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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Efficient computer algorithms for infrared astronomy data processing

Data processing techniques to be studied for use in infrared astronomy data analysis systems are outlined. Only data from space based telescope systems operating as survey instruments are considered. Resulting algorithms, and in some cases specific software, will be applicable for use with the infrared astronomy satellite (IRAS) and the shuttle infrared telescope facility (SIRTF). Operational tests made during the investigation use data from the celestial mapping program (CMP). The overall task differs from that involved in ground-based infrared telescope data reduction.

Pelzmann, R. F., Jr.↗
NASA NTRS1987

Task planning and control synthesis for robotic manipulation in space applications

Space-based robotic systems for diagnosis, repair and assembly of systems will require new techniques of planning and manipulation to accomplish these complex tasks. Results of work in assembly task representation, discrete task planning, and control synthesis which provide a design environment for flexible assembly systems in manufacturing applications, and which extend to planning of manipulatiuon operations in unstructured environments are summarized. Assembly planning is carried out using the AND/OR graph representation which encompasses all possible partial orders of operations and may be used to plan assembly sequences. Discrete task planning uses the configuration map which facilitates search over a space of discrete operations parameters in sequential operations in order to achieve required goals in the space of bounded configuration sets.

Sanderson, A. C.↗
NASA NTRS1991

CFD validation for forebody inlet interactions

Topics covered include the computational fluid dynamics (CFD) task force philosophy, a road map for CFD code validation, computer code validation requirements for forebodies and inlets, the criteria for choosing recommended experiments, an all-body hypersonic experiment, and centerline heat transfer. Information is given in viewgraph form.

Marvin, J. G.↗
NASA NTRS1994

Synthetic vision display evaluation studies

The goal of this research was to help us understand the display requirements for a synthetic vision system for the High Speed Civil Transport (HSCT). Four experiments were conducted to examine the effects of different levels of perceptual cue complexity in displays used by pilots in a flare and landing task. Increased levels of texture mapping of terrain and runway produced mixed results, including harder but shorter landings and a lower flare initiation altitude. Under higher workload conditions, increased texture resulted in an improvement in performance. An increase in familiar size cues did not result in improved performance. Only a small difference was found between displays using two patterns of high resolution texture mapping. The effects of increased perceptual cue complexity on performance was not as strong as would be predicted from the pilot's subjective reports or from related literature. A description of the role of a synthetic vision system in the High Speed Civil Transport is provide along with a literature review covering applied research related to perceptual cue usage in aircraft displays.

Regal, David M.↗
NASA NTRS2001

Quality of Service for Real-Time Applications Over Next Generation Data Networks

This project, which started on January 1, 2000, was funded by the NASA Glenn Research Center for duration of one year. The deliverables of the project included the following tasks: (1) Study of QoS mapping between the edge and core networks envisioned in the Next Generation networks will provide us with the QoS guarantees that can be obtained from next generation networks; (2) Buffer management techniques to provide strict guarantees to real-time end-to-end applications through preferential treatment to packets belonging to real-time applications. In particular, use of ECN to help reduce the loss on high bandwidth-delay product satellite networks needs to be studied; (3) Effect of Prioritized Packet Discard to increase goodput of the network and reduce the buffering requirements in the ATM switches; (4) Provision of new IP circuit emulation services over Satellite IP backbones using MPLS will be studied; and (5) Determine the architecture and requirements for internetworking ATN and the Next Generation Internet for real-time applications. The project has been completed on time. All the objectives and deliverables of the project have been completed. Research results obtained from this project have been published in a number of papers in journals, conferences, and technical reports, included in this document.

Atiquzzaman, Mohammed↗
NASA NTRS2010

Detailed Analysis of the Intra-Ejecta Dark Plains of Caloris Basin, Mercury

The Caloris basin on Mercury is floored by light-toned plains and surrounded by an annulus of dark-toned material interpreted to be ejecta blocks and smooth, dark, ridged plains. Strangely, preliminary crater counts indicate that these intra-ejecta dark plains are younger than the light-toned plains within the Caloris basin. This would imply a second, younger plains emplacement event, possibly involving lower albedo material volcanics, which resurfaced the original ejecta deposit. On the other hand, the dark plains may be pre-Caloris light plains covered by a thin layer of dark ejecta. Another alternative to the hypothesis of young, dark volcanism is the possibility that previous crater counts have not thoroughly distinguished between superposed craters (fresh) and partly-buried craters (old) and therefore have not accurately determined the ages of the Caloris units. This abstract outlines the tasks associated with a new mapping project of the Caloris basin, intended to improve our knowledge of the geology and geologic history of the basin, and thus facilitate an understanding of the thermal evolution of this region of Mercury.

Buczkowski, Debra L.↗
NASA NTRS2012

Evaluating the Efficacy of the Cloud for Cluster Computation

Computing requirements vary by industry, and it follows that NASA and other research organizations have computing demands that fall outside the mainstream. While cloud computing made rapid inroads for tasks such as powering web applications, performance issues on highly distributed tasks hindered early adoption for scientific computation. One venture to address this problem is Nebula, NASA's homegrown cloud project tasked with delivering science-quality cloud computing resources. However, another industry development is Amazon's high-performance computing (HPC) instances on Elastic Cloud Compute (EC2) that promises improved performance for cluster computation. This paper presents results from a series of benchmarks run on Amazon EC2 and discusses the efficacy of current commercial cloud technology for running scientific applications across a cluster. In particular, a 240-core cluster of cloud instances achieved 2 TFLOPS on High-Performance Linpack (HPL) at 70% of theoretical computational performance. The cluster's local network also demonstrated sub-100 ?s inter-process latency with sustained inter-node throughput in excess of 8 Gbps. Beyond HPL, a real-world Hadoop image processing task from NASA's Lunar Mapping and Modeling Project (LMMP) was run on a 29 instance cluster to process lunar and Martian surface images with sizes on the order of tens of gigapixels. These results demonstrate that while not a rival of dedicated supercomputing clusters, commercial cloud technology is now a feasible option for moderately demanding scientific workloads.

Cloud Computing↗
NASA NTRS2022

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗
NASA NTRS1992

Redundant arm control in a supervisory and shared control system

The Extended Task Space Control approach to robotic operations based on manipulator behaviors derived from task requirements is described. No differentiation between redundant and non-redundant robots is made at the task level. The manipulation task behaviors are combined into a single set of motion commands. The manipulator kinematics are used subsequently in mapping motion commands into actuator commands. Extended Task Space Control is applied to a Robotics Research K-1207 seven degree-of-freedom manipulator in a supervisory telerobot system as an example.

Backes, Paul G.↗
DOE OSTI2022

Detection of Forced Change Within Combined Climate Fields Using Explainable Neural Networks

Abstract Assessing forced climate change requires the extraction of the forced signal from the background of climate noise. Traditionally, tools for extracting forced climate change signals have focused on one atmospheric variable at a time, however, using multiple variables can reduce noise and allow for easier detection of the forced response. Following previous work, we train artificial neural networks to predict the year of single‐ and multi‐variable maps from forced climate model simulations. To perform this task, the neural networks learn patterns that allow them to discriminate between maps from different years—that is, the neural networks learn the patterns of the forced signal amidst the shroud of internal variability and climate model disagreement. When presented with combined input fields (multiple seasons, variables, or both), the neural networks are able to detect the signal of forced change earlier than when given single fields alone by utilizing complex, nonlinear relationships between multiple variables and seasons. We use layer‐wise relevance propagation, a neural network explainability tool, to identify the multivariate patterns learned by the neural networks that serve as reliable indicators of the forced response. These “indicator patterns” vary in time and between climate models, providing a template for investigating inter‐model differences in the time evolution of the forced response. This work demonstrates how neural networks and their explainability tools can be harnessed to identify patterns of the forced signal within combined fields.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Passive mapping and intermittent exploration for mobile robots

An adaptive state space architecture is combined with diktiometric representation to provide the framework for designing a robot mapping system with flexible navigation planning tasks. This involves indexing waypoints described as expectations, geometric indexing, and perceptual indexing. Matching and updating the robot's projected position and sensory inputs with indexing waypoints involves matchers, dynamic priorities, transients, and waypoint restructuring. The robot's map learning can be opganized around the principles of passive mapping.

Engleson, Sean P.↗
NASA NTRS2020

Search and Rescue under the Forest Canopy using Multiple UAS

We consider the problem of multi-robot search and rescue under the forest canopy. Forest is a particularly challenging environment for collaborative mapping and exploration, mainly due to the existence of severe perceptual aliasing, which hinders reliable mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) with onboard sensing and autonomy. Each UAV runs a lightweight filtering algorithm for local state estimation, and a dynamic-aware frontier selection algorithm for fast exploration. The essential and computationally intensive task of collaborative simultaneous localization and mapping (CSLAM) is performed at a central ground station. To handle perceptual aliasing, we make use of stable landmarks extracted from trees, which significantly improve precision and recall during place recognition. Furthermore, to recover from incorrect pairwise data associations during loop closure, we propose a novel procedure for global data association based on recently developed techniques on cycle consistent multiway matching. Our algorithm returns a global data association that is guaranteed to be cycle consistent, and is shown to significantly improve precision compared to the input pairwise associations. The overall multi-UAV system is extensively validated during real-world collaborative exploration missions in a forest at NASA Langley Research Center.

Multi-robot systems↗
NASA NTRS1989

Displays, instruments, and the multi-dimensional world of cartography

Cartographers are creators and purveyors of maps. Maps are representations of space, geographical images of the environment. Maps organize spatial information for convenience, particularly for use in performing tasks which involve the environment. There are many different kinds of maps, and there are as many different uses of maps as there are spatial problems to be solved. Maps and the display instrument dichotomy are examined. Also examined are the categories of map use along with the characteristics of maps.

Mccleary, George F., Jr.↗
NASA NTRS2002

A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation

Near-infrared spectroscopy (NIRS) has been used to noninvasively monitor adult human brain function in a wide variety of tasks. While rough spatial correspondences with maps generated from functional magnetic resonance imaging (fMRI) have been found in such experiments, the amplitude correspondences between the two recording modalities have not been fully characterized. To do so, we simultaneously acquired NIRS and blood-oxygenation level-dependent (BOLD) fMRI data and compared Delta(1/BOLD) (approximately R(2)(*)) to changes in oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations derived from the NIRS data from subjects performing a simple motor task. We expected the correlation with deoxyhemoglobin to be strongest, due to the causal relation between changes in deoxyhemoglobin concentrations and BOLD signal. Instead we found highly variable correlations, suggesting the need to account for individual subject differences in our NIRS calculations. We argue that the variability resulted from systematic errors associated with each of the signals, including: (1) partial volume errors due to focal concentration changes, (2) wavelength dependence of this partial volume effect, (3) tissue model errors, and (4) possible spatial incongruence between oxy- and deoxyhemoglobin concentration changes. After such effects were accounted for, strong correlations were found between fMRI changes and all optical measures, with oxyhemoglobin providing the strongest correlation. Importantly, this finding held even when including scalp, skull, and inactive brain tissue in the average BOLD signal. This may reflect, at least in part, the superior contrast-to-noise ratio for oxyhemoglobin relative to deoxyhemoglobin (from optical measurements), rather than physiology related to BOLD signal interpretation.

Non-NASA Center↗
DOE OSTI2025

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Finding Stuff Underwater: Open-Source Tools for Underwater Field Science

Since 2009, we have been developing and testing Exploration Ground Data Systems (xGDS). xGDS is a software suite, built on open-source web technologies, for supporting NASA terrestrial field science analog missions. We will describe our recent work supporting underwater mapping and dive operations at the Pavilion Lake Research Project (PLRP - www.pavilionlake.com). At PLRP we used open-source mapping technologies to meet an operational need to quickly guide divers and underwater vehicles to locations of interest, and the scientific goal of building a map showing the locations and characteristics of the microbialites at the bottom of the lake. We will discuss some of the benefits and lessons-learned from our recent transition from Google Earth to OpenLayers as the primary mapping engine to support our work. Well also explain the challenges we faced and solutions weve developed to support mapping and data collection in an underwater environment.Beyond their immediate value for advancing scientific research on Earth, NASA analogs explore new ideas for supporting scientists working in extreme environments (e.g. underwater) to develop best practices for future human missions to the Moon or Mars. Science at PLRP involved imaging, sampling and characterizing microbialites growing beneath the surface of an alpine lake in British Columbia. To support PLRP operations and science, xGDS helped plan data collection tasks and provided accurate tracking and mapping of the locations of the underwater assets (human-piloted submersibles, remotely operated vehicles (ROVs) and human divers) collecting imagery and samples from the lake. The data collected during our field work was registered with precursor bathymetry data collected by an autonomous underwater vehicle (AUV) and was globally located on a satellite base layer map of the area surrounding the lake.

Earth analogs↗
NASA NTRS1994

McIDAS-eXplorer: A version of McIDAS for planetary applications

McIDAS-eXplorer is a set of software tools developed for analysis of planetary data published by the Planetary Data System on CD-ROM's. It is built upon McIDAS-X, an environment which has been in use nearly two decades now for earth weather satellite data applications in research and routine operations. The environment allows convenient access, navigation, analysis, display, and animation of planetary data by utilizing the full calibration data accompanying the planetary data. Support currently exists for Voyager images of the giant planets and their satellites; Magellan radar images (F-MIDR and C-MIDR's, global map products (GxDR's), and altimetry data (ARCDR's)); Galileo SSI images of the earth, moon, and Venus; Viking Mars images and MDIM's as well as most earth based telescopic images of solar system objects (FITS). The NAIF/JPL SPICE kernels are used for image navigation when available. For data without the SPICE kernels (such as the bulk of the Voyager Jupiter and Saturn imagery and Pioneer Orbiter images of Venus), tools based on NAIF toolkit allow the user to navigate the images interactively. Multiple navigation types can be attached to a given image (e.g., for ring navigation and planet navigation in the same image). Tools are available to perform common image processing tasks such as digital filtering, cartographic mapping, map overlays, and data extraction. It is also possible to have different planetary radii for an object such as Venus which requires a different radius for the surface and for the cloud level. A graphical user interface based on Tel-Tk scripting language is provided (UNIX only at present) for using the environment and also to provide on-line help. It is possible for end users to add applications of their own to the environment at any time.

Limaye, Sanjay S.↗
DOE OSTI2023

Smart Data Mapping for Connecting Power System Model and Geospatial Data

Knowing the geospatial locations of power system model elements is the foundation for analyzing system vulnerability to natural hazards and connecting loads with end users and their communities. However, power system models and geospatial data for power grid assets may have been developed asynchronously without close coordination. Creating a direct mapping between the two may be a challenging task, considering heterogeneous data structures, target uses, historical legacies, and human errors. This work aims to build an automatic data mapping workflow to connect power system model elements and geospatial data for transmission network, and to support energy grid resilience studies for Puerto Rico. The primary steps in this workflow include constructing graphs using geospatial data, and aligning them to the transmission networks defined in the power system data. The results have been evaluated against existing manual mapping practices for part of the Puerto Rico Power Grid model to illustrate the performance of such auto-mapping solutions.

Resilience, geospatial data, grid transmission net↗