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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Spatial greenstone-gneiss relationships: Evidence from mafic-ultramafic xenolith distribution patterns

The distribution patterns of mafic-ultramafic xenoliths within Archaean orthogneiss terrain furnish an essential key for the elucidation of granite-greenstone relations. Most greenstone belts constitute mega-xenoliths rather than primary basin structures. Transition along strike and across strike between stratigraphically low greenstone sequences and xenolith chains demonstrate their contemporaneity. These terrains represent least deformed cratonic islands within an otherwise penetratively foliated deformed gneiss-greenstone crust. Whereas early greenstone sequences are invariably intruded by tonalitic/trondhjemitic/granodioritic gneisses, stratigraphically higher successions may locally overlap older gneiss terrains and their entrained xenoliths unconformably. The contiguity of xenolith patterns suggests their derivation as relics of regional mafic-ultramafic volcanic crustal units and places limits on horizontal movements between individual crustal blocks.

Glikson, A. Y.↗
DOE OSTI2017

Crop yield response to climate change varies with crop spatial distribution pattern

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40% by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Linking basin-scale and pore-scale gas hydrate distribution patterns in diffusion-dominated marine hydrate systems: DIFFUSION-DRIVEN HYDRATE GROWTH IN SANDS

The goal of this study is to computationally determine the potential distribution patterns of diffusion-driven methane hydrate accumulations in coarse-grained marine sediments. Diffusion of dissolved methane in marine gas hydrate systems has been proposed as a potential transport mechanism through which large concentrations of hydrate can preferentially accumulate in coarse-grained sediments over geologic time. Using one-dimensional compositional reservoir simulations, we examine hydrate distribution patterns at the scale of individual sand layers (1 to 20 m thick) that are deposited between microbially active fine-grained material buried through the gas hydrate stability zone (GHSZ). We then extrapolate to two- dimensional and basin-scale three-dimensional simulations, where we model dipping sands and multilayered systems. We find that properties of a sand layer including pore size distribution, layer thickness, dip, and proximity to other layers in multilayered systems all exert control on diffusive methane fluxes toward and within a sand, which in turn impact the distribution of hydrate throughout a sand unit. In all of these simulations, we incorporate data on physical properties and sand layer geometries from the Terrebonne Basin gas hydrate system in the Gulf of Mexico. We demonstrate that diffusion can generate high hydrate saturations (upward of 90%) at the edges of thin sands at shallow depths within the GHSZ, but that it is ineffective at producing high hydrate saturations throughout thick (greater than 10 m) sands buried deep within the GHSZ. As a result, we find that hydrate in fine-grained material can preserve high hydrate saturations in nearby thin sands with burial.

03 NATURAL GAS↗
DOE OSTI2024

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Comparative genomics reveals phylogenetic distribution patterns of secondary metabolites in Amycolatopsis species

Background: Genome mining tools have enabled us to predict biosynthetic gene clusters that might encode compounds with valuable functions for industrial and medical applications. With the continuously increasing number of genomes sequenced, we are confronted with an overwhelming number of predicted clusters. In order to guide the effective prioritization of biosynthetic gene clusters towards finding the most promising compounds, knowledge about diversity, phylogenetic relationships and distribution patterns of biosynthetic gene clusters is necessary. Results: Here, we provide a comprehensive analysis of the model actinobacterial genus Amycolatopsis and its potential for the production of secondary metabolites. A phylogenetic characterization, together with a pan-genome analysis showed that within this highly diverse genus, four major lineages could be distinguished which differed in their potential to produce secondary metabolites. Furthermore, we were able to distinguish gene cluster families whose distribution correlated with phylogeny, indicating that vertical gene transfer plays a major role in the evolution of secondary metabolite gene clusters. Still, the vast majority of the diverse biosynthetic gene clusters were derived from clusters unique to the genus, and also unique in comparison to a database of known compounds. Our study on the locations of biosynthetic gene clusters in the genomes of Amycolatopsis’ strains showed that clusters acquired by horizontal gene transfer tend to be incorporated into non-conserved regions of the genome thereby allowing us to distinguish core and hypervariable regions in Amycolatopsis genomes. Conclusions: Using a comparative genomics approach, it was possible to determine the potential of the genus Amycolatopsis to produce a huge diversity of secondary metabolites. Furthermore, the analysis demonstrates that horizontal and vertical gene transfer play an important role in the acquisition and maintenance of valuable secondary metabolites. Our results cast light on the interconnections between secondary metabolite gene clusters and provide a way to prioritize biosynthetic pathways in the search and discovery of novel compounds.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Optimal pattern distributions in Rete-based production systems

Since its introduction into the AI community in the early 1980's, the Rete algorithm has been widely used. This algorithm has formed the basis for many AI tools, including NASA's CLIPS. One drawback of Rete-based implementation, however, is that the network structures used internally by the Rete algorithm make it sensitive to the arrangement of individual patterns within rules. Thus while rules may be more or less arbitrarily placed within source files, the distribution of individual patterns within these rules can significantly affect the overall system performance. Some heuristics have been proposed to optimize pattern placement, however, these suggestions can be conflicting. This paper describes a systematic effort to measure the effect of pattern distribution on production system performance. An overview of the Rete algorithm is presented to provide context. A description of the methods used to explore the pattern ordering problem area are presented, using internal production system metrics such as the number of partial matches, and coarse-grained operating system data such as memory usage and time. The results of this study should be of interest to those developing and optimizing software for Rete-based production systems.

Scott, Stephen L.↗
NASA NTRS1987

Studies of vesicle distribution patterns in Hawaiian lavas

Basaltic lava flows are generally vesicular, and the broader facts relating to vesicle distribution have long been established; few studies have yet been made with a view to determining how and when vesicles form in the cooling history of the lava, explaining vesicle shape and size distribution, and gaining enough understanding to employ vesicles as a geological tool. Various avenues of approach exist by which one may seek to gain a better understanding of these ubiquitous structures and make a start towards developing a general theory, and three such avenues have recently been explored. One avenue involves the study of pipe vesicles; these are a well known feature of lava flows and are narrow pipes which occur near the base of many pahoehoe flow units. Another avenue of approach is that presented by the distinctive spongy pahoehoe facies of lava that is common in distal locations on Hawaiian volcanoes. A third avenue of approach is that of the study of gas blisters in lava. Gas blisters are voids, which can be as much as tens of meters wide, where the lava split along a vesicle-rich layer and the roof up-arched by gas pressure. These three avenues are briefly discussed.

Walker, George P. L.↗
NASA NTRS1973

Distribution pattern of temperature and biomass in the upwelling area along the NW coast of Africa

Atmospheric conditions and wind systems are considered together with temperature observations. Data from scanning radiometers in the infrared and television cameras for the visible were applied to derive temperature data over cloudfree regions. From the analyzed spacecraft data it is obvious that the distribution of temperature and nonconservative parameters is much more complicated than one might expect from conventional measurements onboard a ship.

Szekielda, K.-H.↗
DOE OSTI2015

Tectonics earthquake distribution pattern analysis based focal mechanisms (Case study Sulawesi Island, 1993–2012)

Indonesia is the meeting zone between three world main plates: Eurasian Plate, Pacific Plate, and Indo – Australia Plate. Therefore, Indonesia has a high seismicity degree. Sulawesi is one of whose high seismicity level. The earthquake centre lies in fault zone so the earthquake data gives tectonic visualization in a certain place. This research purpose is to identify Sulawesi tectonic model by using earthquake data from 1993 to 2012. Data used in this research is the earthquake data which consist of: the origin time, the epicenter coordinate, the depth, the magnitude and the fault parameter (strike, dip and slip). The result of research shows that there are a lot of active structures as a reason of the earthquake in Sulawesi. The active structures are Walannae Fault, Lawanopo Fault, Matano Fault, Palu – Koro Fault, Batui Fault and Moluccas Sea Double Subduction. The focal mechanism also shows that Walannae Fault, Batui Fault and Moluccas Sea Double Subduction are kind of reverse fault. While Lawanopo Fault, Matano Fault and Palu – Koro Fault are kind of strike slip fault.

58 GEOSCIENCES↗
NASA NTRS1979

The development of methods for predicting and measuring distribution patterns of aerial sprays

The capability of conducting scale model experiments which involve the ejection of small particles into the wake of an aircraft close to the ground is developed. A set of relationships used to scale small-sized dispersion studies to full-size results are experimentally verified and, with some qualifications, basic deposition patterns are presented. In the process of validating these scaling laws, the basic experimental techniques used in conducting such studies, both with and without an operational propeller, were developed. The procedures that evolved are outlined. The envelope of test conditions that can be accommodated in the Langley Vortex Research Facility, which were developed theoretically, are verified using a series of vortex trajectory experiments that help to define the limitations due to wall interference effects for models of different sizes.

Ormsbee, A. I.↗
NASA NTRS1981

The development of methods for predicting and measuring distribution patterns of aerial sprays

A set of relationships used to scale small sized dispersion studies to full size results are experimentally verified and, with some qualifications, basic deposition patterns are presented. In the process of validating these scaling laws, the basic experimental techniques used in conducting such studies both with and without an operational propeller were developed. The procedures that evolved are outlined in some detail. The envelope of test conditions that can be accommodated in the Langley Vortex Research Facility, which were developed theoretically, are verified using a series of vortex trajectory experiments that help to define the limitations due to wall interference effects for models of different sizes.

Ormsbee, A. I.↗