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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Validation (not just verification) of Deep Space Missions

ion & Validation (V&V) is a widely recognized and critical systems engineering function. However, the often used definition 'Verification proves the design is right; validation proves it is the right design' is rather vague. And while Verification is a reasonably well standardized systems engineering process, Validation is a far more abstract concept and the rigor and scope applied to it varies widely between organizations and individuals. This is reflected in the findings in recent Mishap Reports for several NASA missions, in which shortfalls in Validation (not just Verification) were cited as root- or contributing-factors in catastrophic mission loss. Furthermore, although there is strong agreement in the community that Test is the preferred method for V&V, many people equate 'V&V' with 'Test', such that Analysis and Modeling aren't given comparable attention. Another strong motivator is a realization that the rapid growth in complexity of deep-space missions (particularly Planetary Landers and Space Observatories given their inherent unknowns) is placing greater demands on systems engineers to 'get it right' with Validation.

verification↗
NASA NTRS2016

Photon Counting Detector Array Algorithms for Deep Space Optical Communications

For deep-space optical communications systems utilizing an uplink optical beacon, a single-photon-counting detector array on the flight terminal can be used to simultaneously perform uplink tracking and communications as well as accurate downlink pointing at photon-starved (pW/sq. m) power levels. In this paper, we discuss concepts and algorithms for uplink signal acquisition, tracking, and parameter estimation using a photon-counting camera. Statistical models of detector output data and signal processing algorithms are presented, incorporating realistic effects such as Earth background and detector/readout blocking. Analysis and simulation results are validated against measured laboratory data using state-of-the-art commercial photon-counting detector arrays, demonstrating sub-microradian tracking errors under channel conditions representative of deep space optical links.

beacon tracking↗
DOE OSTI2026

Federated learning for 2D synchrotron x-ray diffractometry: a cross-institutional approach for phase quantification of Ti–6Al–4V alloy

High-energy Two dimensional (2D) synchrotron x-ray diffractometry provides important insights into the atomistic structure and phase evolution of materials, yet traditional analysis methods remain complex, knowledge-intensive, and computationally demanding. Deep-learning models offer a powerful alternative for automating their analysis. Institutions that hold these datasets may be unwilling to share their data due to privacy and security policies, as well as the challenges associated with large-scale data transfer. As a result, models trained on local datasets often perform well only on their own data but exhibit bias and poor generalization across different instruments or facilities. To overcome these limitations, we explore federated learning (FL) for 2D synchrotron diffractograms, enabling collaborative model training without exchanging raw data. In this study, 2D synchrotron diffractograms of Ti–6Al–4V alloy collected from two independent facilities are used to train convolutional neural networks for predicting the β-phase volume fraction. Experimental results show that federated global models significantly outperform locally trained models in terms of generalization and achieve accuracy comparable to centralized trained models. These findings demonstrate the potential of FL to enable secure, cross-institutional collaboration and enhance the scalability of deep-learning-based materials characterization.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Microwave Radiometer RFI Detection Using Deep Learning

Radio frequency interference (RFI) is a risk for microwave radiometers due to their requirement of very high sensitivity. The Soil Moisture Active Passive (SMAP) mission has an aggressive approach to RFI detection and filtering using dedicated spaceflight hardware and ground processing software. As more sensors push to observe at larger bandwidths in unprotected or shared spectrum, RFI detection continues to be essential. This article presents a deep learning approach to RFI detection using SMAP spectrogram data as input images. The study utilizes the benefits of transfer learning to evaluate the viability of this method for RFI detection in microwave radiometers. The well-known pretrained convolutional neural networks, AlexNet, GoogleNet, and ResNet-101 were investigated. ResNet-101 provided the highest accuracy with respect to validation data (99%), while AlexNet exhibited the highest agreement with SMAP detection (92%).

Microwave radiometry↗
DOE OSTI2022

Water‐Induced Diamond Formation at Earth's Core‐Mantle Boundary

Abstract The carbon and water cycles in the Earth's interior are linked to key planetary processes, such as mantle melting, degassing, chemical differentiation, and advection. However, the role of water in the carbon exchange between the mantle and core is not well known. Here, we show experimental results of a reaction between Fe 3 C and H 2 O at pressures and temperatures of the deep mantle and core‐mantle boundary (CMB). The reaction produces diamond, FeO, and FeH x , suggesting that water can liberate carbon from the core in the form of diamond (“core carbon extraction”) while the core gains hydrogen, if subducted water reaches to the CMB. Therefore, Earth's deep water and carbon cycles can be linked. The extracted core carbon can explain a significant amount of the present‐day mantle carbon. Also, if diamond can be collected by mantle flow in the region, it can result in unusually high seismic‐velocity structures.

Ko, Byeongkwan↗
DOE OSTI2020

Alternative strategies of nutrient acquisition and energy conservation map to the biogeography of marine ammonia-oxidizing archaea

Ammonia-oxidizing archaea (AOA) are among the most abundant and ubiquitous microorganisms in the ocean, exerting primary control on nitrification and nitrogen oxides emission. Although united by a common physiology of chemoautotrophic growth on ammonia, a corresponding high genomic and habitat variability suggests tremendous adaptive capacity. Here, we compared 44 diverse AOA genomes, 37 from species cultivated from samples collected across diverse geographic locations and seven assembled from metagenomic sequences from the mesopelagic to hadopelagic zones of the deep ocean. Comparative analysis identified seven major marine AOA genotypic groups having gene content correlated with their distinctive biogeographies. Phosphorus and ammonia availabilities as well as hydrostatic pressure were identified as selective forces driving marine AOA genotypic and gene content variability in different oceanic regions. Notably, AOA methylphosphonate biosynthetic genes span diverse oceanic provinces, reinforcing their importance for methane production in the ocean. Together, our combined comparative physiological, genomic, and metagenomic analyses provide a comprehensive view of the biogeography of globally abundant AOA and their adaptive radiation into a vast range of marine and terrestrial habitats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Feature selection with distance correlation

Choosing which properties of the data to use as input to multivariate decision algorithms—also known as feature selection—is an important step in solving any problem with machine learning. While there is a clear trend towards training sophisticated deep networks on large numbers of relatively unprocessed inputs (so-called automated feature engineering), for many tasks in physics, sets of theoretically well-motivated and well-understood features already exist. Working with such features can bring many benefits, including greater interpretability, reduced training and run time, and enhanced stability and robustness. We develop a new feature selection method based on distance correlation, and demonstrate its effectiveness on the tasks of boosted top- and W -tagging. Using our method to select features from a set of over 7,000 energy flow polynomials, we show that we can match the performance of much deeper architectures, by using only ten features and two orders-of-magnitude fewer model parameters. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
NASA NTRS1980

A survey of numerical models for wind prediction

A literature review is presented of the work done in the numerical modeling of wind flows. Pertinent computational techniques are described, as well as the necessary assumptions used to simplify the governing equations. A steady state model is outlined, based on the data obtained at the Deep Space Communications complex at Goldstone, California.

Schonfeld, D.↗
NASA NTRS1990

Parsec-Scale Penetration of UV into Molecular Clouds: CII 158 Micron Mapping of W3, NGC 1977, and NGC 2023

The spatial distribution of the 158 microns CII fine structure line in the galactic sources W3, NGC 1977, and NGC 2023 is mapped. The emission arises from warm (100 to 300 K), dense photodissociation regions at the surface of molecular gas. In all three sources, the emission extends over parsec scales or greater. For W3 and NGC 1977, where the UV source/molecular cloud geometry presents an edge on view of the variation of CII intensity into the molecular gas, two dimensional models of the CII emission which include the effects of gas clumping and scattering by dust on the transport of UV photons are constructed. The observed CII distribution and intensity is well modeled by a clumpy or filamentary distribution to the molecular gas, with a clump/interclump gas density ratio of 100 or more, which allows deep penetration of carbon ionizing UV photons into the clouds. The penetration of UV into clumped molecular clouds may also explain the extended far IR continuum emission from these sources. The total luminosity of CII emission from a clumpy molecular cloud with adjacent or embedded octave band stars can be as much as an order of magnitude higher than the CII luminosity of a uniform cloud. In addition, the extended penetration of UV into molecular clouds will affect the abundances of atomic and molecular species and increase the fractional ionization of interclump gas and UV illuminated clump surfaces.

Howe, J. E.↗
NASA NTRS1992

Al Umchaimin depression, Western Iraq: An impact structure?

Al Umchaimin, in Arabic 'hiding place' or 'place of ambush', is located at latitude 32 degrees 35.5 N and longitude 39 degrees 25 E. The nearly circular depression averages 2.75 km in diameter and is 33-42 m deep. It is floored with fine-grained, clay-rich deposits, estimated to be 36 m thick, the surface of which shows well-developed desiccation fissures or mudcracks when dry. Because of its nearly circular planimetric shape and its apparent isolation from other surface and subsurface features, it has been considered by some to be a possible meteorite impact structure and by others to be a surface collapse feature that originated following removal of magma from the subsurface as the magma extruded elsewhere. Al Umchaimin was listed in the U.S. Geological Survey tabulation of 110 structures worldwide for which a meteorite impact origin had been suggested. It was placed in Category 6 Structures for which more data are required for classification. It is concluded that, on the basis of the studies that have been made of Al Umchaimin and on the basis of the brief site visit made, Al Umchaimin probably is not an impact structure but most likely resulted from the enlargement and coalescence of sink holes and eventual collapse of the roof material into the resulting cavity.

Underwood, James R., Jr.↗
NASA NTRS1993

Observation of 3-6 day meridional wind oscillations over the tropical Pacific, 1973-1992: Vertical structure and interannual variability

Rawinsonde data from tropical Pacific stations were examined for westward-propagating 3-6-day meridional wind oscillations in the troposphere and lower stratosphere, 1973-1992. Four types were identified from cross-spectrum and principal component analysis. (1) The dominant oscillation, near 250 mb, had a period slightly greater than 5 days, zonal wavenumber 4-6, and modified Rossby-gravity structure near the date line. (2) In the western Pacific lower troposphere there was broadband activity with short zonal scale, coupled to upper-tropospheric waves in NH summer. (3) In the central Pacific, during NH autumn, there was a well-defined approximately 4 1/2-day oscillation with maximum amplitude in the lower troposphere and baroclinic phase tilt above. The vertical structure suggested coupling to deep tropical convection; this interpretation was supported by correlation of meridional wind with antisymmetric outgoing longwave radiation. (4) In the stratosphere, Rossby-gravity waves had periods less than or equal to 4 days and zonal wavenumber 3-4. Unlike tropospheric waves, these disturbances were coherent in a shallow layer, largest in west phase of quasi-biennial oscillation (QBO) and annual cycle (NH winter-spring).

Dunkerton, Timothy J.↗
NASA NTRS1994

RJ 051542+0104.7: A new magnetic, eclipsing, cataclysmic variable

We present photometric and spectroscopic observations of a recently identified X-ray bright, magnetic cataclysmic variable, RJ 051542+0104.7. The X-ray source was discovered serendipitously by Walter et al. (1994; Walter & Zoonematkermani 1994), and their data imply the presence of a heated white dwarf compatible with a magnetic accretion column. Buckley (1994) has reported the presence of circular polarization. Our optical photometry shows that the system undergoes eclipses with a period of 7.9835 +/- 0.0002 hours. The eclipse is 1 magnitude deep and appears to be total. Our spectra were all obtained near eclipse and show a strong blue continuum with broad Balmer emission as well as He II (4686 and 5411 A), C III/N III (4650 A) and He I lines. The blue continuum and emission lines disappear during eclipse, leaving only the spectrum of a M0 star. Using the observed magnitude during eclipse and ignoring interstellar extinction, the distance is approximately 500 pc. For the secondary to fill its Roche lobe, it must be at least 20% larger than that of a normal dM0 star. This may indicate the red dwarf is far from local thermodynamic equilibrium (LTE) due to strong magnetic braking. We find evidence for cyclotron humps in the continuum spectrum which imply a magnetic field strength in the cyclotron emitting region of up to 55 MG. The unexpected existence of a long period AM Her system should provide constraints on models of polar evolution.

Garnavich, Peter M.↗
NASA NTRS2007

Antenna Technology and other Radio Frequency (RF) Communications Activities at the Glenn Research Center in Support of NASA's Exploration Vision

NASA s Vision for Space Exploration outlines a very ambitious program for the next several decades of the Space Agency endeavors. Ahead is the completion of the International Space Station (ISS); safely flight the shuttle (STS) until 2010; develop and fly the Crew Exploration Vehicle (Orion) by no later than 2014; return to the moon by no later than 2020; extend human presence across the solar system and beyond; implement a sustainable and affordable human and robotic program; develop supporting innovative technologies, knowledge and infrastructure; and promote international and commercial participation in exploration. To achieve these goals, a series of enabling technologies must be developed or matured in a timely manner. Some of these technologies are: spacecraft RF technology (e.g., high power sources and large antennas which using surface receive arrays can get up to 1 Gbps from Mars), uplink arraying (reduce reliance on large ground-based antennas and high operation costs; single point of failure; enable greater data-rates or greater effective distance; scalable, evolvable, flexible scheduling), software define radio (i.e., reconfigurable, flexible interoperability allows for in flight updates open architecture; reduces mass, power, volume), and optical communications (high capacity communications with low mass/power required; significantly increases data rates for deep space). This presentation will discuss some of the work being performed at the NASA Glenn Research Center, Cleveland, Ohio, in antenna technology as well as other on-going RF communications efforts.

Miranda, Felix A.↗
NASA NTRS1978

Radiation Hazard Detector

NASA technology has made commercially available a new, inexpensive, conveniently-carried device for protection, of people exposed to potentially dangerous levels of microwave radiation. Microwaves are radio emissions of extremely high frequency. They can be hazardous but the degree of hazard is not yet well understood. Generally, it is believed that low intensity radiation of short duration is not harmful but that exposure to high levels can induce deep internal burns, affecting the circulatory and nervous systems, and particularly the eyes. The Department of Labor's Occupational Safety and Health Administration (OSHA) has established an allowable safe threshold of exposure. However, people working near high intensity sources of microwave energy-for example, radar antennas and television transmitters-may be unknowingly exposed to radiation levels beyond the safe limit. This poses not only a personal safety problem but also a problem for employers in terms of productivity loss, workman's compensation claims and possible liability litigation. Earlier-developed monitoring devices which warn personnel of dangerous radiation levels have their shortcomings. They can be cumbersome and awkward to use while working. They also require continual visual monitoring to determine if a person is in a dangerous area of radiation, and they are relatively expensive, another deterrent to their widespread adoption. In response to the need for a cheaper and more effective warning system, Jet Propulsion Laboratory developed, under NASA auspices, a new, battery-powered Microwave Radiation Hazard Detector. To bring the product to the commercial market, California Institute Research Foundation, the patent holder, granted an exclusive license to Cicoil Corporation, Chatsworth, California, an electronic components manufacturer.

Source record↗
NASA NTRS2018

The Deep Space Gateway Lightning Mapper (DLM) - Monitoring Global Change and Thunderstorm Processes Through Observations of Earth's High-Latitude Lightning from Cis-Lunar Orbit

Function: Monitor global change and thunderstorm processes through observations of Earth's high-latitude lightning. This instrument will combine long-lived sampling of individual thunderstorms with long-term observations of lightning at high latitudes: How is global change affecting thunderstorm patterns; How do high-latitude thunderstorms differ from low-latitude? Why is the Gateway the optimal facility for this instrument / research: Expected DSG (Deep Space Gateway) orbits will provide nearly continuous viewing of the Earth's high latitudes (50 degrees latitude and poleward); These regions are not well covered by existing lightning mappers (e.g., Lightning Imaging Sensor / LIS, or Geostationary Lightning Mapper / GLM); Polar, Molniya, Tundra, etc. Earth orbits have significant drawbacks related to continuous coverage and/or stable FOVs (Fields of View).

Climate↗
NASA NTRS2016

Determination of Ceres Physical Parameters Using Radiometric and Optical Data

The Dawn spacecraft was launched on September 27th, 2007. Its mission is to rendezvous with and observe the two largest bodies in the main asteroid belt, Vesta and Ceres. It has completed over a year’s worth of direct observations of Vesta from early 2011 through late 2012. In the spring of 2015, the Dawn spacecraft entered orbit around the asteroid Ceres for the start of what is expected to be more than a year of science operations. The science data collected from this encounter consist of infrared (IR) images and spectra, visible images through a number of color filters, gamma ray detections and measurements of the Ceres gravity field. These data will be collected during several science phases: an Approach phase (1500000-4860 km from Ceres), a Survey orbit (4860 km radius), a High Altitude Mapping Orbit (HAMO) (1940 km radius) and a Low Altitude Mapping Orbit (LAMO) (855 km radius). The Approach phase included three Rotational Characterization (RC) opportunities. Designing each science orbit and successfully transferring into that orbit requires a sufficiently accurate estimate of Ceres physical parameters (body fixed frame, GM and harmonics). This paper focuses on work performed to estimate Ceres physical parameters using Deep Space Network (DSN) radiometric tracking data and optical measurements derived from science camera imagery. This paper describes planning for the data acquisition, as well as processing techniques and methodology. The trajectories predicted by the gravity field estimations are also compared with the actual as-flown trajectories. Observations of the gravity at high altitudes are found to be sufficient to design precision orbits at lower altitudes. Follow-up analysis after successfully reaching LAMO is included, as is a discussion of lessons learned.

Kennedy, Brian M.↗
NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗