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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Galba: genome annotation with miniprot and AUGUSTUS

The Earth Biogenome Project has rapidly increased the number of available eukaryotic genomes, but most released genomes continue to lack annotation of protein-coding genes. In addition, no transcriptome data is available for some genomes. Various gene annotation tools have been developed but each has its limitations. Here, we introduce GALBA, a fully automated pipeline that utilizes miniprot, a rapid protein-to-genome aligner, in combination with AUGUSTUS to predict genes with high accuracy. Accuracy results indicate that GALBA is particularly strong in the annotation of large vertebrate genomes. We also present use cases in insects, vertebrates, and a land plant. GALBA is fully open source and available as a docker image for easy execution with Singularity in high-performance computing environments. Our pipeline addresses the critical need for accurate gene annotation in newly sequenced genomes, and we believe that GALBA will greatly facilitate genome annotation for diverse organisms.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

A Gateway to Support Interoperability of OPeNDAP and OGC Protocols

Data access and analysis tools that are developed within specific disciplines and the protocols that they are built upon provide valuable services to their respective users but can actually be a barrier to the interation of data from a broad set of data sources. An example of this is data supported by OPeNDAP that is widely used in the ocean and atmospheric sciences, and data provided through the interface specifications of the Open Geospatial Consortium (OGC) that typically serves the land science community. This paper described a project that is developing a gateway to bridge these two data system infrastructures, in response to a specific need expressed by CEOP, an international science program.

McDonald, Kenneth↗
DOE OSTI2021

The Regional Energy Deployment System (ReEDS): An Open-Access Model for the North American Electricity System

The Regional Energy Deployment System (ReEDS) model is NREL’s flagship capacity expansion planning tool for the electric power sector in North America. Originally developed in 2001, ReEDS has been used primarily by NREL researchers to conduct high-profile analysis of the potential evolution of the electricity system. In September 2019, the core model is being released for public use. In this presentation, we provide an overview of the model architecture, key model features, data sources, lessons learned, and sample model results for the North American electric power system.

42 ENGINEERING↗
DOE OSTI2025

An Open-Access Repository of Synchrophasor Data Quality Examples: Curation and Example Applications

Synchrophasor measurements are critical in providing wide-area situational awareness to power system operators. However, data artifacts may be introduced due to various issues such as loss of communication, loss of GPS signal, internal clock error, and vendor-specific implementation of phasor estimation algorithms. Tools designed to provide actionable insights from synchrophasor data, hence, must be designed to be robust to these data quality issues. In this work, two years of synchrophasor data sourced from multiple electric utilities in the United States were analyzed to identify examples of data quality problems. These examples were then labeled and published in the Grid Event Signature Library, a publicly available repository of power system measurements hosted by the Oak Ridge National Laboratory. This paper describes the data curation process, and illustrates two application use cases where the dataset can be valuable to the research community. In the first use case, a random forest classifier is trained to distinguish power system disturbance signatures from data anomalies introduced in synchrophasor measurements due to clock errors. The second use case studies the impact of data quality issues on an example synchrophasor application (specifically, event start time determination). The choice of data quality problems investigated is informed by the examples in the repository curated in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

MILK : a Python scripting interface to MAUD for automation of Rietveld analysis

Modern diffraction experiments ( e.g. in situ parametric studies) present scientists with many diffraction patterns to analyze. Interactive analyses via graphical user interfaces tend to slow down obtaining quantitative results such as lattice parameters and phase fractions. Furthermore, Rietveld refinement strategies ( i.e. the parameter turn-on-off sequences) tend to be instrument specific or even specific to a given dataset, such that selection of strategies can become a bottleneck for efficient data analysis. Managing multi-histogram datasets such as from multi-bank neutron diffractometers or caked 2D synchrotron data presents additional challenges due to the large number of histogram-specific parameters. To overcome these challenges in the Rietveld software Material Analysis Using Diffraction ( MAUD ), the MAUD Interface Language Kit ( MILK ) is developed along with an updated text batch interface for MAUD . The open-source software MILK is computer-platform independent and is packaged as a Python library that interfaces with MAUD . Using MILK , model selection ( e.g. various texture or peak-broadening models), Rietveld parameter manipulation and distributed parallel batch computing can be performed through a high-level Python interface. A high-level interface enables analysis workflows to be easily programmed, shared and applied to large datasets, and external tools to be integrated with MAUD . Through modification to the MAUD batch interface, plot and data exports have been improved. The resulting hierarchical folders from Rietveld refinements with MILK are compatible with Cinema: Debye–Scherrer , a tool for visualizing and inspecting the results of multi-parameter analyses of large quantities of diffraction data. In this manuscript, the combined Python scripting and visualization capability of MILK is demonstrated with a quantitative texture and phase analysis of data collected at the HIPPO neutron diffractometer.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

A Multidisciplinary Tool for Systems Analysis of Planetary Entry, Descent, and Landing (SAPE)

SAPE is a Python-based multidisciplinary analysis tool for systems analysis of planetary entry, descent, and landing (EDL) for Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Titan. The purpose of SAPE is to provide a variable-fidelity capability for conceptual and preliminary analysis within the same framework. SAPE includes the following analysis modules: geometry, trajectory, aerodynamics, aerothermal, thermal protection system, and structural sizing. SAPE uses the Python language-a platform-independent open-source software for integration and for the user interface. The development has relied heavily on the object-oriented programming capabilities that are available in Python. Modules are provided to interface with commercial and government off-the-shelf software components (e.g., thermal protection systems and finite-element analysis). SAPE runs on Microsoft Windows and Apple Mac OS X and has been partially tested on Linux.

Samareh, Jamshid A.↗
NASA NTRS2018

Enhancements to the Open Access Spectral Band Adjustment Factor Online Calculation Tool for Visible Channels

With close to 40 years of satellite observations, from which, cloud, land-use, and aerosol parameters can be measured, inter-consistent calibrations are needed to normalize retrievals across satellite records. Various visible-sensor inter-calibration techniques have been developed that utilize radiometrically stable Earth targets, e.g., deep convective clouds and desert/polar ice pseudo-invariant calibration sites. Other equally effective, direct techniques for intercalibration between satellite imagers are simultaneous nadir overpass comparisons and ray-matched radiance pairs. Combining independent calibration results from such varied techniques yields robust calibration coefficients, and is a form of self-validation. One potential source of significant error when cross-calibrating satellite sensors, however, are the often small but substantial spectral discrepancies between comparable bands, which must be accounted for. As such, visible calibration methods rely on a Spectral Band Adjustment Factor (SBAF) to account for the spectral-response function- induced radiance differences between analogous imagers. The SBAF is unique to each calibration method as it is a function of the Earth-reflected spectra. In recent years, NASA Langley pioneered the use of SCIAMACHY-, GOME-2-, and Hyperion-retrieved Earth spectra to compute SBAFs. By carefully selecting hyperspectral footprints that best represent the conditions inherent to an inter-calibration technique, the uncertainty in the SBAF is greatly reduced. NASA Langley initially provided the Global Space-based Inter-calibration System processing and research centers with online SBAF tools, with which users select conditions to best match their calibration criteria. This article highlights expanded SBAF tool capabilities for visible wavelengths, with emphasis on the use of the spectral range filtering for the purpose of separating scene conditions for the channel that the SBAF is needed based on the reflectance values of other bands. In other words, spectral filtering will enable better scene-type selection for bands where scene determination is difficult without information from other channels, which should prove valuable to users in the calibration community.

Scarino, Benjamin↗
DOE OSTI2025

Simulating large one-dimensional neutral-atom quantum systems

While abstract models of quantum computation assume a closed system of two-level states, practical quantum devices inevitably couple to the environment in some way, creating sources of noise. Understanding the tolerance to noise of specific quantum algorithms run on specific devices is important for determining the feasibility of quantum computing in the current noisy intermediate-scale quantum era. Of particular interest is understanding the noise sensitivity of these devices as more qubits are added to the system. Classical simulations are a useful tool to understand the effects of this noise, but direct classical simulations of open quantum systems are burdened by an exponentially growing cost in the number of qubits and a large local Hilbert space dimension. For onedimensional, shallow circuits, using tensor networks can replace this exponential cost with a linear one and simulate far wider systems than what would normally be available. In this paper, we describe a tensor network simulation of a neutral atom quantum system under the presence of noise, while introducing a purity-preserving truncation technique that compromises between the simplicity of the matrix product state and the positivity of the matrix product density operator. We apply this simulation to a near-optimized iteration of the quantum approximate optimization algorithm on a transverse field Ising model in order to investigate the influence of large system sizes on the performance of the algorithm. We find that while circuits with a large number of qubits fail more often under noise that depletes the qubit population, their outputs on a successful measurement are just as robust under Rydberg atom dissipation or qubit dephasing as smaller systems. However, such circuits might not perform as well under coherent multiqubit errors such as Rydberg atom crosstalk. We also find that the optimized parameters are especially robust to noise, suggesting that a noisier quantum system can be used to find the optimal parameters before switching to a cleaner system for measurements of observables.

Allen, James↗
DOE OSTI2023

Multiparametric optical label-free imaging to analyze plant cell wall assembly and metabolism. (Final Report)

Plant tissues are often considered not ideal for fluorescence imaging because of the pervasive intrinsic fluorescence of many plant metabolites and the intricate interactions with light of the many semi-crystalline polymers at the cell wall. Our project aims to take advantage of this observed shortcoming by developing a label-free, optical microscopy platform for characterizing multiple fingerprints of important cell wall components and stress-related, at subcellular scale resolution. The new imaging system can collect fingerprints from both emitted and scattered light that can inform on the chemical nature, subcellular distribution, anisotropy, and molecular environment of multiple cell wall components in intact plant tissues. We are combining these imaging capabilities with computational tools that enable correlated registration, integration, and analysis. This fully integrated, multiparametric optical system will be used to address biological problems connected to cell wall assembly in grasses. This includes a focus on developmental and environmental variation of cell wall impregnation with silica, lignin, suberin, and cutin in different tissues and cell types. Our research plan comprises three main goals: (1) To develop an accessible imaging platform and associated open-source software able to extract and integrate fingerprints from fluorescence-associated (multispectral emission, lifetime, and polarization), wide-field polarimetry, second harmonic generation (SHG), and stimulated Raman scattering signals (SRS); (2) To determine unique combination of fingerprints for various cell wall components and selected metabolites; (3) To analyze the process of cell wall silicification in grasses and determine how silicification affects cell wall properties and lignin, cutin, and suberin deposition in other cell types under differ stress conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Powered By ERAD [Slides]

Energy Resilience Analysis for Distribution Power System (ERAD) is a free, open-source Python toolkit for estimating the energy and service impacts of hazards like earthquakes and flooding. It uses a graph-based approach to capture high resolution connectivity among the grid, critical services, and customers and rapidly compute household level metrics and aggregated statistics across large distribution systems. It uses asset fragility curves that relate hazard severity to survival probability for power system equipment including cables, transformers, substations, etc. The tool is designed to be modular and extensible, allowing it to interface with third-party hazard simulators and integrate into broader resilience analysis workflows. ERAD enables researchers, students, communities, distribution utilities, and other stakeholders to understand hazard impacts and evaluate the effectiveness of different programs to improve energy resilience. The webinar was hosted by NLR researcher Aadil Latif.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2008

HDF-EOS Web Server

A shell script has been written as a means of automatically making HDF-EOS-formatted data sets available via the World Wide Web. ("HDF-EOS" and variants thereof are defined in the first of the two immediately preceding articles.) The shell script chains together some software tools developed by the Data Usability Group at Goddard Space Flight Center to perform the following actions: Extract metadata in Object Definition Language (ODL) from an HDF-EOS file, Convert the metadata from ODL to Extensible Markup Language (XML), Reformat the XML metadata into human-readable Hypertext Markup Language (HTML), Publish the HTML metadata and the original HDF-EOS file to a Web server and an Open-source Project for a Network Data Access Protocol (OPeN-DAP) server computer, and Reformat the XML metadata and submit the resulting file to the EOS Clearinghouse, which is a Web-based metadata clearinghouse that facilitates searching for, and exchange of, Earth-Science data.

Ullman, Richard↗
NASA NTRS2019

An Integrated Data Analytics Platform

An Integrated Science Data Analytics Platform is an environment that enables the confluence of resources for scientific investigation. It harmonizes data, tools and computational resources which subsequently enable the research community to focus on the investigation rather than spending time on security, data preparation, management, etc. OceanWorks is a NASA technology integration project to establish a cloud-based Integrated Ocean Science Data Analytics Platform at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) for big ocean science. It focuses on advancement and maturity by bringing together several NASA open-source, big data projects for parallel analytics, anomaly detection, in-situ to satellite data matchup, quality-screened data subsetting, search relevancy, and data discovery. Our communities are relying on data distributed through data centers such as the PO.DAAC, COAPS, NCAR, and many others to conduct their research. In typical investigations, scientists would engage in: search for data, evaluate the relevance of that data, download it, and then apply algorithms to identify trends. Such workflow cannot scale if the research involves a massive amount of data or multi-variate measurements. NASA’s Surface Water and Ocean Topography (SWOT) mission is expected to produce massive amount of observational data during its 3-year nominal mission. Collections like SWOT challenges all existing Earth Science data archival, distribution and analysis paradigms. In this paper, we will discuss how OceanWorks enhances the analysis of physical ocean data where the computation is done on an elastic cloud platform next to the archive to deliver fast, web-accessible services for working with oceanographic measurements.

Yang, Chaowei↗
DOE OSTI2021

CTRAMER: An open-source software package for correlating interfacial charge transfer rate constants with donor/acceptor geometries in organic photovoltaic materials

In this paper, we present CTRAMER (Charge-Transfer RAtes from Molecular dynamics, Electronic structure, and Rate theory)—an opensource software package for calculating interfacial charge-transfer (CT) rate constants in organic photovoltaic (OPV) materials based on ab initio calculations and molecular dynamics simulations. The software is based on identifying representative donor/acceptor geometries within interfacial structures obtained from molecular dynamics simulation of donor/acceptor blends and calculating the corresponding Fermi’s golden rule CT rate constants within the framework of the linearized-semiclassical approximation. While the methods used are well established, the integration of these state-of-the-art tools originating from different disciplines to study photoinduced CT processes with explicit treatment of the environment, in our opinion, makes this package unique and innovative. The software also provides tools for investigating other observables of interest. After outlining the features and implementation details, the usage and performance of the software are demonstrated with results from an example OPV system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

Steps Toward Improved Integration, Search, and Analysis of Heterogeneous Data in the Astrobiology Habitable Environments Database

The Astrobiology Habitable Environments Database (AHED) is a new data system being developed as a long-term, open-access repository for astrobiology data. AHED is intended to store user-contributed results from NASA or externally-funded research in astrobiology, and to encourage sharing and synergy within the astrobiology community. However, the interdisciplinary nature of astrobiology presents some specific challenges to data management, integration, and analysis within AHED. In some disciplines (e.g., genomics), open databases thrive because the contributed products are fairly uniform and standardized (e.g., sequence data). In astrobiology, each investigation produces a unique set of data products; this makes it difficult to search across different datasets to find similar data, or to combine results from separate investigations. With AHED, we are taking steps to ensure there is adequate metadata - both at the dataset and record levels - to facilitate search, integration, and analysis. At the dataset level, we are developing a new metadata standard for describing astrobiology datasets, with detailed information about content, funding source, and scientific relevance, along with a set of topical keywords for characterizing datasets. At the record level, we are encouraging users to provide more structured content and finer-grained metadata. In many user-contributed science data repositories, few restrictions are placed on the uploaded data format, and minimal or no record-level metadata is required; thus users are unburdened when it comes to data preparation. The tradeoff is that deep integration and search across datasets is almost impossible without standardized structures and metadata. Although AHED users are free to upload minimally-described datasets, they will be encouraged to use database authoring tools (supplied by the underlying platform - Open Data Repository's Data Publisher) plus a set of customizable astrobiology-specific templates to help structure their data and provide standardized metadata. In reward for their extra effort, AHED will be able to deliver enhanced search, discovery, and analysis capabilities.

astrobiology↗
DOE OSTI2026

Optimal Co-Design of Integrated Thermal-Electrical Networks and Control Systems for Grid-interactive Efficient District (GED) Energy Systems

This project advances a unified, open-source framework for the optimal co-design of thermal, electrical, and control systems in grid-interactive efficient districts (GEDs). As communities integrate growing levels of distributed energy resources, traditional approaches that model thermal and electrical networks independently lead to reduced efficiency, limited flexibility, and missed opportunities for coordinated operation. To address these challenges, the research team developed a comprehensive suite of physics-based models, control algorithms, and software tools that enable holistic simulation, optimization, and demonstration of district-scale energy systems.

14 SOLAR ENERGY↗
NASA NTRS2016

Further Development and Assessment of a Broadband Liner Optimization Process

The utilization of advanced fan designs (including higher bypass ratios) and shorter engine nacelles has highlighted a need for increased fan noise reduction over a broader frequency range. Thus, improved broadband liner designs must account for these constraints and, where applicable, take advantage of advanced manufacturing techniques that have opened new possibilities for novel configurations. This work focuses on the use of an established broadband acoustic liner optimization process to design a variable-depth, multi-degree of freedom liner for a high speed fan. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design a liner aimed at producing impedance spectra that most closely match the predicted optimum values. The multi-degree of freedom design is carried through design, fabrication, and testing. In-duct attenuation predictions compare well with measured data and the multi-degree of freedom liner is shown to outperform a more conventional liner over a range of flow conditions. These promising results provide further confidence in the design tool, as well as the enhancements made to the overall design process.

Nark, Douglas M.↗
DOE OSTI2023

Comprehensive Analysis of Streaming and Shutdown Dose Rate Experiments at JET with ORNL Fusion Neutronics Workflows

Current experimental fusion systems and conceptual designs of fusion pilot plants (FPPs) are growing in complexity and size. Several radiation metrics are crucial to the safe operation of fusion machines, including neutron flux streaming through openings and the shutdown dose rate (SDDR). Most current designs of advanced experimental fusion systems—and the most probable candidates for FPPs—are based on the tokamak concept, which is prone to neutron streaming through the myriad openings needed for diagnostic and support systems. SDDR is caused by decay gamma rays from radionuclides that become activated by neutrons during the operation of a fusion system that use deuterium-deuterium (DD), tritium-tritium, or deuterium-tritium plasma. Because computational tools have become essential for determining these radiation metrics, they must be validated against reliable and applicable experimental data. Experiments at the Joint European Torus (JET) provide a unique source of experimental data for validating computational tools and nuclear data used to determine SDDR and neutron fluxes in streaming-dominated geometries. Here, this paper presents the comprehensive analysis of the high-performance DD JET SDDR, and streaming experiments performed using Oak Ridge National Laboratory (ORNL) fusion workflows. The computational results were compared with experimental results that consist of online SDDR measurements with ionization chambers and neutron fluence streaming measurements using thermoluminescent detectors. The ratio of calculated-to-experimental SDDR values ranges from 0.6 to 2.5, and the streaming results range from 0.5 to 8.0. Future work will include analyzing the JET 2021 DTE2 campaign alongside the integration of the Shift Monte Carlo transport code into all ORNL fusion neutronics workflows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Sandia GNU Radio Utilities

The Sandia Utilities form an RF toolkit extending the GNU Radio framework for straightforward interaction with bursty RF systems which can be cumbersome using built in capabilities of the framework or other open source extensions. Motivated by the abstract exercise of responding to a modulated burst of information with a unique modulated burst of information, the Sandia Utilities provide several dozen additional debug and signal processing blocks through four software modules. These blocks manifest their utility through a new general concept of operation for GNU Radio applications and extend many existing streaming capabilities to the PDU-based message passing API. Using these concepts and tools, it is straightforward to develop software capabilities to interact with existing and new bursty RF devices.

47 OTHER INSTRUMENTATION↗