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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 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRS2005

NASA Tech Briefs, August 2005

Topics include: Hidden Identification on Parts: Magnetic Machine-Readable Matrix Symbols; System for Processing Coded OFDM Under Doppler and Fading; Multipurpose Hyperspectral Imaging System; Magnetic-Flux-Compensated Voltage Divider; High-Performance Satellite/Terrestrial-Network Gateway; Internet-Based System for Voice Communication With the ISS; Stripline/Microstrip Transition in Multilayer Circuit Board; Dual-Band Feed for a Microwave Reflector Antenna; Quadratic Programming for Allocating Control Effort; Range Process Simulation Tool; Simulator of Space Communication Networks; Computing Q-D Relationships for Storage of Rocket Fuels; Contour Error Map Algorithm; Portfolio Analysis Tool; Glass Frit Filters for Collecting Metal Oxide Nanoparticles; Anhydrous Proton-Conducting Membranes for Fuel Cells; Portable Electron-Beam Free-Form Fabrication System; Miniature Laboratory for Detecting Sparse Biomolecules; Multicompartment Liquid-Cooling/Warming Protective Garments; Laser Metrology for an Optical-Path-Length Modulator; PCM Passive Cooling System Containing Active Subsystems; Automated Electrostatics Environmental Chamber; Estimating Aeroheating of a 3D Body Using a 2D Flow Solver; Artificial Immune System for Recognizing Patterns; Computing the Thermodynamic State of a Cryogenic Fluid; Safety and Mission Assurance Performance Metric; Magnetic Control of Concentration Gradient in Microgravity; Avionics for a Small Robotic Inspection Spacecraft; and Simulation of Dynamics of a Flexible Miniature Airplane.

Source record↗

NASA NTRS2014

Control and Non-Payload Communications (CNPC) Prototype Radio - Generation 2 Flight Test Report

NASA Glenn Research Center conducted a series of flight tests for the purpose of evaluating air-to-ground communications links for future unmanned aircraft systems (UAS). The primary objective of the test effort was to evaluate the transition of the aircraft communications from one ground station to the next, and to monitor data flow during the "hand-off" event. To facilitate the testing, ground stations were installed at locations in Cleveland, Ohio and Albany, Ohio that each provides line-of-sight radio communications with an overflying aircraft. This report describes results from the flight tests including flight parameters, received signal strength measurements, data latency times, and performance observations for the air-to-ground channel.

Ground Stations↗

NASA NTRS2015

The Feasibility of Wearables in an Enterprise Environment and Their Impact on IT Security

This paper is intended to explore the usability and feasibility of wearables in an enterprise environment and their impact on IT Security. In this day and age, with the advent of the Internet of Things, we must explore all the new technology emerging from the minds of the new inventors. This means exploring the use of wearables in regards to their benefits, limitations, and the new challenges they pose to securing computer networks in the Federal environment. We will explore the design of the wearables, the interfaces needed to connect them, and what it will take to connect personal devices in the Federal enterprise network environment. We will provide an overview of the wearable design, concerns of ensuring the confidentiality, integrity, and availability of information and the challenges faced by those doing so. We will also review the implications and limitations of the policies governing wearable technology and the physical efforts to enforce them.

wearables↗

NASA NTRS2016

A Global Repository for Planet-Sized Experiments and Observations

Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP) output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery.

Earth Systems Grid Federation (ESGFC)↗

DOE OSTI2016

Models of TCP in high-BDP environments and their experimental validation

In recent years, the computer networking community has seen a steady growth in bandwidth-delay products (BDPs). Several TCP variants were created to combat the shortcomings of legacy TCP when it comes to operation in high-BDP environments. These variants, among which are CUBIC, STCP, and H-TCP, have been extensively studied in some empirical contexts, and some analytical models exist for CUBIC and STCP. However, since these studies have been conducted, BDPs have risen even more, and new bulk data transfer tools have emerged that utilize multiple parallel TCP streams. In view of these new developments, it is imperative to revisit the question: Which congestion control algorithms are best adapted to current networking environments? In order to help resolve this question, we contribute the following: (i) using first principles, we develop a general throughput-prediction framework that takes into account buffer sizes and maximum window constraints; (ii) we validate the models using measurements and achieve low prediction errors; (iii) we note differences in TCP dynamics between two experimental configurations and find one of them to be significantly more deterministic than the other; we also find that CUBIC and H-TCP outperform STCP, especially when multiple streams are used; and (iv) we present preliminary results for modelling multiple TCP streams for CUBIC and STCP.

Vardoyan, G.↗

DOE OSTI2017

SimCell Status Board

The Virtual SimCell is a method embodied in several software applications based on the Virtual Community Platform (VCP) (ANL-SF-11-049) and its Real-Time Dashboard (RTD) app. The purpose of this method is to more efficiently facilitate emergency preparedness exercises by allowing emergency preparedness exercise Simulation Cells -- SimCells -- to be established and managed through a computer network. SimCells take the place of organizations that would respond to actual emergencies, but are not participants in exercises of emergency preparedness plans. In effect, SimCells serve as actors portraying how those organizations would respond during real emergency events. The SimCell Status Board (SSB) is an RTD mini-app for controllers to communicate exercise events to players and each other by entering information into an integrated system of pre-defined data fields, displaying those data effectively, and preserving them for easy access during exercise evaluations.

Tanzman, Edward↗

DOE OSTI2017

R&D100 Finalist: Neuromorphic Cyber Microscope

The Neuromorphic Cyber Microscope provides security analysts with unprecedented visibility of their network, computer and storage assets. This processor is the world's first practical implementation of neuromorphic technology to a major computer science mission. Working with Lewis Rhodes Labs, engineers at Sandia National Laboratories have created a device that is orders of magnitude faster at analyzing data to identify cyber-attacks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Authscan, version 1.x

Code to detect compromised user credentials in a computer network using host log data.

Turcotte, Melissa↗

DOE OSTI2018

Authscan 2.x

Code to model user credentials on a computer network by considering independently the time series of events generated by each user credential and use these models to detect compromised users credentials by scoring deviation from the learned baseline.

Turcotte, Melissa↗

DOE OSTI2017

NERSC & JGI Seek Elusive Proteins for Gene Editing

A video just released by the Supercomputing 2017 (SC17) conference shows how biologists at UC Berkeley and the Joint Genome Institute (JGI) – a Department of Energy Office of Science User Facility – are using NERSC, the Office of Science’s primary supercomputing center, to identify a class of enzymes capable of editing out genes responsible for disease. This revolutionary work requires petaflops of computing power to sift through billions of DNA sequences in the JGI data portals to identify proteins like Cas9 that, combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), can “edit” a genome. First discovered by researchers at UC Berkeley, the CRISPR-Cas9 system has the power to permanently correct disease-causing mutations in cells, animal models, and eventually human patients to cure certain types of cancer, cardiovascular disease, sickle cell disease, and retinal degeneration. Since the CRISPR system was first identified in the early 2000s, it has become the most promising technology for treating genetic disease in humans and enabling plants to survive stress caused by pests and the environment. The annual SC17 conference will take place November 12-17 in Denver, Colorado. The over 12,000 attendees from academia, government and industry are leaders in researching and delivering high performance computing, networking, data storage and analysis in support of scientific discovery. http://sc17.supercomputing.org

Berkeley Lab, LBNL↗

DOE OSTI2018

Deep Learning for Unsupervised Insider Threat Detection in Structured Cyber Security Data Streams

Analysis of an organization's computer network activity is a key component of early detection and mitigation of insider threat, a growing concern for many organizations. Raw system logs are a prototypical example of streaming data that can quickly scale beyond the cognitive power of a human analyst. As a prospective filter for the human analyst, we present an online unsupervised deep learning approach to detect anomalous network activity from system logs in real time. Our models decompose anomaly scores into the contributions of individual user behavior features for increased interpretability to aid analysts reviewing potential cases of insider threat. Using the CERT Insider Threat Dataset v6.2 and threat detection recall as our performance metric, our novel deep and recurrent neural network models outperform Principal Component Analysis, Support Vector Machine and Isolation Forest based anomaly detection baselines. For our best model, the events labeled as insider threat activity in our dataset had an average anomaly score in the 95.53 percentile, demonstrating our approach's potential to greatly reduce analyst workloads.

Deep Learning, Insider Threat↗

DOE OSTI2017

Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams

Analysis of an organization’s computer network activity is a key component of early detection and mitigation of insider threat, a growing concern for many organizations. Raw system logs are a prototypical example of streaming data that can quickly scale beyond the cognitive power of a human analyst. As a prospective filter for the human analyst, we present an online unsupervised deep learning approach to detect anomalous network activity from system logs in real time. Our models decompose anomaly scores into the contributions of individual user behavior features for increased interpretability to aid analysts reviewing potential cases of insider threat. Using the CERT Insider Threat Dataset v6.2 and threat detection recall as our performance metric, our novel deep and recurrent neural network models outperform Principal Component Analysis, Support Vector Machine and Isolation Forest based anomaly detection baselines. For our best model, the events labeled as insider threat activity in our dataset had an average anomaly score in the 95.53 percentile, demonstrating our approach’s potential to greatly reduce analyst workloads.

Tuor, Aaron R.↗

NASA NTRS1989

Hyperswitch Network For Hypercube Computer

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Chow, Edward↗

NASA NTRS1993

MEDUSA - An overset grid flow solver for network-based parallel computer systems

Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.

Smith, Merritt H.↗

DOE OSTI2025

ChemComp: Compiling and Computing with Chemical Reaction Networks

The exponential growth in computing demands driven by scientific computing, data analytics, and artificial intelligence is pushing conventional CMOS-based high-performance computing systems to their physical and energy efficiency limits. As we approach the era of post-exascale computing, disruptive approaches are necessary to overcome these barriers and achieve substantial gains in energy efficiency. Analog and hybrid digital-analog computing systems have emerged as promising alternatives, offering the potential for orders-of-magnitude improvements in efficiency. Among these, biochemical computing stands out as a novel paradigm capable of leveraging the natural efficiency of chemical reactions, which have shown promise in solving optimization problems by converging to steady states. By scaling up reaction networks or reaction vessel sizes, biochemical systems present an opportunity to meet the high-performance demands of modern computing tasks. Despite their promise, significant theoretical and practical challenges remain, particularly in formulating and mapping computational problems to chemical reaction networks (CRNs) and designing viable biochemical computing devices. This paper addresses these challenges by introducing new ideas to ChemComp, a compilation and emulation framework for chemical computation. This work describes the mechanisms through which solutions to ordinary differential equations (ODEs) that can be represented as CRN systems can be achieved. Furthermore, we explain the design principles of an ODE dialect implemented as a multi-level intermediate representation (MLIR) compiler extension that will be coupled with existing infrastructure. We demonstrate the potential of our framework through a case study emulating a simplified chemical reservoir computing device. This work establishes foundational tools and methodologies necessary to harness the computational power of chemistry, paving the way for the development of energy-efficient, high-performance computing systems tailored to contemporary and future computational needs.

Bohm Agostini, Nicolas↗

DOE OSTI2017

I/O routing in a multidimensional torus network

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

I/O routing in a multidimensional torus network

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

I/O routing in a multidimensional torus network

97 MATHEMATICS AND COMPUTING↗