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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MOSCATO Development and Integration in Fiscal Year 2022

During FY21, we conducted ongoing development work for the MOSCATO (Molten Salt Chemistry and Transport) solver. The code development work primarily consisted of transitioning capabilities from the original version of the solver, which was written in OpenFOAM, into Nek5000. In doing so, a fast, highly parallelizable solver was created that is capable of complex chemistry and corrosion simulations for engineering-scale molten salt systems. The Nek5000 version of MOSCATO is now fully featured and capable of higher-fidelity simulations than were previously possible. Demonstration cases including a thermal convection loop have been simulated to test these new capabilities. We built upon the work for FY22 and improved the code from several different perspectives. First, we improved the user interface by adding a new component to the official Nek5000 input file (.par). This new part contains documents parameters like, salt properties (density, viscosity, Cp, thermal conductivity), diffusion coefficients, standard potential, etc. Second, we built a conversion script to extract salt properties from the MSTDB-TP salt database and write to MOSCATO input file. Third, we migrated the code to NekRS, which is the GPU branch of Nek5000 and suitable for next generation supercomputers. Verification and Validation (V&V) work was also continued in FY22. Two tasks were performed. The first V&V task involved the validation of the Poisson-Nernst-Planck equation solver and Butler-Volmer electrode kinetics, by comparing with numerical and experimental data about thermoelectric cells. The second task involved the comparisons to corrosion results from a thermal convection loop run during the MSRE era. Satisfactory agreement was obtained from both tasks.

Yuan, Haomin↗
DOE OSTI2024

Development of R&D GREET 2023 Rev1 to Estimate Greenhouse Gas Emissions of Sustainable Aviation Fuels for 40B Provision of the Inflation Reduction Act

The federal Interagency Working Group on sustainable aviation fuels (SAF) tasked Argonne National Laboratory with developing a modified version of the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model based on R&D GREET 2023. The goal of the new GREET version is to simulate the life-cycle greenhouse gas (GHG) emissions associated with seven sustainable aviation fuel (SAF) pathways for consideration under the 40B Provision of the Inflation Reduction Act – Sustainable aviation fuel credit. The Provision includes a new GHG-based tax credit to incentivize SAF production and reduce the costs of these fuels.

02 PETROLEUM↗
DOE OSTI2014

Biokinetic data and models for occupational intake of lanthanoids

The lanthanoid (or lanthanide) chemical elements comprise fifteen elements with atomic numbers 57 (lanthanum) through 71 (lutetium). This paper reviews data related to the biological behavior of these elements in the human body and proposes biokinetic models for application to occupational intake of radio-lanthanoids. Generic (element-independent) absorption rates from the respiratory and alimentary tracts to blood are proposed. The proposed systemic models are largely generic but include some element-specific parameter values to reflect regular changes with ionic radius in certain aspects of the behavior of the lanthanoids. This work was performed within the internal dosimetry task group (INDOS) of Committee 2 of the International Commission on Radiological Protection (ICRP).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Novel Multidimensional Tracers for Geothermal Inter-Well Diagnostics

This is the Final Report of the three-year project “Novel Multidimensional Tracers for Geothermal Inter-Well Diagnostics” (DE-EE00003032, April 1, 2010 – March 30, 2013), in which we present our major accomplishments with detailed descriptions of our experimental and theoretical efforts. Upon the successful conduction of this project, we have followed our proposed breakdown work structure completing most of the technical tasks. Finally, we have developed and demonstrated the matrix of smart geothermal tracers and the corresponding interpretation tools together with the novel pre-concentration technique – the Hollow Fiber Liquid-Liquid Micro-Extraction (HFLLME), which present superior performance in terms of the ultralow detection limits (up to 10-12g/mL with signal-to-noise ratio of 2); high workable temperature up to 300°C; and the significant enhancement in the characterization of subsurface environment. We have developed in- depth mechanistic understandings on the complicated chemistry involved in the tracer- matrix interaction as well as developed the unique yet effective experimental protocols (screening methodologies, analytical tools, pre-concentration and derivatization techniques) for achieving a highly efficient yet economically feasible and environmentally friendly geothermal tracer system. The most important findings have been reported to DOE in this Final Report and our 12 Quarterly Reports.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction

Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While it is known that protein structure directly impacts protein function, many functional prediction tasks use only protein sequence. In this work, we isolate protein structure to make functional annotations for proteins in the Protein Data Bank in order to study the expressiveness of different structure-based prediction schemes. We present PersGNN - an end-to-end trainable deep learning model that combines graph representation learning with topological data analysis to capture a complex set of both local and global structural features. While variations of these techniques have been successfully applied to proteins before, we demonstrate that our hybridized approach, PersGNN, outperforms either method on its own as well as a baseline neural network that learns from the same information. PersGNN achieves a 9.3% boost in area under the precision recall curve (AUPR) compared to the best individual model, as well as high F1 scores across different gene ontology categories, indicating the transferability of this approach.

Swenson, Nicolas↗
DOE OSTI2013

The Full Scale Seal Experiment - A Seal Industrial Prototype for Cigeo - 13106

The Full Scale Seal (FSS) Experiment is one of various experiments implemented by Andra, within the frame of the Cigeo (the French Deep Geological Repository) Project development, to demonstrate the technical construction feasibility and performance of seals to be constructed, at time of Repository components (shafts, ramps, drifts, disposal vaults) progressive closure. FSS is built inside a drift model fabricated on surface for the purpose. Prior to the scale 1:1 seal construction test, various design tasks are scheduled. They include the engineering work on the drift model to make it fit with the experimental needs, on the various work sequences anticipated for the swelling clay core emplacement and the concrete containment plugs construction, on the specialized handling tools (and installation equipment) manufactured and delivered for the purpose, and of course on the various swelling clay materials and low pH (below 11) concrete formulations developed for the application. The engineering of the 'seal-as-built' commissioning means (tools and methodology) must also be dealt with. The FSS construction experiment is a technological demonstrator, thus it is not focused on the phenomenological survey (and by consequence, on the performance and behaviour forecast). As such, no hydration (forced or natural) is planned. However, the FSS implementation (in particular via the construction and commissioning activities carried out) is a key milestone in view of comforting phenomenological extrapolation in time and scale. The FSS experiment also allows for qualifying the commissioning methods of a real sealing system in the Repository, as built, at time of industrial operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Affinity-aware checkpoint restart

Current checkpointing techniques employed to overcome faults for HPC applications result in inferior application performance after restart from a checkpoint for a number of applications. This is due to a lack of page and core affinity awareness of the checkpoint/restart (C/R) mechanism, i.e., application tasks originally pinned to cores may be restarted on different cores, and in case of non-uniform memory architectures (NUMA), quite common today, memory pages associated with tasks on a NUMA node may be associated with a different NUMA node after restart. Here, this work contributes a novel design technique for C/R mechanisms to preserve task-to-core maps and NUMA node specific page affinities across restarts. Experimental results with BLCR, a C/R mechanism, enhanced with affinity awareness demonstrate significant performance benefits of 37%-73% for the NAS Parallel Benchmark codes and 6-12% for NAMD with negligible overheads instead of up to nearly four times longer an execution times without affinity-aware restarts on 16 cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dynamic thermal behavior of polycrystalline LaB 6 hollow cathodes

Lanthanum hexaboride (LaB6) hollow cathodes have demonstrated a capability for long life operation, which is critical to many space exploration missions. Thermal characterization of LaB6 hollow cathodes has revealed lower than expected electron emitter temperatures when the cathode reaches a steady state. This phenomenon is observed at discharge currents ranging from 5 to 35 A and xenon mass flow rates of 5–25 SCCM in cathodes with three different orifice diameters. Thus, the currently accepted value of the work function for polycrystalline LaB 6 , 2.67 eV, does not describe well the emission characteristics of LaB6 hollow cathodes operating with internal gas discharges at a steady state. We use empirically measured temperatures combined with a model of the hollow cathode emitter and xenon discharge to estimate the value of the work function, yielding a value ranging from 2.1 to 2.44 eV. This lower work function value implies that LaB6 hollow cathodes are expected to have even longer lifetimes than previously anticipated, further establishing them as a more suited alternative to other conventional cathode technologies for the task of long duration travel. Direct measurements of the work function as a function of depth on a hollow cathode emitter using x-ray photoelectron spectroscopy and ion beam milling indicate that the work function decreases with depth. We postulate several mechanisms that could explain the observed work function enhancement. Altogether, our results have important implications to the design, study approach, and operation of LaB 6 cathodes and potentially other cathodes with hollow configuration. Finally, our work opens the question of why the work function is reduced upon interaction with Xe plasma.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

FY2011 Status Report on SN2ND Neutronics Solver Development

A change in focus of NEAMS to a broader set of reactor types necessitated significant effort being diverted away from SN2ND development in FY2011. Nevertheless, significant gains were made with regard to building the new preconditioner and meeting the objectives of 1) parallelism in energy, 2) a spatial multigrid concept, 3) using SN vector spaces to accommodate the adjoint and time dependent functionalities needed for NEAMS work, and 4) complete manuals and documentation. While the desired goal of an exportable SN2ND solver usable within the NEAMS community for neutronics analysis was not completed, we can be confident that this year’s work puts the SN2ND solver well on its way to meeting that objective. It is important to note that SN2ND is just as capable as any other methodology for doing thermal reactor analysis, but the motivation to execute on smaller scale machines has initiated focused development on simplified treatments such as those proposed in the MOCARV tool. All of the cited coding tasks were completed but not all are fully working (i.e. debugged). The spatial multigrid technique was by far the most time consuming part of the SN2ND development process. It required multiple new data structure concepts along with identifying the necessary changes in the vectors and their associated functions. Combining the spatial multigrid as part of a GMRES preconditioner operating on the full vector space, necessary for parallelization in energy, increased the complexity of that development. Research into spatial multigrid techniques for unstructured meshes, void treatments, and code optimization and acceleration are key development needs for SN2ND. Similar to previous years, a considerable amount of effort was spent on validation work. Again we focused on fast reactor problems such as ZPR experiments and the MONJU reactor in Japan. Conventional drawer homogenized models and partially heterogeneous models were used on the ZPR calculations. The drawer homogenized models produced excellent results for both eigenvalue and foil measurements on four loadings of ZPR-6/7. The partially heterogeneous models of ZPR-6/7 also produced good results, but additional work is necessary to generate consistent effective cross section data. Calculations for MONJU were homogeneous and also gave excellent results. Finally, mock-up heterogeneous calculations were setup and attempted to scope out the performance limitations of SN2ND on whole core heterogeneous calculations. Specifically, heterogeneous models of a PWR, a VHTR, and the MONJU reactor were created using anywhere from 2 group to 33 group cross section data. Meshes with greater than 100,000,000 vertices are necessary for accuracy and a specific non-scaling memory issue in PETSc restricted the SN2ND modeling (VHTR and PWR could not be solved). All of the calculations performed this year indicate that significant computational resources beyond those available today are required to obtain a high fidelity solution possible with SN2ND. The future goals for SN2ND are to get the new version fully working, reliable in execution, and to have comparable performance to the old solver such that it can be released within the NEAMS community. After its export to RSICC, we will rely upon further preconditioner research to be done in collaboration with university partners and through the exascale hub activities. Some of that research will focus on making SN2ND applicable to thermal reactor problems, spatial multigrid, and void treatments.

Smith, M. A.↗
DOE OSTI2021

Deliverable D12 – Distributed Wind Data Catalog Development Guide and Instruction Manual

Pacific Northwest National Laboratory and Technical University of Denmark completed this deliverable as part of Work Package 2: Data Information Catalog for Distributed Wind Research (WP2) for the International Energy Agency Wind Technology Collaboration Programme Task 41: Enabling Wind to Contribute to a Distributed Energy Future (IEA Wind Task 41). As the final deliverable for WP2, Deliverable D12 includes a data instruction guide for the IEA Wind Task 41 distributed wind data catalog. As such, this document includes: a step-by-step explanation of how the IEA Wind Task 41 data catalog was created, how it was populated, and how to use it; future options for the IEA Wind Task 41 data catalog, and a summary with recommendations for future work.

17 WIND ENERGY↗
DOE OSTI2023

Real Time and Forecasted DLR: Use Cases

This document contains two use cases for the utilization of dynamic line ratings in operational practices. These use cases were developed in support of the Transmission Optimization and Grid Enhancing Technology (TOGETS) task force aimed at facilitating the deployment of dynamic line rating and power flow technologies across the United States. The project included a demonstration of the technology on the Idaho National Laboratory system. The procurement documents, tests scripts, and field-validated results from multiple vendors will be published to improve industry’s familiarity with the products. Because of the urgency in performing this work and INL’s unique test setup, the Task Force identified a need for additional public information on the information exchanges required for operationalizing DLR (i.e. integrating DLR’s within actual system operations). As such, this use case document and an accompanying interoperability profile have been developed with input from the Task Force and various vendors whose systems would ultimately support the functionality described. The use case and interoperability profile support two distinct functionalities with different purposes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

CLARIFYING THE NEXUS BETWEEN LIFE CYCLE ASSESSMENT AND CIRCULARITY INDICATORS: A SETAC/ACLCA INTEREST GROUP

Purpose Improving the circularity of resources is important to the sustainability of consumer goods. Current research has indicated that circularity practices and circular economy (CE) methods do not always reduce environmental impacts. The aim of this research is to investigate the adoption of the life cycle assessment (LCA) methodology to improve the environmental impacts of circularity practices. Methods As part of the Society for Environmental Toxicology And Chemistry (SETAC) forum, an interest group (IG) on Circularity and LCA was formed in partnership with the American Center for Life Cycle Assessment (ACLCA) to tackle methodological and technical issues related to circularity in LCA. The IG’s research approach is summarized in four key steps: defining goals and objectives, literature review and gap analysis, ideation, and experimentation. The twelve active persons within this IG meet monthly and have been divided into four sub-working groups (sub-WGs) so that complementary tasks can be completed concurrently in an effective manner. Each sub-WG meets monthly and reports back to the main group for collaboration and brainstorming to meet the research objectives. Results and discussion First, the sub-WG #1, focusing on the “pool of circularity and LCA-based indicators”, analyzed the complementarity between two of the most used circularity indicators and LCA. Second, the sub-WG #2, working on the “evaluation of CE loops performance through LCA”, built a mind map of pain points that reflect the challenges that the LCA practitioners face when combining LCA with CE approaches. Third, the sub-WG #3, dealing with the “trade-offs between circularity and sustainability”, highlighted key alignments and/or conflicts between circularity and sustainability performance depending on the scope, product, industry, or system of analysis. Fourth, the sub-WG #4, focusing on “business and industrial cases”, plans to leverage the knowledge base developed within this IG to develop use cases documenting the benefits and challenges associated with CE-related loops modeling in LCA. Conclusions The first findings of this SETAC/ACLCA IG provide a state-of-the-art overview of the synergists of LCA methodology and the CE measurement frameworks reported in the literature. To move forward and capitalize on the first findings, one valuable point will be to discuss and provide concrete solutions to the pain points that emerged when considering circularity in LCA. Eventually, the knowledge base and resources created within this IG ultimately aim to support the proper application of LCA for practitioners in CE contexts, and could provide relevant inputs for the ISO Technical Committee ISO/TC 323 working on the upcoming standard for the measurement of CE performance.

Life cycle assessment, circular economy, circulari↗
DOE OSTI2020

Chemical Modeling of the Capture of Radioiodine Species

Iodine is a common fission product resulting from the transmutation of uranium fuel in nuclear power reactors. The short-lived radioactive isotope, 131 I, with a half-life of around eight days, would be a particular health concern if released into the environment. Capture materials, such as activated carbon, are used routinely in nuclear power plants and medical isotope production facilities to remove this hazard during normal operations to reduce emissions to acceptable levels. Iodine, unlike other common fission products such as noble gases, is challenging because of the wide range of molecular forms and oxidation states (from +VII in IF 7 to -I in iodide) that it displays, which can interconvert both in the gas phase and in the solution phase for example. The work in this project is focused on three computational tasks. In the first, we consider the binding of iodine-containing molecules of varying oxidation states to the major component of activated carbon – pristine graphene-like sheets. The second task focused on molecular binding and possible chemical transformations resulting from the reaction of molecular iodine with chemical functional groups on the edge of the graphene sheets or surface defects in the sheet itself. The final task was associated with radiolytic breakdown of 131 I to 131 Xe in iodine containing molecules and investigated the resulting molecular fragmentation process both in the gas phase and on the graphene-like surface. For each of the tasks, the intent was to learn about the thermodynamics and kinetics of the chemical transformations and use the calculations to provide parameters for input into kinetic models describing these processes for interpretation of experimental data in future work.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Support CEED-enabled ECP applications in their preparation for Aurora/Frontier

The goal of this milestone was to help CEED-enabled ECP applications (particularly ExaSMR, MARBL, ExaAM, ExaWind and E3SM) in their preparations for the Aurora and Frontier architectures. This work included collaboration with ECP vendors and porting and optimization of CEED’s benchmarks and miniapps to early access hardware. As part of this milestone, we also made the best bake-off problems and bake-off kernel implementation from Nek, MFEM, libParanumal and the external community available in the latest libCEED release, libCEED-0.7. During the milestone period we also organized, in virtual form, the fourth CEED Annual meeting (CEED4AM) which included representatives from ECP applications, vendors and software technology projects. The specific tasks addressed in this milestone were to: (1) Work with vendors to port and run CEED benchmarks on early access systems for Aurora and Frontier; (2) Make the best BP/BK implementations from Nek, MFEM, libParanumal and external community available in libCEED; (3) Organize the next CEED Annual meeting (CEED4AM); and (4) Optimize CEED applications and miniapps for Aurora and Frontier architectures. The artifacts delivered include the next libCEED release, libCEED-0.7, and a number of developments integrated within applications to improve their GPU performance and capabilities. See the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed for more details.

97 MATHEMATICS AND COMPUTING↗