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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program’s (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States’ largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework’s current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

BeeSwarm: Enabling Parallel Scaling Performance Measurement in Continuous Integration for HPC Applications

Testing is one of the most important steps in software development–it ensures the quality of software. Continuous Integration (CI) is a widely used testing standard that can report software quality to the developer in a timely manner during development progress. Performance, especially scalability, is another key factor for High Performance Computing (HPC) applications. There are many existing profiling and performance tools for HPC applications, but none of these are integrated into CI tools. In this work, we propose BeeSwarm, an HPC container based parallel scaling performance system that can be easily applied to the current CI test environments. BeeSwarm is mainly designed for HPC application developers who need to monitor how their applications can scale on different compute resources. We demonstrate BeeSwarm using a multi-physics HPC application with Travis CI, GitLab CI and GitHub Actions while using ChameleonCloud and Google Compute Engine as the compute backends. Finally, our results show that BeeSwarm can be used for scalability and performance testing of HPC applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Optimization and Portability of a Fusion OpenACC-based FORTRAN HPC Code from NVIDIA to AMD GPUs

NVIDIA has been the main provider of GPU hardware in HPC systems for over a decade. Most applications that benefit from GPUs have thus been developed and optimized for the NVIDIA software stack. Recent exascale HPC systems are, however, introducing GPUs from other vendors, e.g. with the AMD GPU-based OLCF Frontier system just becoming available. AMD GPUs cannot be directly accessed using the NVIDIA software stack, and require a porting effort by the application developers. This paper provides an overview of our experience porting and optimizing the CGYRO code, a widely-used fusion simulation tool based on FORTRAN with OpenACC-based GPU acceleration. While the porting from the NVIDIA compilers was relatively straightforward using the CRAY compilers on the AMD systems, the performance optimization required more fine-tuning. In the optimization effort, we uncovered code sections that had performed well on NVIDIA GPUs, but were unexpectedly slow on AMD GPUs. After AMD-targeted code optimizations, performance on AMD GPUs has increased to meet our expectations. Modest speed improvements were also seen on NVIDIA GPUs, which was an unexpected benefit of this exercise.

Sfiligoi, Igor↗
DOE OSTI2024

Results from a multi-laboratory ocean metaproteomic intercomparison: effects of LC-MS acquisition and data analysis procedures

Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-series Study (BATS) in the North Atlantic Ocean collected by in situ pumps and the autonomous underwater vehicle (AUV) Clio were distributed with a paired metagenome, and one-dimensional (1D) liquid chromatographic data-dependent acquisition mass spectrometry analysis was stipulated. Analysis of mass spectra from seven laboratories through a common bioinformatic pipeline identified a shared set of 1056 proteins from 1395 shared peptide constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R 2 values averaged 0.62±0.11, and a Sørensen similarity analysis of the top 1000 proteins revealed 70 %–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. A bioinformatic intercomparison study, involving 10 laboratories using eight software packages, successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Lessons learned and potential improvements in methods were described. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research, including integration into global-scale ocean surveys and ocean biogeochemical models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Snake River Plain Play Fairway Analysis – Phase 1 Report

The Snake River volcanic province (SRP) overlies a thermal anomaly that extends deep into the mantle; it represents one of the highest heat flow provinces in North America. Our goals for this Phase 1 study are to: (1) adapt the methodology of Play Fairway Analysis for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal play fairway model for the SRP and identify the most promising plays, using software tools that are standard in the petroleum industry. The success of play fairway analysis in geothermal exploration depends critically on defining a systematic methodology that is grounded in theory (as developed within the petroleum industry over the last two decades) and within the geologic and hydrologic framework of real geothermal systems. Our preliminary assessment of the data suggests that important undiscovered geothermal resources may be located in several areas of the SRP, including the western SRP (associated with buried lineaments defined by gravity or magnetic anomalies, and capped by extensive deposits of lacustrine sediment), at lineament intersections in the central SRP (along the Banbury-Hagerman trend NW of Twin Falls, and along the northern margin of the Mt Bennett Hills-Camas Prairie area), and along the margins of the eastern SRP. Additional high temperature resources are likely associated with rhyolite domes and crypto-domes in the eastern SRP, but are masked by shallow groundwater flow leading to low upper crustal heat flow values. These blind resources may be exploitable with existing deep drilling technology. Groundwater modeling planned for later phases of the PFA project will address whether temperatures at viable producing depths are sufficient to support electricity production.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Snake River Plain Play Fairway Analysis - Phase 1 Report

The Snake River volcanic province (SRP) overlies a thermal anomaly that extends deep into the mantle; it represents one of the highest heat flow provinces in North America. Our goals for this Phase 1 study are to: (1) adapt the methodology of Play Fairway Analysis for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal play fairway model for the SRP and identify the most promising plays, using software tools that are standard in the petroleum industry. The success of play fairway analysis in geothermal exploration depends critically on defining a systematic methodology that is grounded in theory (as developed within the petroleum industry over the last two decades) and within the geologic and hydrologic framework of real geothermal systems. Our preliminary assessment of the data suggests that important undiscovered geothermal resources may be located in several areas of the SRP, including the western SRP (associated with buried lineaments defined by gravity or magnetic anomalies, and capped by extensive deposits of lacustrine sediment), at lineament intersections in the central SRP (along the Banbury-Hagerman trend NW of Twin Falls, and along the northern margin of the Mt Bennett Hills-Camas Prairie area), and along the margins of the eastern SRP. Additional high temperature resources are likely associated with rhyolite domes and crypto-domes in the eastern SRP, but are masked by shallow groundwater flow leading to low upper crustal heat flow values. These blind resources may be exploitable with existing deep drilling technology. Groundwater modeling planned for later phases of the PFA project will address whether temperatures at viable producing depths are sufficient to support electricity production.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Grid Stability Awareness System (GSAS) (Final Scientific/Technical Report)

The project team developed a software suite named Grid Stability Awareness System (GSAS) for power system near real-time stability monitoring and analysis based on synchrophasor measurement. The software suite consists of five analytical tools: an oscillation monitoring tool, a voltage stability monitoring tool, a transient instability monitoring tool, an angle difference monitoring tool, and an event detection tool. These tools have been integrated into one framework to provide power grid operators with both real-time or near real-time stability status of a power grid and historical information about system stability status. These tools are being considered for real-time use in the operation environment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Tensor networks for High Energy Physics: contribution to Snowmass 2021

Tensor network methods are becoming increasingly important for high-energy physics, condensed matter physics and quantum information science (QIS). We discuss the impact of tensor network methods on lattice field theory, quantum gravity and QIS in the context of High Energy Physics (HEP). These tools will target calculations for strongly interacting systems that are made difficult by sign problems when conventional Monte Carlo and other importance sampling methods are used. Further development of methods and software will be needed to make a significant impact in HEP. We discuss the roadmap to perform quantum chromodynamics (QCD) related calculations in the coming years. The research is labor intensive and requires state of the art computational science and computer science input for its development and validation. We briefly discuss the overlap with other science domains and industry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

In Situ X-ray Radiography and Computational Modeling to Predict Grain Morphology in $\beta$-Titanium during Simulated Additive Manufacturing

The continued development of metal additive manufacturing (AM) has expanded the engineering metallic alloys for which these processes may be applied, including beta-titanium alloys with desirable strength-to-density ratios. To understand the response of beta-titanium alloys to AM processing, solidification and microstructure evolution needs to be investigated. In particular, thermal gradients (Gs) and solidification velocities (Vs) experienced during AM are needed to link processing to microstructure development, including the columnar-to-equiaxed transition (CET). In this work, in situ synchrotron X-ray radiography of the beta-titanium alloy Ti-10V-2Fe-3Al (wt.%) (Ti-1023) during simulated laser-powder bed fusion (L-PBF) was performed at the Advanced Photon Source at Argonne National Laboratory, allowing for direct determination of Vs. Two different computational modeling tools, SYSWELD and FLOW-3D, were utilized to investigate the solidification conditions of spot and raster melt scenarios. The predicted Vs obtained from both pieces of computational software exhibited good agreement with those obtained from in situ synchrotron X-ray radiography measurements. The model that accounted for fluid flow also showed the ability to predict trends unobservable in the in situ synchrotron X-ray radiography, but are known to occur during rapid solidification. A CET model for Ti-1023 was also developed using the Kurz–Giovanola–Trivedi model, which allowed modeled Gs and Vs to be compared in the context of predicted grain morphologies. Both pieces of software were in agreement for morphology predictions of spot-melts, but drastically differed for raster predictions. The discrepancy is attributable to the difference in accounting for fluid flow, resulting in magnitude-different values of Gs for similar Vs.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Development and Assessment of CTF for Pin-resolved BWR Modeling

CTF is the modernized and improved version of the subchannel code, COBRA-TF. It has been adopted by the Consortium for Advanced Simulation for Light Water Reactors (CASL) for subchannel analysis applications and thermal hydraulic feedback calculations in the Virtual Environment for Reactor Applications Core Simulator (VERA-CS). CTF is now jointly developed by Oak Ridge National Laboratory and North Carolina State University. Until now, CTF has been used for pressurized water reactor modeling and simulation in CASL, but in the future it will be extended to boiling water reactor designs. This required development activities to integrate the code into the VERA-CS workflow and to make it more ecient for full-core, pin resolved simulations. Additionally, there is a significant emphasis on producing high quality tools that follow a regimented software quality assurance plan in CASL. Part of this plan involves performing validation and verification assessments on the code that are easily repeatable and tied to specific code versions. This work has resulted in the CTF validation and verification matrix being expanded to include several two-phase flow experiments, including the General Electric 3 3 facility and the BWR Full-Size Fine Mesh Bundle Tests (BFBT). Comparisons with both experimental databases is reasonable, but the BFBT analysis reveals a tendency of CTF to overpredict void, especially in the slug flow regime. The execution of these tests is fully automated, analysis is documented in the CTF Validation and Verification manual, and the tests have become part of CASL continuous regression testing system. This paper will summarize these recent developments and some of the two-phase assessments that have been performed on CTF.

Salko, Robert K↗
DOE OSTI2022

Tsdat: An Open-Source Data Standardization Framework for Marine Energy and Beyond

Many organizations are tasked with the collection and processing of large quantities of data from various measurement devices. Data reported from these sources are often not interoperable with datasets and software used by analysts and other organizations in the same domain, introducing barriers for collaboration on large-scale projects. This poses a particular problem for cross-device comparisons and machine learning applications, which rely on large quantities of data from multiple sources. To address these challenges, the open-source Time-Series Data Pipelines (Tsdat) Python framework was developed by Pacific Northwest National Laboratory, with strategic guidance and direction provided by the National Renewable Energy Laboratory and Sandia National Laboratories to facilitate collaboration and accelerate advancements in the marine energy domain through the development of an open-source ecosystem of tools. This paper will describe the Tsdat framework and the data standards within which it operates. A beta version of Tsdat has been released and is being used by several projects in marine energy, wind energy, and building energy systems.

big data↗
DOE OSTI2016

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites. Topical Report

This project aimed to integrate, optimize, and validate the fiber orientation and length distribution models previously developed and implemented in the Autodesk® Simulation Moldflow® Insight (ASMI) software package for injection-molded long-carbon-fiber (LCF) thermoplastic composite structures. The project was organized into two phases. Phase 1 demonstrated the ability of the advanced ASMI package to predict fiber orientation and length distributions in LCF/polypropylene (PP) and LCF/polyamide-6, 6 (PA66) plaques within 15% of experimental results. Phase 2 validated the advanced ASMI package by predicting fiber orientation and length distributions within 15% of experimental results for a complex three-dimensional (3D) Toyota automotive part injection-molded from LCF/PP and LCF/PA66 materials. Work under Phase 2 also included estimate of weight savings and cost impacts for a vehicle system using ASMI and structural analyses of the complex part. The present report summarizes the completion of Phases 1 and 2 work activities and accomplishments achieved by the team comprising Pacific Northwest National Laboratory (PNNL); Purdue University (Purdue); Virginia Polytechnic Institute and State University (Virginia Tech); Autodesk, Inc. (Autodesk); PlastiComp, Inc. (PlastiComp); Toyota Research Institute North America (Toyota); Magna Exteriors and Interiors Corp. (Magna); and University of Illinois. Figure 1 illustrates the technical approach adopted in this project that progressed from compounding LCF/PP and LCF/PA66 materials, to process model improvement and implementation, to molding and modeling LCF/PP and LCF/PA66 plaques. The lessons learned from the plaque study and the successful validation of improved process models for fiber orientation and length distributions for these plaques enabled the project to go to Phase 2 to mold, model, and optimize the 3D complex part.

42 ENGINEERING↗
DOE OSTI2024

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

pnnl/Temwizard

TEMWizard is used to visualize results from Atomap, an open-source software tool for determining the position and other features of atomic columns in transmission electron microscopy images.

Oostrom, Marjolein↗
DOE OSTI2017

NBIC Biofeeds: A Digital Tool for Open Source Biosurveillance across Federal Agencies

The National Biosurveillance Integration Center (NBIC) is developing a scalable, flexible open source data collection, analysis, and dissemination tool to support biosurveillance operations by the U.S. Department of Homeland Security (DHS) and its federal interagency partners. The NBIC integrates, analyzes, and distributes key information about health and disease events to help ensure the nation’s responses are well-informed, save lives, and minimize economic impact. NBIC serves as a bridge between Federal, State, Local, Territorial, and Tribal entities to conduct biosurveillance across human, animal, plant, and environmental domains. The integration of information enables early warning and shared situational awareness of biological events to inform critical decisions directing response and recovery efforts. To meet its mission objectives, NBIC utilizes a variety of datasets, including open source information, to provide comprehensive coverage of biological events occurring across the globe. NBIC Biofeeds is a digital tool designed to improve the efficiency of reviewing and analyzing large volumes of open source reporting by biosurveillance analysts on a daily basis; moreover, the system provides a mechanism to disseminate tailored feeds allowing NBIC to better meet the specific information needs of individual, interagency partners. The tool is currently under development by the Department of Energy (DOE), Pacific Northwest National Laboratory (PNNL)and it is in a testing and evaluation phase supported by NBIC biosurveillance subject matter experts. Integration with the Defense Threat Reduction Agency (DTRA), Biosurveillance Ecosystem(BSVE) is also underway. NBIC Biofeeds Version 1 is expected to be fully operational in Fiscal Year 2017. The PNNL is applying agile methodology to streamline the build of NBIC Biofeeds to specifications required for operational use by NBIC and its federal interagency partners. Biosurveillance, analytics, and system engineering subject matter experts provide guidance on the implementation of features in the tool to ensure functionality aligns with operational workflows and production support. PNNL is leveraging software from a previous government effort to repurpose the technology to meet NBIC needs. NBIC Biofeeds incorporates the open source, document-orientated MongoDB database to capture user- and system-generated metadata on hundreds of thousands of records, in part, to establish baselines to aid prospective and retrospective analysis on emerging biological events. NBIC Biofeeds integrates a biosurveillance taxonomy (uniquely developed by NBIC),which includes input from interagency partners to recognize critical characteristics of a biological event. In NBIC Biofeeds Version1, metadata capture of reported events is done manually by NBIC analysts; however, moving forward in Version 2, the tool will be further automated to flag significant reporting on biological events with a human remaining in the loop to confirm the validity of the system-generated tags. To serve as a one-stop tool for open source biosurveillance, NBIC Biofeeds automatically harvests information from thousands of websites, utilizing third party aggregators, paid subscriptions to data feeds, and scraping of high priority sources. Users can develop desired queries for automatic updating, leverage a unique review and curation mechanism, and further analyze data from topical, geographic, and temporal visualization features in the tool. To meet NBIC’s information sharing needs, the tool allows for design of tailored RSS feeds and electronic message-based delivery of analysis on biological events, intended for recipients in the government with unique missions around human, animal, plant, and environmental health. Through current testing and evaluation – underway by biosurveillance subject matter experts – NBIC Biofeeds is demonstrating value in supporting open source biosurveillance by the Center for more rapid recognition and sharing of key event characteristics. Centralizing access and analysis of this data set into a single system is increasing the efficiency of daily, global biosurveillance, while enhancing the value of information identified through use of the querying, curation, and production support features in the tool.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

The first pilot project of the consortium for top-down proteomics: A status report

Pilot Project #1—the identification and characterization of human histone H4 proteoforms by top-down MS—is the first project launched by the Consortium for Top-Down Proteomics (CTDP) to refine and validate top-down MS. Within the initial results from seven participating laboratories, all reported the probability-based identification of human histone H4 (UniProt accession P62805) with expectation values ranging from 10-13 to 10-105. Regarding characterization, a total of 74 proteoforms were reported, with 21 done so unambiguously; one new PTM, K79ac, was identified. Inter-laboratory comparison reveals aspects of the results that are consistent, such as the localization of individual PTMs and binary combinations, while other aspects are more variable, such as the accurate characterization of low-abundance proteoforms harboring >2 PTMs. An open-access tool and discussion of proteoform scoring are included, along with a description of general challenges that lie ahead including improved proteoform separations prior to mass spectrometric analysis, better instrumentation performance, and software development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A Generic Communication Protocol for Remote Laboratories: an Implementation on e-lab

The remote laboratories at IST (Instituto Superior Tecnico), e-lab, serve as a valuable tool for education and training based on remote control technologies. Due to the high number and increase of remotely operated experiments a generic protocol was developed to perform the communication between the software driver and the respective experimental setup in an easier and more unified way. The training in these fields of students and personnel can take advantage of such infrastructure with the purpose of deploying new experiments in a faster way. More than 10 experiments using the generic protocol are available on-line in a 24 x 7 way. (authors)

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

F3D Image Processing and Analysis for Many - and Multi-core Platforms

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.

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