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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Conservative-coordinate transformations for atmospheric measurements

This lecture describes a technique by which atmospheric measurements of trace species with medium to long lifetimes can be 'coincidentally' compared and validated even though measurements are taken at different locations and different times In other words, the method, under suitable counditions, can remove a large amount of the natural meteorological variability. The technique involves the use of quasi-Lagrangian or conservative coordinates - air parcel tags which are invariant or nearly invariant under the motion of the parcel. The technique is called 'reconstruction', since measurements taken at one location can be reconstructed at different locations. In order to do this, the data are transformed into the conservative coordinates and accumulated. Within the conservative reference frame, much of the meteorological variability is removed. Once enough data are obtained within the system, the observations can be tranformed back into physical space at any location and compared with other measurements. The method by which the trace species data are obtained makes no difference; satellite, balloon, rocket, aircraft and ground-based data all become equivalent and can be intercompared. The conservative-coordinate system not only allows for intercomparison of data, but shows how data can be taken in such a way as to maximize the physical scope of the information. In other words, the method automatically suggests when conditions might be suitable to obtain information with different environmental situations. It also allows for the forecast of constituent fields using only the meteorological forecasts and limited observational data.

Schoeberl, M. R.↗
NASA NTRS1998

The Effect of Clouds Upon Limb Scattered Radiances and the Retrieval of Ozone Profiles Using These Radiances

The use of limb scattered radiance profiles to retrieve ozone profiles is currently being investigated. The goal is to produce ozone profiles with better vertical resolution than is available with the Backscattered Ultraviolet (BUV) technique and with much greater spatial and temporal coverage than with the solar occultation method (i.e. SAGE II). This method, which uses UV and visible light scattered from the earth's limb, has recently been proven to work for clear sky cases with data from the STS-87 flight of the Shuttle Ozone Sounding Limb Experiment/Limb Ozone Retrieval Experiment (SOLSE/LORE). As to be expected, clouds have a substantial impact upon the limb radiance (increasing the radiance as much as 80-100% is some cases). Here we use a variety of radiative transfer models and limited SOLSE/LORE data to investigate the effect of clouds upon the limb radiance at wavelengths used in the ozone retrieval (approximately 600 nm). Though the presence of clouds can greatly increase the limb radiance, they have a minimal effect upon the retrieved ozone profile, since the retrieval uses a differential absorption technique.

Flittner, D. E.↗
NASA NTRS2002

Space Radiation Cancer Risk Projections for Exploration Missions: Uncertainty Reduction and Mitigation

In this paper we discuss expected lifetime excess cancer risks for astronauts returning from exploration class missions. For the first time we make a quantitative assessment of uncertainties in cancer risk projections for space radiation exposures. Late effects from the high charge and energy (HZE) ions present in the galactic cosmic rays including cancer and the poorly understood risks to the central nervous system constitute the major risks. Methods used to project risk in low Earth orbit are seen as highly uncertain for projecting risks on exploration missions because of the limited radiobiology data available for estimating HZE ion risks. Cancer risk projections are described as a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Monte-Carlo sampling from subjective error distributions represents the lack of knowledge in each factor to quantify risk projection overall uncertainty. Cancer risk analysis is applied to several exploration mission scenarios. At solar minimum, the number of days in space where career risk of less than the limiting 3% excess cancer mortality can be assured at a 95% confidence level is found to be only of the order of 100 days.

Cucinotta, Francis↗
NASA NTRS2022

TechEdSat-13: The First Flight of a Neuromorphic Processor

Neuromorphic processors, inspired by the wiring of the brain, permit certain classes of Artificial Intelligence/Machine Learning (AI/ML) algorithms to run far more efficiently. Ultimately, such systems will make the small- and nano-satellite platforms even more useful in terms of greatly improved power, communication and internal data management. In addition, on-board processing of images and data will help to not only rapidly interpret the information, but also reduce the amount of data that needs to be transmitted to ground stations. This initial flight experiment uses the Intel/Loihi processor combined with a custom interface board and three communication channels to run the AI/ML scripts. These will vary with increasing length and complexity during the course of the mission. The algorithms will use the (at first) limited sensor data to ‘learn’ - with comparisons to similar architecture in comparable ground experiments. Some of the applications for successor flights in the TES-n flight series include Cognitive Communications, whereby the overall communication system is optimized per overflight – by optimizing timing and data transmission functions. Lastly, the performance of the Loihi 14nm process technology will be monitored for performance in the LEO radiation environment, thus looking for induced hardware and software errors. This information will help guide future radiation protection techniques to extend the lifetime and overall utility. The TES-13 is a 3U nanosat successfully launched by the Virgin Orbit Launcher-1 on January 13, 2022, and will presage more flights and AI/ML applications to come.

TechEdSat↗
NASA NTRSDate not supplied

Squeezing Every Last 'Bit' of Information from Enceladus Mass Spectrometry

Potential opportunities to return to Enceladus in Discovery and Flagship class missions inspire development of next-generation instruments and creative approaches to sample collection, sample analysis, and data analysis and transmission strategies. Mass spectrometers (MS) are ideally suited to future Enceladus missions due to their analytical power in identifying a range of molecular and ionic compositions – including complex organics – and potentially astrobiologically-important features such as isotope ratios, chirality, and enantiomeric excess. However, long communication delays from Enceladus and limited bandwidth limits the data transmission from these higher-data-volume instruments, likely delaying mission-related response to new data. We explore the utility of data science and machine learning (ML) on isotope ratio (IR)MS data collected from laboratory analogs of Enceladus to: 1) process data quickly for rapid ground-based analyses, 2) understand if compositional and biosignature information could be extracted from IRMS data, and 3) evaluate whether onboard ML techniques could improve sample analysis, cadence, and transmission prioritization. Laboratory analogs analyzed isotopes of volatile CO2 that interacted with seawaters of varying composition, and include both abiotic and biotic (microbially-influenced) experiments. Enceladus’s alkaline oceans promote speciation of carbon into multiple forms (e.g., H2CO3 / CO2, HCO3-, and CO32-), each of which could be isotopically fractionated by abiotic or biotic reactions. Large (>2‰) changes in carbon isotopes (δ13C) are observed from some biotic experiments inoculated with complex microbial ecosystems relative to the abiotic seawaters. ML training and classification suggests that microbial samples can be distinguished from abiotic samples, yet that a broad range of microbial experiments are necessary to train ML models to cover a range of complexities including disequilibria, and isotopic and compositional fractionation.

geochemistry↗
NASA NTRS1993

Detection of dust impacts by the Voyager planetary radio astronomy experiment

The Planetary Radio Astronomy (PRA) instrument detected large numbers of dust particles during the Voyager 2 encounter with Neptune. The signatures of these impacts are analyzed in some detail. The major conclusions are described. PRA detects impacts from all over the spacecraft body, not just the PRA antennas. The signatures of individual impacts last substantially longer than was expected from complementary Plasma Wave Subsystem (PWS) data acquired by another Voyager experiment. The signatures of individual impacts demonstrate very rapid fluctuations in signal strength, so fast that the data are limited by the speed of response of the instrument. The PRA detects events at a rate consistently lower than does the Plasma Wave subsystem. Even so, the impact rate is so great near the inbound crossing of the ring plane that no reliable estimate of impact rate can be made for this period. The data are consistent with the presence of electrons accelerated by ions within an expanding plasma cloud from the point of impact. An ancillary conclusion is that the anomalous appearance of data acquired at 900 kHz appears to be due to an error in processing the PRA data prior to their delivery rather than due to overload of the PRA instrument.

Evans, David R.↗
NASA NTRSDate not supplied

TechEdSat-13: The First Flight of an AI/ML Neuromorphic Processor

Neuromorphic processors, inspired by the wiring of the brain, permit certain classes of Artificial Intelligence/Machine Learning (AI/ML) algorithms to run far more efficiently. Ultimately, such systems will make the small- and nano-satellite platforms even more useful in terms of greatly improved power, communication and internal data management. In addition, on-board processing of images and data will help to not only rapidly interpret the information, but also reduce the amount of data that needs to be transmitted to ground stations. This initial flight experiment uses the Intel/ Loihi processor combined with a custom interface board and three communication channels to run the AI/ML scripts. These will vary with increasing length and complexity during the course of the mission. The algorithms will use the (at first) limited sensor data to ‘learn’ - with comparisons to similar architecture in comparable ground experiments. Some of the applications for successor flights in the TES-n flight series include Cognitive Communications, whereby the overall communication system is optimized per overflight – by optimizing timing and data transmission functions. Lastly, the performance of the Loihi 14nm process technology will be monitored for performance in the LEO radiation environment, thus looking for induced hardware and software errors. This information will help guide future radiation protection techniques to extend the lifetime and overall utility. The TES-13 is a 3U nanosat successfully launched by the Virgin Orbit Launcher-1 on January 13, 2022, and will presage more flights and AI/ML applications to come.

TechEdSat↗
NASA NTRS1983

Approach to establishing the effect of aeroelasticity on aerodynamic characteristics of the space shuttle orbiter

The static aeroelastic effects on the longitudinal stability and elevon/aileron effectiveness of the space transportation system (STS) Space Shuttle orbiter were estimated by a simplified approach called the elevon torsional stiffness (ETS) method. This method employs rigid model wind tunnel test results to predict aeroelastic effects. Lateral/directional stability and rudder effectiveness were based on results of a wind tunnel test in which a flexible tail model was used. Comparisons with selective flight data are made in this paper. Results of correlations with flight data (although limited at the present time) verify the predicted aeroelastic effects for the orbiter. The orbiter's structural characteristics are such that the effects of aeroelasticity, whether estimated using analytical techniques or simplified methods, do not appear to affect the vehicle performance to any great extent. The large amount of scatter in the flight-extracted data made verification of the aeroelastic corrections very difficult. Generally, the simplified elevon torsional stiffness method provided better correlation with flight test results than he analytical method and reduced the verification effort and cost.

Schlosser, D. C.↗
NASA NTRS2003

[Signal Processing Suite Design]

Our role in this project was to participate in the design of the signal processing suite to analyze plasma density measurements on board a small constellation (3 or 4) satellites in Low Earth Orbit. As we are new to space craft experiments, one of the challenges was to simply gain understanding of the quantity of data which would flow from the satellites, and possibly to interact with the design teams in generating optimal sampling patterns. For example, as the fleet of satellites were intended to fly through the same volume of space (displaced slightly in time and space), the bulk plasma structure should be common among the spacecraft. Therefore, an optimal, limited bandwidth data downlink would take advantage of this commonality. Also, motivated by techniques in ionospheric radar, we hoped to investigate the possibility of employing aperiodic sampling in order to gain access to a wider spatial spectrum without suffering aliasing in k-space.

Sahr, John D.↗
NASA NTRS2017

Hover Performance of Isolated Proprotors and Propellers - Experimental Data

The use of Computational Fluid Dynamics (CFD) is gaining momentum within the aeronautical community. A relatively small segment of this community is applying CFD technology in the prediction of VSTOL aircraft performance. An even smaller group of engineers are refining and applying fluid dynamics solvers to the problem of predicting hover performance of helicopter rotors and proprotors designed by rotorcraft advocates. This small group of CFD engineers who are attacking the hover performance problem have, today, been using a quite limited experimental data base upon which to demonstrate their progress. This is because their concentration has been on only two successful tiltrotor flying; namely the XV-15 and the MV-22B. No attention appears (as yet) to be directed at the CL-84 or the XC-142A. The purpose of this report is to expand the experimental data base of both proprotors and propellers so that comparisons of test and various theories can be made to several more configurations of these propulsive devices used by VSTOL aircraft.

Hover↗
NASA NTRS1981

Remote sensing research in geographic education: An alternative view

It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.

Wilson, H.↗
NASA NTRS1985

Tropospheric ozone - Seasonal behavior, trends, and anthropogenic influence

In the present analysis of tropospheric ozone data, attention is given to spatial and temporal variations. Two modes of seasonal behavior are noted for surface ozone at mid-latitudes: a broad summer maximum within a few hundred km of industrial/urban areas in Europe and the U.S., and a minimum in summer or autumn in sparcely populated regions that are remote from industrial activity. These and limited historical data indicate that summertime concentrations of ozone near the surface in the rural areas of Europe and the U.S. may have increased between 20 and 100 percent since the 1940s. It is suggested that the summer maximum in ozone and other observed trends are due to photochemical production associated with anthropogenic emissions of NO(x), hydrocarbons, and CO from fossil fuel combustion.

Logan, J. A.↗
NASA NTRSDate not supplied

Estimating Forest Stand Height in Savannakhet, Lao PDR Using InSAR and Backscatter Methods with L-Band SAR Data

Forest stand height (FSH), or average canopy height, serves as an important indicator for forest monitoring. The information provided about above ground biomass for greenhouse gas emissions reporting, and estimating carbon storage is relevant for reporting for Reducing Emissions from Deforestation and Forest Degradation (REDD+). A novel forest height estimation method utilizing a fusion of backscatter and Interferometric Synthetic Aperture Radar (InSAR) data from JAXA’s Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) are applied to a use case in Savannakhet, Lao. Compared with LiDAR, the estimated height from the fusion method had an RMSE of 4.90 m and an R2 of 0.26. These results are comparable to previous studies using SAR estimation techniques. Despite limitations of data quality and quantity, the Savannakhet, Lao use case demonstrates the applicability of these techniques utilizing L-band SAR data for estimating FSH in tropical forests and can be used as a springboard for use of L-band data from the future NASA-ISRO SAR (NISAR) mission.

remote sensing↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗
NASA NTRS1985

Magnetization models for the source of the 'Kentucky anomaly' observed by Magsat

Both the aeromagnetic data and magnetic anomaly data obtained by Magsat indicate the presence of a very magnetic source region within the crust beneath Kentucky and Tennessee. A source model was previously developed to fit surface gravity and long-wavelength aeromagnetic data, using limited seismic constraint. For the present study the model was further developed, and it is demonstrated that the source region for the satellite anomaly is considerably more extensive than the Kentucky body sensu stricto. The extended source region is modeled using both prismatic model sources and dipole array sources. Magnetization directions for the source region found by inversion of various combinations of scalar and vector data are found to be close to the main field direction, implying the lack of a strong remanent component. It is shown by simulation that in a case (such as this) where the geometry of the source is known, if a strong remanent component is present its direction is determinable, but by scalar data as readily as vector data. Magnetization magnitude for the extended source region is about 3 A/m if the vertical extent of the source includes the whole of the crust.

Mayhew, M. A.↗
NASA NTRS2007

Determination of the Far-Infrared Cosmic Background Using COBE/DIRBE and WHAM Data

Determination of the cosmic infrared background (CIB) at far infrared wavelengths using COBE/DIRBE data is limited by the accuracy to which foreground interplanetary and Galactic dust emission can be modeled and subtracted. Previous determinations of the far infrared CIB (e.g., Hauser et al. 1998) were based on the detection of residual isotropic emission in skymaps from which the emission from interplanetary dust and the neutral interstellar medium were removed. In this paper we use the Wisconsin H(alpha) Mapper (WHAM) Northern Sky Survey as a tracer of the ionized medium to examine the effect of this foreground component on determination of the CIB. We decompose the DIRBE far infrared data for five high Galactic latitude regions into HI- and H(alpha)- correlated components and a residual component. Eased on FUSE H2 absorption line observations, the contribution of a11 H2-correlated component is expected to he negligible. We find the H(alpha)-correlated component to be consistent with zero for each region, and we find that addition of an H(alpha)-correlated component in modeling the foreground emission has negligible effect on derived CIB results. Our CIB detections and 2(sigma) upper limits are essentially the same as those derived by Hauser et al. and are given by (nu)I(sub nu)(nW/sq m/sr) < 75, < 32, 25+/-8, and 13+/-3 at gamma = 60, 100, 140, and 240 microns, respectively. Our residuals have not been subjected to a detailed anisotropy test, so our CIB results do not supersede those of Hauser et al. Mie derive upper limits on the 100 micron emissivity of the ionized medium that are typically about 40% of the 100 micron emissivity of the neutral atomic medium. This low value may be caused in part by a lower dust-to-gas mass ratio in the ionized medium than in the neutral medium, and in part by a shortcoming of using H(alpha) intensity as a tracer of far infrared emission. If H(alpha) is not a reliable tracer, our analysis would underestimate the emissivity of the ionized medium, and both our analysis and the Hauser et al. analysis may slightly overestimate the CIB. We estimate the possible effect for the CIB to be only about 5%, which is much smaller than the quoted uncertainties. From a comparison of the Hauser et al. CIB results with the integrated galaxy brightness from Spitzer source counts, we obtain 2(sigma) upper limits on a possible diffuse CIB component that are 26 nW/sq m/sr at 140 microns and 8.5 nW/sq m/sr at 240 microns.

Odegard, N.↗
NASA NTRS2004

Evaluation of CO2, N2 and He as Fire Suppression Agents in Microgravity

The U.S. modules of the International Space Station use gaseous CO2 as the fire extinguishing agent. This was selected as a result of extensive experience with CO2 as a fire suppressant in terrestrial applications, trade studies on various suppressants, and experiments. The selection of fire suppressants and suppression strategies for NASA s Lunar and Martian exploration missions will be based on the same studies and normal-gravity data unless reduced gravity fire suppression data is obtained. In this study, the suppressant agent concentrations required to extinguish a flame in low velocity convective flows within the 20-sec of low gravity on the KC-135 aircraft were investigated. Suppressant gas mixtures of CO2, N2, and He with the balance being oxygen/nitrogen mixtures with either 21% or 25% O2 were used to suppress flames on a 19-mm diameter PMMA cylinder in reduced gravity. For each of the suppressant mixtures, limiting concentrations were established that would extinguish the flame at any velocity. Similarly, concentrations were established that would not extinguish the flame. The limiting concentrations were generally consistent with previous studies but did suggest that geometry had an effect on the limiting conditions. Between the extinction and non-extinction limits, the suppression characteristics depended on the extinguishing agent, flow velocity, and O2 concentration. The limiting velocity data from the CO2, He, and N2 suppressants were well correlated using an effective mixture enthalpy per mole of O2, indicating that all act via O2 displacement and cooling mechanisms. In reduced gravity, the agent concentration required to suppress the flames increased as the velocity increased, up to approximately 10 cm/s (the maximum velocity evaluated in this experiment). The effective enthalpy required to extinguish flames at velocities of 10 cm/s is approximately the same as the concentrations in normal gravity. A computational study is underway to further evaluate these findings.

Ruff, Gary A.↗