerous microbes in food require sample return to Earth, a situation not viable for deep-space missions. While the science behind generating foods and bioproducts is covered by other white papers, in this paper we discuss a crucial gap uniting all of them: how to ensure that such products are free of unwanted microbial contamination and safe for crew to consume. Because Earth-based food safety systems cannot be directly applied in space, safety assurance is currently a critical bottleneck in the space production of food and other bioproducts. Future sustainable deep-space missions will require NASA to devote more resources in the coming decade to understanding the biological and physical science principles underlying microbial food safety in space, and to developing efficient, reliable methods in this area.

microbiology↗
NASA NTRSDate not supplied

Multiphase Simulations of the SLS Launch Environment

NASA’s Space Launch System (SLS), which will send astronauts back to the Moon in the next few years, is powered by four RS-25 engines and two RSRMV solid rocket boosters (SRBs). During launch the SLS propulsion system generates intense acoustics and other powerful waves, such as ignition overpressure (IOP) which, if unmitigated, have the potential to damage the vehicle and possibly cause loss of mission or crew. To protect the vehicle from these powerful waves, the SLS launch pad design includes an ignition overpressure/sound suppression (IOP/SS) system which sprays 270,000 gallons per minute of water very close to the SRB and RS-25 nozzles. The SRB and RS-25 engine plumes, and the proximity of the IOP/SS water, create a complex multiphase (gas and liquid) environment during the SLS ignition sequence. The interplay among these systems creates challenges related to water spray into/onto engine nozzles, potential debris transport, and additional transient loads due to strong plume-water interactions - all of which the SLS vehicle must be able to withstand. Prior to the Artemis I launch, the SLS multiphase liftoff environment was largely unknown due to differences from the Space Shuttle and other programs. Some data was available from tests of individual systems, but no integrated testing or analysis was available. Even post-launch analysis of Artemis I cannot provide a full understanding of the complex physics involved due to limited (or obstructed) camera views and instrumentation. Computational fluid dynamics (CFD) is being used to investigate the details of the multiphase environment which could not be measured, help comprehend the data gathered from the launch, and ultimately identify phenomena that are a concern for future flights. Project Details Engineers at NASA’s Marshall Space Flight Center (MSFC) have executed simulations using the Loci/STREAM-Volume of Fluid (VoF) multiphase CFD solver to understand this environment. Initial efforts successfully validated the CFD solver on various tests, giving confidence to simulate the SLS multiphase liftoff environment prior to the Artemis I launch. The CFD simulation of the SLS ignition sequence was conducted in three phases. First the IOP/SS water system was simulated for approximately 6 seconds to reach a quasi-steady state. Next, the RS-25 engine plumes were activated and held at full power for 1 second. Lastly, the SRB booster was activated and the simulation was carried out until just prior to vehicle motion. This simulation process mimics the conditions that exist at launch. Results and Impact The SLS ignition sequence simulation results provide deep understanding of the underlying physics occuring during launch. Observations from the simulation include reduction of water splashing into/onto the engine nozzles, change in angling of the dense water sheets, and the origin of the powerful ignition overpressure (IOP) wave. These observations directly inform the SLS program on subjects including plume-water induced side loads, debris transport, and the acoustic launch environment. Additionally, with post launch comparison of CFD observations to flight data, these tools can be applied to launch vehicles and environments other than SLS with confidence. Why HPC Matters The SLS ignition sequence CFD simulations are conducted on meshes up to hundreds of millions of cells on thousands of processors for weeks at a time. These simulations generate terabytes of data that must also be stored and archived for future use on HPC systems. Simply put, the CFD simulations would not be possible without NASA HPC resources. What’s Next Comparisons between the Artemis I flight data and the CFD simulations will be continued to both improve confidence in the CFD results and provide deeper understanding into the SLS multiphase launch environment. This will be used to provide insight for decision making for the first manned SLS flight, Artemis II. Future simulations will target new configurations of the SLS IOP/SS water required to support the more powerful variants of the SLS vehicle, such as Block 1B. Additionally, this capability provides NASA the ability to investigate launch environments for vehicles other than SLS to support other missions.

Travis Rivord↗
NASA NTRS1989

Interactions among radiation, convection, and large-scale dynamics in a general circulation model

The effects of radiatively active clouds on the climate simulated by a GCM are studied, focusing on the effects of upper tropospheric stratiform clouds associated with deep cumulus convection and the interactions of these clouds with convection and the large-scale circulation. The isolated effects of atmospheric cloud radiative forcing are analyzed using a model climate of an ocean-covered earth. It is found that the upper tropospheric cloudiness associated with cumulus convection has a powerful influence on both the convection and the large-scale circulation. Consideration is given to the importance of developing a GCM which includes a direct representation of the radiative, thermodynamical, and dynamical couplings between the convection parameterization and the large-scale saturation parameterization.

Randall, David A.↗
NASA NTRS2012

Electric Propulsion Induced Secondary Mass Spectroscopy

A document highlights a means to complement remote spectroscopy while also providing in situ surface samples without a landed system. Historically, most compositional analysis of small body surfaces has been done remotely by analyzing reflection or nuclear spectra. However, neither provides direct measurement that can unambiguously constrain the global surface composition and most importantly, the nature of trace composition and second-phase impurities. Recently, missions such as Deep Space 1 and Dawn have utilized electric propulsion (EP) accelerated, high-energy collimated beam of Xe+ ions to propel deep space missions to their target bodies. The energies of the Xe+ are sufficient to cause sputtering interactions, which eject material from the top microns of a targeted surface. Using a mass spectrometer, the sputtered material can be determined. The sputtering properties of EP exhaust can be used to determine detailed surface composition of atmosphereless bodies by electric propulsion induced secondary mass spectroscopy (EPI-SMS). EPI-SMS operation has three high-level requirements: EP system, mass spectrometer, and altitude of about 10 km. Approximately 1 keV Xe+ has been studied and proven to generate high sputtering yields in metallic substrates. Using these yields, first-order calculations predict that EPI-SMS will yield high signal-to-noise at altitudes greater than 10 km with both electrostatic and Hall thrusters.

Amini, Rashied↗
NASA NTRS2022

Mars 2020 Entry, Descent, and Landing as Observed by Radio Science Techniques at UHF and X-band Frequencies

On February 18, 2021, NASA’s Mars 2020 Rover “Perseverance” conducted the Entry, Descent, and Landing (EDL) sequence to land safely on the surface of Mars at Jezero Crater. Due to the criticality of the EDL sequence, redundant telecommunications strategies were utilized to observe the event. The rover transmitted an X-band (8.4 GHz) signal encoded with Multiple Frequency Shift Keying tones direct-to-Earth and a UHF (401.5 MHz) signal with 8 kbps encoded telemetry to orbiters, which relayed the signal back to Earth at X-band. NASA’s Deep Space Network complexes at Goldstone, California and Madrid, Spain received the direct-to-Earth X-band signal. Two of the largest steerable radio telescopes in the world, the 100-meter Green Bank Telescope in West Virginia and the Effelsberg 100-meter Radio Telescope in Germany also received the UHF carrier signal on Earth. During the EDL event, full spectrum recordings of the UHF and X-band signals were captured at these observatories using open-loop receivers. Real-time and post-processing signal analysis to determine power level, received frequency, and Doppler shift allowed determination of the spacecraft’s health and safety state during critical sequences, including event detection such as atmospheric entry, plasma blackouts, and parachute deployment. Simultaneous observations of the UHF and X-band radio links allow for redundancy in the event of a fault and greatly improve confidence in Doppler event detection.

Gladden, Roy↗
NASA NTRS2023

Impact of Satellite Orbit Drift on Modis Earth Scene Observations Used in Calibration of the Reflective Solar Bands

After more than 20 years in orbit, NASA’s Terra and Aqua satellites have both started drifting away from their historically maintained orbits. The MODIS instruments on Terra and Aqua continue to collect valuable Earth observation data, but the changing orbits present a challenge for maintaining accurate calibration. The MODIS reflective solar bands (RSB), spanning the wavelength range from 412 nm to 2130 nm, are calibrated on orbit using a combination of regular data collections from an on-board solar diffuser, the Moon, and pseudo-invariant Earth scenes. Starting in the Collection 6 Level 1B (L1B) data products, the RSB calibration began using data from desert targets for a few of the visible bands to better track changes in the response versus scan angle that could not be captured by the on-board calibration. The use of Earth scene data has been extended recently for Terra MODIS calibration in Collection 6.1 (C6.1) and the upcoming Collection 7 (C7) L1B to also include data from ocean scenes and deep convective clouds (DCC). Drifts in both the orbit inclination and ground track of Terra and Aqua lead to changes in the solar illumination angles and satellite view angles of the Earth scenes. We discuss how these orbital changes impact the desert and DCC targets used for MODIS RSB calibration and present the accompanying changes made to our C6.1 and C7 calibration algorithms. We also discuss remaining future challenges, such as better characterization of bi-directional reflectance distribution functions, and possible alternative calibration strategies.

MODIS↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗