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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Joint Radioisotope Electric Propulsion Studies - Neptune System Explorer

The Neptune System Explorer (NSE) mission concept study assessed opportunities to conduct Cassini-like science at Neptune with a radioisotope electric propulsion (REP) based spacecraft. REP is based on powering an electric propulsion (EP) engine with a radioisotope power source (RPS). The NSE study was commissioned under the Joint Radioisotope Electric Propulsion Studies (JREPS) project, which sought to determine the technical feasibility of flagship class REP applications. Within JREPS, special emphasis was given toward identifying tall technology tent poles, as well as recommending any new RPS technology developments that would be required for complicated REP missions. Based on the goals of JREPS, multiple RPS (e.g. thermoelectric and Stirling based RPS) and EP (e.g. Hall and ion engines) technology combinations were traded during the NSE study to determine the most favorable REP design architecture. Among the findings from the study was the need for >400We RPS systems, which was driven by EP operating powers and the requirement for a long-lived mission in the deep solar system. Additionally multiple development and implementation risks were identified for the NSE concept, as well as REP missions in general. Among the strengths of the NSE mission would be the benefits associated with RPS and EP use, such as long-term power (approx. 2-3kW) at Neptune and flexible trajectory options for achieving orbit or tours of the Neptune system. Although there are still multiple issues to mitigate, the NSE concept demonstrated distinct advantages associated with using REP for deep space flagship-class missions.

radioisotope power source (RPS)↗
NASA NTRS2019

Scroll Filter System Development for Crewed Deep Space Missions

On board the International Space Station, particulate HEPA filters known as Bacterial Filter Elements (BFE's) are used as the main ventilation filters on the US modules. They consist of two stages of filtration, a static screen filter and a HEPA filter element. Historically, these filters have performed well during the life of the ISS. However, as NASA sets its sights towards mission beyond low earth orbit, or deep space, more capable filters requiring minimal maintenance will be essential because of the nature of these remote and of long duration missions. Therefore NASA is currently developing new filter systems for these mission. One of the filter designs being considered is a new filter system, coined the Scroll BFE. This filter provides two stages of filtration. The first stage is a pre-filter stage using a roll of screen media on a motorized spooling, or scrolling, mechanism to automate the change-out of the screen media in the flow. The second and finishing stage is a static HEPA filter element similar to the ones used on the ISS BFE's. The volume and dimensional format of the filter matches that of the ISS BFE which facilitates is deployment as potential future flight technology demonstration on board the ISS. Ground tests are underway to assess the filter system's performance under industrial standard test protocols applied in a custom designed filtration test stand. In addition, a method of generating relevant particulate matter loads, such as loose fibrous matter, is also being devised to challenge the filter in testing. The latter test challenge will help determine the pre-filter's capacity for handling layers of lint, or fibrous, particulate matter. Early results confirm HEPA efficiency performance of the HEPA stage. This paper will present the results of ground testing of the Scroll Filter System prototype.

Agui, Juan H.↗
NASA NTRS2014

Insights on TTL Dehydration Mechanisms from Microphysical Modelling of Aircraft Observations

The Tropical Tropopause Layer (TTL), a transition layer between the upper troposphere and lower stratosphere in the tropics, serves as the entryway of various trace gases into the stratosphere. Of particular interest is the transport of water vapor through the TTL, as WV is an important greenhouse gas and also plays a significant role in stratospheric chemistry by affecting polar stratospheric cloud formation and the ozone budget. While the dominant control of stratospheric water vapor by tropical cold point temperatures via the "freeze-drying" process is generally well understood, the details of the TTL dehydration mechanisms, including the relative roles of deep convection, atmospheric waves and cloud microphysical processes, remain an active area of research. The dynamical and microphysical processes that influence TTL water vapor concentrations are investigated in simulations of cloud formation and dehydration along air parcel trajectories. We first confirm the validity of our Lagrangian models in a case study involving measurements from the Airborne Tropical TRopopause EXperiment (ATTREX) flights over the central and eastern tropical Pacific in Oct-Nov 2011 and Jan-Feb 2013. ERA-Interim winds and seasonal mean heating rates from Yang et al. (2010) are used to advance parcels back in time from the flight tracks, and time-varying vertical profiles of water vapor along the diabatic trajectories are calculated in a one-dimensional cloud model as in Jensen and Pfister (2004) but with more reliable temperature field, wave and convection schemes. The simulated water vapor profiles demonstrate a significant improvement over estimates based on the Lagrangian Dry Point, agreeing well with aircraft observations when the effects of cloud microphysics, subgrid-scale gravity waves and convection are included. Following this approach, we examine the dynamical and microphysical control of TTL water vapor in the 30ºS-30ºN latitudinal belt and elucidate the dominant processes in the winter and summer seasons. Implications of the TTL dehydration processes for the regulation of global stratospheric humidity will be discussed.

stratosphere↗
NASA NTRSDate not supplied

Neurovascular Responses to Simulated Deep Space Radiation in a Human Organ-on-a-Chip Model

A major health risk for human deep space exploration is central nervous system (CNS) damage by galactic cosmic ray radiation. Simulated galactic cosmic rays or their components, especially the high-linear energy transfer (LET) particles such as 56Fe ions, have been shown to cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates interactions between CNS and the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuroinflammation. However, there have been few studies on BBB and astrocyte functions in regulating CNS responses, especially in human tissue analogs. Therefore, we utilized a high-throughput 3D organ-on-a-chip system, seeded with human induced pluripotent stem cell-derived astrocytes and brain endothelial cells, or brain endothelial cells alone, to study human neurovascular responses to simulated deep space radiation. We investigated the permeability and morphology of vascular structures formed by endothelial cells, as well as oxidative stress and secreted cytokines and chemokine levels over 1-7 days after irradiation with 0.25 – 0.5 Gy 5-ion simplified simulated galactic cosmic rays or 0.3 – 0.8 Gy high-LET 600 MeV/n 56Fe particles, and compared the outcomes to low-LET X-ray irradiation. We observed that simulated deep space radiation caused delayed astrocyte activation in a pattern resembling CNS responses to brain injury, caused oxidative stress and the production of inflammatory cytokines, and compromised BBB integrity by damaging tight junctions, thus increasing vascular permeability. Furthermore, our results indicate that astrocytes have a dual role in regulating radiation responses: they exacerbate blood-brain barrier permeability early after irradiation, followed by switching to a more protective scar-like phenotype by reducing oxidative stress and pro-inflammatory cytokine and chemokine secretion. In a follow-up study using the same platform, we investigated the dose-rate effects of ionizing radiation, by exposing our model to chronic, low dose-rate, gamma radiation. Our model was significantly improved by adding additional cell types composing the BBB, modelling immune cell infiltration into the brain, and studying the effect of an antioxidant, to measure more complex outcomes and model more closely the effect of deep space radiation on the human BBB. In summary, our results present a human neurovascular model for space radiation studies and potential future automated payload adaptation, and suggest astrocyte regulatory mechanisms as targets for countermeasures to mitigate human neurovascular impairments during deep space exploration.

Ionizing radiation↗
DOE OSTI2021

Consensus Equilibrium for Subsurface Delineation

Heterogeneity and insufficient site characterization limit our knowledge of the subsurface. Inversion techniques, which minimize the mismatch between observations and model predictions, have become an essential tool of subsurface characterization. Most optimization-based approaches fail to incorporate various implicit priors and capture the geological complexity. We overcome these limitations by deploying the plug-and-play and consensus equilibrium (CE) strategies, which provide a flexible framework for image reconstruction. Our CE methodology for spatial delineation of geologic formations consists of an image denoiser and a variational auto-encoder (deep learning-based emulator). The former ameliorates the reconstruction noise, yielding well-defined geological structures; its mathematical equivalence with the proximal operator allows the deployment of advanced denoisers (e.g., CNN-based denoiser) that do not correspond to a regularization objective. The latter defines a geology prior that imposes a geological constraint, for example, continuity and shape of geological features, onto the reconstructed image. Here, we conduct a series of numerical experiments dealing with transient two-dimensional flow driven by a pumping well and natural hydraulic head gradient. They demonstrate the CE framework's ability to delineate, both probabilistically and deterministically, complex subsurface environments with sufficient quality.

42 ENGINEERING↗
DOE OSTI2023

Using the Shallow Strain Tensor to Characterize Deep Geologic Reservoirs

Abstract Storing and recovering water, carbon, and heat from geologic reservoirs is central to managing resources in a changing climate. We tested the hypothesis that the strain tensor caused by injecting or producing fluids can be measured at shallow depths and interpreted to advance understanding of underlying deep aquifers or reservoirs. Geodetic‐grade strainmeters were deployed at 30 m depth overlying the Bartlesville Formation, a 500‐m‐deep sandstone near Tulsa, OK. The strainmeters are 220 m east of injection well 9A completed in a permeable lens at the base of the Bartlesville Formation. Water was injected into well 9A at approximately 1.0 L/s during four tests that ranged in duration from a few hours to a few weeks. The horizontal strain increased (tension) and the circumferential strain was a few times larger than the radial strain. The vertical strain decreased (compression) during injection. Strain rates were approximately 100 nε/day during the first few hours, but the rates decreased and were approximately 10 nε/day during most of the tests. Four independent methods of poroelastic simulation and inversion predict reservoir properties and geometries that are similar to each other and consistent with independent information about the reservoir. All strain interpretations predict that a boundary to the permeable lens occurs beneath the vicinity of the strainmeters, which is consistent with core data from the site. The boundary of the permeable lens is located by matching the vertical, radial and circumferential strains, which demonstrates the value of measuring the strain tensor.

Murdoch, Lawrence C.↗
DOE OSTI2023

Accelerating network layouts using graph neural networks

Graph layout algorithms used in network visualization represent the first and the most widely used tool to unveil the inner structure and the behavior of complex networks. Current network visualization software relies on the force-directed layout (FDL) algorithm, whose high computational complexity makes the visualization of large real networks computationally prohibitive and traps large graphs into high energy configurations, resulting in hard-to-interpret “hairball” layouts. Here we use Graph Neural Networks (GNN) to accelerate FDL, showing that deep learning can address both limitations of FDL: it offers a 10 to 100 fold improvement in speed while also yielding layouts which are more informative. We analytically derive the speedup offered by GNN, relating it to the number of outliers in the eigenspectrum of the adjacency matrix, predicting that GNNs are particularly effective for networks with communities and local regularities. Finally, we use GNN to generate a three-dimensional layout of the Internet, and introduce additional measures to assess the layout quality and its interpretability, exploring the algorithm’s ability to separate communities and the link-length distribution. The novel use of deep neural networks can help accelerate other network-based optimization problems as well, with applications from reaction-diffusion systems to epidemics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

KF·B(OH) 3 : a KBBF-type material with large birefringence and remarkable deep-ultraviolet transparency

In this work, we discuss a designed material with large birefringence and remarkable deep-ultraviolet transparency, KF·B(OH) 3 that has been discovered. The well-aligned [F·B(OH) 3 ] – layers endow a very large bandgap (7.63 eV), comparably large birefringence (0.114 @1064 nm), and the reinforced interlayer bonding of ca. 2.16 × KBe 2 BO 3 F 2 .

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

Image Search for Scientific Data (camBIR) v1.0

camBIR is the CAMERA based image retrieval, a software that takes several different kinds of imagery, such as 2 dimensional images, both scientific as well as non scientific. camBIR is specially designed for training different kinds of Deep Convolutional Neural Network, including new Deep Learning architectures, such as ResNet, Inception-ResNet, NasNet, DenseNet…. It can be used to automate the classification, sort and rank of X-ray imagery such as microCT, GISAXS, GIWAXS, SAXS and WAXS.

Ushizima, Daniela↗
DOE OSTI2023

Transient Pressure Interference During CO2 Injection in Saline Aquifers

Abstract CO2 injection in subsurface geological formations (e.g. deep saline aquifers) causes pressure perturbations over a large area surrounding the injection well. Observation wells are widely considered in geologic CO2 storage (GCS) projects where the pressure perturbation induced by CO2 injection is measured. In this work, we use analytical and numerical modeling tools along with field data to examine the pressure behavior in GCS projects before and after CO2 arrival at an observation well. Prior to CO2 arrival, a baseline pressure trend is established which corresponds to single-phase brine flow across the observation well (approximated by Theis solution). Therefore, analysis of early-time pressure data is straightforward, provides the single-phase flow characteristics (mobility and storativity), and helps establishing a baseline pressure change that can be extended beyond the single-phase flow period at the observation well. Upon CO2 arrival, a departure from this baseline trend is expected. For the pressure to detect the CO2 arrival at an observation well, the departure from baseline pressure behavior must be significant and well above the background noise levels. We use existing analytical models to determine the strength of the expected pressure departure signal from the baseline trend upon CO2 arrival. The strength of the expected pressure departure is found to be directly proportional to the mobility ratio. Accordingly, we establish a criterion to determine whether the pressure at an observation well can detect the CO2 arrival. We present an analysis approach through application to synthetic and field data and show the characteristic pressure behavior before and after CO2 arrival. We show that while generally the pressure can be either above or below the expected baseline pressure trend, it would be likely above the baseline upon CO2 arrival. This is because the mobility ratio becomes less than unity after CO2 arrival. We show that depending on the reservoir characteristics, changes in the pressure trend may or may not be sufficient to detect the CO2 arrival.

Engineering↗
DOE OSTI2021

Geologic Assessment and Recommended New Well Locations to Improve the Area 25 Potable Water System, Nevada National Security Site

The Mission Support and Test Services, LLC (MSTS) Geoscience Operations Group performed a hydrogeologic study of an area of interest in Area 25 at the request of the MSTS Enterprise Infrastructure Program to identify potential locations for a new water well to replace J-14 Water Well (J-14 WW). Based on limited subsurface hydrogeologic data for the area, geologists developed two options for construction of a new well. Option 1 is to construct the well within approximately 250 feet (ft) of J-14 WW, and Option 2 is to construct the well approximately 1,550 ft north of J-11 Water Well (J-11 WW). Option 1 may be preferred, as the hydrogeology is better understood adjacent to an existing well. A well drilled at the Option 2 location would not have to be as deep as that at the Option 1 location, but the hydrogeologic setting is more uncertain at this greater distance from a verified subsurface geologic data point.

58 GEOSCIENCES↗
DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Identifying and Explaining Anomalous Activity in Surveillance Video with Compression Algorithms

The primary purpose of this document is to outline the progress made on the LDRD titled “Identifying and Explaining Anomalous Activity in Surveillance Video with Compression Algorithms” in FY22 and FY23. In this LDRD, we explored the usage of compression-based analytics to identify anomalous activity in video. We developed a novel algorithm, Spatio-Temporal N-Gram PPM (STNG PPM) that accounts for spatially and temporally aware anomalies in video. We extracted features using motions vectors from video as well as operating on the raw features. STNG PPM is comparable to many deep learning approaches but does not require specialized hardware (GPUs) to run efficiently. We also examine the evaluation metrics and propose novel measures addressing faults in the current evaluation measures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Facilitating the exploitation of ERTS-1 imagery using snow enhancement techniques

The author has identified the following significant results. The applications of ERTS-1 imagery for geological fracture mapping regardless of season has been repeatedly confirmed. The enhancement provided by a differential cover of snow increases the number and length of fracture-lineaments which can be detected with ERTS-1 data and accelerates the fracture mapping process for a variety of practical applications. The geological mapping benefits of the program will be realized in geographic areas where data are most needed - complex glaciated terrain and areas of deep residual soils. ERTS-1 derived fracture-lineament maps which provide detail well in excess of existing geological maps are not available in the Massachusetts-Connecticut area. The large quantity of new data provided by ERTS-1 may accelerate and improve field mapping now in progress in the area. Numerous other user groups have requested data on the techniques. This represents a major change in operating philosophy for groups who to data judged that snow obscured geological detail.

Wobber, F. J.↗
NASA NTRS1982

Analysis of general-aviation accidents using ATC radar records

It is pointed out that general aviation aircraft usually do not carry flight recorders, and in accident investigations the only available data may come from the Air Traffic Control (ATC) records. A description is presented of a technique for deriving time-histories of aircraft motions from ATC radar records. The employed procedure involves a smoothing of the raw radar data. The smoothed results, in combination with other available information (meteorological data and aircraft aerodynamic data) are used to derive the expanded set of motion time-histories. Applications of the considered analytical methods are related to different types of aircraft, such as light piston-props, executive jets, and commuter turboprops, as well as different accident situations, such as takeoff, climb-out, icing, and deep stall.

Wingrove, R. C.↗
NASA NTRS1985

Nd and Sr isotopic compositions of tektite material from Barbados and their relationship to North American tektites

The isotopic composition of microtektites from Barbados was determined to establish their possible source and their relationship to known tektite strewn fields. Analyzed samples included microtektites and tektite fragments from the Barbados oceanic beds, samples of deep sea ooze, in which they occur, and of underlying volcanic ash, as well as glass beads from Lake Wanapitei Crater. Isotope ratios (Sr-87/Sr-86, Nd-143/Nd-144, Rb-87/Sr-86, and Sm-147/Nd-144) were determined, and the epsilon values for Sr and Nd plotted on the diagram available for the fields of North America, Australia, Ivory Coast, and Moldavite tektites. The epsilon coordinates of all Barbados microtektite and bulk tektite samples plot precisely within the narrow field determined by North American tektites (epsilon Sr, 111; epsilon Nd, -6.2), yield an Nd model age of 0.6 AE, and are distinct from all other fields. The isotopic signatures of samples from sea ooze, ash layer, and of the Lake Wanapitei glass beads are clearly different from all known tektite classes. It is concluded that the Barbados tektites are of the same source and temporal event as the North American tektites.

Ngo, H. H.↗
NASA NTRS2003

A Study of the X-ray Source Population in the Dwarf Galaxy NGC 6822

The dlrr galaxy NGC 6822 is a distant member of the Local Group. It is a site of recent star formation, rich in HII regions and OB associations, as well as containing an older globular cluster population. We present results of a deep Chandra observation of NGC 6822. The brightest source is extended and most likely a SNR. In addition to spectral analysis of the brightest sources, we extend the luminosity function down to the 10(sup)35 erg/s range.

Tennant, Allyn F.↗