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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Automated Model for Improved Mapping of Country-Scale High-Resolution Coastal Bathymetry

Accurate and up-to-date maps of coastal bathymetry are critical for a variety of sectors from vessel navigation to port construction and are increasingly vital to inform coastal infrastructure management amid accelerating sea-level rise and more frequent and severe storm-surge events. The primary challenges to accurate and efficient bathymetric mapping from optical remote sensing are: accurately modeling light attenuation in both the atmosphere and water column; and inefficient data processing pipelines for highresolution satellite imagery. To address the effects of light attenuation within the water-column we have developed a novel physics-based bathymetry model that accounts for variations in water-column inherent optical properties on a pixel-by-pixel basis in optically-shallow aquatic environments, which represents a major advancement. For applications to satellite imagery, we have developed a software package that automatically applies the robust 6S atmospheric correction algorithm, estimates the bottom depth from the physics-based bathymetry model, which corrects for attenuation by suspended particulate matter and colored dissolved organic matter in the water column on a pixel-by-pixel basis, and leverages highperformance computing for rapid application to region-scale (e.g., CONUS) 2-meter resolution imagery datasets. Our approach is tailored to sensors that collect data at two-meter resolution with high return times for frequent updates. We mapped 591 WorldView satellite images for Florida, North Carolina, and Alaska and validated the maps against LiDAR-derived bathymetry data. Results show median RMSE of 1.75, 1.59, and 2.67 meters, respectively. By combining the strengths of Oak Ridge National Laboratory in high-performance computing and remote-sensing science with the water-column modeling expertise of Scripps Institution of Oceanography we advance the state of bathymetric mapping capability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Effects of alpha stopping power modelling on the ignition threshold in a directly-driven inertial confinement fusion capsule

The alpha-particle energy deposition mechanism modifies the ignition conditions of the thermonuclear Deuterium-Tritium fusion reactions, and constitutes a key issue in achieving high gain in Inertial Confinement Fusion implosions. One-dimensional hydrodynamic calculations have been performed with the code Multi-IFE to simulate the implosion of a capsule directly irradiated by a laser beam. The diffusion approximation for the alpha energy deposition has been used to optimize three laser profiles corresponding to different implosion velocities. A Monte-Carlo package has been included in Multi-IFE to calculate the alpha energy transport, and in this case the energy deposition uses both the LP and the BPS stopping power models. Homothetic transformations that maintain a constant implosion velocity have been used to map out the transition region between marginally-igniting and high-gain configurations. Furthermore, the results provided by the two models have been compared and it is found that – close to the ignition threshold – in order to produce the same fusion energy, the calculations performed with the BPS model require about 10% more invested energy with respect to the LP model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

ALS/Milo: BL402 RSXD data analysis

Suite of tools designed to simply data collection, extraction, reduction, and plotting for resonant soft x-ray scattering experiments performed at ALS beamline 4.0.2; speeds up the process of converting data into meaningful information for users to publish experimental results. * Python software routines for processing CCD images, including reciprocal space maps, diffraction peak alignment, resonant spectral profiles, line-cut comparisons, coordinate transforms, etc. * Scan file generator, optimized for typical uses cases, reduces burden on users by handling complex operations behind the scenes of a simplified user interface * Deployed at beamline endstation computers; packaged and deployable as standardized PyPI package * Under version control (git) and hosted on LBL-sponsored repository (bitbucket)

Shafer, Padraic↗
DOE OSTI2018

Using Stage Level Microseismic Analysis to Gain Insight into Fracture Efficiency and Completion Effectiveness

Microseismic event density heat maps at sequential time intervals during the treatment of individual completion stages have been developed to better understand fracture behavior on a stage level. Animating these heat maps through time on a single stage provides fascinating visual insights into the dynamic sequencing of populations of events, event timing and their likely genesis, providing a new way of visualizing and interpreting microseismic data sets. This technique leverages heat-map benefits from URTEC 2674376, excluding microseismic event clusters that may obscure or skew statistical analysis of the event densities, thus allowing for more accurate assessment of geologic features, stimulated rock volume, near-field concentration of events due to varying cluster spacing, fracture efficiency and stress shadowing. Far-field microseismic events prior to ramp up of treatment pressure are clearly indicated from this technique that cannot be observed with standard heat maps with certain completion designs. Unambiguous changes in microseismic event character from these far-field pre-ramp up events to those near-field events occurring at the onset of pressure are also observed. Applying a stage by stage approach on packages of wells and different locations provides robust statistical conclusions pertaining to reservoir behavior during well completion.

Wang, Iris↗
NASA NTRS1989

Algorithmic considerations of integrated design for CSI on a hypercube architecture

An approach is presented to the integrated design problem for actively controlled large, flexible mechanical systems for which Control Structure Interaction (CSI) problems are of concern. The two coupled design problems were identified as the optimal Structural Design problem the optimal Controller Design problem. These two problems can be addressed within a decision making loop that would consider each separately, and then sequentially analyze the effects of one on the other. Embedded in such a loop would be the simulation and coordination tasks as part of the decision tools required in a total (software) package. All of the above are compute-intensive tasks. In any such task, possible decompositions and gains due to the inherent parallelism have to be exploited. The problems under consideration, as applied to large flexible mechanical structures, are particularly suited to be mapped onto multicomputer systems in a hypercube topology.

Oezguener, UE.↗
NASA NTRS2002

P32Tools: reduction of ISOPHOT P32 oversampled maps

During the IS0 mission, the ISOPHOT instrument has collected more than 1100 observations in oversampled mapping mode (AOT PHT32) in the wavelength range of45 to 240 microns. The observations comprise mapping of small and large extended regions, but also faint point sources. PHT32 observations are affected by strong signal transients due to flux changes generated by the relatively fast chopper movement. A program described by Tuffs & Gabriel (2002), was developed to correct for these effects. It was integrated in the ISOPHOT Interactive Analysis (PIA) via a graphical user interface (GUI), so that most aspects of the processing can be addressed in a coherent and user friendly environment. The resulting package 'P32Tools' was introduced to the user community at three hands-on workshops on PHT32 processing held in spring 2001. The hands-on experience from these workshops lead to further improvements. Here we present an overview of the functionalities of the final release of this new software.

ISOPHOT oversampled mapping ISOPHOT Interactive An↗
DOE OSTI2018

Fast inference of deep neural networks in FPGAs for particle physics

Here, recent results at the Large Hadron Collider (LHC) have pointed to enhanced physics capabilities through the improvement of the real-time event processing techniques. Machine learning methods are ubiquitous and have proven to be very powerful in LHC physics, and particle physics as a whole. However, exploration of the use of such techniques in low-latency, low-power FPGA (Field Programmable Gate Array) hardware has only just begun. FPGA-based trigger and data acquisition systems have extremely low, sub-microsecond latency requirements that are unique to particle physics. We present a case study for neural network inference in FPGAs focusing on a classifier for jet substructure which would enable, among many other physics scenarios, searches for new dark sector particles and novel measurements of the Higgs boson. While we focus on a specific example, the lessons are far-reaching. A companion compiler package for this work is developed based on High-Level Synthesis (HLS) called hls4ml to build machine learning models in FPGAs. The use of HLS increases accessibility across a broad user community and allows for a drastic decrease in firmware development time. We map out FPGA resource usage and latency versus neural network hyperparameters to identify the problems in particle physics that would benefit from performing neural network inference with FPGAs. For our example jet substructure model, we fit well within the available resources of modern FPGAs with a latency on the scale of 100 ns.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Novus: An Unmanned Aerial System and Virtual Reality Flight Deck for Data Collection and Visualization

Many emerging technologies offer tremendous new capabilities that will, without question, redefine how we interact with, utilize, understand, and optimize the energy systems around us. Drones offer a new ability to remotely capture data in ways that have previously been impractical. However, their flight control systems remain rudimentary and limit the ability of researchers to fully take advantage of these platforms as remote sensing devices. In this project, we constructed a hexarotor drone and outfitted it with advanced (yet inexpensive) sensors as well as a telemetry data management and control package. We then created a virtual reality flight deck that allows a drone operator to define waypoints "on-the-fly" or take manual control over flight operations. The flight deck provides a live on-board video stream display, a 3-dimensional topographic map with the drone’s position in space overlaid onto it, as well as a data visualization framework that keeps critical information immediately available to the operator. These advances provide a new platform for scientific data collection such as thermography of building envelopes or solar arrays. As the drone is in flight and data are being collected, these data are relayed to the virtual reality environment where they can be inspected for integrity and the flight plan altered if necessary to collect higher quality data. Future work will focus on implementing 3-dimensional mapping using both visible and thermal imagery collected from the drone, and streaming those into the virtual reality flight deck in real time.

Source record↗
DOE OSTI2024

Improving Cost and Efficiency of the Scalable Solid Oxide Fuel Cells Power System

The objective of this project was to design and develop a 20kW range small-scale solid oxide fuel cells (SOFC) power system for applications such as data centers and commercial buildings. The original plan included a 5,000 hours demonstration and a Techno-Economic Analysis (TEA) which were dropped as part of project termination. The original project plan was to use a stack with a cross-flow cell design which had previously been tested for 500 hours at a community college in Malta, NY. However, it was decided to move to the advanced R-SOFC co-flow cell developed under Department of Energy Award DE-FE0031971. The advanced cell design has the advantage of a larger active area for the same manufacturing footprint which results in fewer required cells for the same stack power, hence a higher volumetric power density (kW/L) and lower cost per kW than the original cross-flow cell design. A full SOFC system Simulink model was developed and calibrated with testing data from a fuel cell stack and BOP (balance of plant) components. The simulation results from the calibrated model showed an acceptable match with the experimental data. A structural analysis conducted for various load scenarios indicated no high stress areas for all spatial directions. Major electrical system components were acquired, built and successfully tested. System sensors were verified and validated against controls. Safety checks, a diagnostic check, PID tuning, and control software commissioning tasks were also conducted. The power electronics prototype was delivered and trial testing completed. Balance of Plant component testing and simulation work was conducted to characterize Reformer-Heat Exchanger heat transfer and backpressure and reformer catalyst methane conversion and product selectivity. Simulations were conducted to design the Anode and Cathode fluid passages and size the air-air and fuel-fuel heat exchangers. A Burner operation map was created from test data and the Anode Gas Recirculation blower was tested to evaluate its durability. The SOFC system used a horizontal style design where components sit directly on a casting with a direct connection to the skid. This design has efficient packaging and a small footprint with approximate dimensions of 750 mm x 700 mm x 1700 mm. An SOFC system was built and successfully tested at the Malta, NY facility The system for over 500 hours under load of which over 300 hours was at full load of 20 kW.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1989

A study of the spatial scales of discrete polar auroral arcs

Recent theoretical works have dealt with the identification and evaluation of the physical processes that determine the characteristic scale sizes of discrete auroral arcs. It is broadly acknowledged that a characteristic spatial width of approximately 100 km (at ionospheric heights) results naturally from the ionospheric mapping of the high-altitude magnetospheric convection electric field. However, recent analysis of the spatial power spectral distributions of electric and magnetic field variations has revealed structure at much smaller spatial scales. In this analysis, precipitating auroral electron data from the J-package sensor on the Defense Meteorological Satellite Program satellite is used to study the spatial scale sizes and size distributions of polar auroral arcs. A monotonically decreasing inverse-wavelength spectrum with a slope near unity is common, with no strictly preferred scale sizes, although the scale spectrum does flatten at scales larger than approximately 100 to 200 km. Typical observed widths of the auroral arcs tend to be much smaller than the resistive scale length, and the observed widths do not have a strong dependence on local ionospheric parameters.

Gorney, David J.↗
DOE OSTI2025

Integrating Ultra-Coarse-Grained Protein Models into Accessible Workflows for Multiscale Molecular Dynamics

To capture protein conformational transitions using molecular dynamics (MD), several simulation resolutions covering different spatial and temporal scales are typically needed. All-atom (AA) simulations provide fine resolution, but are computationally infeasible for large systems over longer durations. Coarse-grained (CG) and ultra-coarse-grained (UCG) models have a lower resolution and computational cost while still being able to conserve essential protein features. Prior work on a Multiscale Machinelearned Modeling Infrastructure (MuMMI) combined both AA and CG simulations to study RAS-RAF protein interactions, leveraging CG models for longer time scales and using AA to investigate unusual conformations in greater detail. However, MuMMI is still resource-intensive, and this study aims to maximize exploration of the protein conformational space while reducing computational cost. In this paper, we build on prior work that integrates UCG models based on heterogeneous elastic network modeling (hENM) into the MuMMI workflow. We demonstrate that UCG models enable accurate sampling of protein conformations, focusing on simulating RAS-RAF protein interactions. Using higher-resolution CG Martini simulation data, we can automatically refine intramolecular interactions in UCG models. We present a scalable Python package that uses fluctuations observed in higher-resolution CG Martini simulations to estimate bond coefficients of the UCG model. We built novel machine learning-based backmapping methods to recover more detailed CG Martini structures from UCG structures, using diffusion models to learn the mapping between scales. Finally, we present UCG-mini-MuMMI, an accessible and less compute-intensive version of MuMMI as a resource for the scientific community. Incorporating UCG models into MD studies is applicable to a broad range of systems and proteins, and our study offers insights into the advantages and limitations of these methods.

Chemical structure↗
DOE OSTI2023

Field studies of PERC and Al-BSF PV module performance loss using power and I-V timeseries

We have studied the degradation of both full-sized modules and minimodules with PERC and Al-BSF cell variations in fields while considering packaging strategies. We demonstrate the implementations of data-driven tools to analyze large numbers of modules and volumes of timeseries data to obtain the performance loss and degradation pathways. This data analysis pipeline enables quantitative comparison and ranking of module variations, as well as mapping and deeper understanding of degradation mechanisms. The best performing module is a half-cell PERC, which shows a performance loss rate ( PLR ) of −0.27 ± 0.12% per annum (%/ a ) after initial losses have stabilized. Minimodule studies showed inconsistent performance rankings due to significant power loss contributions via series resistance, however, recombination losses remained stable. Overall, PERC cell variations outperform or are not distinguishable from Al-BSF cell variations.

Curran, Alan J.↗
NASA NTRS1984

Effects of the motions of a platform-mounted payload on the nutational stability of a dual-spin spacecraft - A Galileo case study

In the presence of spacecraft nutation, tracking of an inertially fixed target by the Galileo scan platform requires the use of two control loops to move the scan platform and the stator in such a way as to compensate for spacecraft motion. The effect of these control loops on spacecraft nutational stability is examined using an eigenvalue analysis approach as well as several computer analysis packages. It was found that the actions of these control loops tend to drive nutation to the point of neutralizing, and even overpowering the damping actions of the spacecraft nutation damper, for pointing directions close to the spacecraft's poles. Stable and unstable zones are mapped out for two sets of spacecraft mass properties, and contributions of rotor asymmetry and stator flexibility are also discussed.

Man, G. K.↗
NASA NTRS2022

Physical and Chemical Conditions in the N113 Star-Forming Region in the Low-Metallicity Large Magellanic Cloud

The Large Magellanic Cloud (LMC) is the nearest (~50 kpc) star-forming galaxy characterized by a low metallicity (Z~0.3-0.5 Z⨀) similar to galaxies during the early phases of their assembly. As a result, star formation studies in the LMC provide a stepping stone to understanding star formation at earlier epochs of the universe where these processes cannot be directly observed. N113 is one of the most prominent star-forming regions in the LMC hosting one of the most massive giant molecular clouds.N113 is small enough to be imaged in its entirety, but large enough to showcase many important phenomena such as multiple generations of stars, stellar feedback, and different environments. We present our findings from an investigation of the early stages of star formation in the N113 region using the Atacama Large Millimeter/submillimeter Array (ALMA)molecular line data probing a wide density range: 12CO, 13CO, and C18O (2-1), 13COand C18O (1-0), HCN (1-0), HCO+ (1-0), H13CN (1-0) and (3-2), H13CO+ (1-0) and (3-2), CS (2-1) and (5-4), as well as 1.3 mm and 3 mm continuum. We used the Python package quick clump to identify molecular clumps. We utilized the multiline non-LTE fitting tool based on models from RADEX developed by Finn et al. (2021, ApJ, 917, 106)to construct the CO, HCN, HCO+, and CS temperature and column density, and the H2density maps of N113. We constructed a catalog of molecular clumps including their physical properties, chemical abundances, sizes, velocities, and velocity dispersions. To establish the evolutionary status of the clumps, their positions were compared with previously identified young stellar objects (YSOs) from the Spitzer/SAGE and Herschel/HERITAGE surveys, as well as water and OH masers. We compared the properties of the clumps in N113 to those in the Galaxy and other regions in the LMC to assess the impact of the environment (e.g., metallicity, stellar feedback) on the star formation process.

Jonathon Noswitz↗
NASA NTRS2023

The First Extragalactic Detection of Higher-Order Hydrogen Recombination Lines

The Large Magellanic Cloud (LMC) is the nearest (~50 kpc) star-forming galaxy characterized by a low metallicity (Z~0.3-0.5 Z⨀) similar to galaxies during the early phases of their assembly. As a result, star formation studies in the LMC provide a stepping stone to understanding star formation at earlier epochs of the universe where these processes cannot be directly observed. N113 is one of the most prominent star-forming regions in the LMC hosting one of the most massive giant molecular clouds. N113 is small enough to be imaged in its entirety, but large enough to showcase many important phenomena such as multiple generations of stars, stellar feedback, and different environments. We present our findings from an investigation of the early stages of star formation in the N113 region using the Atacama Large Millimeter/submillimeter Array (ALMA) molecular line data probing a wide density range: 12CO, 13CO, and C18O (2-1), 13CO and C18O (1-0), HCN (1-0), HCO+ (1-0), H13CN (1-0) and (3-2), H13CO+ (1-0) and (3-2), CS (2-1) and (5-4), as well as 1.3 mm and 3 mm continuum. We used the Python package quickclump to identify molecular clumps. We utilized the multiline non-LTE fitting tool based on models from RADEX developed by Finn et al. (2021, ApJ, 917, 106) to construct the CO, HCN, HCO+, and CS temperature and column density, and the H2 density maps of N113. We constructed a catalog of molecular clumps including their physical properties, chemical abundances, sizes, velocities, and velocity dispersions. To establish the evolutionary status of the clumps, their positions were compared with previously identified young stellar objects (YSOs) from the Spitzer/SAGE and Herschel/HERITAGE surveys, as well as water and OH masers. We compared the properties of the clumps in N113 to those in the Galaxy and other regions in the LMC to assess the impact of the environment (e.g., metallicity, stellar feedback) on the star formation process.

Marta M Sewilo↗
DOE OSTI2013

Benchmark for evaluation and validation of reactor simulations (BEAVRS)

Advances in parallel computing have made possible the development of high-fidelity tools for the design and analysis of nuclear reactor cores, and such tools require extensive verification and validation. This paper introduces BEAVRS, a new multi-cycle full-core Pressurized Water Reactor (PWR) depletion benchmark based on two operational cycles of a commercial nuclear power plant that provides a detailed description of fuel assemblies, burnable absorbers, in-core fission detectors, core loading patterns, and numerous in-vessel components. This benchmark enables analysts to develop extremely detailed reactor core models that can be used for testing and validation of coupled neutron transport, thermal-hydraulics, and fuel isotopic depletion. The benchmark also provides measured reactor data for Hot Zero Power (HZP) physics tests, boron letdown curves, and three-dimensional in-core flux maps from fifty-eight instrumented assemblies. Initial comparisons between calculations performed with MIT's OpenMC Monte Carlo neutron transport code and measured cycle 1 HZP test data are presented, and these results display an average deviation of approximately 100 pcm for the various critical configurations and control rod worth measurements. Computed HZP radial fission detector flux maps also agree reasonably well with the available measured data. All results indicate that this benchmark will be extremely useful in validation of coupled-physics codes and uncertainty quantification of in-core physics computational predictions. The detailed BEAVRS specification and its associated data package is hosted online at the MIT Computational Reactor Physics Group web site (http://crpg.mit.edu/), where future revisions and refinements to the benchmark specification will be made publicly available. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Drone flight visible images, digital elevation maps, and geotiffs, Council, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along each flight path. This package includes data from four flight paths over the NGEE Arctic Council Road Site near mile marker 71 in the Seward Peninsula, Alaska in July 2017. Derived image products for each flight include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Drone flight visible images, digital elevation maps, and geotiffs, Teller, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along the flight path. This package includes data from a flight path over the NGEE Arctic Teller Site, west of mile marker 27 Bob Blodgett Highway in the Seward Peninsula, Alaska in July 2017. Derived image products include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗