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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Efficient smoothed particle radiation hydrodynamics I: Thermal radiative transfer

This work presents efficient solution techniques for radiative transfer in the smoothed particle hydrodynamics discretization. Two choices that impact efficiency are how the material and radiation energy are coupled, which determines the number of iterations needed to converge the emission source, and how the radiation diffusion equation is solved, which must be done in each iteration. The coupled material and radiation energy equations are solved using an inexact Newton iteration scheme based on nonlinear elimination, which reduces the number of Newton iterations needed to converge within each time step. During each Newton iteration, the radiation diffusion equation is solved using Krylov iterative methods with a multigrid preconditioner, which abstracts and optimizes much of the communication when running in parallel. The code is verified for an infinite medium problem, a one-dimensional Marshak wave, and a two and three-dimensional manufactured problem, and exhibits first-order convergence in time and second-order convergence in space. For these problems, the number of iterations needed to converge the inexact Newton scheme and the diffusion equation is independent of the number of spatial points and the number of processors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

ADDS-EVS: An agent-based deployment decision-support system for electric vehicle services

Rapid and sustainable development of the electric vehicle (EV) industry places the requirement for the plan of EV deployment. For public EV, existing models mainly focus on the charging facility design and fail to capture the multi-modal scenarios. In this work, we develop an agent-based decision-support system for multi-modal electric transits to locate the optimal combinations of key parameters, including the fleet size, the transit schedule, the charging facility design, and the routing strategy. We demonstrate the utilities of our system by simulating public EV services deployed to serve travel needs related to a transportation hub in New York City. To support the decision of the fleet size, we summarize system-level performances including the total satisfied demand, passengers' waiting time, vehicle idling time. The spatial and temporal patterns are extracted to serve a deeper understanding of system dynamics and service quality. Finally, we investigate the interaction between the fleet size design and the routing strategy. The results suggest a necessity of integrating the operation strategies into the planning phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Digital Miniature Cathode Ray Magnetometer

In this study, we introduce the concept and construction of an innovative Digital Miniature Cathode Ray Magnetometer designed for the precise detection of magnetic fields. This device addresses several limitations inherent to magnetic probes such as D.C. offset, nonlinearity, temperature drift, sensor aging, and the need for frequent recalibration, while capable of operating in a wide range of magnetic fields. The core principle of this device involves the utilization of a charged particle beam as the sensitivity medium. The system leverages the interaction of an electron beam with a scintillator material, which then emits visible light that is captured by an imager. The emitted scintillation light is captured by a CMOS sensor. This sensor not only records the scintillation light but also accurately determines the position of the electron beam, providing invaluable spatial information crucial for magnetic field mapping. The key innovation lies in the combination of electron beam projection, CMOS imager scintillation-based detection, and digital image signal processing. By employing this synergy, the magnetometer achieves remarkable accuracy, sensitivity and dynamic range. The precise position registration enabled by the CMOS sensor further enhances the device’s utility in capturing complex magnetic field patterns, allowing for 2D field mapping. In this work, the optimization of the probe’s performance is tailored for applications related to the characterization of insertion devices in light sources, including undulators.

Turqueti, Marcos↗
NASA NTRS1985

Review of image processing fundamentals

Image processing through convolution, transform coding, spatial frequency alterations, sampling, and interpolation are considered. It is postulated that convolution in one domain (real or frequency) is equivalent to multiplication in the other (frequency or real), and that the relative amplitudes of the Fourier components must be retained to reproduce any waveshape. It is suggested that all digital systems may be considered equivalent, with a frequency content approximately at the Nyquist limit, and with a Gaussian frequency response. An optimized cubic version of the interpolation continuum image is derived as a set of cubic spines. Pixel replication has been employed to enlarge the visable area of digital samples, however, suitable elimination of the extraneous high frequencies involved in the visable edges, by defocusing, is necessary to allow the underlying object represented by the data values to be seen.

Billingsley, F. C.↗
NASA NTRS2011

Assessing the Impact of Advanced Satellite Observations in the NASA GEOS-5 Forecast System Using the Adjoint Method

The adjoint of a data assimilation system provides a flexible and efficient tool for estimating observation impacts on short-range weather forecasts. The impacts of any or all observations can be estimated simultaneously based on a single execution of the adjoint system. The results can be easily aggregated according to data type, location, channel, etc., making this technique especially attractive for examining the impacts of new hyper-spectral satellite instruments and for conducting regular, even near-real time, monitoring of the entire observing system. In this talk, we present results from the adjoint-based observation impact monitoring tool in NASA's GEOS-5 global atmospheric data assimilation and forecast system. The tool has been running in various off-line configurations for some time, and is scheduled to run as a regular part of the real-time forecast suite beginning in autumn 20 I O. We focus on the impacts of the newest components of the satellite observing system, including AIRS, IASI and GPS. For AIRS and IASI, it is shown that the vast majority of the channels assimilated have systematic positive impacts (of varying magnitudes), although some channels degrade the forecast. Of the latter, most are moisture-sensitive or near-surface channels. The impact of GPS observations in the southern hemisphere is found to be a considerable overall benefit to the system. In addition, the spatial variability of observation impacts reveals coherent patterns of positive and negative impacts that may point to deficiencies in the use of certain observations over, for example, specific surface types. When performed in conjunction with selected observing system experiments (OSEs), the adjoint results reveal both redundancies and dependencies between observing system impacts as observations are added or removed from the assimilation system. Understanding these dependencies appears to pose a major challenge for optimizing the use of the current observational network and defining requirements for future observing systems.

Gelaro, Ron↗
NASA NTRS2022

Optimized Umkehr Profile Algorithm for Ozone Trend Analyses

The long-term record of Umkehr measurements from four NOAA Dobson spectrophotometers was reprocessed after updates to the instrument calibration procedures. In addition, a new data quality-control tool was developed for the Dobson automation software (WinDobson). This paper presents a comparison of Dobson Umkehr ozone profiles from NOAA ozone network stations (Boulder, OHP, MLO, Lauder) against several satellite records, including Aura Microwave Limb Sounder (MLS; ver. 4.2), and combined SBUV and OMPS records (NASA AGG and NOAA COH). A subset of satellite data is selected to match Dobson Umkehr observations at each station spatially (distance less than 200 km) and temporally (within 24 hours). Umkehr Averaging Kernels (AKs) are applied to vertically smooth all overpass satellite profiles prior to comparisons. The station Umkehr record consists of several instrumental records, which have different optical characterizations, and thus instrument-specific stray light contributes to the data processing errors and creates step changes in the record. This work evaluates the overall quality of Umkehr long-term measurements at NOAA ground-based stations and assesses the impact of the instrumental changes on the stability of the Umkehr ozone profile record. This paper describes a method designed to correct biases and discontinuities in the retrieved Umkehr profile that originate from the Dobson calibration process, repair, or optical realignment of the instrument. The M2GMI and GMI CTM ozone profile model output matched to station location and date of observation is used to evaluate instrumental step changes in the Umkehr record. Homogenization of the Umkehr record and discussion of the apparent stray light error in retrieved ozone profiles are the focus of this paper. Homogenization of ground-based records is of great importance for studies of long-term ozone trends and climate change.

Umkehr↗
DOE OSTI2020

Indicator Patterns of Forced Change Learned by an Artificial Neural Network

Abstract Many problems in climate science require the identification of signals obscured by both the “noise” of internal climate variability and differences across models. Following previous work, we train an artificial neural network (ANN) to predict the year of a given map of annual‐mean temperature (or precipitation) from forced climate model simulations. This prediction task requires the ANN to learn forced patterns of change amidst a background of climate noise and model differences. We then apply a neural network visualization technique (layerwise relevance propagation) to visualize the spatial patterns that lead the ANN to successfully predict the year. These spatial patterns thus serve as “reliable indicators” of the forced change. The architecture of the ANN is chosen such that these indicators vary in time, thus capturing the evolving nature of regional signals of change. Results are compared to those of more standard approaches like signal‐to‐noise ratios and multilinear regression in order to gain intuition about the reliable indicators identified by the ANN. We then apply an additional visualization tool (backward optimization) to highlight where disagreements in simulated and observed patterns of change are most important for the prediction of the year. This work demonstrates that ANNs and their visualization tools make a powerful pair for extracting climate patterns of forced change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Medium and Heavy-Duty Electric Vehicle Infrastructure - Load Operations and Deployment (HEVI-LOAD) v1.0

In order to support the California state goals to reduce the carbon and pollution emissions (AB2127), The goal of this project (HEVI-Pro) is to project the charging infrastructure needs by future medium- and heavy- duty electric vehicles, and assess optimal deployment the infrastructure in California and provide grid impacts analysis. The MHDV projections will also consider transportation system and electric system interaction with light duty vehicles. The project consists of 2 approaches in general: top-down approach that takes aggregated MHDV adoptions as the inputs and provide the county-level projections of charging load profile and infrastructure need, and the bottom-up approach that that incorporates more granular (temporal, spatial and duty-cycle-specific) behaviors of a variety of MHDVs into activity simulations/optimizations for further analysis.

Wang, Bin↗
DOE OSTI2025

A parcel-level evaluation of distributed wind opportunity in the contiguous United States

This study examines the potential for distributed wind (DW) energy across the contiguous United States, leveraging advancements in the National Renewable Energy Laboratory's distributed wind model, dWind. The novel modeling approach described here utilizes a high-resolution dataset and analyzes over 150 million parcels, a significant improvement from prior methods that extrapolated results from a smaller random sample. This achievement is enabled through key model performance improvements, such as transitioning to multiprocessing, which reduces runtime by 97 %. This optimized, high-resolution approach allows the inspection of technology deployment potential and impact on a variety of scales tailored to individual properties and regions. The results here align with prior work showing substantial opportunity for energy generation using DW technologies. Key findings reveal a substantial increase from prior results in estimated technical and economic potential for DW. Metrics tuned to highlight economic potential also show increased incentives supporting rural adoption. Results are spatially aggregated for usability and published via the U.S. Department of Energy Wind Data Portal and a custom scenario visualization platform, aiding policymakers, industry, and property owners in assessing DW viability across various scenarios and spatial scales.

17 WIND ENERGY↗
NASA NTRS1993

Parallel spatial direct numerical simulations on the Intel iPSC/860 hypercube

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube is documented. The direct numerical simulation approach is used to compute spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows. The feasibility of using the PSDNS on the hypercube to perform transition studies is examined. The results indicate that the direct numerical simulation approach can effectively be parallelized on a distributed-memory parallel machine. By increasing the number of processors nearly ideal linear speedups are achieved with nonoptimized routines; slower than linear speedups are achieved with optimized (machine dependent library) routines. This slower than linear speedup results because the Fast Fourier Transform (FFT) routine dominates the computational cost and because the routine indicates less than ideal speedups. However with the machine-dependent routines the total computational cost decreases by a factor of 4 to 5 compared with standard FORTRAN routines. The computational cost increases linearly with spanwise wall-normal and streamwise grid refinements. The hypercube with 32 processors was estimated to require approximately twice the amount of Cray supercomputer single processor time to complete a comparable simulation; however it is estimated that a subgrid-scale model which reduces the required number of grid points and becomes a large-eddy simulation (PSLES) would reduce the computational cost and memory requirements by a factor of 10 over the PSDNS. This PSLES implementation would enable transition simulations on the hypercube at a reasonable computational cost.

Joslin, Ronald D.↗
NASA NTRS2000

Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics

This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.

Ellsworth, David↗
NASA NTRS2015

A Framework for Orbital Performance Evaluation in Distributed Space Missions for Earth Observation

Distributed Space Missions (DSMs) are gaining momentum in their application to earth science missions owing to their unique ability to increase observation sampling in spatial, spectral and temporal dimensions simultaneously. DSM architectures have a large number of design variables and since they are expected to increase mission flexibility, scalability, evolvability and robustness, their design is a complex problem with many variables and objectives affecting performance. There are very few open-access tools available to explore the tradespace of variables which allow performance assessment and are easy to plug into science goals, and therefore select the most optimal design. This paper presents a software tool developed on the MATLAB engine interfacing with STK, for DSM orbit design and selection. It is capable of generating thousands of homogeneous constellation or formation flight architectures based on pre-defined design variable ranges and sizing those architectures in terms of predefined performance metrics. The metrics can be input into observing system simulation experiments, as available from the science teams, allowing dynamic coupling of science and engineering designs. Design variables include but are not restricted to constellation type, formation flight type, FOV of instrument, altitude and inclination of chief orbits, differential orbital elements, leader satellites, latitudes or regions of interest, planes and satellite numbers. Intermediate performance metrics include angular coverage, number of accesses, revisit coverage, access deterioration over time at every point of the Earth's grid. The orbit design process can be streamlined and variables more bounded along the way, owing to the availability of low fidelity and low complexity models such as corrected HCW equations up to high precision STK models with J2 and drag. The tool can thus help any scientist or program manager select pre-Phase A, Pareto optimal DSM designs for a variety of science goals without having to delve into the details of the engineering design process.

Earth Science↗
NASA NTRS2019

Operational Stability Limits in Rotating Detonation Engine Numerical Simulations

An instability is described which arises in computational fluid dynamic (CFD) simulations of semi-idealized rotating detonation engines (RDE) configured with a throat at the exit. Its existence is verified by examining output from two independently developed CFD codes simulating the same configuration and producing solutions that agree well. The instability is shown to be thermo-acoustic in that a spatial integral of the product of pressure and heat release fluctuations develops a regular oscillation which grows in time. The instability can become severe enough to cause detonation failure. Its onset is shown to be closely linked to the size of the exit throat and the size of the inlet restriction; both parameters that strongly influence RDE performance. It is shown that the instability places a cap on ideal RDEperformance, but that an optimized exhaust throat and inlet restriction combination still yields substantial pressure gain. Other parametric sensitivities are also examined in terms ofinstability growth. These include axial length, inlet manifold pressure, and air-fuel ratio.

Paxson, Daniel E.↗
NASA NTRS2020

ExoSpec Project: An Exoplanet Spectroscopy Technology Research Collaboration Based at NASA’s Goddard Space Flight Center and Ames Research Center

The exoplanet atmosphere characterization goals of future UV/Optical/Infrared flagship space missions will drive challenging design requirements for instrument wavefront controls, spatial and spectral sampling, spectral bandwidth, and detector performance. The new ExoSpec Project links four previously distinct research efforts at Goddard and Ames for enabling and enhancing the characterization of directly-imaged exoplanets. ExoSpec is comprised of three laboratory subsystem demonstrations: high-contrast integral field spectrographs, p-channel CCDs, and parabolic deformable mirrors. A fourth component, exoplanet spectral retrieval, is an iterative data simulation activity driven by the goal of optimizing the system-level instrument design for atmosphere retrieval metrics. The ExoSpec Project’s emphasis on system-level spectroscopy performance complements the objectives of other technology demonstrations supported by NASA.

Neil T Zimmerman↗
NASA NTRS1988

Base reaction optimization of redundant manipulators for space applications

One of the problems associated with redundant manipulators which were proposed for space applications is that the reactions transmitted to the base of the manipulator as a result of the motion of the manipulator will cause undesirable effects on the dynamic behavior of the supporting space structure. It is therefore necessary to minimize the magnitudes of the forces and moments transmitted to the base. It is shown that kinematic redundancy can be used to solve the dynamic problem of minimizing the magnitude of the base reactions. The methodology described is applied to a four degree-of-freedom spatial manipulator with one redundant degree-of-freedom.

Chung, C. L.↗
DOE OSTI2022

Preparation of metrological states in dipolar-interacting spin systems

Abstract Spin systems are an attractive candidate for quantum-enhanced metrology. Here we develop a variational method to generate metrological states in small dipolar-interacting spin ensembles with limited qubit control. For both regular and disordered spatial spin configurations the generated states enable sensing beyond the standard quantum limit (SQL) and, for small spin numbers, approach the Heisenberg limit (HL). Depending on the circuit depth and the level of readout noise, the resulting states resemble Greenberger-Horne-Zeilinger (GHZ) states or Spin Squeezed States (SSS). Sensing beyond the SQL holds in the presence of finite spin polarization and a non-Markovian noise environment. The developed black-box optimization techniques for small spin numbers ( N ≤ 10) are directly applicable to diamond-based nanoscale field sensing, where the sensor size limits N and conventional squeezing approaches fail.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

High-throughput printing of combinatorial materials from aerosols

The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces 1 . Whereas traditional combinatorial deposition methods can generate material libraries 2,3 , these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid–liquid or solid–solid phases 4–6 . We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Absolute contrast estimation for soft X-ray photon fluctuation spectroscopy using a variational droplet model

Abstract X-ray photon fluctuation spectroscopy using a two-pulse mode at the Linac Coherent Light Source has great potential for the study of quantum fluctuations in materials as it allows for exploration of low-energy physics. However, the complexity of the data analysis and interpretation still prevent recovering real-time results during an experiment, and can even complicate post-analysis processes. This is particularly true for high-spatial resolution applications using CCDs with small pixels, which can decrease the photon mapping accuracy resulting from the large electron cloud generation at the detector. Droplet algorithms endeavor to restore accurate photon maps, but the results can be altered by their hyper-parameters. We present numerical modeling tools through extensive simulations that mimic previous x-ray photon fluctuation spectroscopy experiments. By modification of a fast droplet algorithm, our results demonstrate how to optimize the precise parameters that lift the intrinsic counting degeneracy impeding accuracy in extracting the speckle contrast. These results allow for an absolute determination of the summed contrast from multi-pulse x-ray speckle diffraction, the modus operandi by which the correlation time for spontaneous fluctuations can be measured.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗