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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

A distributed analysis and visualization system for model and observational data

The objective of this proposal is to develop an integrated and distributed analysis and display software system which can be applied to all areas of the Earth System Science to study numerical model and earth observational data from storm to global scale. This system will be designed to be easy to use, portable, flexible and easily extensible and to adhere to current and emerging standards whenever possible. It will provide an environment for visualization of the massive amounts of data generated from satellites and other observational field measurements and from model simulations during or after their execution. Two- and three-dimensional animation will also be provided. This system will be based on a widely used software package from NASA called GEMPAK and prototype software for three dimensional interactive displays built at NCSA. The underlying foundation of the system will be a set of software libraries which can be distributed across a UNIX based supercomputer and workstations.

Wilhelmson, Robert↗
NASA NTRS1992

Radar Analysis and Visualization Environment (RAVEN): Software for polarimetric radar analysis

Imaging radar data provides information about the geometric and dielectric properties of the Earth's surface. The Jet Propulsion Laboratory (JPL) polarimetric Airborne Synthetic Aperture Radar (AIRSAR) is currently obtaining imaging radar data for use in geologic, vegetation, snow and ice, and ocean studies. In the near future, the Shuttle Imaging Radar C (SIR-C/X-SAR) and the Earth Observing System Synthetic Aperture Radar (EOS SAR) will also collect polarimetric radar data. A need exists for a user-friendly, interactive software package for analysis of these polarimetric radar data sets. Previous software packages, such as JPL's Multiview, while providing some analysis capabilities for these data, did not allow interactive viewing and were tied to specific image display hardware with operating system dependencies. A prototype software system, the 'Radar Analysis and Visualization Environment' (RAVEN) under development at the Center for the Study of Earth from Space (CSES) at the University of Colorado, is designed to deal with data from the JPL AIRSAR instrument and other proposed polarimetric radar instruments. RAVEN is being developed using the Interactive Data Language (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system in an X-windows environment to allow for rapid, interactive visualization of AIRSAR data in both image and graphical ways. It provides a user-friendly interface through the use of menus, sliders, buttons, and display windows.

Kierein-Young, K. S.↗
NASA NTRSDate not supplied

PlanetarY Telemetric Helicopter for Investigation and Analysis (PYTHIA): A Rotorcraft for Martian Lava Tube Exploration

The PlanetarY Telemetric Helicopter for Investigation and Analysis (PYTHIA) project presents an early feasibility study into future Mars rotorcraft. With the success of Ingenuity and the current development of the Mars Sample Retrieval Helicopters, there is motivation to explore additional vehicle concepts for Mars exploration. This work presents an early conceptual design of a lava tube exploring quadrotor. The nominal mission for the PYTHIA quadrotor includes a two-phase in-depth exploration of one or mutliple lava tubes in the area of interest, Arsia Mons. A sizing analysis was completed using the NASA Design and Analysis of Rotorcraft (NDARC) tool. An eight-bladed quadrotor was selected based on the NDARC sizing sweeps. With preliminary vehicle and blade sizing completed, a flow visualization study was conducted. Two simulations were completed in Rotorcraft Computational Fluid Dynamics (RotCFD): one of the quadrotor alone and another in a lava tube. This paper introduces a baseline reference mission, preliminary vehicle design, and initial sizing analysis of a rotorcraft to explore Martian lava tubes.

PlanetarY↗
NASA NTRSDate not supplied

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗
NASA NTRS1976

Aerodynamic validation of a SCAR design

Wind tunnel test of the McDonnell Douglas Supersonic Cruise Aircraft, designed for a cruise Mach number of 2.2, was conducted in the NASA Ames Unitary Plan Wind Tunnels. Extensive force, pressure, and flow visualization data were obtained over a Mach number range from 0.5 to 2.4. Comparisons between theory and measurements of both forces and pressure concentrate on the results obtained in the supersonic tunnel. Schlieren and tuft pictures are presented to help provide an understanding of the nonlinearities observed at off-design conditions.

Roensch, R. L.↗
DOE OSTI2019

TexTonic: Interactive Visualization for Exploration and discovery of Very Large Text Collections

TexTonic is a visual analytic system for interactive exploration of very large unstructured text collections. TexTonic visualizes hierarchical clusters of representative terms, snippets, and documents in a single, multi-scale spatial layout. Exploration is supported by interacting with the visualization and directly manipulating the terms in the visualization using semantic interactions. These semantic interactions steer the underlying analytic model by translating user interactions within the visualization to contextual updates to the supporting data model. The combination of semantic interactions and information visualization at multiple levels of the data hierarchy helps users manage information overload so that they can more effectively explore very large text collections. In this paper we describe TexTonic’s data processing and analytic pipeline, user interface and interaction design principles, and the results of a user study conducted mid-development with experienced data analysts. We also discuss the implications TexTonic could have on visual exploration and discovery tasks

human centered computing, Visual analytics, Inform↗
DOE OSTI2015

MO-FG-303-01: FEATURED PRESENTATION and BEST IN PHYSICS (THERAPY): Automating LINAC QA: Design and Testing of An Image Acquisition and Processing System Utilizing a Combination of Radioluminescent Phosphors, Embedded X-Ray Markers and Optical Measurements

Purpose: The recent development of phosphors to visualize radiation beams from linear accelerators (LINAC) offers a unique opportunity for evaluating radiation fields within the context of the treatment space. The purpose of this study was to establish an automated, self-calibrating prototype system for performing quality assurance (QA) measurements. Methods: A thin layer of Gd{sub 2}O{sub 2}S:Tb phosphor and fiducial markers were embedded on several planar faces of a custom-designed phantom. The phantom was arbitrarily placed near iso-center on the couch of a LINAC equipped with on-board megavoltage (MV) and kilovoltage (kV) imagers. A plan consisting of several beams and integrated image acquisitions was delivered. Images of the phantom were collected throughout the delivery. Salient features, such as fiducials, crosshairs and beam edges were then extracted from these images used to calibrate the system, adjust for variations in phantom placement, and perform measurements. Beam edges were visualized by imaging the light generated by the phosphor on the phantom enabling direct comparison with the light field and laser locations. Registration of MV, kV and optical image data was performed using the embedded fiducial markers, enabling comparison of imaging center locations. Measurements specified by TG-142 were calculated and compared with those obtained from a commercially available QA system. Results: The system was able to automatically extract the location of the fiducials, lasers, light field and radiation field from the acquired images regardless of phantom positioning. It was also able to automatically identify the locations of fiducial markers on kV and MV images. All collected measurements were within TG-142 guidelines. The difference between the prototype and commercially available system were less than 0.2 mm. Conclusion: The prototype system demonstrated the capability of accurately and autonomously evaluating various TG-142 parameters independent of operator input and phantom setup.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Standardized nomenclature for photovoltaic connectors

Photovoltaic (PV) systems rely on discrete connectors for the efficient and safe flow of power from module to module and from strings to combiner boxes and inverters. Despite their functional importance, no common nomenclature for PV connectors currently exists, resulting in confusion and miscommunication. Misunderstood terms like "MC4 compatible", "cross-mating", "intermating", "female", and "male" can lead to installation and maintenance errors and compromise system reliability. We believe a standardized terminology will reduce confusion, help support installation best practices, aid in maintenance and repair, inform next-generation designs, and provide a technical basis for improved codes and standards. To that end, we are proposing a standardized glossary for 4 mm PV connectors (the most common type of connector used in PV applications) based on, and validated by, a Sandia National Laboratories' investigation that included the following sources: 1) a comprehensive review of official documents from 20 connector manufacturers, including schematics, datasheets, installation manuals, and catalogs, as well as relevant patents; 2) two rounds of surveys distributed to stakeholders, including connector manufacturers, engineers, asset owners, test labs, and researchers; and 3) visual examination of 25 different models of 4 mm single-pole DC PV connectors to document variations in design and functionality. This work provides a foundation for establishing a clear and consistent terminology for PV connectors that will in turn enable progress toward greater reliability and collaboration across the industry.

14 SOLAR ENERGY↗
NASA NTRS2013

Enhanced Flight Vision Systems and Synthetic Vision Systems for NextGen Approach and Landing Operations

Synthetic Vision Systems and Enhanced Flight Vision System (SVS/EFVS) technologies have the potential to provide additional margins of safety for aircrew performance and enable operational improvements for low visibility operations in the terminal area environment with equivalent efficiency as visual operations. To meet this potential, research is needed for effective technology development and implementation of regulatory standards and design guidance to support introduction and use of SVS/EFVS advanced cockpit vision technologies in Next Generation Air Transportation System (NextGen) operations. A fixed-base pilot-in-the-loop simulation test was conducted at NASA Langley Research Center that evaluated the use of SVS/EFVS in NextGen low visibility approach and landing operations. Twelve crews flew approach and landing operations in a simulated NextGen Chicago O'Hare environment. Various scenarios tested the potential for using EFVS to conduct approach, landing, and roll-out operations in visibility as low as 1000 feet runway visual range (RVR). Also, SVS was tested to evaluate the potential for lowering decision heights (DH) on certain instrument approach procedures below what can be flown today. Expanding the portion of the visual segment in which EFVS can be used in lieu of natural vision from 100 feet above the touchdown zone elevation to touchdown and rollout in visibilities as low as 1000 feet RVR appears to be viable as touchdown performance was acceptable without any apparent workload penalties. A lower DH of 150 feet and/or possibly reduced visibility minima using SVS appears to be viable when implemented on a Head-Up Display, but the landing data suggests further study for head-down implementations.

Kramer, Lynda J.↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Catalyst Revised: Rethinking the ParaView in Situ Analysis and Visualization API

As in situ analysis goes mainstream, ease of development, deployment, and maintenance becomes essential, perhaps more so than raw capabilities. In this paper, we present the design and implementation of Catalyst, an API for in situ analysis using ParaView, which we refactored with these objectives in mind. Furthermore, our implementation combines design ideas from in situ frameworks and HPC tools like Ascent and MPICH.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Q-VR: System-Level Design for Future Mobile Collaborative Virtual Reality

High Quality Mobile Virtual Reality (VR) is what the incoming graphics technology era demands: users around the world, regardless of their hardware and network conditions, can all enjoy the immersive virtual experience. However, the state-of-the-art software-based mobile VR designs cannot fully satisfy the realtime performance requirements due to the highly interactive nature of user's actions and complex environmental constraints during VR execution. Inspired by the unique human visual system effects and the strong correlation between VR motion features and realtime hardware-level information, we propose Q-VR, a novel dynamic collaborative rendering solution via software-hardware co-design for enabling future low-latency high-quality mobile VR. At software-level, Q-VR provides flexible high-level tuning interface to reduce network latency while maintaining user perception. At hardware-level, Q-VR accommodates a wide spectrum of hardware and network conditions across users by effectively leveraging the computing capability of the increasingly powerful VR hardware. Extensive evaluation on real-world games demonstrates that Q-VR can achieve an average end-to-end performance speedup of 3.4x (up to 6.7x) over the traditional local rendering design in commercial VR devices, and a 4.1x frame rate improvement over the state-of-the-art static collaborative rendering.

Xie, Chenhao↗
NASA NTRS1995

Space and time aliasing structure is monthly mean polar-orbiting satellite data

Monthly mean wind fields from the European Remote Sensing Satellite (ERS1) scatterometer are presented. A banded structure which resembles the satellite subtrack is clearly and consistently apparent in the isotachs as well as the u and v components of the routinely produced fields. The structure also appears in the means of data from other polar-orbiting satellites and instruments. An experiment is designed to trace the cause of the banded structure. The European Centre for Medium-Range Weather Forecast (ECMWF) gridded surface wind analyses are used as a control set. These analyses are also sampled with the ERS1 temporal-spatial samplig pattern to form a simulated scatterometer wind set. Both sets are used to create monthly averages. The banded structures appear in the monthly mean simulated data but do not appear in the control set. It is concluded that the source of the banded structure lies in the spatial and temporal sampling of the polar-orbiting satellite which results in undersampling. The problem involves multiple timescales and space scales, oversampling and under-sampling in space, aliasing in the time and space domains, and preferentially sampled variability. It is shown that commonly used spatial smoothers (or filters), while producing visually pleasing results, also significantly bias the true mean. A three-dimensional spatial-temporal interpolator is designed and used to determine the mean field. It is found to produce satisfactory monthly means from both simulated and real ERS1 data. The implications to climate studies involving polar-orbiting satellite data are discussed.

Zeng, Lixin↗
DOE OSTI2025

Techno-economics of hydrocarbon fuel production and recyclables recovery from landfill-destined municipal solid waste: AI-enhanced materials recovery facility design

Sustainable aviation fuels (SAF) production from cellulosic paper fractions of municipal solid waste (MSW) destined for landfills has strong potential to advance environmental, social, and economic sustainability across the aviation and waste sectors. This study proposes an artificial intelligence-enabled material recovery facility (AI-MRF) design to efficiently characterize, separate, process, and convert recovered paper waste from MSW into intermediate chemicals and SAF. The AI-MRF, designed to process 233,091 metric tons of MSW annually, integrates smart manufacturing technologies including AI, visual and hyperspectral imaging, multi-sensor data, and traditional sorting systems. Well-characterized and sorted cellulosic paper waste was utilized for chemical and fuel production scenarios, while clean plastics, metals, and glass were considered for recycling. Conversion of paper waste into intermediate sugars achieved a net present value (NPV) of up to $\$67$ million. For sugar-to-SAF production scenarios, the minimum fuel selling price (MFSP) was calculated at $\$6.11$ per gasoline gallon equivalent (GGE) when excluding recyclable revenue, and $\$4.03$ per GGE when halving recyclable revenue. The MFSP was further reduced to $\$1.96$ per GGE when accounting for SAF sales and recyclables. Nationally, this approach could yield about 2 billion GGE of hydrocarbon fuel annually from available MSW in the United States.

09 BIOMASS FUELS↗
DOE OSTI2014

Analyzer-based phase-contrast imaging system using a micro focus x-ray source

Here we describe a new in-laboratory analyzer based phase contrast-imaging (ABI) instrument using a conventional X-ray tube source (CXS) aimed at bio-medical imaging applications. Phase contrast-imaging allows visualization of soft tissue details usually obscured in conventional X-ray imaging. The ABI system design and major features are described in detail. The key advantage of the presented system, over the few existing CXS ABI systems, is that it does not require high precision components, i.e., CXS, X-ray detector, and electro-mechanical components. To overcome a main problem introduced by these components, identified as temperature stability, the system components are kept at a constant temperature inside of three enclosures, thus minimizing the electrical and mechanical thermal drifts. This is achieved by using thermoelectric (Peltier) cooling/heating modules that are easy to control precisely. For CXS we utilized a microfocus X-ray source with tungsten (W) anode material. In addition the proposed system eliminates tungsten's multiple spectral lines by selecting monochromator crystal size appropriately therefore eliminating need for the costly mismatched, two-crystal monochromator. The system imaging was fine-tuned for tungsten Kα{sub 1} line with the energy of 59.3 keV since it has been shown to be of great clinical significance by a number of researchers at synchrotron facilities. In this way a laboratory system that can be used for evaluating and quantifying tissue properties, initially explored at synchrotron facilities, would be of great interest to a larger research community. To demonstrate the imaging capability of our instrument we use a chicken thigh tissue sample.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design

Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art graph learning model. However, it remains notoriously challenging to inference GCNs over large graph datasets, limiting their application to large real-world graphs and hindering the exploration of deeper and more sophisticated GCN graphs. This is because real-world graphs can be extremely large and sparse. Furthermore, the node degree of GCNs tends to follow the power-law distribution and therefore have highly irregular adjacency matrices, resulting in prohibitive inefficiencies in both data processing and movement and thus substantially limiting the achievable GCN acceleration efficiency. To this end, this paper proposes the first GCN algorithm and accelerator Co-Design framework dubbed GCoD which can largely alleviate the aforementioned GCN irregularity and boost GCNs' inference efficiency. Specifically, on the algorithm level, GCoD integrates a divide and conquer GCN training strategy that polarizes the graphs to be either denser or sparser in local neighborhoods without compromising the model accuracy, resulting in graph adjacency matrices that (mostly) have merely two levels of workload and enjoys largely enhanced regularity and thus ease of acceleration. On the hardware level, we further develop a dedicated two-pronged accelerator with a separated engine to process each of the aforementioned workloads, further boosting the overall utilization and acceleration efficiency. Extensive experiments and ablation studies validate that our GCoD consistently outperforms state-of-the-art designs in terms of accelerator efficiency while maintaining or even improving the task accuracy. Additionally, we visualize GCoD trained graph adjacency matrices to better understand its advantages. All codes and pre-trained models will be released upon acceptance.

You, Haoran↗
DOE OSTI2021

CrossCheck: Rapid, Reproducible, and Interpretable Model Evaluation

Evaluation beyond aggregate performance metrics, e.g. F1-score, is crucial to both establish an appropriate level of trust in machine learning models and identify future model improvements. In this paper we demonstrate CrossCheck, an interactive visualization tool for rapid crossmodel comparison and reproducible error analysis. We describe the tool and discuss design and implementation details. We then present three use cases (named entity recognition, reading comprehension, and clickbait detection) that show the benefits of using the tool for model evaluation. CrossCheck allows data scientists to make informed decisions to choose between multiple models, identify when the models are correct and for which examples, investigate whether the models are making the same mistakes as humans, evaluate models’ generalizability and highlight models’ limitations, strengths and weaknesses. Furthermore, CrossCheck is implemented as a Jupyter widget, which allows rapid and convenient integration into data scientists’ model development workflows.

Arendt, Dustin L.↗