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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Parallel processing for scientific computations

The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.

Alkhatib, Hasan S.↗
NASA NTRS2004

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Alena, Richard I.↗
DOE OSTI2026

Queen bees offload pesticide burden to eggs when social buffering is overwhelmed

Honey bee colonies pollinate about one-third of the world’s food crops, and their rapid decline directly threatens agricultural productivity and ecosystem stability. Understanding how colony-level social defenses influence pesticide fate and the circumstances under which they fail is therefore a crucial question in pollinator biology. We used biological accelerator mass spectrometry (BioAMS), a sensitive radiotracer technique, to track the movement of a model pesticide through a small honey bee colony under laboratory conditions. We tested the hypothesis that social buffering protects honey bees from toxic accumulation and that this protection can be overcome, leading to maternal offloading of the pesticide to developing eggs. Consistent with this hypothesis, our results identified three key mechanisms governing chemical movement within a social insect colony: (1) worker bees initially decrease dietary pesticide levels by 95% through diet filtering and deposition in honeycombs, though this declines to 86% by day 10; (2) queen bees maintain markedly lower pesticide levels than workers but, over time, they accumulate the pesticide in their ovaries and transfer it into developing eggs, revealing a previously undocumented protective mechanism in reproductive individuals; and (3) the presence of a queen bee shifts colony-wide chemical distribution by concentrating worker exposure and increasing pesticide deposition in wax. Our findings show that honey bee colonies function as integrated detoxification networks, in which chemical fate depends on complex social behaviors and caste-specific physiology. When social buffering is overwhelmed, reproductive queens may survive by transferring their chemical burden to their offspring.

Biological and medical sciences↗
DOE OSTI2021

Controlling Amphiphilic Polymer Folding beyond the Primary Structure with Protein-Mimetic Di(Phenylalanine)

While methods for polymer synthesis have proliferated, their functionality pales in comparison to natural biopolymers–strategies are limited for building the intricate network of noncovalent interactions necessary to elicit complex, protein-like functions. Using a bioinspired di(phenylalanine) acrylamide (FF) monomer, we explored the impact of various noncovalent interactions in generating ordered assembled structures. Amphiphilic copolymers were synthesized that exhibit β-sheet-like local structure upon collapsing into single-chain assemblies in aqueous environments. Here, the systematic analysis of a series of amphiphilic copolymers illustrated that the global collapse is primarily driven by hydrophobic forces. Hydrogen-bonding and aromatic interactions stabilize local structure, as β-sheet-like interactions were identified via circular dichroism and thioflavin T fluorescence. Similar analysis of phenylalanine (F) and alanine-phenylalanine acrylamide (AF) copolymers found that distancing the aromatic residue from the polymer backbone is sufficient to induce β-sheet-like local structure akin to the FF copolymers; however, the interactions between AF subunits are less stable than those formed by FF. Further, hydrogen-bond donating hydrophilic monomers disrupt internal structure formed by FF within collapsed assemblies. Collectively, these results illuminate design principles for the facile incorporation of multiple facets of protein-mimetic, higher-order structure within folded synthetic polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Design and evaluation of a cyber‐physical testbed for improving attack resilience of power systems

Abstract A power system is a complex cyber‐physical system whose security is critical to its function. A major challenge is to model, analyse and visualise the communication backbone of the power systems concerning cyber threats. To achieve this, the design and evaluation of a cyber‐physical power system (CPPS) testbed called Resilient Energy Systems Lab (RESLab) are presented to capture realistic cyber, physical, and protection system features. RESLab is architected to be a fundamental platform for studying and improving the resilience of complex CPPS to cyber threats. The cyber network is emulated using Common Open Research Emulator (CORE), which acts as a gateway for the physical and protection devices to communicate. The physical grid is simulated in the dynamic time frame using Power World Dynamic Studio (PWDS). The protection components are modelled with both PWDS and physical devices including the SEL Real‐Time Automation Controller (RTAC). Distributed Network Protocol 3 (DNP3) is used to monitor and control the grid. Then, the design is exemplified and the tools are validated. This work presents four case studies on cyberattack and defence using RESLab, where we demonstrate false data and command injection using Man‐in‐the‐Middle and Denial of Service attacks and validate them on a large‐scale synthetic electric grid.

Sahu, Abhijeet↗
DOE OSTI2026

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗
DOE OSTI2020

Deep learning approaches for neural decoding across architectures and recording modalities

Decoding behavior, perception or cognitive state directly from neural signals is critical for brain–computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method in many machine learning tasks ranging from speech recognition to image segmentation. The success of deep networks in other domains has led to a new wave of applications in neuroscience. In this article, we review deep learning approaches to neural decoding. Here, we describe the architectures used for extracting useful features from neural recording modalities ranging from spikes to functional magnetic resonance imaging. Furthermore, we explore how deep learning has been leveraged to predict common outputs including movement, speech and vision, with a focus on how pretrained deep networks can be incorporated as priors for complex decoding targets like acoustic speech or images. Deep learning has been shown to be a useful tool for improving the accuracy and flexibility of neural decoding across a wide range of tasks, and we point out areas for future scientific development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantifying uncertainty in machine learning for nuclear binding energy

Techniques from artificial intelligence and machine learning are increasingly employed in nuclear theory; however, the uncertainties that arise from the complex parameter manifold encoded by the neural networks are often overlooked. Epistemic uncertainties arising from training the same network multiple times for an ensemble of initial weight sets offer a first insight into the confidence of machine learning predictions, but they often come with a high computational cost. Instead, we apply a single-model uncertainty quantification method called Δ-UQ that gives epistemic uncertainties with one-time training. Here, we demonstrate our approach on a two-feature model of nuclear binding energies per nucleon with proton and neutron number pairs as inputs. We show that Δ-UQ can produce reliable and self-consistent epistemic uncertainty estimates and can be used to assess the degree of confidence in predictions made with deep neural networks.

Huang, Mengyao [Lawrence Livermore National Labora↗
DOE OSTI2025

SymProp: Scaling Sparse Symmetric Tucker Decomposition via Symmetry Propagation

Sparse symmetric tensors are an important class of tensors, and their decompositions serve as powerful tools for revealing low-rank structures. This paper introduces SymProp, a novel approach for scaling sparse symmetric Tucker decomposition by propagating symmetry through intermediate computations. SymProp optimizes two key computational kernels: Sparse Symmetric Tensor Times Same Matrix chain (S3 TTMc) for Higher-Order Orthogonal Iteration (HOOI) and Sparse Symmetric Tensor Times Same Matrix chain Times Core (S3 TTMcTC) for Higher-Order QR Iteration (HOQRI). Our method employs a metaprogramming-based index iteration approach to efficiently handle the upper triangular parts of intermediate dense symmetric tensors. SymProp achieves up to 50.9× speedup over SPLATT and up to 360.8× over Compressed Sparse Symmetric (CSS) format on the S3 TTMc operation. Moreover, our S3 TTMc and S3 TTMcTC implementations support tensor orders four levels higher than state-of-the-art methods. Our HOQRI demonstrates superior scalability and up to a 33.6× speedup over optimized HOOI. By enabling more scalable Tucker decompositions for higher orders, decomposition ranks, and dimension sizes, SymProp opens new possibilities for analyzing complex hypergraph structures in fields such as network science, data mining, and machine learning.

Li, Zecheng [North Carolina State University]↗
DOE OSTI2023

Introduction to the Special Section on Control and Management of Electric Power Systems With High Shares of Inverter-Based Resources

The growing interest in the integration of variable renewable energy (VRE) and distributed energy resources (DER) on both policy and economic grounds is driving the transformation of electric power systems. The significant deployment of VRE and DER can effectively displace the conventional synchronous generator-based power plants that for decades have been the foundation for power system generation and stability in electric power systems. Inverter-based resources (IBRs) introduce a high-level of uncertainty, variability, and complexity into the operation of electric power networks, and the transformation to IBRs raises a wide range of technical questions and operational challenges. The optimal coordination and control of these resources requires greater interoperability and necessitates significant upgrades of grid automation, including real-time monitoring.

distributed power generation↗
DOE OSTI2024

First-generation college student forges ahead, now key to Lab's mission

Fatima Woody was just 17 and a student at Pojoaque Valley High School when she first started her career as a Los Alamos Neutron Science Center receptionist. Now she's in a crucial role that keeps plutonium pit production and other mission processes operating with as little interruption as possible. Over nearly four decades, Fatima has gradually advanced from her initial positions as a receptionist and administrative secretary to become a computer technician, then a computer system professional who specializes in project management. Today, she coordinates the workflow for nearly two dozen deployed information technology technicians who keep the computer systems and networks operating at the high-tech complex that houses the Lab's Plutonium Facility.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Nutrient Exposure Alters Microbial Composition, Structure, and Mercury Methylating Activity in Periphyton in a Contaminated Watershed

The conversion of mercury (Hg) to monomethylmercury (MMHg) is a critical area of concern in global Hg cycling. Periphyton biofilms may harbor significant amounts of MMHg but little is known about the Hg-methylating potential of the periphyton microbiome. Therefore, we used high-throughput amplicon sequencing of the 16S rRNA gene, ITS2 region, and Hg methylation gene pair (hgcAB) to characterize the archaea/bacteria, fungi, and Hg-methylating microorganisms in periphyton communities grown in a contaminated watershed in East Tennes(see United States). Furthermore, we examined how nutrient amendments (nitrate and/or phosphate) altered periphyton community structure and function. We found that bacterial/archaeal richness in experimental conditions decreased in summer and increased in autumn relative to control treatments, while fungal diversity generally increased in summer and decreased in autumn relative to control treatments. Interestingly, the Hg-methylating communities were dominated by Proteobacteria followed by Candidatus Atribacteria across both seasons. Surprisingly, Hg methylation potential correlated with numerous bacterial families that do not contain hgcAB, suggesting that the overall microbiome structure of periphyton communities influences rates of Hg transformation within these microbial mats. To further explore these complex community interactions, we performed a microbial network analysis and found that the nitrate-amended treatment resulted in the highest number of hub taxa that also corresponded with enhanced Hg methylation potential. This work provides insight into community interactions within the periphyton microbiome that may contribute to Hg cycling and will inform future research that will focus on establishing mixed microbial consortia to uncover mechanisms driving shifts in Hg cycling within periphyton habitats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

VPS45 is required for both diffuse and tip growth of Arabidopsis thaliana cells

Introduction VPS45 belongs to the Sec1/Munc18 family of proteins, which interact with and regulate Qa-SNARE function during membrane fusion. We have shown previously that Arabidopsis thaliana VPS45 interacts with the SYP61/SYP41/VTI12 SNARE complex, which locates on the trans -Golgi network (TGN). It is required for SYP41 stability, and it functions in cargo trafficking to the vacuole and in cell expansion. It is also required for correct auxin distribution during gravitropism and lateral root growth. Results As vps45 knockout mutation is lethal in Arabidopsis, we identified a mutant, vps45-3 , with a point mutation in the VPS45 gene causing a serine 284-to-phenylalanine substitution. The VPS45-3 protein is stable and maintains interaction with SYP61 and SYP41. However, vps45-3 plants display severe growth defects with significantly reduced organ and cell size, similar to vps45 RNAi transgenic lines that have reduced VPS45 protein levels. Root hair and pollen tube elongation, both processes of tip growth, are highly compromised in vps45-3 . Mutant root hairs are shorter and thicker than those of wild-type plants, and are wavy. These root hairs have vacuolar defects, containing many small vacuoles, compared with WT root hairs with a single large vacuole occupying much of the cell volume. Pollen tubes were also significantly shorter in vps45-3 compared to WT. Discussion We thus show that VPS45 is essential for proper tip growth and propose that the observed vacuolar defects lead to loss of the turgor pressure needed for tip growth.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

ORRC/SAIL interface control document for SAIL OFT data tapes, revision A

The formats for all orbital flight tests magnetic tape recordings produced in the Johnson Space Center Shuttle Avionics Laboratories which are required to be processed in the orbiter data reduction complex or by the mission control center network interference processor are described.

Source record↗
NASA NTRS1987

A 30/20 GHz FSS feasibility study

The near term feasibility of direct-to-subscriber services were determined using the 30/20 GHz Fixed Satellite Service (FSS) frequency bands. Those technologies which need to be further developed before such a system can be implemented, were identified. To determine this feasibility, dozens of potential applications were examined for their near-term viability, and the subscriber base of three promising applications were estimated. The system requirements, terminal design, and satellite architecture were all investigated to determine whether a 30/20 GHz FSS system is technically and economically feasible by mid-1990s. It was concluded that such a system is feasible, although maturation of some technologies is needed. This system would likely consist of one or two multibeam satellites serving hub/spoke networks of simple user terminals and more complex, mutli-channel terminals of the service providers. Rain compensation would be accomplished non-adaptively through the use of coding, nonuniform satellite TWT power that is a function of a beam's anticipated downlink fading, and signal regeneration of traffic to the wettest climate regions. It was estimated that a potential market of almost two million users could exist in in the mid-1990s time frame for home banking and financial services via Ka-band satellites.

Source record↗
NASA NTRS1990

Whole earth telescope observations of the white dwarf G29-38 - Phase variations of the 615 second period

An extensive set of high-speed photometric observations obtained with the Whole Earth Telescope network is used to show that the complex light curve of the ZZ Zeti (DAV) star G29-38 is dominated by a single, constant amplitude period of 615 s during the time span of these observations. The pulse arrival times for this period exhibit a systematic variation in phase readily explained by light-travel time effects produced by reflex orbital motion about an unseen companion. The best-fit model to the observations indicates a highly eccentric orbit, a period of 109 + or - 13 days and a minimum mass of 0.5 solar mass for the companion.

Winget, D. E.↗
NASA NTRS1993

CRAY mini manual. Revision D

This document briefly describes the use of the CRAY supercomputers that are an integral part of the Supercomputing Network Subsystem of the Central Scientific Computing Complex at LaRC. Features of the CRAY supercomputers are covered, including: FORTRAN, C, PASCAL, architectures of the CRAY-2 and CRAY Y-MP, the CRAY UNICOS environment, batch job submittal, debugging, performance analysis, parallel processing, utilities unique to CRAY, and documentation. The document is intended for all CRAY users as a ready reference to frequently asked questions and to more detailed information contained in the vendor manuals. It is appropriate for both the novice and the experienced user.

Tennille, Geoffrey M.↗
NASA NTRS1995

Computer-Assisted Monitoring Of A Complex System

Propulsion System Advisor (PSA) computer-based system assists engineers and technicians in analyzing masses of sensory data indicative of operating conditions of space shuttle propulsion system during pre-launch and launch activities. Designed solely for monitoring; does not perform any control functions. Although PSA developed for highly specialized application, serves as prototype of noncontrolling, computer-based subsystems for monitoring other complex systems like electric-power-distribution networks and factories.

Beil, Bob J.↗