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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Software management for the NO ν A Experiment

The NO$\nu$A software (NO$\nu$ASoft) is written in C++, and built on the Fermilab Computing Division's art framework that uses ROOT analysis software. NO$\nu$ASoft makes use of more than 50 external software packages, is developed by more than 50 developers and is used by more than 100 physicists from over 30 universities and laboratories in 3 continents. The software builds are handled by Fermilab's custom version of Software Release Tools (SRT), a UNIX based software management system for large, collaborative projects that is used by several experiments at Fermilab. The system provides software version control with SVN configured in a client-server mode and is based on the code originally developed by the BaBar collaboration. In this paper, we present efforts towards distributing the NO$\nu$A software via the CernVM File System distributed file system. Here, we will also describe our recent work to use a CMake build system and Jenkins, the open source continuous integration system, for NOASoft.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

beluga

beluga is an open-source optimal control software that uses publicly available, indirect methods from GitHub. beluga's indirect optimization engine has been reworked to follow a lazy functional paradigm. This improves the software's flexibility and enables users to create their own optimization processes without modification of the source code. beluga is general-purpose and therefore very broad in scope and application. SAND2020-12847 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sparapany, Michael↗
DOE OSTI2017

LLVM Infrastructure and Tools Project Summary

This project works with the open source LLVM Compiler Infrastructure (http://llvm.org) to provide tools and capabilities that address needs and challenges faced by ECP community (applications, libraries, and other components of the software stack). Our focus is on providing a more productive development environment that enables (i) improved compilation times and code generation for parallelism, (ii) additional features/capabilities within the design and implementations of LLVM components for improved platform/performance portability and (iii) improved aspects related to composition of the underlying implementation details of the programming environment, capturing resource utilization, overheads, etc. -- including runtime systems that are often not easily addressed by application and library developers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

SplitML

SplitML (Signal Processing Library for Interference rejecTion by Machine Learning) is a code repository for a set of tools for interference rejection in complex time-domain signals. The goal of the tools is to provide machine learning modeling capabilities for rejecting interference. Recent related machine learning algorithms for signal processing have focused mostly on speech enhancement or multi-speaker speech separation; the tools in SplitML will extend these innovations to generic time-domain signals of interest. SplitML includes tools for generating synthetic noisy signals, code for customized machine learning models applicable to interference rejection, and tools for evaluating such algorithms against standard signal processing techniques. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.

Klein, Natalie↗
DOE OSTI2021

DERMS-RT (Distributed Energy Resource Management Solution using Real-Time Optimization) [SWR-20-46]

DERMS-RT provides a distributed energy resource management solution using real-time optimization to control different types of distributed energy resources (DERs) — such as rooftop PVs, battery energy storage systems, HVAC loads, electric water heater loads, and EV charging loads, and use these DERs to provide distribution voltage regulation and peak demand management services. The control approach implemented by DERM-RT is developed based on the real-time optimal power flow and distributed control previously developed by NREL researchers. The software codes are designed to provide modular DER management solution that can be easily applied to control heterogeneous DERs in distribution grids in coordination with centralized utility management systems. Also, DERMS-RT provides application programming interface (API) to extract useful grid model information from an open-source power system simulation software, use the information to solve the optimization problem, and apply the optimal set-points to the controlled DERs. In this way, DERMS-RT provides a plug-and-play function for implementing the real-time DER control on different utility system models, and it can be used as a simulation testbed to demonstrate the impact of real-time DER optimization on improving grid operations.

Ding, Fei↗
DOE OSTI2013

Transformations, Inc. Net Zero Energy Communities, Devens, Easthampton, Townsend, Massachusetts (Fact Sheet)

In 2009, Transformations, Inc. partnered with U.S. Department of Energy (DOE) Building America team Building Science Corporation (BSC) to build new net zero energy houses in three developments in Massachusetts. The company has been developing strategies for cost-effective super-insulated homes in the New England market since 2006. After years of using various construction techniques, it has developed a specific set of assemblies and specifications that achieve a 44.9% reduction in energy use compared with a home built to the 2009 International Residential Code, qualifying the houses for the DOE's Challenge Home. The super-insulated houses provide data for several research topics in a cold climate. BSC studied the moisture risks in double stud walls insulated with open cell spray foam and cellulose. The mini-split air source heat pump (ASHP) research focused on the range of temperatures experienced in bedrooms as well as the homeowners' perceptions of equipment performance. BSC also examined the developer's financing options for the photovoltaic (PV) systems, which take advantage of Solar Renewable Energy Certificates, local incentives, and state and federal tax credits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

New Whole-House Case Study: Transformations, Inc. Net Zero Energy Communities, Devens, Easthampton, Townsend, Massachusetts

In 2009, Transformations, Inc. partnered with Building America team Building Science Corporation (BSC) to build new net zero energy houses in three developments in Massachusetts. The company has been developing strategies for cost-effective super-insulated homes in the New England market since 2006. After years of using various construction techniques, it has developed a specific set of assemblies and specifications that achieve a 44.9% reduction in energy use compared with a home built to the 2009 International Residential Code, qualifying the houses for the DOE’s Challenge Home. The super-insulated houses provide data for several research topics in a cold climate. BSC studied the moisture risks in double stud walls insulated with open cell spray foam and cellulose. The mini-split air source heat pump (ASHP) research focused on the range of temperatures experienced in bedrooms as well as the homeowners’ perceptions of equipment performance. BSC also examined the developer’s financing options for the photovoltaic (PV) systems, which take advantage of Solar Renewable Energy Certificates, local incentives, and state and federal tax credits.

air source heat pump↗
DOE OSTI2015

The Electrolyte Genome project: A big data approach in battery materials discovery

We present a high-throughput infrastructure for the automated calculation of molecular properties with a focus on battery electrolytes. The infrastructure is largely open-source and handles both practical aspects (input file generation, output file parsing, and information management) as well as more complex problems (structure matching, salt complex generation, and failure recovery). Using this infrastructure, we have computed the ionization potential (IP) and electron affinities (EA) of 4830 molecules relevant to battery electrolytes (encompassing almost 55,000 quantum mechanics calculations) at the B3LYP/6-31+G(*) level. We describe automated workflows for computing redox potential, dissociation constant, and salt-molecule binding complex structure generation. We present routines for automatic recovery from calculation errors, which brings the failure rate from 9.2% to 0.8% for the QChem DFT code. Automated algorithms to check duplication between two arbitrary molecules and structures are described. We present benchmark data on basis sets and functionals on the G2-97 test set; one finding is that a IP/EA calculation method that combines PBE geometry optimization and B3LYP energy evaluation requires less computational cost and yields nearly identical results as compared to a full B3LYP calculation, and could be suitable for the calculation of large molecules. Our data indicates that among the 8 functionals tested, XYGJ-OS and B3LYP are the two best functionals to predict IP/EA with an RMSE of 0.12 and 0.27 eV, respectively. Application of our automated workflow to a large set of quinoxaline derivative molecules shows that functional group effect and substitution position effect can be separated for IP/EA of quinoxaline derivatives, and the most sensitive position is different for IP and EA. Published by Elsevier B.V

Battery↗
DOE OSTI2018

Umpire: Status Report and Future Development Plan

Umpire is a open-source C++ library that provides memory and resource management functions for use with heterogeneous memory spaces. The Umpire library is being developed to simplify coordination and sharing of limited memory resources for complex integrated applications developed in the ECP/ATDM and ASC programs, and other multi-physics codes that combine many physics packages and libraries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Umpire: Integration with Other Software Technologies

Umpire is an open-source C++ library that provides memory and resource management functions for use with heterogeneous memory spaces. The Umpire library is being developed to simplify coordination and sharing of limited memory resources for complex integrated applications developed in the ECP/ATDM and ASC programs, and other multi-physics codes that combine many physics packages and libraries. The overarching goal of Umpire is to provide a single application-facing API for memory management on all platforms by decoupling memory operations from platform-specific memory spaces. It provides operations for: memory space discovery, memory provisioning, allocation and transfers, and introspection. Umpire development began in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory (LLNL). Umpire is funded primarily by LLNL ASC and ATMD portfolios and receives a small amount of support as part of ECP ST Project 2.3.1.06 STMP08-ISC. The source code is hosted and developed on GitHub. In this report, we explore possible integrations with other memory hierarchy management software. We examine both projects supported by ECP, as well as third-party and vendor provided tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Cloverleaf Data Artifacts for ArtIMis LDRD

This report summarizes the use of the open-source CloverLeaf/CloverLeaf3D mini-apps to generate synthetic data sets to train foundation models for the ArtIMis LDRD DI. These data artifacts are intended to be used by LANL collaborators and shared externally with our university and institutional partners. Note that CloverLeaf/CloverLeaf3D is not a LANL simulation code.

97 MATHEMATICS AND COMPUTING↗
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↗
DOE OSTI2021

U.S.-China Clean Energy Research Center Building Energy Efficiency (CERC-BEE) Open-Source Retrofit Targeting Tool (CRADA FP00007338 Final Report)

To increase the cost-saving energy and carbon dioxide (CO 2 ) emissions reductions in buildings and portfolios at the scale and speed necessary to limit climate change, researchers at LBNL and Johnson Controls (JCI) developed the Building Efficiency Targeting Tool for Energy Retrofits (BETTER). BETTER is a software tool that consists of three components: (1) the BETTER analytical engine source code (which was developed with intellectual property provided by JCI under CRADA FP00007338); (2) the BETTER web application, developed by LBNL and McQuillen Interactive Pty. Ltd; and (3) the BETTER application programming interface (API), also developed by LBNL and McQuillen Interactive Pty. Ltd. BETTER enables building and portfolio owners, managers, and service providers worldwide to quickly, easily identify cost-saving energy efficiency retrofits in existing buildings and portfolios without expensive site visits or complex modeling. With minimal data input, the tool benchmarks a building’s electric and fossil energy usage against peers; quantifies energy, cost and greenhouse gas (GHG) emission reduction potentials at the building and portfolio levels; and recommends energy efficiency measures to decarbonize and electrify buildings and portfolios, targeting specific energy savings levels. No other tool so comprehensively analyzes buildings and portfolios with such ease. If fully implemented, it is estimated that BETTER could help reduce emissions equivalent to planting 1.3 billion trees globally by 2030. Moreover, an additional 50-75% of embodied GHG emissions could be avoided in each case where BETTER results in a building being retrofitted instead of demolished and replaced, providing substantial additional decarbonization benefits for the buildings sector. BETTER has garnered multiple awards and avid interest from investors. In 2020, it earned a R&D 100 Award for innovation and a LBNL Director’s Award for Technology Transfer. In 2021, BETTER was named an EarthX E-Capital Summit Climate Tech Prize semi-finalist

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization

Objective: The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interoperability across different institutions due to coding differences. We propose a Multiview Incomplete Knowledge Graph Integration (MIKGI) algorithm to integrate information from multiple sources with partially overlapping EHR concept codes to enable translations between healthcare systems. Methods: The MIKGI algorithm combines knowledge graph information from (i) embeddings trained from the co-occurrence patterns of medical codes within each EHR system and (ii) semantic embeddings of the textual strings of all medical codes obtained from the Self-Aligning Pretrained BERT (SAPBERT) algorithm. Due to the heterogeneity in the coding across healthcare systems, each EHR source provides partial coverage of the available codes. MIKGI synthesizes the incomplete knowledge graphs derived from these multi-source embeddings by minimizing a spherical loss function that combines the pairwise directional similarities of embeddings computed from all available sources. MIKGI outputs harmonized semantic embedding vectors for all EHR codes, which improves the quality of the embeddings and enables direct assessment of both similarity and relatedness between any pair of codes from multiple healthcare systems. Results: With EHR co-occurrence data from Veteran Affairs (VA) healthcare and Mass General Brigham (MGB), MIKGI algorithm produces high quality embeddings for a variety of downstream tasks including detecting known similar or related entity pairs and mapping VA local codes to the relevant EHR codes used at MGB. Based on the cosine similarity of the MIKGI trained embeddings, the AUC was 0.918 for detecting similar entity pairs and 0.809 for detecting related pairs. For cross-institutional medical code mapping, the top 1 and top 5 accuracy were 91.0% and 97.5% when mapping medication codes at VA to RxNorm medication codes at MGB; 59.1% and 75.8% when mapping VA local laboratory codes to LOINC hierarchy. When trained with 500 labels, the lab code mapping attained top 1 and 5 accuracy at 77.7% and 87.9%. MIKGI also attained best performance in selecting VA local lab codes for desired laboratory tests and COVID-19 related features for COVID EHR studies. Compared to existing methods, MIKGI attained the most robust performance with accuracy the highest or near the highest across all tasks. Conclusions: The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.

Zhou, Doudou↗
DOE OSTI2014

SU-E-T-210: Independent MU Dose Calculation Software for S and S IMRT Using Modified Clarkson Integration Sector

Purpose: The purpose of this work was to develop and validate an open source independent MU dose calculation software for S and S IMRT based in the algorithm proposed by Kung et.al. Methods: Treatment plans were done using Iplan v4.5 BrainLAB TPS and S and S IMRT modality. A 6MV photon beam produced by a Primus linear accelerator equipped with an Optifocus MLC was used. TPS dose calculation algorithms were pencil beam and Monte Carlo. 230 IMRT treatments plans were selected for the study. The software was written under MALTLAB environment. Treatment plans were imported by the software using RTP format. Field fluences were reconstructed adding all segments.The algorithm implemented in the software calculates the dose at a reference point as the sum of primary and scatter dose. The primary dose is obtained by masking the fluence map with a circle of radius 1cm. The scatter dose is obtained through a shaped ring mask around the previous circle with a thickness of 0.5cm; the rings are increased one after another with constant thickness until cover the entire map of influence. The dosimetric parameters Sc, Sp and TPR vary depending on radio, the transmission effect of the MLC, inverse square law and dose profile are used for the calculation. Results: The average difference between measured and independent calculated dose was 0.4% ± 2.2% [−6.8%, 6.4%]. For 91% of the studied plans the difference was less than 3%. The difference between the measured and TPS dose with pencilbeam algorithm was 2.6% ± 1.41% [−2.0%, 5.6%] and Monte Carlo algorithm was 0.4% ± 1.5% [−4.9%, 3.7%]. The differences obtained are comparable to that obtained with the ionization chamber and TPS. Conclusion: The developed software is suitable for use in S and S IMRT dose calculation. This application is open and can be downloading under request.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Bayesian Optimization for Anything (BOA): An open-source framework for accessible, user-friendly Bayesian optimization

We introduce Bayesian Optimization for Anything (BOA), a high-level Bayesian Optimization (BO) framework and model wrapping toolkit, which presents a novel approach to simplifying BO, with the goal of making it more accessible and user-friendly, particularly for those with limited expertise in the field. BOA addresses common barriers in implementing BO, focusing on ease of use, reducing the need for deep domain knowledge, and cutting down on extensive coding requirements. A notable feature of BOA is its language-agnostic architecture, which facilitates broader application in various fields and to a wider audience. We showcase BOA's application through three examples: a high-dimensional optimization with parameters of the SWAT+ watershed model, a highly parallelized optimization of this intrinsically non-parallel model, and a multi-objective optimization of the FETCH Tree-Crown Hydrodynamics model. Furthermore, these test cases illustrate BOA's effectiveness in addressing complex optimization challenges in diverse scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Hazma meets HERWIG4DM: precision gamma-ray, neutrino, and positron spectra for light dark matter

Herein we present a new open-source package, Hazma 2, that computes accurate spectra relevant for indirect dark matter searches for photon, neutrino, and positron production from vector-mediated dark matter annihilation and for spin-one dark matter decay. The tool bridges across the regimes of validity of two state of the art codes: Hazma 1, which provides an accurate description below hadronic resonances up to center-of-mass energies around 250 MeV, and Herwig4DM, which is based on vector meson dominance and measured form factors, and accurate well into the few GeV range. The applicability of the combined code extends to approximately 1.5 GeV, above which the number of final state hadrons off of which we individually compute the photon, neutrino, and positron yield grows exceedingly rapidly. We provide example branching ratios, particle spectra and conservative observational constraints from existing gamma-ray data for the well-motivated cases of decaying dark photon dark matter and vector-mediated fermionic dark matter annihilation. Finally, we compare our results to other existing codes at the boundaries of their respective ranges of applicability. Hazma 2 is freely available on GitHub athttps://github.com/LoganAMorrison/Hazma.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Unveiling the microbial realm with VEBA 2.0: a modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic and viral multi-omics from either short- or long-read sequencing

Abstract The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA’s versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible software suite that bridges the gap between genomics and biotechnological solutions.

59 BASIC BIOLOGICAL SCIENCES↗