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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Longitudinal analysis of host protein serum signatures of treatment and recovery in pulmonary tuberculosis

A better understanding of treatment progression and recovery in pulmonary tuberculosis (TB) infectious disease is crucial. This study analyzed longitudinal serum samples from pulmonary TB patients undergoing interventional treatment to identify surrogate markers for TB-related outcomes. Serum that was collected at baseline and 8, 17, 26, and 52 weeks from 30 TB patients experiencing durable cure were evaluated and compared using a sensitive LC-MS/MS proteomic platform for the detection and quantification of differential host protein signatures relative to timepoint. The global proteome signature was analyzed for statistical differences across the time course and between disease severity and treatment groups. A total of 676 proteins showed differential expression in the serum over these timepoints relative to baseline. Comparisons to understand serum protein dynamics at 8 weeks, treatment endpoints at 17 and 26 weeks, and post-treatment at 52 weeks were performed. The largest protein abundance changes were observed at 8 weeks as the initial effects of antibiotic treatment strongly impacted inflammatory and immune modulated responses. However, the largest number of proteome changes was observed at the end of treatment time points 17 and 26 weeks respectively. Post-treatment 52-week results showed an abatement of differential proteome signatures from end of treatment, though interestingly those proteins uniquely significant at post-treatment were almost exclusively downregulated. Patients were additionally stratified based upon disease severity and compared across all timepoints, identifying 461 discriminating proteome signatures. These proteome signatures collapsed into discrete expression profiles with distinct pathways across immune activation and signaling, hemostasis, and metabolism annotations. Insulin-like growth factor (IGF) and Integrin signaling maintained a severity signature through 52 weeks, implying an intrinsic disease severity signature well into the post-treatment timeframe. Previous proteome studies have primarily focused on the 8-week timepoint in relation to culture conversion status. While this study confirms previous observations, it also highlights some differences. The inclusion of additional end of treatment and post-treatment time points offers a more comprehensive assessment of treatment progression within the serum proteome. Examining the expression dynamics at these later time periods will help in the investigation of relapse patients and has provided indicative markers of response and recovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Quantitative Performance Assessment of Proxy Apps and Parents

This report completes the AD-CD-PA-1040 Milestone: We will develop a quantitative methodology to compare the fidelity of the ECP proxy applications with respect to the parent ECP application they represent. Fidelity includes comparison of appropriate dynamic execution characteristics (e.g., memory characteristics for a memory-matching proxy), computational requirements, and hardware bottlenecks. This methodology will include metrics and platform specifications (e.g., tools, specific systems), and will be applied to evaluate 4 ECP proxy applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

AOI.1 Application of Artificial Intelligence techniques enabling coal fired power plants the ability to achieve higher efficiency, improved availability, and increased reliability of their operations (Final Report)

During this effort, SparkCognition with support from the Electric Power Research Institute (EPRI) was tasked with applying artificial intelligence (AI) to improve the reliability, efficiency, and safety of operations at a coal-fired plant. By implementing AI techniques, like machine learning (ML), it is believed that operators can leverage existing data sources to gain more insights such as advanced warning of machine degradation. With enough lead time, a reliability engineer can take action to minimize, or even avoid, impact to production. To complete this work effort, SparkCognition developed and refined an ML-based model using sensor data for a Steam Turbine unit at a host site. The models were deployed in an online, web-based solution that allows users to visualize model outputs and supporting data. The final solution, based on SparkCognition’s proprietary software platform called SparkPredict®, was shared with EPRI who completed an online evaluation of results to determine the solution’s ability to detect actionable events.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Toward a persistent event-streaming system for high-performance computing applications

High-performance computing (HPC) applications have traditionally relied on parallel file systems and file transfer services to manage data movement and storage. Alternative approaches have been proposed that use direct communications between application components, trading persistence and fault tolerance for speed. Event-driven architectures, as popularized in enterprise contexts, present a compelling middle ground, avoiding the performance cost and API constraints of parallel file systems while retaining persistence and offering impedance matching between application components. However, adapting streaming frameworks to HPC workloads requires addressing challenges unique to HPC systems. This paper investigates the potential for a streaming framework designed for HPC infrastructures and use cases. We introduce Mofka, a persistent event-streaming framework designed specifically for HPC environments. Mofka combines the capabilities of a traditional streaming service with optimizations tailored to the HPC context, such as support for massively multicore nodes, efficient scaling for large producer-consumer workflows, RDMA-enabled high-performance network communications, specialized network fabrics with multiple links per node, and efficient handling of large scientific data payloads. Built using the Mochi suite of HPC data service components, Mofka provides a lightweight, modular, and high-performance solution for persistent streaming in HPC systems. We present the architecture of Mofka and evaluate its performance against Kafka and Redpanda using benchmarks on diverse platforms, including Argonne's Polaris and Oak Ridge's Frontier supercomputers, showing up to 8× improvement in throughput in some scenarios. We then demonstrate its utility in several real-world applications: a tomographic reconstruction pipeline, a workflow for the discovery of metal-organic frameworks for carbon capture, and the instrumentation of Dask workflows for provenance tracking and performance analysis.

HPC↗
NASA NTRS1984

Techniques for digital enhancement of Landsat MSS data using an Apple II+ microcomputer

The information provided by remotely sensed data collected from orbiting platforms has been useful in many research fields. Particularly convenient for evaluation are generally digital data stored on computer compatible tapes (CCT's). The major advantages of CCT's are the quality of the data and the accessibility to computer manipulation. Minicomputer systems are widely used for the required computer processing operations. However, microprocessor-related technological advances make it now possible to process CCT data with computing systems which can be obtained at a much lower price than minicomputer systems. A detailed description is provided of the design considerations of a microcomputer-based Digital Image Analysis System (DIAS). Particular attention is given to the algorithms which are incorporated for eighter edge enhancement or smoothing Landsat multispectral scanner data.

Harrington, J. A., Jr.↗
NASA NTRS1987

Impact of satellite-based data on FGGE general circulation statistics

The NASA Goddard Laboratory for Atmospheres (GLA) analysis/forecast system was run in two different parallel modes in order to evaluate the influence that data from satellites and other FGGE observation platforms can have on analyses of large scale circulation; in the first mode, data from all observation systems were used, while in the second only conventional upper air and surface reports were used. The GLA model was also integrated for the same period without insertion of any data; an independent objective analysis based only on rawinsonde and pilot balloon data is also performed. A small decrease in the vigor of the general circulation is noted to follow from the inclusion of satellite observations.

Salstein, David A.↗
NASA NTRS2021

Teleoperation and Visualization Interfaces for Remote Intervention in Space

Approaches to robotic manufacturing, assembly, and servicing of in-space assets range from autonomous operation to direct teleoperation, with many forms of semi-autonomous teleoperation in between. Because most approaches require one or more human operators at some level, it is important to explore the control and visualization interfaces available to those operators, taking into account the challenges due to significant telemetry time delay. We consider one motivating application of remote teleoperation, which is ground-based control of a robot on-orbit for satellite servicing. This paper presents a model-based architecture that: 1) improves visualization and situation awareness, 2) enables more effective human/robot interaction and control, and 3) detects task failures based on anomalous sensor feedback. We illustrate elements of the architecture by drawing on 10 years of our research in this area. The paper further reports the results of several multi-user experiments to evaluate the model-based architecture, on ground-based test platforms, for satellite servicing tasks subject to round-trip communication latencies of several seconds. The most significant performance gains were obtained by enhancing the operators’ situation awareness via improved visualization and by enabling them to precisely specify intended motion. In contrast, changes to the control interface, including model-mediated control or an immersive 3D environment, often reduced the reported task load but did not significantly improve task performance. Considering the challenges of fully autonomous intervention, we expect that some form of teleoperation will continue to be necessary for robotic in-situ servicing, assembly, and manufacturing tasks for the foreseeable future. We propose that effective teleoperation can be enabled by modeling the remote environment, providing operators with a fused view of the real environment and virtual model, and incorporating interfaces and control strategies that enable interactive planning, precise operation, and prompt detection of errors.

space robotics↗
NASA NTRS2021

ISAAC

This document describes the ISAAC (Integrated Structural Assembly of Advanced Composites) robotic system. ISAAC is a highly accurate, automated robotic platform used to support research on the design, analysis, manufacturing and evaluation of advanced composite materials and structures. ISAAC can build composite parts using automated fiber placement (AFP) and stitching through the thickness of dry fabric. The system is frequently upgraded to include new capabilities. ISAAC is located at the NASA Langley Research Center

carbon-epoxy↗
NASA NTRS2026

SCOAPE-II: A 2024 Multiplatform Measurement Campaign off the US Gulf Coast to Assess Oil and Gas Emissions on the Outer Continental Shelf

Nine years ago, the Department of Interior’s Bureau of Ocean Energy Management (BOEM), the Agency with Air Quality (AQ) jurisdiction over the Outer Continental Shelf (OCS) of the US Gulf Coast west of 87.5° W longitude, asked NASA to determine the feasibility of using satellite data to measure offshore emissions in a region of concentrated oil and natural gas (ONG) operations. To study this issue NASA and BOEM conducted the May 2019 Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf. SCOAPE addressed both technological and scientific issues related to measuring nitrogen dioxide (NO 2 , a common air pollutant), including contrasting near-shore and deepwater regimes. Given the April 2023 launch of the geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) AQ satellite, a 2024 SCOAPE-II was conducted in the Gulf with both ship and aircraft measurements. We present an overview of the SCOAPE-II campaign, analysis and validation of satellite-observed NO 2 , and evaluate measurements of methane from ship, aircraft, and satellite near ONG platforms. Our SCOAPE-II results are as follows: 1) Satellite NO 2 measurements (∼13:30 local time) from the TROPOspheric Monitoring Instrument (TROPOMI) are more accurate than TEMPO’s hourly scans (8.6% vs. 23.6% mean absolute bias); a new version of TEMPO data is currently being processed; 2) ship and aircraft measurements captured dozens of NO 2 and methane plumes from ONG operations, showing that they are persistent emitters; 3) satellite measurements of methane failed to replicate ship and aircraft measurements, presenting ongoing challenges for operational emissions monitoring over the Gulf.

satellite validation↗
DOE OSTI2015

Design of a Large-scale Virtual Power Grid for Research Community

Due to security and liability concerns, the research community has limited access to realistic large-scale power grid models to test and validate new operation and control methodologies. It is also difficult for industry to evaluate the relative value of competing new tools without a common platform for comparison. This paper proposes to develop a large-scale virtual power grid model that retains basic features and represents future trends of major U.S. electric interconnections. The proposed model will include realistic power flow and dynamics information as well as a relevant geospatial distribution of assets. This model will be made widely available to the research community for various power system stability and control studies and can be used as a common platform for comparing the efficacies of various new technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Test Methodologies for Hydrogen Sensor Performance Assessment: Chamber vs. Flow Through Test Apparatus: Preprint

Certification of hydrogen sensors to standards often prescribes using large-volume test chambers [1, 2]. However, feedback from stakeholders such as sensor manufacturers and end-users indicate that chamber test methods are often viewed as too slow and expensive for routine assessment. Flow through test methods potentially are an efficient, cost-effective alternative for sensor performance assessment. A large number of sensors can be simultaneously tested, in series or in parallel, with an appropriate flow through test fixture. The recent development of sensors with response times of less than 1s mandates improvements in equipment and methodology to properly capture the performance of this new generation of fast sensors; flow methods are a viable approach for accurate response and recovery time determinations, but there are potential drawbacks. According to ISO 26142 [1], flow through test methods may not properly simulate ambient applications. In chamber test methods, gas transport to the sensor can be dominated by diffusion which is viewed by some users as mimicking deployment in rooms and other confined spaces. Alternatively, in flow through methods, forced flow transports the gas to the sensing element. The advective flow dynamics may induce changes in the sensor behaviour relative to the quasi-quiescent condition that may prevail in chamber test methods. One goal of the current activity in the JRC and NREL sensor laboratories [3, 4] is to develop a validated flow through apparatus and methods for hydrogen sensor performance testing. In addition to minimizing the impact on sensor behaviour induced by differences in flow dynamics, challenges associated with flow through methods include the ability to control environmental parameters (humidity, pressure and temperature) during the test and changes in the test gas composition induced by chemical reactions with upstream sensors. Guidelines on flow through test apparatus design and protocols for the evaluation of hydrogen sensor performance are being developed. Various commercial sensor platforms (e.g., thermal conductivity, catalytic and metal semiconductor) were used to demonstrate the advantages and issues with the flow through methodology.

14 SOLAR ENERGY↗
DOE OSTI2016

Computer Codes V and V Tests with a Large-Scale Sodium Thermal-Hydraulic Test Facility (STELLA)

The Korea Atomic Energy Research Institute (KAERI) is carrying out the design of a 'Prototype Generation IV Sodium-cooled Fast Reactor (PGSFR)' in cooperation with Argonne National Laboratory (ANL) in the US. In regard to computer codes V and V, a large-scale sodium thermal-hydraulic test program is currently being progressed in parallel with the PGSFR design, which is called STELLA (Sodium Test Loop for Safety Simulation and Assessment). The final objective of this program is to collect a separate and integral effect test database to validate the safety analysis codes and other thermal hydraulic design codes. In the first phase of the STELLA program, the sodium component test loop (hereafter called STELLA-1) was constructed at the KAERI site, and it has been used for performance tests of key sodium heat exchangers in PGSFR. Since this sodium test loop is basically for separate effects tests to verify the performance of key sodium components, the test database obtained from STELLA-1 has been used for the V and V of safety codes as well as heat exchanger design codes. The second phase of the program aiming at an integral effect test is called STELLA-2, which will be used for synthetic review of the key safety issues of PGSFR. The basic and detailed design phases of the STELLA-2 test facility are underway in accordance with the specific design requirements reflecting the whole design features of PGSFR. The facility installation is scheduled to be completed by 2018. Then the main experiments including the start-up tests will begin and the first integral effect test database will be constructed by the end of 2019. Based on the STELLA-2 platform, a simulation of the PGSFR transient will be made to evaluate the plant dynamic behaviors and demonstrate the decay heat removal performance. Multi-dimensional effects coming from a large sodium pool system will be identified as well. The test database obtained from the STELLA-2 experiment will be used for the validation of the safety analysis codes and other thermal hydraulics codes, and this project finally contributes to the specific design phase of PGSFR. This paper presents both the results of heat transfer tests for the key sodium heat exchangers using STELLA-1 and the first results of heat exchanger design codes V and V. The recent progress of the engineering design for the STELLA-2 test section is introduced and its specific design parameters are also presented in this paper with detailed evaluation results of their scaling distortions. A large-scale sodium thermal-hydraulic test program (STELLA) was introduced with the specific activities for separate and integral effects tests. The test database obtained from STELLA-1 was successfully used to validate both the heat exchanger design and safety analysis codes. Specific design features of the integral effects test facility (STELLA- 2) with a scaling ratio of 1/5 in length and 1/125 in volume were also presented. Validation of the STELLA-2 facility design is underway using system codes and CFD tools. Dedicated water-mockup experiments to verify the scaling design of key subsystems are currently being conducted as well. (authors)

42 ENGINEERING↗
NASA NTRS2012

Cumulative Measurement Errors for Dynamic Testing of Space Flight Hardware

Located at the NASA Johnson Space Center in Houston, TX, the Six-Degree-of-Freedom Dynamic Test System (SDTS) is a real-time, six degree-of-freedom, short range motion base simulator originally designed to simulate the relative dynamics of two bodies in space mating together (i.e., docking or berthing). The SDTS has the capability to test full scale docking and berthing systems utilizing a two body dynamic docking simulation for docking operations and a Space Station Remote Manipulator System (SSRMS) simulation for berthing operations. The SDTS can also be used for nonmating applications such as sensors and instruments evaluations requiring proximity or short range motion operations. The motion base is a hydraulic powered Stewart platform, capable of supporting a 3,500 lb payload with a positional accuracy of 0.03 inches. The SDTS is currently being used for the NASA Docking System testing and has been also used by other government agencies. The SDTS is also under consideration for use by commercial companies. Examples of tests include the verification of on-orbit robotic inspection systems, space vehicle assembly procedures and docking/berthing systems. The facility integrates a dynamic simulation of on-orbit spacecraft mating or de-mating using flight-like mechanical interface hardware. A force moment sensor is used for input during the contact phase, thus simulating the contact dynamics. While the verification of flight hardware presents unique challenges, one particular area of interest involves the use of external measurement systems to ensure accurate feedback of dynamic contact. The measurement systems for the test facility have two separate functions. The first is to take static measurements of facility and test hardware to determine both the static and moving frames used in the simulation and control system. The test hardware must be measured after each configuration change to determine both sets of reference frames. The second function is to take dynamic measurements during hardware motion and contact. While performing dynamic testing of an active docking system, researchers found that the data from the motion platform, test hardware and two external measurement systems exhibited frame offsets and rotational errors. While the errors were relatively small when considering the motion scale overall, they substantially exceeded the individual accuracies for each component. After evaluating both the static and dynamic measurements, researchers found that the static measurements introduced significantly more error into the system than the dynamic measurements even though, in theory, the static measurement errors should be smaller than the dynamic. In several cases, the magnitude of the errors varied widely for the static measurements. Upon further investigation, researchers found the larger errors to be a consequence of hardware alignment issues, frame location and measurement technique whereas the smaller errors were dependent on the number of measurement points. This paper details and quantifies the individual and cumulative errors of the docking system and describes methods for reducing the overall measurement error. The overall quality of the dynamic docking tests for flight hardware verification was improved by implementing these error reductions.

Winnitoy, Susan↗
DOE OSTI2019

Applying Machine Learning to Understand Write Performance of Large-scale Parallel Filesystems

In high-performance computing (HPC), I/O performance prediction offers the potential to improve the efficiency of scientific computing. In particular, accurate prediction can make runtime estimates more precise, guide users toward optimal checkpoint strategies, and better inform facility provisioning and scheduling policies. HPC I/O performance is notoriously difficult to predict and model, however, in large part because of inherent variability and a lack of transparency in the behaviors of constituent storage system components. In this work we seek to advance the state of the art in HPC I/O performance prediction by (1) modeling the mean performance to address high variability, (2) deriving model features from write patterns, system architecture and system configurations, and (3) employing Lasso regression model to improve model accuracy. We demonstrate the efficacy of our approach by applying it to a crucial subset of common HPC I/O motifs, namely, file-per-process checkpoint write workloads. We conduct experiments on two distinct production HPC platforms—Titan at the Oak Ridge Leadership Computing Facility and Cetus at the Argonne Leadership Computing Facility—to train and evaluate our models. We find that we can attain ≤ 30% relative error for 92.79% and 99.64% of the samples in our test set on these platforms, respectively.

Xie, Bing↗
NASA NTRS1981

Visible infrared spin-scan radiometer atmospheric sounder radiometric calibration - An inflight evaluation from intercomparisons with HIRS and radiosonde measurements

The ability to conduct soundings from a geostationary platform has been demonstrated with the Visible IR spin-scan radiometer Atmospheric Sounder (VAS) aboard GOES-4. While a negative offset reaching 2.0-3.0 C for the upper atmospheric CO2 bands of VAS was observed in comparisons with High Resolution IR Radiation Sounder (HIRS) measurements and analyses of radiosonde data, VAS radiances are consistent with that material. After removing the offset, the temperature profiles derived from VAS radiances agree very well with those observed by radiosondes. Time variations in the atmospheric state are discernible from VAS soundings at three-hour intervals, and were confirmed by radiosonde observations.

Menzel, W. P.↗
NASA NTRS2021

Systems Engineering and Assurance Modeling (SEAM): A Web-Based Solution for Integrated Mission Assurance

We present an overview of the Systems Engineering and Assurance Modeling (SEAM) platform, a web-browser-based tool which is designed to help engineers evaluate the radiation vulnerabilities and develop an assurance approach for electronic parts in space systems. The SEAM framework consists of three interconnected modeling tools, a SysML compatible system description tool, a Goal Structuring Notation (GSN) visual argument tool, and Bayesian Net and Fault Tree extraction and export tools. The SysML and GSN sections also have a coverage check application that ensures that every radiation fault identified on the SysML side is also addressed in the assurance case in GSN. The SEAM platform works on space systems of any degree of radiation hardness but is especially helpful for assessing radiation performance in systems with commercial-off-the-shelf (COTS) electronic components.

SEAM↗