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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Clean Cities Coalitions: 2016 Activity Report

The U.S. Department of Energy's (DOE's) national network of Clean Cities Coalitions advance the nation's economic, environmental, and energy security by supporting local actions to promote the use of domestic fuels within transportation. The nearly 100 Clean Cities coalitions, whose territory covers 80% of the U.S. population, bring together stakeholders in the public and private sectors to use alternative and renewable fuels, idle-reduction (IR) measures, fuel economy improvements, and new transportation technologies as they emerge. To ensure success, coalitions leverage a robust set of expert resources and tools provided by national laboratories and DOE. Each year, Clean Cities coordinators submit annual reports of their activities and accomplishments for the previous calendar year. Data and information are submitted via an online tool that is maintained as part of the Alternative Fuels Data Center (AFDC) at the National Renewable Energy Laboratory (NREL). Coordinators submit a range of data that characterize the membership, funding, projects, and activities of their coalitions. They also submit data about sales of alternative fuels; use of alternative fuel vehicles (AFVs), plug-in electric vehicles (PEVs), and hybrid electric vehicles (HEVs); IR initiatives; fuel economy improvement activities; and programs to reduce vehicle miles traveled (VMT). NREL analyzes the submitted data to determine how broadly energy use in the U.S. has shifted due to coalition activities, which are summarized in this report.

2016 metrics↗
DOE OSTI2023

A National Infrastructure for Artificial Intelligence on the Grid (NI4AI) (Final Scientific/Technical Report)

Electric utilities have traditionally taken a very pragmatic yet myopic approach with grid sensors and the resulting collected data. Sensors are purchased and deployed to solve a specific, known problem that has risen to sufficient awareness as to justify the effort of deploying sensors and the needed capital investment. This sensor data flows into proprietary software packages with limited functionality intended only to address the initial problem. This approach aligns with the financial incentives of the utility to deploy capital into fixed hardware assets for which the corporations earn a rate of return. This mentality stands in stark contrast to the big data revolution that started nearly 25 years ago with the rise of Google. In this worldview, data is a fundamental business asset; successful organizations collect, store, explore, merge, and exploit as much data as possible to not only solve problems well understood today but also to tackle new problems that will inevitably rise tomorrow. The ARPA-E Open Innovation 2018 project entitled A National Infrastructure for Artificial Intelligence on the Grid or NI4AI for short was designed to demonstrate this alternative paradigm for using data. To do this, the project was composed of three key thrust areas. The first major component deployed a variety of high-frequency grid sensors and captured terabytes of both wide-scale and localized grid measurements, generating high-value datasets for grid research and algorithm development. The second aspect made available PingThings’ PredictiveGridTM, a horizontally scalable, cloud-based data management and AI platform built for time series data to explore and exploit the collected data. Finally, the project fostered a diverse and open research community composed of experts from numerous fields through focused educational content, code sharing, and data science competitions. Shifting away from “single use” sensors and closed data silos within electric utilities is a major benefit to the public at large. This legacy approach to data is incredibly (1) capital intensive (new sensors must be deployed for each new problem and problems tend to arise continuously) and (2) painfully slow (new problems must be identified first and then new sensors must be deployed to collect data to begin to address the issue). The transition to a carbon neutral grid requires a massive transformation of the existing grid infrastructure and will continue to challenge the legacy grid in unforeseen ways. The only way to make the energy transition cost effective is for utilities to abandon this dated data paradigm and adopt more contemporary approaches. NI4AI has shown that it is technically possible and economically feasible to ingest, explore, and exploit grid data collected from even very high frequency sensing, such as continuous point on wave sensors collecting measurements 10,000 times a second. In fact, the PredictiveGrid platform used is commercially available and deployed at several utilities in the United States. Project accomplishments were numerous and included (1) making available a state of the art time series platform to the community, (2) collecting over 520 streams of time series data from grid sensors totaling over 1 trillion grid measurements, and (3) developing and nurturing a community within the industry focused on the use of data to create value for utilities and, ultimately, end consumers.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Aeroacoustic Evaluation of Flap and Landing Gear Noise Reduction Concepts

Aeroacoustic measurements for a semi-span, 18% scale, high-fidelity Gulfstream aircraft model are presented. The model was used as a test bed to conduct detailed studies of flap and main landing gear noise sources and to determine the effectiveness of numerous noise mitigation concepts. Using a traversing microphone array in the flyover direction, an extensive set of acoustic data was obtained in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel with the facility in the acoustically treated open-wall (jet) mode. Most of the information was acquired with the model in a landing configuration with the flap deflected 39 deg and the main landing gear alternately installed and removed. Data were obtained at Mach numbers of 0.16, 0.20, and 0.24 over directivity angles between 56 deg and 116 deg, with 90 deg representing the overhead direction. Measured acoustic spectra showed that several of the tested flap noise reduction concepts decrease the sound pressure levels by 2 - 4 dB over the entire frequency range at all directivity angles. Slightly lower levels of noise reduction from the main landing gear were obtained through the simultaneous application of various gear devices. Measured aerodynamic forces indicated that the tested gear/flap noise abatement technologies have a negligible impact on the aerodynamic performance of the aircraft model.

Khorrami, Mehdi R.↗
NASA NTRS1983

The UARS and open data system concept and analysis study. Executive summary

Alternative concepts for a common design for the UARS and OPEN Central Data Handling Facility (CDHF) are offered. The designs are consistent with requirements shared by UARS and OPEN and the data storage and data processing demands of these missions. Because more detailed information is available for UARS, the design approach was to size the system and to select components for a UARS CDHF, but in a manner that does not optimize the CDHF at the expense of OPEN. Costs for alternative implementations of the UARS designs are presented showing that the system design does not restrict the implementation to a single manufacturer. Processing demands on the alternative UARS CDHF implementations are discussed. With this information at hand together with estimates for OPEN processing demands, it is shown that any shortfall in system capability for OPEN support can be remedied by either component upgrades or array processing attachments rather than a system redesign.

Mittal, M.↗
NASA NTRS1987

Data Bus Adapts to Changing Traffic Level

Access becomes timed when collisions threaten. Two-mode scheme used to grant terminals access to data bus. Causes bus to alternate between random accessibility and controlled accessibility to optimize performance and adapt to changing data-traffic conditions. Bus is part of 100-Mb/s optical-fiber packet data system.

Lew, Eugene↗
NASA NTRS1993

Program Aids In Printing FORTRAN-Coded Output

FORPRINT computer program prints FORTRAN-coded output files on most non-Postscript printers with such extra features as control of fonts for Epson and Hewlett Packard printers. Rewrites data to printer and inserts correct printer-control codes. Alternative uses include ability to separate data or ASCII file during printing by use of editing software to insert "1" in first column of data line that starts new page. Written in FORTRAN 77.

Akian, Richard A.↗
NASA NTRS2022

Ogle-2018-BLG-0799lb: A Q ∼ 2.7 × 10(−3) Planet With Spitzer Parallax

We report the discovery and analysis of a planet in the microlensing event OGLE-2018-BLG-0799. The planetary signal was observed by several ground-based telescopes, and the planet-host mass ratio is q = (2.65 ± 0.16) × 10(−3). The ground-based observations yield a constraint on the angular Einstein radius θE, and the microlensing parallax vector πE, is strongly constrained by the Spitzer data. However, the 2019 Spitzer baseline data reveal systematics in the Spitzer photometry, so there is ambiguity in the magnitude of the parallax. In our preferred interpretation, a full Bayesian analysis using a Galactic model indicates that the planetary system is composed of an Mplanet = 0.26+0.22 −0.11M(J) planet orbiting an Mhost = 0.093+0.082 −0.038 Mʘ , at a distance of DL = 3.71+3.24 −1.70 kpc. An alternate interpretation of the data shifts the localization of the minima along the arc-shaped microlens parallax constraints. This, in turn, yields a more massive host with median mass of 0.13 Mʘ at a distance of 6.3 kpc. This analysis demonstrates the robustness of the osculating circles formalism, but shows that further investigation is needed to assess how systematics affect the specific localization of the microlens parallax vector and, consequently, the inferred physical parameters.

gravitational lensing↗
NASA NTRS1986

Conceptual design for a food production, water and waste processing, and gas regeneration module

During the first six month period, the RECON (Regenerative Concepts Group) team collected reference material, made visits to consult with other researchers, and invited distinguished visitors to speak on the status of closed life support activities. A decision was made to develop the data base and modeling such that artificial intelligence (AI) methods could be used to manipulate data and examine concept alternatives. Six discrete tasks and a project schedule were outlined for the first year. The first two tasks have been essentially completed and have resulted in a sample set of assumptions for general use in defining candidate systems and for the specification of closed system characteristics. To model a closed environment, decisions were necessary to establish the amounts of food, air, water and waste products. Although recognized that data would eventually be normalized on the basis of a single human, the amount of data in existence for four person crews led to the decision to use this as a baseline. Information on existing concepts was collected from NASA sources, from industry, and libraries. Concept modeling was begun, hardware and software obtained, technical tasks identified and experimental work initiated.

Nicks, O. W.↗
DOE OSTI2025

Alternative mixed integer linear programming optimization for joint job scheduling and data allocation in grid computing

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer quadratically constrained program. To tackle the nonlinearity in the constraint, we alternatively fix a subset of decision variables and optimize the remaining ones via Mixed Integer Linear Programming (MILP). We solve the MILP problem at each iteration via an off-the-shelf MILP solver. Our experimental results show that our method significantly outperforms existing heuristic methods, employing either independent optimization or joint optimization strategies. We have also verified the generalization ability of our method over grid environments with various sizes and its high robustness to the algorithm setting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Clustering with general photo- z uncertainties: application to Baryon Acoustic Oscillations

ABSTRACT Photometric data can be analysed using the 3D correlation function ξp to extract cosmological information via e.g. measurement of the Baryon Acoustic Oscillations (BAO). Previous studies modeled ξp assuming a Gaussian photo-z approximation. In this work we improve the modeling by incorporating realistic photo-z distribution. We show that the position of the BAO scale in ξp is determined by the photo-z distribution and the Jacobian of the transformation. The latter diverges at the transverse scale of the separation s⊥, and it explains why ξp traces the underlying correlation function at s⊥, rather than s, when the photo-z uncertainty σz/(1+ z) ≳ 0.02. We also obtain the Gaussian covariance for ξp. Due to photo-z mixing, the covariance of ξp shows strong off-diagonal elements. The high correlation of the data causes some issues to the data fitting. None the less, we find that either it can be solved by suppressing the largest eigenvalues of the covariance or it is not directly related to the BAO. We test our BAO fitting pipeline using a set of mock catalogs. The data set is dedicated for Dark Energy Survey Year 3 (DES Y3) BAO analyses and includes realistic photo-z distributions. The theory template is in good agreement with mock measurement. Based on the DES Y3 mocks, ξp statistic is forecast to constrain the BAO shift parameter α to be 1.001 ± 0.023, which is well consistent with the corresponding constraint derived from the angular correlation function measurements. Thus, ξp offers a competitive alternative for the photometric data analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Space transfer vehicle accommodations at transportation nodes

This task identifies requirements for accommodation of space transfer vehicles (STVs) at orbital transportation nodes. Requirements are based on mission models which include high energy missions and human exploration initiatives. Study data includes results of trade studies evaluating STV accommodations concepts at Space Station nodes and at alternative free-flying nodes. Data and scars on the Phase One Space Station Freedom to allow growth to the accommodation concepts are identified.

Hueter, Uwe↗
NASA NTRS1988

Data volume reduction for imaging radar polarimetry

Two alternative methods are presented for digital reduction of synthetic aperture multipolarized radar data using scattering matrices, or using Stokes matrices, of four consecutive along-track pixels to produce averaged data for generating a synthetic polarization image.

Zebker, Howard A.↗
NASA NTRS1989

Data volume reduction for imaging radar polarimetry

Two alternative methods are disclosed for digital reduction of synthetic aperture multipolarized radar data using scattering matrices, or using Stokes matrices, of four consecutive along-track pixels to produce averaged data for generating a synthetic polarization image.

Zebker, Howard A.↗
NASA NTRS2021

A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks

Retrieval of aquatic biogeochemical variables, such as the near-surface concentration of chlorophyll-a (Chla) in inland and coastal waters via remote observations, has long been regarded as a challenging task. This manuscript applies Mixture Density Networks (MDN) that use the visible spectral bands available by the Operational Land Imager (OLI) aboard Landsat-8 to estimate Chla. We utilize a database of co-located in situ radiometric and Chla measurements (N = 4,354), referred to as Type A data, to train and test an MDN model (MDN(A)). This algorithm’s performance, having been proven for other satellite missions, is further evaluated against other widely used machine learning models (e.g., support vector machines), as well as other domain-specific solutions (OC3), and shown to offer significant advancements in the field. Our performance assessment using a held-out test data set suggests that a 49% (median) accuracy with near-zero bias can be achieved via the MDN(A) model, offering improvements of 20 to 100% in retrievals with respect to other models. The sensitivity of the MDN(A) model and benchmarking methods to uncertainties from atmospheric correction (AC) methods, is further quantified through a semi-global matchup dataset (N = 3,337), referred to as Type B data. To tackle the increased uncertainties, alternative MDN models (MDN(B)) are developed through various features of the Type B data (e.g., Rayleigh-corrected reflectance spectra ρ(s)). Using held-out data, along with spatial and temporal analyses, we demonstrate that these alternative models show promise in enhancing the retrieval accuracy adversely influenced by the AC process. Results lend support for the adoption of MDN(B) models for regional and potentially global processing of OLI imagery, until a more robust AC method is developed. Index Terms—Chlorophyll-a, coastal water, inland water, Landsat-8, machine learning, ocean color, aquatic remote sensing.

Brandon Smith↗
NASA NTRS2015

Introducing GFWED: The Global Fire Weather Database

The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5 latitude by 2-3 longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded data sets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia,Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DCD1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously identified in MERRAs precipitation, and they reinforce the need to consider alternative sources of precipitation data. GFWED can be used for analyzing historical relationships between fire weather and fire activity at continental and global scales, in identifying large-scale atmosphereocean controls on fire weather, and calibration of FWI-based fire prediction models.

bias↗
NASA NTRS1996

An Efficient Variable-Length Data-Compression Scheme

Adaptive variable-length coding scheme for compression of stream of independent and identically distributed source data involves either Huffman code or alternating run-length Huffman (ARH) code, depending on characteristics of data. Enables efficient compression of output of lossless or lossy precompression process, with speed and simplicity greater than those of older coding schemes developed for same purpose. In addition, scheme suitable for parallel implementation on hardware with modular structure, provides for rapid adaptation to changing data source, compatible with block orientation to alleviate memory requirements, ensures efficiency over wide range of entropy, and easily combined with such other communication schemes as those for containment of errors and for packetization.

Cheung, Kar-Ming↗
NASA NTRS2013

Integrating a Microwave Radiometer into Radar Hardware for Simultaneous Data Collection Between the Instruments

The conventional method for integrating a radiometer into radar hardware is to share the RF front end between the instruments, and to have separate IF receivers that take data at separate times. Alternatively, the radar and radiometer could share the antenna through the use of a diplexer, but have completely independent receivers. This novel method shares the radar's RF electronics and digital receiver with the radiometer, while allowing for simultaneous operation of the radar and radiometer. Radars and radiometers, while often having near-identical RF receivers, generally have substantially different IF and baseband receivers. Operation of the two instruments simultaneously is difficult, since airborne radars will pulse at a rate of hundreds of microseconds. Radiometer integration time is typically 10s or 100s of milliseconds. The bandwidth of radar may be 1 to 25 MHz, while a radiometer will have an RF bandwidth of up to a GHz. As such, the conventional method of integrating radar and radiometer hardware is to share the highfrequency RF receiver, but to have separate IF subsystems and digitizers. To avoid corruption of the radiometer data, the radar is turned off during the radiometer dwell time. This method utilizes a modern radar digital receiver to allow simultaneous operation of a radiometer and radar with a shared RF front end and digital receiver. The radiometer signal is coupled out after the first down-conversion stage. From there, the radar transmit frequencies are heavily filtered, and the bands outside the transmit filter are amplified and passed to a detector diode. This diode produces a DC output proportional to the input power. For a conventional radiometer, this level would be digitized. By taking this DC output and mixing it with a system oscillator at 10 MHz, the signal can instead be digitized by a second channel on the radar digital receiver (which typically do not accept DC inputs), and can be down-converted to a DC level again digitally. This unintuitive step allows the digital receiver to sample both the radiometer and radar data at a rapid, synchronized data rate (greater than 1 MHz bandwidth). Once both signals are sampled by the same digital receiver, high-speed quality control can be performed on the radiometer data to allow it to take data simultaneously with the radar. The radiometer data can be blanked during radar transmit, or when the radar return is of a power level high enough to corrupt the radiometer data. Additionally, the receiver protection switches in the RF front end can double as radiometer calibration sources, the short (four-microsecond level) switching periods integrated over many seconds to estimate the radiometer offset. The major benefit of this innovation is that there is minimal impact on the radar performance due to the integration of the radiometer, and the radiometer performance is similarly minimally affected by the radar. As the radar and radiometer are able to operate simultaneously, there is no extended period of integration time loss for the radiometer (maximizing sensitivity), and the radar is able to maintain its full number of pulses (increasing sensitivity and decreasing measurement uncertainty).

McLinden, Matthew↗
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↗