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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 577 records · Page 32

Development of MCAERO wing design panel method with interactive graphics module

A reliable and efficient iterative method has been developed for designing wing section contours corresponding to a prescribed subcritical pressure distribution. The design process is initialized by using MCAERO (MCAIR 3-D Subsonic Potential Flow Analysis Code) to analyze a baseline configuration. A second program DMCAERO is then used to calculate a matrix containing the partial derivative of potential at each control point with respect to each unknown geometry parameter by applying a first-order expansion to the baseline equations in MCAERO. This matrix is calculated only once but is used in each iteration cycle to calculate the geometry perturbation and to analyze the perturbed geometry. The potential on the new geometry is calculated by linear extrapolation from the baseline solution. This extrapolated potential is converted to velocity by numerical differentiation, and velocity is converted to pressure by using Bernoulli's equation. There is an interactive graphics option which allows the user to graphically display the results of the design process and to interactively change either the geometry or the prescribed pressure distribution.

Hawk, J. D.↗

Contributions of Solar Wind and Micrometeoroids to Molecular Hydrogen in the Lunar Exosphere

We investigate the density and spatial distribution of the H2 exosphere of the Moon assuming various source mechanisms. Owing to its low mass, escape is non-negligible for H2. For high-energy source mechanisms, a high percentage of the released molecules escape lunar gravity. Thus, the H2 spatial distribution for high-energy release processes reflects the spatial distribution of the source. For low energy release mechanisms, the escape rate decreases and the H2 redistributes itself predominantly to reflect a thermally accommodated exosphere. However, a small dependence on the spatial distribution of the source is superimposed on the thermally accommodated distribution in model simulations, where density is locally enhanced near regions of higher source rate. For an exosphere accommodated to the local surface temperature, a source rate of 2.2 g s-1 is required to produce a steady state density at high latitude of 1200 cm-3. Greater source rates are required to produce the same density for more energetic release mechanisms. Physical sputtering by solar wind and direct delivery of H2 through micrometeoroid bombardment can be ruled out as mechanisms for producing and liberating H2 into the lunar exosphere. Chemical sputtering by the solar wind is the most plausible as a source mechanism and would require 10-50 of the solar wind H+ inventory to be converted to H2 to account for the observations.

Impact↗

Version 0 EOSDIS - An overview

Attention is given to NASA's Earth Observing System Data and Information System (EOSDIS), which is to be a single, distributed but internally consistent evolutionary system to support the planning and execution of EOS data acquisitions and to process, archive, and distribute EOS data products and selected non-EOS data to enable interdisciplinary studies of the earth. V0 EOSDIS, a logical step in this evolutionary process, is to address both technical and managerial challenges. Technical challenges include developing a multidiscipline, distributed system for searching and ordering data in a heterogeneous environment, and standardizing data formats and distribution techniques among differing communities and organizations. Managerial challenges include establishing and maintaining a structure consisting of geographically distributed entities such that cooperative development is carried out effectively despite organizational differences, maintaining interactions with the scientific community to ensure its close involvement despite its size and diversity, and keeping the expectations for V0 consistent with its schedules and resources.

Ramapriyan, H. K.↗

Synthetic Foveal Imaging Technology

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

Monacos, Steve P.↗

The effect of temperature and pressure on the distribution of iron group elements between metal and olivine phases in the process of differentiation of protoplanetary material

The distribution patterns of Ni, Co, Mn, and Cr were studied in olivines of various origins: from meteorites (chondrites, achondrites, pallasites), which are likely analogs of the protoplanetary material, to peridotite inclusions in kimberlite pipes, which are analogs of mantle material. According to X-ray microanalysis data, nickel is concentrated in peridotite olivines, while manganese is concentrated in meteoritic olivines. The maximum chromium content was found in ureilites, which were formed under reducing conditions. Experiments at pressures of 20 to 70 kbar and temperatures of 1100 to 2000 C have shown that in a mixture of olivine and Ni metal or NiO, nickel enters the silicate phase, displacing Fe into the metallic phase. Equilibrium temperatures were estimated from the Fe, Ni distribution coefficients between the metal and olivine: 1500 K for pallasites, 1600 K for olivine-bronzite H6 chondrites, 1200 K for olivine-hypersthene L6, 900 K for LL6, and 1900 K for ureilites (at P = 1 atm). The equilibrium conditions of peridotites are close to T = 1800 K and P over 100 kbar. It is concluded that there is a sharp difference between the conditions of differentiation of the protoplanetary material at the time meteorites were formed and the conditions of differentiation of the planets into concentric layers.

Vinogradov, A. P.↗

Geographic Distribution of Wetland Parameters: the Foundation of a Data Base

Few quantitative estimates exist concerning the large fluxes of various materials between wetlands and adjacent bodies of water and the atmosphere. Three areas research were identified which will aid in the quantitative assessment of wetland biogeochemical processes: (1) geographic distribution of wetland parameters, (2) the processes involved in wetland material fluxes, and (3) the extrapolation of local measurements of material fluxes and storage to large geographic areas.

Source record↗

Scalable low-loss cryogenic packaging of quantum memories in CMOS-foundry processed photonic chips

Optically linked solid-state quantum memories such as color centers in diamond are a promising platform for distributed quantum information processing and networking. Photonic integrated circuits (PICs) have emerged as a crucial enabling technology for these systems, integrating quantum memories with efficient electrical and optical interfaces in a compact and scalable platform. Packaging these hybrid chips into deployable modules while maintaining low optical loss and resiliency to temperature cycling is a central challenge to their practical use. We demonstrate a packaging method for PICs using surface grating couplers and angle-polished fiber arrays that is robust to temperature cycling, offers scalable channel count, applies to a wide variety of PIC platforms and wavelengths, and offers pathways to automated high-throughput packaging. Using this method, we show optically and electrically packaged quantum memory modules integrating all required qubit controls on chip, operating at millikelvin temperatures with <3 dB losses achievable from fiber to quantum memory for the TE 0 mode at a wavelength of 737 nm.

Bernson, Robert [Tyndall National Institute, Cork ↗

Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.

active distribution systems↗

LandScan mosaic enables high-resolution gridded population estimates with explicit uncertainty

Gridded population datasets represent high-resolution distributions of human occupancy, enabling informed decision-making across a broad range of fields. These data products are valuable for assessing environmental risk, urban development, disaster preparedness and resource allocation—areas where accurate population estimates directly enhance policy effectiveness and optimize resource distribution. Despite the importance of gridded population datasets, traditional population modeling approaches often overlook inherent uncertainties in the estimation process. This limitation can create a false sense of certainty in population estimates, potentially leading to flawed decisions by those who rely on the data. To address this methodological gap, we introduce a probabilistic machine learning modeling framework, LandScan Mosaic, that explicitly incorporates uncertainty into the population modeling process. Our approach systematically quantifies uncertainty in three key modeling parameters of the LandScan HD gridded population dataset: building use types, floor counts, and occupancy rates. By employing Monte Carlo simulations, we propagate these uncertainties through the modeling process, yielding probability distributions of population counts in place of deterministic point estimates. We demonstrate the practical application of this framework in Iloilo City, Philippines, using structured decision-making techniques and our probabilistic estimates to identify and prioritize areas most affected by projected flooding, supporting targeted interventions that address both economic and social risks. In doing so, we propose a population-specific approach for incorporating confidence into structured decision making processes. Through a comparative analysis with conventional deterministic approaches and point estimate approaches, including LandScan HD and WorldPop, we evaluate how the incorporation of machine learning and uncertainty influences decision rankings. This research advances population distribution modeling by offering a robust, quantitative approach that explicitly accounts for uncertainty in the underlying data, along with guidance for how users can apply uncertainty in their decision-making.

Environmental sciences↗

Performance Evaluation of Different Parallel Programming Models in SCALE-Shift Sequences for Criticality and Shielding Applications [Abstract]

The SCALE code system has been widely used for nuclear criticality safety, reactor physics, radiation shielding, source term generation, and inventory analyses by researchers, industry, and regulatory bodies. Although limited support for shared- and distributed-memory parallel processing was introduced via C++ threading, OpenMP, and MPI, a hybrid parallel programming model with both distributed- and shared-memory parallelism has not been fully supported in the SCALE code system.

Nuclear Criticality Safety Program (NCSP)↗

The ATLAS Workflow Management System Evolution in the LHC Run3 and towards the High-Luminosity LHC era

The ATLAS experiment has 18+ years of experience using workload management systems to deploy and develop workflows to process and to simulate data on the distributed computing infrastructure. Simulation, processing and analysis of LHC experiment data require the coordinated work of heterogeneous computing resources. In particular, the ATLAS experiment utilizes the resources of 250 computing centers worldwide, the power of supercomputing centres, and national, academic and commercial cloud computing resources. In this contribution, we present new techniques for cost-effectively improving efficiency introduced in workflow management system software. The evolution from a mesh framework to new types of computing facilities such as cloud and HPCs is described, as well as new types of production and analysis workflows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A new technique for predicting geosynchronous satellite collision probability

A new technique has been developed to predict the probability of an expired geosynchronous satellite colliding with an active satellite. This new technique employs deterministic methods for modeling the motion of satellites and applies statistical techniques to estimate the collision probability. The collision probability is used to estimate the expected time between collisions based on realistic distributions of expired and active satellites. The primary advantage of this new technique is that realistic distributions can be used in the prediction process instead of uniform distributions as has been used in previous techniques. The expected time between collisions based on a current NORAD database is estimated to be in the hundreds of years.

Mccormick, B.↗

RNAV Adherence Data Integration System Using Aviation and Environmental Sources

The RADI system described in this technical memorandum outlines a framework that can be used to fuse a variety of data including surveillance recordings, environmental observations, and procedural information to produce features that would otherwise not be observable by any single data source. The process is designed with scalability in mind so that large scale batch processing can be executed on a typical distributed cluster environment. This process was initially developed as a prototype to quickly assess adherence and iterate and engineer relevant features of interest that can assist in determining factors for non-adherence to procedural requirements.

Avrekh, Ilya↗

Applications of tethered satellites to some problems of terrestrial physics

An evaluation is made of the applicability of tethered satellites to geomagnetic field and low altitude magnetospheric/ionospheric plasma investigations. Geomagnetic field observations from tethered satellites with gradiometers promise higher field measurement accuracy and the separation of current effects; plasma observations are important in understanding such processes as the deposition of magnetospheric energy into the upper atmosphere, and the influence of magnetospheric current distribution on this process. The unusual requirements that emerge for attitude knowledge and dynamic isolation in the satellite's instrumentation are discussed.

Webster, William J., Jr.↗

Use of Open Networks and Delay-Tolerant Protocol to Decrease WAN Latency of EOS near Real-Time Data

Since 1999, NASA's Earth Observing System Data Operations System (EDOS) project at Goddard Space Flight Center (GSFC) has provided high-rate data capture, level zero processing, and product distribution services for a majority of NASA's EOS (Earth Observing System) high-rate missions, including Terra, Aqua, Aura, ICESat, EO-1, SMAP, and OCO-2. EDOS high-rate science and engineering (150-300 Mbps) data-driven capture systems are deployed at 7 worldwide ground stations which are connected via both private (closed) and public (open) wide area networks (WANs) to the centralized EDOS Level Zero Processing Facility (LZPF) located at GSFC, where the data is processed and Level 0 products are distributed to users worldwide. All data transferred over the open networks to GSFC traverse an IPSec tunnel, providing the same level of security as a VPN connection. EDOS produces both time-based and near real-time products (session-based). Near real-time data products are produced from a single ground station contact; time-based products are produced from multiple ground station contacts. EDOS is the primary supplier of EOS Level 0 data to the NASA near real-time user community known as the Land, Atmosphere Near real-time Capability for EOS (LANCE). For the past few years, EDOS has streamlined its systems to reduce WAN latency for near real-time data delivery, including implementing Quality of Service (QoS), expanding closed network bandwidth, adding open network connections with more bandwidth, and implementing a delay-tolerant protocol to mitigate long round-trip times to remote ground stations.

Delay-Tolerant Protocol↗

GES DISC Data Recipes in Jupyter Notebooks

The Earth Science Data and Information System (ESDIS) Project manages twelve Distributed Active Archive Centers (DAACs) which are geographically dispersed across the United States. The DAACs are responsible for ingesting, processing, archiving, and distributing Earth science data produced from various sources (satellites, aircraft, field measurements, etc.). In response to projections of an exponential increase in data production, there has been a recent effort to prototype various DAAC activities in the cloud computing environment. This, in turn, led to the creation of an initiative, called the Cloud Analysis Toolkit to Enable Earth Science (CATEES), to develop a Python software package in order to transition Earth science data processing to the cloud. This project, in particular, supports CATEES and has two primary goals. One, to transition data recipes created by the Goddard Earth Science Data and Information Service Center (GES DISC) into an interactive and educational environment using JupyterNotebooks. Two, to acclimate Earth scientists to cloud computing. To accomplish these goals, we create JupyterNotebooks to compartmentalize the different steps of data analysis and help users obtain and parse data from the command line. We also develop a Docker container, comprised of Jupyter Notebooks, Python dependencies, and command line tools, and configure it into an easy-to-deploy package. The end result is an end-to-end product that simulates the use case of end users working in the cloud computing environment.

discoverability↗

Statistical prediction with Kanerva's sparse distributed memory

A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presented. In conditions of near- or over-capacity, where the associative-memory behavior of the model breaks down, the processing performed by the model can be interpreted as that of a statistical predictor. Mathematical results are presented which serve as the framework for a new statistical viewpoint of sparse distributed memory and for which the standard formulation of SDM is a special case. This viewpoint suggests possible enhancements to the SDM model, including a procedure for improving the predictiveness of the system based on Holland's work with genetic algorithms, and a method for improving the capacity of SDM even when used as an associative memory.

Rogers, David↗