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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 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

NASA CARA Tools

The NASA Conjunction Assessment Risk Analysis (CARA) team has created and posted to GitHub a set of MATLAB software tools for collision assessment (CA) analysis. The software is provided to the public under a NASA Open-Source Software Agreement and is maintained/updated by the CARA Analysis team. Capabilities provided within the toolset include algorithms in assessing probability of collision (Pc), collision consequence, covariance realism, Orbit Determination (OD) quality assessment, and single covariance max Pc. Additionally, a set of utilities are provided for astrodynamics topics closely related to CA, such as: Conjunction Data Message (CDM) parsing, covariance transformations, coordinate system transformations, etc. The repository is regularly updated on a monthly basis and new functionality will be added as algorithms are approved for public release. This presentation will provide a brief introduction to the toolset, highlight some of the key components which can be used in operations, and will present information on algorithms that are in the release pipeline and can be expected soon. This software will enable operators to independently perform CA calculations using the same core algorithms that CARA uses in operations.

L. Baars↗

NASA NTRSDate not supplied

NASA CARA Tools

Luis Baars↗

NASA NTRSDate not supplied

Graph Representation Learning for Dengue Forecasting

In 2017, the largest recorded dengue outbreak in Sri Lanka’s history occurred. Since then, dengue has continued to threaten national health across Sri Lanka. The development of an effective Early Warning System (EWS) for dengue outbreaks is essential for Sri Lanka’s Ministry of Health to take preventative measures. We propose the use of Graph Neural Networks as EWS. Using earth observational data from NASAs global satellites and dengue incidence data from Sri Lanka s Ministry of Health, we developed a series of traditional and graph representation EWS to forecast Dengue cases across Sri Lanka’s 25 districts between 2013 and 2022. We demonstrate empirically that Graph Neural Networks which incorporate spatiotemporal relations significantly outperform traditional EWS such as Autoregressive Integrated Moving Average (ARIMA), Random Forest, and Long Short-Term Memory (LSTM). Our source code is available on GitHub and will be provided in the final submission.

Graph Neural Networks↗

NASA NTRS2024

Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications

This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA’s Harmonized Landsat and Sentinel-2 data archive at 30m resolution, the new 300M and 600M parameter models incorporate temporal and location embeddings for enhanced performance across various geospatial tasks. Through extensive benchmarking with GEOBench, the 600M version outperforms the previous Prithvi-EO model by 8% across a range of tasks. It also outperforms six other geospatial foundation models when benchmarked on remote sensing tasks from different domains and resolutions (i.e. from 0.1m to 15m). The results demonstrate the versatility of the model in both classical earth observation and high-resolution applications. Early involvement of end-users and subject matter experts (SMEs) are among the key factors that contributed to the project’s success. In particular, SME involvement allowed for constant feedback on model and dataset design, as well as successful customization for diverse SME-led applications in disaster response, land use and crop mapping, and ecosystem dynamics monitoring. Prithvi-EO-2.0 is available on Hugging Face and IBM terratorch, with additional resources on GitHub. The project exemplifies the Trusted Open Science approach embraced by all involved organizations.

Daniela Szwarcman↗

DOE OSTI2016

Scraper

This application is a set of utility scripts for obtaining the public data available via the GitHub REST API.

Source record↗

DOE OSTI2016

CIVET: Continuous Integration, Verification, Enhancement, and Testing

A Git server (GitHub, GitLab, BitBucket) sends event notifications to the Civet server. These are either a " Pull Request" or a "Push" notification. Civet then checks the database to determine what tests need to be run and marks them as ready to run. Civet clients, running on dedicated machines, query the server for available jobs that are ready to run. When a client gets a job it executes the scripts attached to the job and report back to the server the output and exit status. When the client updates the server, the server will also update the Git server with the result of the job, as well as updating the main web page.

Alger, Brian↗

DOE OSTI2019

Cosmic Microwave Background Anisotropy Numerical Solution (CMBAns) I: An Introduction to $C_l$ Calculation

Cosmological Boltzmann codes are often used by researchers for calculating the CMB angular power spectra from different theoretical models, for cosmological parameter estimation, etc. Therefore, the accuracy of a Boltzmann code is of utmost importance. Different Markov Chain Monte Carlo based parameter estimation algorithms typically require 10^3 - 10^4 iterations of Boltzmann code. This makes the time complexity of such codes another critical factor. In the last two decades, several Boltzmann packages, such as CMBFAST, CAMB, CMBEasy, CLASS etc., have been developed. In this paper, we present a new cosmological Boltzmann code, CMBAns, that can be used for accurate calculation of the CMB power spectrum. At present, CMBAns is developed for a flat background matrix. It is mostly written in the C language. However, we borrowed the concept of class from C++. This gives researchers the flexibility to develop their own independent package based on CMBAns, without an in-depth understanding of the source code. We also develop multiple stand-alone facilities which can be directly compiled and run on a given parameter set. In this paper, we discuss all the mathematical formulation, approximation schemes, integration methods etc., that are used in CMBAns. The package will be made available through github for public use in the near future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

The ESIF-HPC-2 Benchmark Suite: Preprint

We describe the development of the ESIF-HPC-2 benchmark suite, a collection of kernel and application benchmark codes for measuring computational and I/O performance from single nodes to full HPC systems that was used for acceptance testing in our recent HPC procurement. The configurations of the benchmarks used for our system is presented. We also describe a set of 'dimensions' that can be used to classify benchmarks and assess coverage of a suite systematically. The collection is offered cost-free as a GitHub repository for general usage and further development.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

OpenCGRA: An Open-Source Unified Framework for Modeling,Testing, and Evaluating CGRAs

Coarse-grained reconfigurable arrays (CGRAs),loosely defined as arrays of functional units (e.g, adder, sub-tractor, multiplier, divider, or larger multi-operation units, butsmaller than a general-purpose core) interconnected through aNetwork-on-Chip, provide higher flexibility than domain-specificASIC accelerators while offering increased hardware efficiencywith respect to fine-grained reconfigurable devices, such as FieldProgrammable Gate Arrays (FPGAs). The fast evolving fieldsof machine learning and edge computing, which are seeing acontinuous flow of novel algorithms and larger models, makeCGRAs ideal target architectures to allow domain specializationwithout loosing too much generality. They also generally offerquicker and more effective reconfigurability than FPGAs, po-tentially allowing adaptation during actual algorithm execution,and implement a dataflow programming paradigm that adaptswell to these emerging workloads. Designing and generating aCGRA, however, still requires to define the type and number ofthe specific functional units, implement their interconnect andthe network topology, and perform its simulation and validation,given a variety of workloads of interest.In this paper, we propose OpenCGRA, a Python-based unifiedframework that integrates generation, modeling, testing and eval-uation for CGRAs. OpenCGRA is the first open-source integratedframework able to support the full top-to-bottom design flow forspecializing and implementing CGRAs: modeling at different ab-straction levels (functional level, cycle level, register-transfer level),generation, simulation, testing at different granularities (unit test-ing, integration testing, property-based testing), and characteriza-tion (area, power, and timing). OpenCGRAs will be made availableon GitHub.

CGRA, synthesis↗

DOE OSTI2021

Open-Source PSCAD Grid-Following and Grid-Forming Inverters and a Benchmark for Zero-Inertia Power System Simulations: Preprint

This paper presents open-source, flexible, and easily-scalable models of grid following and grid forming inverters for the PSCAD software platform. The models are intended for system integration studies, particularly stability analyses of power systems with high penetration of inverter-based generation. To verify the model functionality, they are implemented in a IEEE9-bus system in a zero-inertia operational scenario of 100% inverter-based generation. The models have been made available open source at the PyPSCAD NREL GitHub page.

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

DOE OSTI2021

DESC DC2 Data Release Note

In preparation for cosmological analyses of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the LSST Dark Energy Science Collaboration (LSST DESC) has created a 300 deg$^2$ simulated survey as part of an effort called Data Challenge 2 (DC2). The DC2 simulated sky survey, in six optical bands with observations following a reference LSST observing cadence, was processed with the LSST Science Pipelines (19.0.0). In this Note, we describe the public data release of the resulting object catalogs for the coadded images of five years of simulated observations along with associated truth catalogs. We include a brief description of the major features of the available data sets. To enable convenient access to the data products, we have developed a web portal connected to Globus data services. We describe how to access the data and provide example Jupyter Notebooks in Python to aid first interactions with the data. We welcome feedback and questions about the data release via a GitHub repository.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Updates to the Instant Online PV LCOE Calculator Tool

Levelized cost of energy (LCOE) is an important metric for techno-economic analysis of PV modules, systems, and performance. An NREL team within DuraMAT has developed a simplified PV-specific LCOE calculator as an alternative to the NREL System Advisor Model (SAM) for applications that do not have the degree of detail required by SAM. This webinar will review recent data and new features that have been added to the simplified calculator this year, including breakeven buttons, commercial system options, and inverter loading ratios. It will also review the structure of the source code on GitHub, how to edit a local version of the calculator, and walk through some example use cases for the calculator.

calculator↗

DOE OSTI2021

Introducing PRIMRE’s MRE Software Knowledge Hub

This paper focuses on the role of the Marine Renewable Energy (MRE) Software Knowledge Hub on the Portal and Repository for Information on Marine Renewable Energy (PRIMRE). The MRE Software Knowledge Hub provides online services for MRE software users and developers, and seeks to develop assessments and recommendations for improving MRE software in the future. Online software discovery platforms, known as the Code Hub and the Code Catalog, are provided. The Code Hub is a collection of open-source MRE software that includes a landing page with search functionality, linked to files hosted on the MRE Code Hub GitHub organization. The Code Catalog is a searchable online platform for discovery of useful (open-source or commercial) software packages, tools, codes, and other software products. To gather information about the existing MRE software landscape, a software survey is being performed, the preliminary results of which are presented herein. Initially, the data collected in the MRE software survey will be used to populate the MRE Software knowledge hub on PRIMRE, and future work will use data from the survey to perform a gap analysis and develop a vision for future software development. Additionally, as one of PRIMRE’s roles is to support development of MRE software within project partners, a silo of knowledge relating to best practices has been gathered.

marine, energy, open source software, MHKiT, MRE C↗

DOE OSTI2021

Introducing PRIMRE's MRE Software Knowledge Hub (February 2021)

This paper focuses on the role of the Marine Renewable Energy (MRE) Software Knowledge Hub on the Portal and Repository for Information on Marine Renewable Energy (PRIMRE). The MRE Software Knowledge Hub provides online services for MRE software users and developers, and seeks to develop assessments and recommendations for improving MRE software in the future. Online software discovery platforms, known as the Code Hub and the Code Catalog, are provided. The Code Hub is a collection of open-source MRE software that includes a landing page with search functionality, linked to files hosted on the MRE Code Hub GitHub organization. The Code Catalog is a searchable online platform for discovery of useful (open-source or commercial) software packages, tools, codes, and other software products. To gather information about the existing MRE software landscape, a software survey is being performed, the preliminary results of which are presented herein. Initially, the data collected in the MRE software survey will be used to populate the MRE Software knowledge hub on PRIMRE, and future work will use data from the survey to perform a gap analysis and develop a vision for future software development. Additionally, as one of PRIMRE's roles is to support development of MRE software within project partners, a silo of knowledge relating to best practices has been gathered. An early draft of new guidance developed from this knowledge is presented.

gap analysis↗

DOE OSTI2022

Developing an Interactive Landscape for Mobility Resources: Preprint

As the world continues to be increasingly driven by data, the ways researchers and professionals sort and collect this data is critical. In the world of mobility data, new levels of data from public transportation systems, location services, and other means are being lost due to how little organization exists. Much of the data is proprietary, and there are few if any de jure or even de facto standards connecting data. There is also little knowledge about the gaps that exist in the data. In this project, we created an interactive landscape where mobility resources are categorized and organized in an easy to use, living document. We made this landscape with open-source code from the CNCF Cloud Native Landscape and repurposed it to the mobility data's needs. Additionally, unlike previous sources that organize mobility data, this document can be updated through GitHub by those in the field to keep its sources relevant. Following the creation of a beta version of the landscape, we conducted several interviews with industry researchers and professionals to ensure the landscape would be useful. The result is an online hub where mobility researchers and resource creators can easily access research and collaborate.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Pele: An Exascale-Ready Suite of Combustion Codes

High fidelity simulations of realistic combustion devices are extremely demanding computationally because of the requirements to capture complex fuel chemical decomposition, its intricate interactions with turbulent, often multiphase, flows, and the wide separation of space and time scales between the thin flame and the device boundaries. Software required to carry out such computations tends to be extremely complex, particularly when designed to exploit hardware accelerators, and can be difficult to port and maintain. We present Pele, a performance portable suite of tools for the simulation of combustion systems, including codes to evolve reactive multiphase configurations in the low Mach number and compressible flow regimes, along with a set of inter-compatible post processing and in situ analysis tools. The Pele suite of tools is built on top of the AMReX framework for block-structured adaptive mesh refinement, which provides efficient data structures and algorithms that enable the development of a wide variety of efficient mesh and particle based PDE integration schemes. A hierarchical MPI+X parallelism scheme supports CPU-only and accelerated architectures, where X can be OpenMP, CUDA, and HIP based approaches for intra-node computational work distribution. The algorithms and data structures underlying the Pele simulation and analysis tools are highly scalable and performant across a wide variety of high-performance computing platforms, including DOEs newest exascale-class machines, Frontier and Aurora. The simulation and analysis tools are fully documented and freely distributed as open source via GitHub. We present key algorithmic and software challenges, solution strategies, performance and resulting set of capabilities.

AMReX↗

DOE OSTI2023

PV Validation Hub

The Validation Hub will be a clearinghouse for the transfer of novel algorithms and software from the PV research community to industry. Potential algorithms tested in the Hub could include the estimation of various PV loss factors and the detection of various operational issues. The primary function of the Hub will be for developers to submit executable code which will run on hosted data sets. Developers will receive private reports on the accuracy and performance (e.g., run-time) of the submitted algorithms, and public high level summaries will be hosted. These summaries will indicate the organization who submitted the algorithm (e.g., links to GitHub pages, documentation websites, etc.), high-level accuracy metrics, and standardized performance metrics. These results will be stored in a publicly available database, accessible through the Hub, with the ability for users to sort and filter the results. In short, the Hub will be presented to public users as a collection of interactive leaderboards, organized around specific analysis tasks pertinent to the PV data science community. These tasks include things such as the estimation of various PV loss factors and the detection of various operational issues. We will present progress on the development of this hub, including preliminary results of comparative validation of PV data science algorithms and progress towards building the platform itself.

algorithm↗

DOE OSTI2023

Methodology and Tool for the Physical Security Analysis of Micro and Advanced Reactors

This work proposes a dynamic evaluation methodology to relax the conservatism in physical security evaluation, by leveraging an ongoing work in the Light Water Reactor Sustainability pathway. This methodology is implemented in a dynamic risk assessment tool named Event Modeling Risk Assessment using Linked Diagrams (EMRALD). The work extends EMRALD’s capability to support a sandbox feature where analysts can easily create attack scenarios and modify advanced/small modular reactor (A/SMR) security and safety features using templates. This approach saves time and cost since the analysis does not require creating detailed computer-aided design models, as is commonly required in commercial force-on-force software tools. EMRALD is completely free to use at https://emraldapp.inl.gov. We have developed basic templates including physical barriers, intrusion sensors, physical areas, and safety actions, that can be downloaded from EMRALD’s GitHub site: https://github.com/idaholab/EMRALD. These templates use generic data commonly used for training purposes, which do not reflect any actual operating nuclear reactor. Users may adjust the data in the templates with their own dataset and/or create new templates in EMRALD. The proposed methodology combines security and safety by assessing sabotage effects up to the radiological consequence to the public instead of merely the core damage state. This practice follows the industry standard for advanced non-light-water reactors currently proposed for endorsement by the Nuclear Regulatory Commission. The combination of security and safety is expressed in an achievability-consequence chart. EMRALD can be used to generate data for this chart. A hypothetical case study using a representative sodium-cooled fast reactor (SFR) facility is presented in this report to demonstrate this methodology. This case study does not contain any actual nuclear plant information. This work will benefit A/SMR vendors and utilities to implement security by design during the reactor design iteration phase, such that they do not have to perform upgrades and retrofits to the reactor after it is installed to improve its physical protection system. The tool may also be used to analyze domestic or foreign reactor designs to support the International Nuclear Security Techniques for Advanced Reactors (INSTAR) bilateral missions. Future works are planned to implement the methodology on a reference SFR reactor and a reference high-temperature gas-cooled reactor to obtain insights and lessons-learned for the A/SMR community.

97 MATHEMATICS AND COMPUTING↗