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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Jet Propulsion Laboratory: Annual Report 2008

Nothing is more exciting than when science mines the far end of our knowledge for the new and the unexpected. In 2008, the world was taken by surprise when JPL astronomers announced the discovery of organic compounds on a planet orbiting another star. We were equally excited to learn from the Spitzer Space Telescope that many, if not most, sun-like stars have rocky planets roughly similar to Earth. Together these are very intriguing clues in our quest to learn if there is life elsewhere in the universe, which certainly has to be one of the most profound mysteries of our age.There are times when, dealing with unknowns, we are reminded to be humble. Very impressive progress is being made by the team developing our next flagship mission, Mars Science Laboratory. Ther conclusion, however, is that it would not be safe to try to fly during the Mars launch window in 2009, and reset for the next opportunity in 2011. We are lucky to have valuable assets that support us as we venture into the unknown. One is the global Deep Space Network, which functions both as our communication gateway to our spacecraft across the solar system as well as a research tool itself in conducting radar astronomy. Our successes depend on our entire team, administrators and business specialists as much as technical people. There are those who help share our missions with the public, finding imaginative venues such as sending out dispatches on the Internet's Twitter.com during the Phoenix mission. We also benefit greatly from the intellectual infusion that comes from our unique identity as a division of the California Institute of Technology and a member of the NASA family.

National Aeronautics and Space Administration (NAS↗
NASA NTRS2013

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗
NASA NTRS2018

NASA's Space Launch System Moves into Testing and Integration

NASA's Space Launch System (SLS) has moved from design and manufacturing into testing and integration for its first flight as early as December 2019. In 2017, the NASA/industry team completed manufacturing of all major structural elements for the launch vehicle for Exploration Mission-I (EM-1 ). That work included shipping the first major flight hardware element to the launch site. The team processed all four RS-25 engines for stage integration, cast all 10 booster flight motor segments, and manufactured all five major sections of the core stage. The program also completed major structural work on the B-2 test stand at Stennis Space Center, which will be used for the core stage "green run" test; delivered the core stage and engine simulators used for training; and much of the transportation equipment for the core stage. Engineers completed structural testing on the upper stage/payload section of the vehicle as well as the engine section test article. In 2018, the program will deliver the Orion Stage Adapter (OSA) to Exploration Ground Systems (EGS) at KSC and send the test articles for the core stage liquid hydrogen tank, liquid oxygen tank, and intertank to NASA's Marshall Space Flight center for structural testing. Additionally, workers will begin the challenging process of integrating the major sections of the 212-foot EM-1 core stage. This work is focused on the initial Block 1 variant of SLS, capable of launching more than 70 metric tons (t) to low Earth orbit (LEO). However, work concurrently is underway on the Block lB variant, which will enable 105 t to LEO and more than 37t to trans-lunar injection (TLI). Block lB will be the workhorse vehicle of NASA's lunar exploration plans. As the needs of the nation's deep space exploration program grow, SLS performance is designed to evolve to a payload mass of 130 t to LEO and up to 45t to TLI. The advantages of this mass - as well as volume- are critical to the entire exploration architecture for deep space exploration. They translate to greater capability, greater infrastructure and operational simplicity, less overall mission risk, and opportunities to accomplish unprecedented exploration and discovery. This paper will discuss SLS progress to date and planned future work.

Honeycutt, John↗
NASA NTRS2016

Dynamic Stall Suppression Using Combustion-Powered Actuation (COMPACT)

Retreating blade stall is a well-known phenomenon that limits rotorcraft speed, maneuverability, and efficiency. Airfoil dynamic stall is a simpler problem, which demonstrates many of the same flow phenomena. Combustion Powered Actuation (COMPACT) is an active flow control technology, which at the outset of this work, had been shown to mitigate static and dynamic stall at low Mach numbers. The attributes of this technology suggested strong potential for success at higher Mach numbers, but such experiments had never been conducted. The work detailed in this report documents a 3-year effort focused on assessing the effectiveness of COMPACT for dynamic stall suppression at freestream conditions up to Mach 0.5. The work done has focused on implementing COMPACT on a high-lift rotorcraft airfoil: the VR-12. This selection was made in order to ensure that any measured benefits are over and above the capabilities of state-of-the-art high-lift rotorcraft airfoils. The detailed Computational Fluid Dynamics (CFD) simulations, wind-tunnel experiments, and system-level modeling conducted have shown the following: (1) COMPACT, in its current state of development, is capable of reducing the adverse effects of deep dynamic stall at Mach numbers up to 0.4; (2) The two-dimensional (2D) CFD results trend well compared to the experiments; and (3) Implementation of the CFD results into a system-level model suggest that significant rotor-level benefits are possible.

Matalanis, Claude G.↗
NASA NTRS2012

Global Long-Term SeaWiFS Deep Blue Aerosol Products available at NASA GES DISC

Long-term climate data records about aerosols are needed in order to improve understanding of air quality, radiative forcing, and for many other applications. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a global well-calibrated 13- year (1997-2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). Recently, global aerosol products derived from SeaWiFS with Deep Blue algorithm (SWDB) have become available for the entire mission, as part of the NASA Making Earth Science data records for Use in Research for Earth Science (MEaSUREs) program. The latest Deep Blue algorithm retrieves aerosol properties not only over bright desert surfaces, but also vegetated surfaces, oceans, and inland water bodies. Comparisons with AERONET observations have shown that the data are suitable for quantitative scientific use [1],[2]. The resolution of Level 2 pixels is 13.5x13.5 km2 at the center of the swath. Level 3 daily and monthly data are composed by using best quality level 2 pixels at resolution of both 0.5ox0.5o and 1.0ox1.0o. Focusing on the southwest Asia region, this presentation shows seasonal variations of AOD, and the result of comparisons of 5-years (2003- 2007) of AOD from SWDB (Version 3) and MODIS Aqua (Version 5.1) for Dark Target (MYD-DT) and Deep Blue (MYD-DB) algorithms.

Shen, Suhung↗
NASA NTRSDate not supplied

BioSentinel ISS mission: Analysis of ISS Flight Data and Lessons Learned

As we prepare for a future with a human presence on the Moon, Mars, and beyond, the need for countermeasures to protect astronauts against deep space radiation is ever pressing. However, our understanding of how life operates in the space environment, especially past the protection of the Van Allen radiation belts, is critically limited. BioSentinel, a biological CubeSat, aims to further investigate the effects of deep space ionizing radiation, utilizing the budding yeast Saccharomyces cerevisiae to examine the cell’s DNA damage response. The yeast wild type and a rad51Δ mutant strain defective for DNA damage repair will be monitored via the redox dye alamarBlue and a 3-color LED detection system. Selected as a secondary payload on Artemis I, BioSentinel will be the first deep space biological experiment in a half-century and the first biological CubeSat or free-flyer to ever reach a heliocentric orbit. Notably, BioSentinel is the only biological CubeSat to include an ISS control study in addition to a ground control. Comparisons between the ground, ISS, and free-flyer experiments will allow us to isolate the effects of deep space radiation from those of microgravity. The ISS study also provides a unique platform to conduct important technological and biological testing of BioSentinel’s instrumentation in preparation for the deep space mission. In this work, we use a series of data processing tools and scripts to analyze ISS flight data as well as samples exposed to simulated space radiation at Brookhaven National Laboratory, specifically looking at cell growth, metabolic activity, and duplication rates based on optical absorbance and alamarBlue kinetics. These analyses provide a crucial set of controls and a framework for analyzing and interpreting future data sets from the free-flyer, helping us gain further insight into the health risks astronauts will face when exposed to deep space radiation.

Kylie Lauren Lo-Wen Akiyama↗
DOE OSTI2022

Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria

To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate, often transiently, forming large protein assemblies. They are not well understood due to experimental challenges in capturing and characterizing protein-protein interactions (PPIs), especially transient ones. Using AF2Complex, we introduce a high-throughput, deep learning pipeline to identify PPIs within the Escherichia coli cell envelope and apply it to several proteins from an OMP biogenesis pathway. Among the top confident hits obtained from screening ~1500 envelope proteins, we find not only expected interactions but also unexpected ones with profound implications. Subsequently, we predict atomic structures for these protein complexes. These structures, typically of high confidence, explain experimental observations and lead to mechanistic hypotheses for how a chaperone assists a nascent, precursor OMP emerging from a translocon, how another chaperone prevents it from aggregating and docks to a β-barrel assembly port, and how a protease performs quality control. This work presents a general strategy for investigating biological pathways by using structural insights gained from deep learning-based predictions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Electronic Components and Circuits for Extreme Temperature Environments

Planetary exploration missions and deep space probes require electrical power management and control systems that are capable of efficient and reliable operation in very low temperature environments. Presently, spacecraft operating in the cold environment of deep space carry a large number of radioisotope heating units in order to maintain the surrounding temperature of the on-board electronics at approximately 20 C. Electronics capable of operation at cryogenic temperatures will not only tolerate the hostile environment of deep space but also reduce system size and weight by eliminating or reducing the radioisotope heating units and their associate structures; thereby reducing system development as well as launch costs. In addition, power electronic circuits designed for operation at low temperatures are expected to result in more efficient systems than those at room temperature. This improvement results from better behavior and tolerance in the electrical and thermal properties of semiconductor and dielectric materials at low temperatures. The Low Temperature Electronics Program at the NASA Glenn Research Center focuses on research and development of electrical components, circuits, and systems suitable for applications in the aerospace environment and deep space exploration missions. Research is being conducted on devices and systems for reliable use down to cryogenic temperatures. Some of the commercial-off-the-shelf as well as developed components that are being characterized include switching devices, resistors, magnetics, and capacitors. Semiconductor devices and integrated circuits including digital-to-analog and analog-to-digital converters, DC/DC converters, operational amplifiers, and oscillators are also being investigated for potential use in low temperature applications. An overview of the NASA Glenn Research Center Low Temperature Electronic Program will be presented in this paper. A description of the low temperature test facilities along with selected data obtained through in-house component and circuit testing will also be discussed. Ongoing research activities that are being performed in collaboration with various organizations will also be presented.

Patterson, Richard L.↗
DOE OSTI2023

Energy Assets Transformation Web Mapping Application

This submission contains the link and geospatial materials used in the Energy Assets Transformation Web Mapping Application. The zip file contains 19 geospatial layers in a file geodatabase called EAT.gdb to be grouped in the following categories. 1. Industrial Assets: Coal Generation Units Retirements 2012-2040 (EIA); Examples of Repurposing Projects (32 projects in total); Abandoned Coal Mines (CORD, SkyTruth); Abandoned or Orphaned Wells (for ten states only). 2. Energy Transition Communities: 48C (e) Tax Credits - Designated Energy Communities (IRA); Index of Deep Disadvantage; Local Energy Action Program (LEAP); EJ Index for Proximity to Hazardous Waste (EPA). 3. Regional Landscape: State-Level Funding Programs (relevant to repurposing projects, for 2022 and 2023 only); Coal Flows from Mine to Plant 2021 (EIA), Variable Renewable Energy Shares (Wind and Solar, 2021, EIA). 4. Supporting Infrastructure: Railroads (HIFLD), Electric Power Transmission Lines (HIFLD), Major Highways (NHPN, DOT), Major Ports (National Atlas of the U.S.); Independent System Operators (HIFLD), NERC Regions and Subregions (HIFLD).

abandoned coal mines↗
DOE OSTI2022

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is an imperative need to enhance grid emergency control to maintain system reliability and security. Towards this end, great progress has been made in developing deep reinforcement learning (DRL) based grid control solutions in recent years. However, existing DRL-based solutions have two main limitations: 1) they cannot handle well with a wide range of grid operation conditions, system parameters, and contingencies; 2) they generally lack the ability to fast adapt to new grid operation conditions, system parameters, and contingencies, limiting their applicability for real-world applications. Here, in this paper, we mitigate these limitations by developing a novel deep meta-reinforcement learning (DMRL) algorithm. The DMRL combines the meta strategy optimization together with DRL, and trains policies modulated by a latent space that can quickly adapt to new scenarios. We test the developed DMRL algorithm on the IEEE 300-bus system. We demonstrate fast adaptation of the meta-trained DRL polices with latent variables to new operating conditions and scenarios using the proposed method, which achieves superior performance compared to the state-of-the-art DRL and model predictive control (MPC) methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Deep Search for Decaying Dark Matter with XMM-Newton Blank-Sky Observations

Sterile neutrinos with masses in the keV range are well-motivated extensions to the Standard Model that could explain the observed neutrino masses while also making up the dark matter (DM) of the universe. If sterile neutrinos are DM then they may slowly decay into active neutrinos and photons, giving rise to the possibility of their detection through narrow spectral features in astrophysical x-ray data sets. Here, we perform the most sensitive search to date for this and other decaying DM scenarios across the mass range from 5 to 16 keV using archival XMM-Newton data. We reduce 547 Ms of data from both the MOS and PN instruments using observations taken across the full sky and then use this data to search for evidence of DM decay in the ambient halo of the Milky Way. We determine the instrumental and astrophysical baselines with data taken far away from the Galactic Center, and use Gaussian process modeling to capture additional continuum background contributions. No evidence is found for unassociated x-ray lines, leading us to produce the strongest constraints to date on decaying DM in this mass range.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

A deep PSPC obervation of the Cyg OB2 association

The Cyg OB2 Association contains six of the fifteen most luminous stars in the Galaxy as well as the most luminous and most heavily reddened Galactic star, Cyg OB2 #12. In addition, the association contains a number of Wolf-Rayet stars, at least one early-type binary (Cyg OB2 #5), and a trapezium-like system (Cyg OB2 #8). Though not physically associated with the association, the X-ray source Cyg X-3 lies within a half degree of the center of the association. The association is a known source of X-rays. The X-ray emission from this region includes a contribution from Cyg X-3, as well as coronal emission from OB stars and hot diffuse gas. The region was extensively sampled by the HEAO-2 IPC (136 ks, which includes a single pointing of 57 ks on the central region of the association). A 3.6 ks PSPC observation of this region was obtained in the AO1 pointing phase. In addition, the four brightest OB stars (Cyg OB2 #5, #8A, #9, and #12) have been extensively monitored with the VLA. These stars show evidence of strong radio variability, and nonthermal radio emission characteristics. Several of these radio observations were taken within about a month of an IPC observation, and the two PSPC observations. We obtained a 19.5 ks exposure of the Cyg OB2 Association using the ROSAT PSPC instrument. Scientific tasks included: (1) extracting the PSPC spectral distributions of the brightest OB stars; (2) comparing the 19.5 ks spectral data with the 3.6 ks spectral data; (3) investigating the long term X-ray variability (15 years); and (4) comparing the X-ray and radio variability.

Waldron, Wayne↗
NASA NTRS2000

Weather Support to the NASA Deep Space Network

This paper outlines the evolution and development of SMG weather support and describes the Goldstone forecast production currently being disseminated as well as the next generation forecast product planned for future implementation.

weather↗
DOE OSTI2022

CaMn 0.9 Ti 0.1 O 3 based redox catalysts for chemical looping – Oxidative dehydrogenation of ethane: Effects of Na 2 MoO 4 promoter and degree of reduction on the reaction kinetics

Reduction kinetics and stability of 20 wt% Na 2 MoO 4 -promoted CaMn 0.9 Ti 0.1 O 3 were investigated for its applications in Chemical Looping – Oxidative Dehydrogenation (CL-ODH) of ethane, a potential alternative for ethylene production with higher efficiency and lower emissions. Here, the present work reports a kinetics model and parameters for a Na 2 MoO 4 -promoted, Ti-doped CaMnO 3 (CaMn 0.9 Ti 0.1 O 3 ) redox catalyst under H 2 and C 2 H 4 . A first-order reaction model provides the best fit for the reduction of Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 under H 2 , while the C 2 H 4 reduction is well described by an Avrami–Erofe’ev model. The activation energy for C 2 H 4 oxidation is approximately three times higher than that for H 2 conversion, showing that the activation of C 2 H 4 is significantly more difficult on the surface of the redox catalyst. The reduction rate of Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 under H 2 at 750 °C is more than two orders of magnitude greater than that under C 2 H 4 , while the reduction rate of unpromoted CaMn 0.9 Ti 0.1 O 3 is comparable under H 2 and C 2 H 4 , showing that the addition of Na 2 MoO 4 effectively suppresses C 2 H 4 combustion relative to H 2 oxidation. The kinetics results for Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 confirm its excellent selectivity towards hydrogen combustion, making it a promising candidate under CL-ODH. Additionally, the stability of the CaMn 0.9 Ti 0.1 O 3 @ Na 2 MoO 4 core-shell structure, which was the underlying reason for the excellent selectivity, was examined under both shallow and deep reductions. It was determined that deep reduction of the redox catalyst, e.g. higher than 80% solid conversion, would lead to loss of sodium and hence to decreased selectivity for hydrogen combustion. In contrast, the core-shell structure was well-maintained, exhibiting excellent performance after 50 redox cycles when deep reduction of the redox catalyst was avoided. This study offers a basis for both the CL-ODH reactor design and redox catalyst optimizations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Learning physics at future $e^–e^+$ colliders with machine

Information deformation and loss in jet clustering are one of the major limitations for precisely measuring hadronic events at future $e^–e^+$ colliders. Because of their dominance in data, the measurements of such events are crucial for advancing the precision frontier of Higgs and electroweak physics in the next decades. We show that this difficulty can be well-addressed by synergizing the event-level information into the data analysis, with the techniques of deep neutral network. In relation to this, we introduce a CMB-like observable scheme, where the event-level kinematics is encoded as Fox-Wolfram (FW) moments at leading order and multi-spectra of spherical harmonics at higher orders. Then we develop a series of jet-level (w/ and w/o the FW moments) and event-level classifiers, and analyze their sensitivity performance comparatively with two-jet and four-jet events. As an application, we analyze measuring Higgs decay width at $e^–e^+$ colliders with the data of 5ab –1 @240GeV. The precision obtained is significantly better than the baseline ones presented in documents. We expect this strategy to be applied to many other hadronic- event measurements at future $e^–e^+$ colliders, and to open a new angle for evaluating their physics capability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Dissipation and Bathymetric Sensitivities in an Unstructured Mesh Global Tidal Model

Abstract The mechanisms and geographic distribution of global tidal dissipation in barotropic tidal models are examined using a high resolution unstructured mesh finite element model. Mesh resolution varies between 2 and 25 km and is especially focused on inner shelves and steep bathymetric gradients. Tidal response sensitivities to bathymetric changes are examined to put into context response sensitivities to frictional processes. We confirm that the Ronne Ice Shelf dramatically affects Atlantic tides but also find that bathymetry in the Hudson Bay system is a critical control. We follow a sequential frictional parameter optimization process and use TPXO9 data‐assimilated tidal elevations as a reference solution. From simulated velocities and depths, dissipation within the global model is estimated and allows us to pinpoint dissipation at high resolution. Boundary layer dissipation is extremely focused with 1.4% of the ocean accounting for 90% of the total. Internal tide friction is much more distributed with 16.7% of the ocean accounting for 90% of the total. Often highly regional dissipation can impact basin‐scale and even ocean wide tides. Optimized boundary layer friction parameters correlate very well with the physical characteristics of the locality with high friction factors associated with energetic tidal regions, deep ocean island chains, and ice covered areas. Global complex M 2 tide errors are 1.94 cm in deep waters. Total global boundary layer and internal tide dissipation are estimated, respectively, at 1.83 and 1.49 TW. This continues the trend in the literature toward attributing more dissipation to internal tides.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Revealing the closed pore formation of waste wood-derived hard carbon for advanced sodium-ion battery

Abstract Although the closed pore structure plays a key role in contributing low-voltage plateau capacity of hard carbon anode for sodium-ion batteries, the formation mechanism of closed pores is still under debate. Here, we employ waste wood-derived hard carbon as a template to systematically establish the formation mechanisms of closed pores and their effect on sodium storage performance. We find that the high crystallinity cellulose in nature wood decomposes to long-range carbon layers as the wall of closed pore, and the amorphous component can hinder the graphitization of carbon layer and induce the crispation of long-range carbon layers. The optimized sample demonstrates a high reversible capacity of 430 mAh g −1 at 20 mA g −1 (plateau capacity of 293 mAh g −1 for the second cycle), as well as good rate and stable cycling performances (85.4% after 400 cycles at 500 mA g −1 ). Deep insights into the closed pore formation will greatly forward the rational design of hard carbon anode with high capacity.

25 ENERGY STORAGE↗
DOE OSTI2023

Time-Resolved Line Shapes of Single Quantum Emitters via Machine Learned Photon Correlations

Solid-state single-photon emitters (SPEs) are quantum light sources that combine atomlike optical properties with solid-state integration and fabrication capabilities. SPEs are hindered by spectral diffusion, where the emitter’s surrounding environment induces random energy fluctuations. Timescales of spectral diffusion span nanoseconds to minutes and require probing single emitters to remove ensemble averaging. Photon correlation Fourier spectroscopy (PCFS) can be used to measure time-resolved single emitter line shapes, but is hindered by poor signal-to-noise ratio in the measured correlation functions at early times due to low photon counts. Here, we develop a framework to simulate PCFS correlation functions directly from diffusing spectra that match well with experimental data for single colloidal quantum dots. We use these simulated datasets to train a deep ensemble autoencoder machine learning model that outputs accurate, noiseless, and probabilistic reconstructions of the noisy correlations. Using this model, we obtain reconstructed time-resolved single dot emission line shapes at timescales as low as 10 ns, which are otherwise completely obscured by noise. This enables PCFS to extract optical coherence times on the same timescales as Hong-Ou-Mandel two-photon interference, but with the advantage of providing spectral information in addition to estimates of photon indistinguishability. Further, our machine learning approach is broadly applicable to different photon correlation spectroscopy techniques and SPE systems, offering an enhanced tool for probing single emitter line shapes on previously inaccessible timescales.

74 ATOMIC AND MOLECULAR PHYSICS↗