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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Differential Cratering of Synchronously Rotating Satellites by Ecliptic Comets

We use Monte Carlo methods to simulate impacts of ecliptic comets on the synchronously rotating satellites of giant planets. We reconfirm the long-standing prediction that the cratering rate should be much higher on the leading hemispheres than on the trailing hemisphere; indeed we find that previously published analytical formulations modestly underestimate the degree of apex-antapex asymmetry to be expected. We then compare our results to new mapping of impact craters on Ganymede, Callisto, and Triton. Ganymede reveals a pronounced apex-antapex asymmetry that is nonetheless much less than predicted. All of Triton's confirmed impact craters are clustered toward the apex of motion, far exceeding the predicted asymmetry. No asymmetry is observed on Callisto. In each case at least one of our basic assumptions must be wrong. Likely candidates include the following: (i) the surfaces of all but the most sparsely cratered satellites are saturated or nearly saturated with impact craters; (ii) these satellites have rotated nonsynchronously over geological time; (iii) most of the craters are made not by heliocentric (Sun-orbiting) comets and asteroids but rather by planetocentric (planet-orbiting) debris of indeterminate origin; or (iv) pathological endogenic resurfacing has created illusions of structure. Callisto's surface is readily classified as nearly saturated. Ganymede's bright terrains, although less heavily cratered than those of Callisto, can also be explained by crater densities approaching saturation on a world where endogenic processes were active. The leading alternative is nonsynchronous rotation, an explanation supported by the distribution of catenae (crater chains produced by impact of tidally disrupted comets). Triton's craters can be explained by planetocentric debris or by capricious resurfacing, but both hypotheses are inherently improbable.

Zahnle, Kevin↗
DOE OSTI2025

Transformation rate maps of dissolved organic carbon in the contiguous US

Riverine dissolved organic carbon (DOC) plays a vital role in regional and global carbon cycles. However, the processes of DOC conversion from soil organic carbon (SOC) and leaching into rivers are insufficiently understood, inconsistently represented, and poorly parameterized, particularly in land surface and Earth system models. As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux (P r ), accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. We then derive high-resolution P r maps over the contiguous US (CONUS) using SOC data from two different sources: the Harmonized World Soil Database v1.2 (HWSD) and SoilGrids 2.0. Both maps are developed following the same five major steps: (1) selecting independent catchments where observed riverine DOC data are available with reasonable quality; (2) estimating catchment-average SOC for the independent catchments; (3) estimating the P r values for these catchments based on the generic formula and catchment-average SOC; (4) developing a predictive model of P r with machine learning (ML) techniques and catchment-scale climate, hydrology, geology, and other attributes; and (5) deriving a national map of P r based on the ML model. For evaluation, we compare the DOC concentration derived using the P r map and the observed DOC concentration values at evaluation catchments. The resulting mean absolute scaled error and coefficient of determination are 0.73 and 0.47 for the HWSD-based model and 0.58 and 0.72 for the SoilGrids-based model, respectively, suggesting the effectiveness of the overall methodology. Efforts to constrain uncertainty and evaluate sensitivity of P r to different factors are discussed. To illustrate the use of such maps, we derive a riverine DOC concentration reanalysis dataset over CONUS. The two P r maps, robustly derived and empirically validated, lay a critical cornerstone for better simulating the terrestrial carbon cycle in land surface and Earth system models. Our findings not only set a foundation for improving our predictive understanding of the terrestrial carbon cycle at the regional and global scales, but also hold promises for informing policy decisions related to decarbonization and climate change mitigation. The data presented in this study are publicly available at https://doi.org/10.5281/zenodo.14563816 (Li et al., 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Abstract Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Software Architecture and Hardware Organization in Mu2e Solenoid Field Mapping System

Herein, the Mu2e field mapping system is designed to produce high accuracy field maps of the detector solenoid used in the experiment. The data acquisition system is mobile and uses a self-propelled mapper with rotating arms equipped with 3D Hall probes. The measurements require not only accurate magnetic field readouts, but also accurate locations of all Hall probes while measuring data. The latter is accomplished by using the laser tracker to measure positions of several retroreflectors on the field mapper during data acquisition. The measurement process requires scanning the whole space inside the large solenoid and takes many hours to complete, which necessitates its full automation. The automation software includes control of the mapper, readout of Hall and NMR probes and control of a laser tracker, including prediction of retroreflector positions and execution of quality control checks. The software architecture and data acquisition hardware of the field mapping system are described, with special attention given to control of the laser tracker and its integration with the rest of the system.

3d hall probes↗
DOE OSTI2023

Advancing wildlife connectivity in land use planning: a case study with four-toed salamanders

Stable habitat connections that wildlife can safely traverse are essential to biodiversity conservation and healthy ecosystems. We developed high-resolution landscape connectivity models to predict resistance to movement by a threatened wetland-obligate amphibian, the four-toed salamander ( Hemidactylium scutatum ), and identified priority management areas on the 13,000-ha Department of Energy Oak Ridge Reservation (ORR) from 2019 to 2022. We developed a resistance surface based on aerial light detection and ranging data (LiDAR), >30 years of field-based mapping of forest, hydrologic, and geologic features, and contemporary population surveys, alongside derived predictors at <1-m resolution. We then modeled predicted movement corridors using a circuit theory-based modeling approach. We worked closely with land management and natural resources personnel to integrate ecological modeling with broader land use priorities, monetary costs, and feasibility. We identified important terrestrial and aquatic areas on ORR and simulated management scenarios to promote stable connections for four-toed salamanders. This approach allowed us to narrow down a list of 438 potential habitat manipulation sites to 10 sites where open-bottomed culverts and buffers could be implemented. This smaller-scale restoration approach produced a similar increase in landscape connectivity while costing <20% of a larger-scale approach based on barrier removal. We successfully identified feasible, cost-effective management strategies that integrated knowledge from a variety of sources. In conclusion, we offer a strategy that permitted integration of wildlife management goals into infrastructure upgrades wherein wildlife was not an initial consideration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

ELM‐MOSART‐DOC: A Large‐Scale Riverine Dissolved Organic Carbon Model and Its Application Over the United States

Riverine dissolved organic carbon (DOC), primarily sourced from soil organic carbon (SOC), plays a crucial role in regional and global carbon cycles. However, the complexities of the underlying mechanisms and limited observations present significant challenges for predictive understanding of DOC at regional or larger scales. Recently, we developed a machine learning‐based (ML) map of DOC transformation rates, bridging the gap between SOC and DOC leaching flux and simplifying terrestrial DOC representation. Building on this advancement, we introduce ELM‐MOSART‐DOC, a DOC module integrated into the riverine component of the Energy Exascale Earth System Model (E3SM)—the Model for Scale Adaptive River Transport (MOSART). ELM‐MOSART‐DOC simulates DOC transport and transformation across both headwater streams and river networks, including those managed. Model validation demonstrates the ability of ELM‐MOSART‐DOC to accurately capture long‐term average DOC concentrations, with Kling‐Gupta Efficiency (KGE) scores of 0.58 and 0.76 at large and local stations, respectively. We further assess the impact of reservoirs through different simulation schemes, revealing that reservoirs significantly alter DOC fluxes by regulating streamflow patterns and promoting DOC mineralization. Model simulations indicate that reservoirs reduce total DOC flux from the Mississippi River into the ocean by 7.5%, with the long‐term average annual export decreasing from 3.34 to 3.14 teragrams (Tg) per year. ELM‐MOSART‐DOC integrates process‐based modeling with ML parameterization to enhance the predictive understanding of riverine biogeochemical processes. This approach reduces uncertainties in modeling regional and global carbon cycle ESMs and provides new insights into carbon cycling and its implications for global environmental change.

Li, Lingbo [Univ. of Houston, TX (United States); ↗
DOE OSTI2021

EPIsembleVis: A geo-visual analysis and comparison of the prediction ensembles of multiple COVID-19 models

In this work, we present EPIsembleVis, a web-based comparative visual analysis tool for evaluating the consistency of multiple COVID-19 prediction models. Our approach analyzes a collection of COVID-19 predictions from different epidemiological models as an ensemble and utilizes two metrics to quantify model performance. These metrics include (a) prediction uncertainty (represented as the dispersion of predictions in each ensemble) and (b) prediction error (calculated by comparing individual model predictions with the recorded data). Through an interactive visual interface, our approach provides a data-driven workflow for (a) selecting and constructing the COVID-19 model prediction ensemble based on the spatiotemporal overlap of available predictions of multiple epidemiological models, (b) quantifying the model performance using both the uncertainty of each model prediction ensemble, and the error of each ensemble member that represents individual model predictions, and (c) visualizing the spatiotemporal variability in the projection performance of individual models using a suite of novel ensemble visualization techniques, such as the data availability map, a spatiotemporal textured-tile calendar, multivariate rose chart, and time-series leaflet glyph. We demonstrate the capability of our ensemble visual interface through a case study that investigates the performance of weekly COVID-19 predictions, which are provided through the COVID-19 Forecast Hub UMass-Amherst Influenza Forecasting Center of Excellence [47] for the United States and United States Territories. The EPIsembleVis tool is implemented using open-source web technologies and adaptive system design, rendering it interoperable with Elasticsearch and Kibana for automatically ingesting COVID-19 predictions from online repositories, and it is generalizable for analyzing worldwide projections from more epidemiological models.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1976

On global gravity anomalies and two-scale mantle convection

The two-scale model of mantle convection developed by Richter and Parsons (1975) predicts that if the depth of the convective layer is about 600 km, then for a plate moving at 10 cm/yr, longitudinal convective rolls will be produced in about 50 million years, and the strike of these rolls indicates the direction of motion of the plate relative to the upper mantle. The paper tests these predictions by examining a new global free air gravity model complete to the 30th degree and order. The free air gravity map developed shows a series of linear positive and negative anomalies (with transverse wavelengths of about 2000 km) spanning the Pacific Ocean, crossing the Pacific rise and striking parallel to the Hawaiian seamounts. It is suggested that the pattern of these anomalies may indicate the presence of longitudinal convective rolls beneath the Pacific plates, a result which tends to support the predictions of Richter and Parsons.

Marsh, B. D.↗
DOE OSTI2025

Evolution of structure growth during dark energy domination: Insights from the cross-correlation of DESI galaxies with CMB lensing and galaxy magnification

We use a hybrid effective field theory (HEFT) model to constrain the evolution of low-redshift (z≲0.4) matter fluctuations by cross-correlating DESI Bright Galaxy Survey (BGS) legacy imaging with the latest cosmic microwave background (CMB) lensing maps from Planck and Atacama cosmology telescope. Our tomographic BGS analysis finds that the evolution and amplitude of matter fluctuations align with CMB-conditioned Λ cold dark matter predictions. When including DESI baryon acoustic oscillation (BAO) measurements we obtain σ8=0.876-0.067+0.051 from BGS alone. Jointly analyzing BGS and luminous red galaxy (LRG) cross-correlations with the same CMB lensing maps yields σ8=0.791±0.021. As a complementary approach we isolate the galaxy magnification signal from the cross-correlation of nonoverlapping BGS and LRG photometric redshift bins, ruling out the null-magnification hypothesis at 11σ. For the first time, we constrain quasilinear structure growth from the (finite-difference calibrated) galaxy magnification signal and find σ8=0.720±0.047(stat)±0.050(sys) assuming a linear bias model and including BAO data.

Sailer, Noah↗
NASA NTRS2024

Electrical Properties of Lunar Environment Used for Predicting Lunar RF Propagation Characteristics

This contribution treats the lunar propagation environment as a three region medium: lunar exosphere, lunar regolith, and lunar bedrocks. Then it provides models for predicting the electromagnetic characteristics of each region. The electromagnetic characteristics could be electric characteristics represented by the complex relative permittivity, or magnetic characteristics represented by the complex relative permeability or both electric and magnetic characteristics. The lunar exosphere and the lunar bedrocks have only electric characteristics. The lunar regolith has both electric and magnetic characteristics. The complex relative permittivity models for lunar regolith are mapping of the corresponding models for Earth surface components reported in ITU-R P. 527-6. The complex relative permittivity prediction model of lunar exosphere is expressed in terms of a plasma frequency similar to the ordinary wave critical frequency in the corresponding model for the ionosphere. Based on this fascicle the following can be concluded for the frequency bands of 390 MHz and above: • The lunar exosphere can be treated as a free space, • The lunar regolith can be considered as non-magnetic, • The regolith complex relative permittivity has no temperature dependence, • The real part of the regolith complex relative permittivity depends only on regolith bulk density and it has no frequency dependence, and • The variation of regolith complex relative permittivity with regolith depth should be taken into consideration. Moreover, at frequencies of 2400 MHz and above, the lunar regolith can be treated as a uniform medium with complex relative permittivity equal to the corresponding complex relative permittivity at the regolith surface.

Electrical Permittivity↗
NASA NTRS2019

Image Processing Methods for Coronal Hole Segmentation, Matching, and Map Classification

The paper presents the results from a multi-year effort to develop and validate image processing methods forselecting the best physical models based on solar image observations. The approach consists of selecting the physical models based on their agreement with coronal holes extracted from the images. Ultimately, the goal is to use physical models to predict geomagnetic storms. We decompose the problem into three subproblems: (i) coronal hole segmentation based on physical constraints, (ii) matching clusters of coronal holes between different maps, and (iii) physical map classification. For segmenting coronal holes, we develop a multi-modal method that uses segmentation maps from three different methods to initialize a level-set method that evolves the initial coronal hole segmentation to the magnetic boundary. Then, we introducea new method based on Linear Programming for matchingclusters of coronal holes. The final matching is then performedusing Random Forests. The methods were carefully validatedusing consensus maps derived from multiple readers, manualclustering, manual map classification, and method validation for50 maps. The proposed multi-modal segmentation method significantly outperformed SegNet, U-net, Henney-Harvey, and FCNby providing accurate boundary detection. Overall, the methodgave a 95.5% map classification accuracy.

Jatla, Venkatesh↗
NASA NTRS2000

Photogrammetrically Measured Distortions of Composite Structure Microwave Reflectors at Approximately 90 K

The Microwave Anisotropy Probe (MAP) Observatory, scheduled for a fall 2000 launch, is designed to measure temperature fluctuations (anisotropy) and produce a high sensitivity and high spatial resolution (better than 0.3 deg.) map of the cosmic microwave background (CMB) radiation over the entire sky between 22 and 90 GHz. MAP utilizes back-to-back composite Gregorian telescopes supported on a composite truss structure to focus the microwave signals into 10 differential microwave receivers. Proper position and shape of the telescope reflectors at the operating temperature of approximately 90 K is a critical element to ensuring mission success. We describe the methods and analysis used to validate the in-flight position and shape predictions for the reflectors based on photogrammetric (PG) metrology data taken under vacuum with the reflectors at approximately 90 K. Contour maps showing reflector distortion analytical extrapolations were generated. The resulting reflector distortion data are shown to be crucial to the analytical assessment of the MAP instrument's microwave system in-flight performance.

Mule, Peter↗
DOE OSTI2021

Experimentally Inferred Fusion Yield Dependencies of OMEGA Inertial Confinement Fusion Implosions

Statistical modeling of experimental and simulation databases has enabled the development of an accurate predictive capability for deuterium-tritium layered cryogenic implosions at the OMEGA laser. Here, a physics-based statistical mapping framework is described and used to uncover the dependencies of the fusion yield. This model is used to identify and quantify the degradation mechanisms of the fusion yield in direct-drive implosions on OMEGA. The yield is found to be reduced by the ratio of laser beam to target radius, the asymmetry in inferred ion temperatures from the $l$ = 1 mode, the time span over which tritium fuel has decayed, and parameters related to the implosion hydrodynamic stability. When adjusted for tritium decay and $l$ = 1 mode, the highest yield in OMEGA cryogenic implosions is predicted to exceed 2 × 10 14 fusion reactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2010

Predicting Airspace Capacity Impacts Using the Consolidated Storm Prediction for Aviation

Convective weather is currently the largest contributor to air traffic delays in the United States. In order to make effective traffic flow management decisions to mitigate these delays, weather forecasts must be made as early and as accurately as possible. A forecast product that could be used to mitigate convective weather impacts is the Consolidated Storm Prediction for Aviation. This product provides forecasts of cloud water content and convective top heights at 0- to 8-hour look-ahead times. The objective of this study was to examine a method of predicting the impact of convective weather on air traffic sector capacities using these forecasts. Polygons representing forecast convective weather were overlaid at multiple flight levels on a sector map to calculate the fraction of each sector covered by weather. The fractional volume coverage was used as the primary metric to determine convection s impact on sectors. Results reveal that the forecasts can be used to predict the probability and magnitude of weather impacts on sector capacity up to eight hours in advance.

Russell, Carl↗
DOE OSTI2022

Generalized Analysis of Dynamic Flow Fouling on Heat Transfer Surfaces

Several energy applications involve flow of untreated heat transfer fluids that contain trace amounts of mineral salts, such as calcium carbonate and calcium sulfate, which show reverse solubility with temperature. The gradual accretion of these salts onto the heat transfer surfaces causes fouling that degrades thermal performance over time. While fouling of bare surfaces has been extensively studied, fouling of nonwetting superhydrophobic or liquid-infused surfaces is less understood, especially under dynamic flow conditions. This study presents a systematic experimental analysis to elucidate dynamic flow fouling of calcium carbonate and calcium sulfate on smooth, superhydrophobic and liquid-infused surfaces in a generalized manner. Here, copper tubes with modified inner surface wettability are fabricated and subjected to forced convection at different flow rates and fouling salt concentrations. Fouling characteristics of the two salts on the different surfaces are examined through microstructural analysis, and quantified in terms of asymptotic fouling resistance that measures the total extent of fouling, and a threshold time, which correlates to the onset of significant fouling. Using Taguchi design of experiments, the study reports, for the first time, closed-form analytical relationships for the asymptotic fouling thermal resistance and threshold time on the Reynolds number, dimensionless concentration of fouling agent and dimensionless infused liquid viscosity that represents the different surface types in a unified manner. It is shown that the analytical model accurately predicts the fouling characteristics in up to about 97% of the data, based on which contour maps of optimum surface designs for minimizing fouling resistance are presented. The results provide information on designing surfaces for reduced fouling or for estimating the fouling characteristics for a given surface in applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Identifying common stored product insects using automated deep learning methods

Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Toxin-Antitoxin Systems Reflect Community Interactions Through Horizontal Gene Transfer

Bacterial evolution through horizontal gene transfer (HGT) reflects their community interactions. In this way, HGT networks do well at mapping community interactions, but offer little toward controlling them—an important step in the translation of synthetic strains into natural contexts. Toxin–antitoxin (TA) systems serve as ubiquitous and diverse agents of selection; however, their utility is limited by their erratic distribution in hosts. Here we examine the heterogeneous distribution of TAs as a consequence of their mobility. By systematically mapping TA systems across a 10,000 plasmid network, we find HGT communities have unique and predictable TA signatures. We propose these TA signatures arise from plasmid competition and have further potential to signal the degree to which plasmids, hosts, and phage interact. To emphasize these relationships, we construct an HGT network based solely on TA similarity, framing specific selection markers in the broader context of bacterial communities. This work both clarifies the evolution of TA systems and unlocks a common framework for manipulating community interactions through TA compatibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

static-subid: Deterministic subordinate UID/GID assignment for unprivileged containers

static-subid calculates predictable subordinate UID and GID ranges for Linux users based on their UID, ensuring consistent ID mappings across multiple systems. Unlike shadow-utils' sequential allocation (which depends on creation order), static-subid uses a deterministic formula that guarantees the same user UID always receives the same subordinate ID range. Subordinate IDs enable user namespaces for unprivileged container runtimes (Podman, Docker rootless mode, LXC) by mapping container UIDs/GIDs to host subordinate IDs without requiring root privileges.

Riehecky, Pat [Fermi National Accelerator Laborato↗