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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Mars Planimetric Mapping

The 1:5,000,000 scale shaded relief maps of Mars originally compiled from Mariner 9 pictures are being upgraded by adding details visible on Viking Orbiter images. This work is done by modifying the original airbrush drawings; no attempt is made to reposition features according to the latest control nets. Thirteen of these maps have been published to date, two are in compilation, and two are in press. A hard cover atlas containing reduced scale versions of all Mars cartographic products will be published upon completion of the revisions of the 1:5,000,000 scale maps, the 1:2,000,000 scale photomosaics, and Mars color albedo mapping tasks. This atlas will supersede the existing Atlas of Mars prepared by Batson and others.

Batson, R. M.↗
NASA NTRS1995

Learning in Neural Networks: VLSI Implementation Strategies

Fully-parallel hardware neural network implementations may be applied to high-speed recognition, classification, and mapping tasks in areas such as vision, or can be used as low-cost self-contained units for tasks such as error detection in mechanical systems (e.g. autos). Learning is required not only to satisfy application requirements, but also to overcome hardware-imposed limitations such as reduced dynamic range of connections.

Neural Networks↗
DOE OSTI2019

Managing variations among nodes in parallel system frameworks

Systems, apparatuses, and methods for managing variations among nodes in parallel system frameworks. Sensor and performance data associated with the nodes of a multi-node cluster may be monitored to detect variations among the nodes. A variability metric may be calculated for each node of the cluster based on the sensor and performance data associated with the node. The variability metrics may then be used by a mapper to efficiently map tasks of a parallel application to the nodes of the cluster. In one embodiment, the mapper may assign the critical tasks of the parallel application to the nodes with the lowest variability metrics. In another embodiment, the hardware of the nodes may be reconfigured so as to reduce the node-to-node variability.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids using Genetic Algorithms

In this paper, we propose a distributed approach for mapping a single large application to a heterogeneous grid environment. To minimize the execution time of the parallel application, we distribute the mapping overhead to the available nodes of the grid. This approach not only provides a fast mapping of tasks to resources but is also scalable. We adopt a hierarchical grid model and accomplish the job of mapping tasks to this topology using a scheduler tree. Results show that our three-phase algorithm provides high quality mappings, and is fast and scalable.

Sanyal, Soumya↗
NASA NTRS1997

The Development of an Electronic Aircraft Taxi Navigation Display

This paper describes the development of an electronic aircraft taxi navigation display as part of NASA's Terminal Area Productivity (TAP) Program. The impetus for the development of this specific display, and the TAP program as a whole, is the current bottleneck in surface operations experienced during low-visibility operations. Simply stated, while modern aircraft are equipped to fly and land in low-visibility conditions, they lack the related technology required to allow them to efficiently and safely navigation from the runway to the gate. Pilots under such conditions consequently taxi slower, sometimes get lost and have to stop, and occasionally collide with other aircraft. Based on a review of available display and navigation sensor technologies, and a one-year information requirements study conducted aboard several commercial aircraft flights, it was determined that an electronic aircraft taxi navigation display was the most viable option for improving the efficiency of low-visibility taxi operations. Based on flight deck observations and pilot interviews, previous map display research, other taxi map display efforts, and part-task taxi map research, an advanced taxi navigation display has been developed and is currently being tested. The taxi navigation display is presented as a head-down cockpit display and includes a track-up perspective airport surface view, taxiway, gate and runway labels, ownship position, traffic icons and collision annunciation, graphical route guidance, heading indicator, rotating compass, RVR wedge, stop bars, zoom control, and datalink message window. The development and support for each of the features will be discussed in detail. Additional information is contained in the original extended abstract.

Andre, Anthony D.↗
NASA NTRSDate not supplied

IMPACT 1.0—Task Impairment: A Novel Approach for Assessing Impairment during Exploration-Class Missions

Exploration-class and International Space Station (ISS) missions have significantly different levels of associated medical risk for crewmembers. The Integrated Medical Model (IMM), the probabilistic risk assessment tool used for ISS medical trade-space analyses, uses a Functional Impairment (FI) metric to determine quality time lost should a crewmember be afflicted with a medical condition. While IMM-based FI has been successful for ISS operations, it has limitations when applied to exploration-class missions. As the National Aeronautics and Space Administration (NASA) looks ahead to Gateway, Artemis, and Martian missions, a novel, dynamic, and mission-appropriate impairment paradigm is necessary for accurate contingency planning. This paradigm, Task Impairment (TI), fulfills that need by utilizing mission-specific tasks. TI will allow future capability for a loss of mission metric, previously not available with IMM. TI serves as a replacement metric for FI within IMPACT, the next-generation trade-space analysis tool suite created to replace the IMM. IMPACT significantly increases the fidelity of probabilistic risk assessment for exploration-class missions. The Human Exploration of Mars Preliminary List of Crew Tasks (MTL, a source of 1100+ exploration-class mission-specific tasks for crewmembers) was used to calculate TI. Using the Task List, 18 individual Human System Categories were identified as being required to perform each task (e.g., Cardiopulmonary, Cognitive, etc.). Each of the 1200+ tasks were mapped to the Human System categories listed in the Task List. The total number of tasks in each category were tallied to determine how many tasks required each Human System. Lastly, each of the 120 medical conditions from the IMPACT condition list were mapped to the Human System categories to complete the TI calculation. NASA subject matter experts across five medical specialties established consensus for the mapping of each condition. The resulting total tasks impaired by each condition were used to calculate discrete TI values. This process was repeated for each of the four severity/resource utilization variants of each condition, and for each of the three phases of clinical care. Through this process, discrete TI values were calculated for each of the 120 IMPACT medical conditions and their variants. The Task Impairment metric provides higher fidelity, dynamic utility, and quicker analysis of medical impairment compared to the previous Functional Impairment metric used for the Integrated Medical Model. TI will be used for higher fidelity medical impairment analysis and contingency planning during Lunar, Martian, and other long-term exploration-class missions.

William L Fernandez↗
DOE OSTI2024

IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming

Task-based programming models are gaining traction in scientific computing. IRIS is a portable runtime system that exploits multiple heterogeneous programming systems and can discover available resources and manage multiple diverse programming systems (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, and OpenMP) simultaneously. It accounts for the constraints of task dependencies and provides customizable scheduling policies to map those tasks to heterogeneous devices. In this paper, we present new capabilities added to IRIS to improve its portability for heterogeneous programming, build-friendliness, and performance efficiency. The new additions include vendor-specific kernel support, a runtime system with a foreign function interface to eliminate writing wrapper or boilerplate code for heterogeneous kernels, an easy-to-use and configurable CMake-based build environment, automatic and efficient data transfers and orchestration, and the Hunter and DAGGER toolchains to evaluate IRIS’s task scheduling algorithms.

Miniskar, Narasinga Rao↗
DOE OSTI2025

Development of a Multi-Robot System for Autonomous Inspection of Nuclear Waste Tank Pits

This paper introduces the overall design plan, development timeline, and preliminary progress of the Autonomous Pit Exploration System project. This project aims to develop an advanced multi-robot system for the efficient inspection of nuclear waste-storage tank pits. The project is structured into three phases: Phase 1 involves data collection and interface definition in collaboration with Hanford Site experts and university partners, focusing on tank riser geometry and hardware solutions. Phase 2 includes the selection of sensors and robot components, detailed mechanical design, and prototyping. Phase 3 integrates all components into a cohesive system managed by a master control package which also incorporates digital twin and surrogate models, and culminates in comprehensive testing and validation at a simulated tank pit at the Idaho National Laboratory. Additionally, the system’s communication design ensures coordinated operation through shared data, power, and control signals. For transportation and deployment, an electric vehicle (EV) is chosen to support the system for a full 10 h shift with better regulatory compliance for field deployment. A telescopic arm design is selected for its simple configuration and superior reach capability and controllability. Preliminary testing utilizes an educational robot to demonstrate the feasibility of splitting computational tasks between edge and cloud computers. Successful simultaneous localization and mapping (SLAM) tasks validate our distributed computing approach. More design considerations are also discussed, including radiation hardness assurance, SLAM performance, software transferability, and digital twinning strategies.

Nuclear waste management↗
NASA NTRS1999

Can practice eliminate the psychological refractory period effect?

Can people learn to perform two tasks at the same time without interference? To answer this question, the authors trained 6 participants for 36 sessions in a Psychological Refractory Period (PRP) experiment, where Task 1 required a speeded vocal response to an auditory stimulus and Task 2 required a speeded manual response to a visual stimulus. The large PRP effect found initially (353 ms in Session 1) shrank to only about 40 ms over the course of practice, disappearing entirely for 1 of the 6 participants. This reduction in the PRP effect with practice is considerably larger than has been previously reported. The obtained pattern of factor interactions between stimulus onset asynchrony and each of three task difficulty manipulations (Task 1 judgment difficulty, Task 2 stimulus contrast, and Task 2 mapping compatibility) supports a postponement (bottleneck) account of dual-task interference, both before and after practice.

Pitch Perception/physiology↗
DOE OSTI2023

Machine Learning for Cardiac Electrical Imaging

PyTorch code for cardiac electrical imaging using the 12-lead ECG. This code is associated with the paper from CINC 2022. If you use this code, please cite: Paper : https://cinc.org/2022/Program/accepted/26_Preprint.pdf Dataset : https://library.ucsd.edu/dc/object/bb29449106 The code support two tasks: Task 1: Activation Map Reconstruction from ECG Task 2: Transmembrane potential Reconstruction from ECG

Larma, MikelLandajuela↗
NASA NTRS1992

Use of nontraditional flight displays for the reduction of central visual overload in the cockpit

The use of nontraditional flight displays to reduce visual overload in the cockpit was investigated in a dual-task paradigm. Three flight displays (central, peripheral, and ecological) were used between subjects for the primary tasks, and the type of secondary task (object identification or motion judgment) and the presentation of the location of the task in the visual field (central or peripheral) were manipulated with groups. The two visual-spatial tasks were time-shared to study the possibility of a compatibility mapping between task type and task location. The ecological display was found to allow for the most efficient time-sharing.

Weinstein, Lisa F.↗
NASA NTRS2004

Accessing FMS Functionality: The Impact of Design on Learning

In modern commercial and military aircraft, the Flight Management System (FMS) lies at the heart of the functionality of the airplane. The nature of the FMS has also caused great difficulties learning and accessing this functionality. This study examines actual Air Force pilots who were qualified on the newly introduced advanced FMS and shows that the design of the system itself is a primary source of difficulty learning the system. Twenty representative tasks were selected which the pilots could be expected to accomplish on an ' actual flight. These tasks were analyzed using the RAFIV stage model (Sherry, Polson, et al. 2002). This analysis demonstrates that a great burden is placed on remembering complex reformulation of the task to function mapping. 65% of the tasks required retaining one access steps in memory to accomplish the task, 20% required two memorized access steps, and 15% required zero memorized access steps. The probability that a participant would make an access error on the tasks was: two memorized access steps - 74%, one memorized access step - 13%, and zero memorized access steps - 6%. Other factors were analyzed as well, including experience with the system and frequency of use. This completed the picture of a system with many memorized steps causing difficulty with the new system, especially when trying to fine where to access the correct function.

Fennell, Karl↗
NASA NTRSDate not supplied

2024 IEEE GRSS Data Fusion Contest Flood Rapid Mapping

The Challenge Task As a result of climate change, extreme hydrometeorological events are becoming increasingly frequent. Flood rapid mapping products play an important role in informing flood emergency response and management. These maps are generated quickly from remote sensing data during or after an event to show the extent of flooding. They provide important information for emergency response, and damage assessment. The aim of this challenge is to develop data fusion algorithms that generate flood maps by processing spatial data from a variety of sources. The goal of this IEEE challenge (sponsored by NASA and CNES) is to design and develop an algorithm that will combine multi-source data to classify flood surface water extent–that is, water and non-water areas. Provided data sources include optical and SAR remote sensing images as well as a digital terrain model. The output is a gridded flood map where each grid cell is labeled water or non-water. The difficulty of detecting flooded areas can vary greatly depending on the conditions in the area of interest and the event. This data fusion challenge has two tracks representing this variance.

Jacqueline J Le Moigne-stewart↗
DOE OSTI2019

Performance analysis and optimization for scalable deployment of deep learning models for country-scale settlement mapping on Titan supercomputer

Here, we present a scalable object detection workflow for detecting objects, such as settlements, from remotely sensed (RS) imagery. We have successfully deployed this workflow on Titan supercomputer and utilized it for the task of mapping human settlement at a country scale. The performance of various stages in the workflow was analyzed before making it operational. The workflow implemented various strategies to address issues such as suboptimal resource utilization and long-tail effects due to unbalanced image workload, data loss due to runtime failures, and maximum wall-time constraints imposed by Titan's job scheduling policy. A mean shift clustering–based static load balancing strategy was implemented, which partitions the image load such that each partition contained similar-sized images. Furthermore, a checkpoint-restart strategy was added in the workflow as a fault-tolerance mechanism to prevent the data losses due to unforeseen runtime failures. The performance of the above-mentioned strategies was observed in various scenarios, such as node failure, exceeding wall time, and successful completion. Using this workflow, we have examined an RS data set that has a spatial resolution of 0.31 m and is comprised of 685 675 km 2 of area of the Republic of Zambia in under six hours using 5426 nodes of the Titan supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗
NASA NTRS2012

Motion-Capture-Enabled Software for Gestural Control of 3D Models

Current state-of-the-art systems use general-purpose input devices such as a keyboard, mouse, or joystick that map to tasks in unintuitive ways. This software enables a person to control intuitively the position, size, and orientation of synthetic objects in a 3D virtual environment. It makes possible the simultaneous control of the 3D position, scale, and orientation of 3D objects using natural gestures. Enabling the control of 3D objects using a commercial motion-capture system allows for natural mapping of the many degrees of freedom of the human body to the manipulation of the 3D objects. It reduces training time for this kind of task, and eliminates the need to create an expensive, special-purpose controller.

Norris, Jeffrey S.↗