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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DeepDataProfiler: A Platform and Methodology for the Analysis and Interpretation of Neural Networks

The DeepDataProfiler is a methodology and framework for providing interpretability to trained neural networks. Its approach is to decompose a network into a weighted graph of neurons and synapses and link the components of the graph to human identifiable concepts. By identifying concepts important to the network and tracking the decision process employed by the network, the network becomes more transparent and less like a black box. Spurious decisions and poor generalization strategies can be identified and a measure of trustworthiness can be established.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Leveraging microfluidic dielectrophoresis to distinguish compositional variations of lipopolysaccharide in E. coli

Lipopolysaccharide (LPS) is the unique feature that composes the outer leaflet of the Gram-negative bacterial cell envelope. Variations in LPS structures affect a number of physiological processes, including outer membrane permeability, antimicrobial resistance, recognition by the host immune system, biofilm formation, and interbacterial competition. Rapid characterization of LPS properties is crucial for studying the relationship between these LPS structural changes and bacterial physiology. However, current assessments of LPS structures require LPS extraction and purification followed by cumbersome proteomic analysis. This paper demonstrates one of the first high-throughput and non-invasive strategies to directly distinguish Escherichia coli with different LPS structures. Using a combination of three-dimensional insulator-based dielectrophoresis (3DiDEP) and cell tracking in a linear electrokinetics assay, we elucidate the effect of structural changes in E. coli LPS oligosaccharides on electrokinetic mobility and polarizability. We show that our platform is sufficiently sensitive to detect LPS structural variations at the molecular level. To correlate electrokinetic properties of LPS with the outer membrane permeability, we further examined effects of LPS structural variations on bacterial susceptibility to colistin, an antibiotic known to disrupt the outer membrane by targeting LPS. Our results suggest that microfluidic electrokinetic platforms employing 3DiDEP can be a useful tool for isolating and selecting bacteria based on their LPS glycoforms. Future iterations of these platforms could be leveraged for rapid profiling of pathogens based on their surface LPS structural identity.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2023

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers, and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Carl Malings↗
NASA NTRSDate not supplied

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Nathan R. Pavlovic↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗
DOE OSTI2020

Dragonstone Strategy Kickoff Report [Slides]

The oil & natural gas (ONG) system like any other heavy industrial process, relies on a complex system of information technology (IT) and operational technology (OT) devices. Cyber-preparedness varies across the ONG industry from organization to organization. Common challenges include remote locations, long-lived field assets, and insufficient capabilities to find and track malware. ONG companies tend to be concerned with lack of cyber-awareness from employees, risk stemming from remote access for operations & maintenance, and software vulnerabilities within third-party equipment. For a variety of reasons, the general consensus from stakeholders interviewed by LLNL is that the state of cybersecurity within the electric grid is currently outpacing its ONG cousin. Existing strategies for the resilience and cybersecurity of the electric grid can and should be leveraged to provide immediate benefits to the ONG system. In LLNL’s view, there are two key factors currently limiting the development of necessary cyber-practices within the ONG industry: regulatory overlap and inefficiencies, and lack of industry awareness of potentially useful technologies for solving known issues. In the months following this report, LLNL will develop a cyber-resilience roadmap for the oil & gas pipeline sector, coupling threat intelligence, industry knowledge base, and ongoing outreach

02 PETROLEUM↗
DOE OSTI2023

Dark Matter and Track Triggering with the CMS Experiment (Final Report)

This report summarizes the progress from DOE Early Career Award entitled “Dark Matter and Track Triggering with the CMS Experiment”. The first major goal of the project was to establish a sensitive Dark Matter (DM) search program for the CMS experiment in Run-2 of the LHC. Two related strategies were developed to accomplish this goal. First, we designed and executed searches for DM produced in association with heavy flavor quark pairs, top/anti-top (ttbar) and bottom/anti-bottom (bbbar). In addition, we sought to maximize the power of Run-2 DM searches through the development of a statistical combination of all major search channels within a consistent theoretical framework. The results of these aspects of the project are detailed in Section 1. The second major goal of the project was to develop a real-time “Level-1” tracking trigger system for the high-luminosity LHC (HL-LHC) CMS upgrade. Charged particle tracking in the first stage of the CMS trigger will be crucial for surviving the high-pileup environment expected at the HL-LHC. The L1 tracking trigger must process all front-end hit data sent from the inner Tracker and will have just 4us to output track primitives to the downstream L1 trigger without data loss. Our development of the CMS tracking trigger is described in Section 2. The team supported by the award is given in Section 3. The project resulted in 10 peer reviewed publications, a graduate student thesis, and contributions to the CMS Phase-2 Tracker Technical Design Report, as is detailed in Section 4. Our development work for the CMS tracking trigger has been integrated in the backend system architecture for the Tracker upgrade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Network Based Estimation of Wind Farm Power and Velocity Data Under Changing Wind Direction

This paper describes an estimation algorithm for velocity and power output signals in a wind farm under changing wind direction. A graph-theoretic definition describes the wind farm as a collection of nodes (turbines) and time-varying weighted edges (inter-turbine wake propagation) that change as a function of incoming wind direction. The velocity at each turbine is determined through a discrete input-output model. Changes in wind direction serve as the input and the output is defined in terms of a time-varying weighted adjacency matrix that depends on the time-delay of information propagation between turbines. These delays, which are defined in terms of the advection speed of the wind and the distance between the turbines, capture the delayed effect of wind direction changes on the inter-connectivity of the graph as the wind conditions at the farm inlet propagate through the turbine array. An event-based update framework is employed to capture time-dependent topology changes due to shifts in wind direction. Simulation results for dynamically changing wind inlet directions to a circular wind farm are compared to predictions from both the static and dynamic versions of the FLOw Redirection and Induction in Steady State (FLORIS) model. The approach is shown to enable real-time tracking of dynamic changes to wind farm power output within a framework that can be easily integrated into real-time, horizon-based, control strategies that typically do not account for wind direction changes.

distributed↗
NASA NTRS1984

Model estimation and identification of manual controller objectives in complex tracking tasks

A methodology is presented for estimating the parameters in an optimal control structural model of the manual controller from experimental data on complex, multiinput/multioutput tracking tasks. Special attention is devoted to estimating the appropriate objective function for the task, as this is considered key in understanding the objectives and strategy of the manual controller. The technique is applied to data from single input/single output as well as multi input/multi outpuut experiments, and results discussed.

Schmidt, D. K.↗
NASA NTRS1992

An experimental evaluation and comparison of explicit force control strategies for robotic manipulator

The authors present an experimental evaluation and comparison of basic strategies that have been proposed for force control of robot manipulators. This experimental review of force control methodologies is unique in its breadth. The commonality amongst the experiments has permitted the ability to objectively compare and contrast these strategies, and draw conclusions about the efficacy of each. The results support previous analysis and show the superiority of integral force control for force trajectory tracking.

Volpe, Richard↗
NASA NTRS2002

Recent Results from CHAMP Tracking and Accelerometer Data Analysis

The CHAMP mission's unique combination of sensors and orbit configuration will enable unprecedented improvements in modeling and understanding the Earth's static gravity field and its temporal variations. CHAMP is the first of two missions (GRACE to be launched in the early part of 02') that combine a new generation of Global Positioning System (GPS) receivers, a high precision three-axis accelerometer, and star cameras for the precision attitude determination. In order to isolate the gravity signal for science investigations, it is necessary to perform a detailed reduction and analysis of the GPS and Satellite Laser Ranging (SLR) tracking data in conjunction with the accelerometer and attitude data. Precision orbit determination based on the GPS and SLR tracking data will isolate the orbit perturbations, while the accelerometer data will be used to distinguish the non-gravitational forces from those due to the geopotential (static, and time varying). In preparation for the CHAMP and GRACE missions, extensive modifications have been made to NASA/GSFC's GEODYN orbit determination software to enable the simultaneous reduction of spacecraft tracking (e.g. GPS and SLR), three-axis accelerometer and precise attitude data. Several weeks of CHAMP tracking and accelerometer data have been analyzed and the results will be presented. Precision orbit determination analysis based on tracking data alone in addition to results based on the simultaneous reduction of tracking and accelerometer data will be discussed. Results from a calibration of the accelerometer will be presented along with the results from various orbit determination strategies.

Luthcke, S. B.↗
NASA NTRS2002

CHAMP Tracking and Accelerometer Data Analysis Results

The CHAMP (Challenging Minisatellite Payload) mission's unique combination of sensors and orbit configuration will enable unprecedented improvements in modeling and understanding the Earth's static gravity field and its temporal variations. CHAMP is the first of two missions (GRACE (Gravity Recovery and Climate Experiment) to be launched in the later part of '01) that combine a new generation of GPS (Global Positioning System) receivers, a high precision three axis accelerometer, and star cameras for the precision attitude determination. In order to isolate the gravity signal for science investigations, it is necessary to perform a detailed reduction and analysis of the GPS and SLR tracking data in conjunction with the accelerometer and attitude data. Precision orbit determination based on the GPS and SLR (Satellite Laser Ranging) tracking data will isolate the orbit perturbations, while the accelerometer data will be used to distinguish the surface forces from those due to the geopotential (static, and time varying). In preparation for the CHAMP and GRACE missions, extensive modifications have been made to NASA/GSFC's GEODYN orbit determination software to enable the simultaneous reduction of spacecraft tracking (e.g. GPS and SLR), three axis accelerometer and precise attitude data. Several weeks of CHAMP tracking and accelerometer data have been analyzed and the results will be presented. Precision orbit determination analysis based on tracking data alone in addition to results based on the simultaneous reduction of tracking and accelerometer data will be discussed. Results from a calibration of the accelerometer will be presented along with the results from various orbit determination strategies. Gravity field modeling status and plans will be discussed.

Lemoine, Frank G.↗
NASA NTRS2011

Mars Sample Return - Launch and Detection Strategies for Orbital Rendezvous

This study sets forth conceptual mission design strategies for the ascent and rendezvous phase of the proposed NASA/ESA joint Mars Sample Return Campaign. The current notional mission architecture calls for the launch of an acquisition/cache rover in 2018, an orbiter with an Earth return vehicle in 2022, and a fetch rover and ascent vehicle in 2024. Strategies are presented to launch the sample into a coplanar orbit with the Orbiter which facilitate robust optical detection, orbit determination, and rendezvous. Repeating ground track orbits exist at 457 and 572 km which provide multiple launch opportunities with similar geometries for detection and rendezvous.

Orbiter's trans-Earth injection (TEI):↗
NASA NTRS2022

Near-Earth Object Surveyor Overview

The Near-Earth Object (NEO) Surveyor is designed to detect, categorize and characterize Near-Earth Objects (NEOs) using infrared imaging. The project was approved to enter the preliminary design phase (Phase B) in FY21 after an extended Concept Development Phase (Phase A). The NEO Surveyor project responds to US Public Law 109-155[1], National Research Council’s report “Defending Planet Earth: Near-Earth Object Surveys & Hazard Mitigation Strategies (2010)”[2], the U. S. National Near-Earth Object Preparedness Strategy and Action Plan (June 2018)[3], and the objectives of NASA’s Planetary Defense Coordination Office (PDCO). The goals of the NEO Surveyor project are to: (1) identify impact hazards to the Earth posed by NEOs (defined as asteroids and comets that come within 1.3 AU of the Sun) by performing a comprehensive survey of the NEO population; (2) obtain detailed physical characterization data for individual objects that are likely to pose an impact hazard; (3) characterize the entire population of potentially hazardous NEOs to inform potential mitigation strategies. The mission will make significant progress toward the George E. Brown, Jr. NEO Survey Program objective defined by the U. S. Congress of detecting, tracking, cataloging, and characterizing at least 90% of NEOs equal to or larger than 140 m in diameter. The project is a collaboration between NASA-JPL, the University of Arizona (UA) and industry, with Ball Aerospace notably providing the spacecraft and key instrument elements. This paper will describe the overall NEO Surveyor Project objectives, initial spacecraft and instrument design and development plans and mission concept.

Veto, Michael↗
DOE OSTI2020

Maximizing Yield with Improved Single-Axis Backtracking on Cross-Axis Slopes: Preprint

Many tracking PV systems avoid row-to-row shading by backtracking in morning and afternoon. Because the common single-axis backtracking implementation assumes the array is in a horizontal plane, it does not fully prevent row-to-row shading in arrays installed on cross-axis slopes. This paper simulates the effect of reduced self-shading on annual production with two modified backtracking strategies. Depending on the array geometry and the steepness of the cross-axis grade, using a modified backtracking strategy improved annual yield by 3-10%.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Optics Studies for Multipass Energy Recovery at CEBAF: ER@CEBAF

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson Lab focuses on demonstrating highest energy recovery in super conducting linac in the low-current range. Continuous electron beam accelerate up to 7.5 GeV within 5-passes and decelerate in the next 5-passes recovering RF energy and dumps at a low energy dump. The beamline optics design for recirculating linacs require special attention to avoid beam instabilities due to RF wakefields. Usually, multi-pass linac beam lines require stronger focusing at lower energies as that is necessary to avoid beam breakup (BBU) instabilities, even with this small beam current. The CEBAF linac optics optimization is focused on balancing over-focusing at higher energies and beta excursions at lower energies. The race-track-shaped geometry of CEBAF accelerator allows its linacs to accommodate multiple energy beams simultaneously, while individual recirculating arcs transporting one beam energy, are shared between accelerating/decelerating beams. For the linac optics optimization process, an extended strategy is used that is originally used in 6-pass Recirculating Linac design of the LHeC, to represent the ten passes through a single linac. Using proper mathematical expressions, linac optics optimization can be achieved with evolutionary genetic algorithms, with Multi-Objective optimization. This thesis introduces a CEBAF optics redesign tailored to accommodates the ER@CEBAF multi-pass ER scheme. The isochronous arcs were retuned to match into optics solutions for optimized 10-pass linacs. Within this work, a single bunch particle tracking analysis presented here focuses on the further improvements of the beamline and beam transportation.

Neththikumara, Isurumali↗
NASA NTRS2012

On-orbit Performance of MODIS Solar Diffuser Stability Monitor

MODIS has 20 reflective solar bands (RSBs) in the visible (VIS), near-infrared (NIR) , and shortwave infrared (SWIR) spectral regions. MODIS RSBs are calibrated on-orbit by a solar diffuser (SD) with its on-orbit degradation tracked by a solar diffuser stability monitor (SDSM). The SDSM is an instrument by itself, consisting of a solar integration sphere (SIS) with 9 individual filtered detectors covering wavelengths from 0.41 to 0.94 micrometers. It functions as a ratioing radiometer with alternate observations made of the direct sunlight (Sun view) and that diffusely reflected from the SD panel (SD view) during each scheduled SD/SDSM calibration event. Since launch, Terra and Aqua MODIS and their SDSM have successfully operated for more than 12 and 10 years, respectively. The VIIRS, on-board the newly launched Suomi National Polar orbiting Partnership (NPP) spacecraft, has been designed and built with strong MODIS heritage and carries a similar and improved SD and SDSM calibration system. This paper provides an overview of SDSM design functions, its on-orbit calibration strategies and performance for both Terra and Aqua MODIS missions. Discussions of its on-orbit performance are focused on changes in SDSM detector responses over time and their impact on tracking SD on-orbit degradation. Also presented in this paper are lessons learned from MODIS SDSM and improvements made for the VIIRS SDSM, and preliminary comparisons of their on-orbit performance.

Xiong, Xiaoxiong↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗