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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

UNESE Data Analysis - Disko Elm Gas Transport Characteristics (NA-22 Quarterly Report)

Two research papers describing gas transport studies in subsurface containment environments appropriate for underground nuclear explosions were revised and accepted for publication in the peer-reviewed journals, Nature – Scientific Reports and Journal of Geophysical Research. The Nature – Scientific Reports paper is a primary deliverable and describes the gas-transport experiment performed in P Tunnel (NNSS) and 1) subsequent analysis of field data as part of the UNESE program. The Journal of Geophysical Research paper describes an experiment, supported mainly by DARPA and led by researchers at Weston Geophysical and New Mexico Tech., with 2) analyses supported by this project to evaluate the ability of SF6 gas tracer to track xenon gas migration under conditions related to a previous UNESE experiment. Two new tasks consider 3) evaluation of detonation heating and multiphase flow on arrival of xenon at the surface and 4) the impact of surface or Langmuir adsorption of gases being transported through pores and along fractures.

58 GEOSCIENCES↗
DOE OSTI2024

Process Intensification for Nanostructure Aluminum Extrusions

A new technology called Shear Assisted Processing and Extrusion (ShAPE™), pioneered at the Pacific Northwest National Laboratory (PNNL), has the potential to revolutionize the US extrusion industry. Maturation of the ShAPE™ process would create a new cross cutting US manufacturing technology that advances three key the objectives within AMO; namely, nanomaterials processing, process intensification, and materials for extreme and harsh environments. PNNL and SCM Metals Products, Inc. (SCM), a division of Kymera International, will collaborate to mature the ShAPE™ extrusion process beyond TRL 3 to increase the likelihood of its adoption by industry. PNNL’s custom (one-of-a-kind in the world) ShAPE™ machine will be used to extrude round rods of high strength aluminum alloy feedstock powder provided by SCM. As proof-of-concept, PNNL has previously extruded 5 mm diameter rods with SCM aluminum alloy powder AL-12.4TM. This project aims to scale up the process to a diameter of 25 mm while retaining the excellent mechanical properties achieved for the 5 mm diameter rods. The degree of process intensification with ShAPE™ will also be estimated. The primary objectives of this project are as follows. 1) Fabricate 25 mm diameter nanostructured extrusions in bulk, directly from AL-12.4TM aluminum alloy powder without the need for canning, degassing, compaction, and other intermediate steps typical of powder metallurgy extrusion. 2) Achieve a microstructure with an ultrafine grained (UFG <1 µm) aluminum matrix having refined and homogenously distributed nanoscale second phases. 3) Show that the ram force can be significantly reduced compared to conventional powder metallurgy extrusion of the same material and estimate the extent of process intensification that may be possible with ShAPE™. 4) Demonstrate improved high-temperature mechanical properties compared to conventional extrusion of the same material. The following tasks will be undertaken to achieve these objectives. PNNL will develop the die set and process parameters necessary to fabricate Al-12.4TM extrusions with a 25 mm diameter. Microstructural analysis will be performed by PNNL while mechanical testing will be conducted by SCM. With information learned from the process development and characterization, PNNL will perform an estimate of the degree of process intensification that may be possible with ShAPE™.

42 ENGINEERING↗
DOE OSTI2023

Design and License Application Development for TRISO-X (Final Scientific Technical Report)

This is the final progress report submitted by X-energy, LLC (XE) to the Department of Energy in support of cooperative agreement DE-NE0008745. This report provides a high-level summary of the work performed during the entire period of performance, running from August 24, 2018 – August 22, 2022. This span of time covers the original 3-year award and a one year no-cost extension. There were five tasks within this project: (1) project management, (2) systems engineering and studies, (3) TRISO-X Facility design, (4) facility license application development, and (5) support to application review. Detailed reporting during execution of the project was provided by a total of 16 quarterly reports, voluntary monthly update presentations, and annual summary presentations. Technical work products include 103 X-energy technical reports, 38 subcontractor (Centrus technical reports), 75 Nuclear Criticality Safety Evaluations/Calculation reports, and 272 miscellaneous design documents (e.g., Engineering Service Orders, Engineering Component Specifications, Procedures, Guidelines/Policies, Design and Interface Requirements documents, and Drawings). All 29 of the X Energy milestones/deliverables were met early or on time and are archived in the DOE Office of Nuclear Energy’s Program Information Control System: Nuclear Energy under Fiscal Year 2018, Work Breakdown Structure F.OA – Industry FOA FY 2018 Awards, F.03 – X-Energy TRISO-X Project. All other work products are available to DOE upon request.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Models to Incorporate Reaction Mechanisms into DG-OSPREY: Fixed-Bed Simulations for Organic Iodides Capture Using Ag 0 Z

As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Illinois Basin Regional DAC Hub TA-1: Feasibility (Phase-0) (Final Scientific/Technical Report)

The overall objective of this project was to complete a feasibility study for a Regional Direct Air Capture (DAC) Hub that encompasses Illinois, Indiana, and Kentucky. The geographic construct of this hub was based on the Illinois Basin – a geological area where at least seven (7) geological storage studies were conducted. The Hub was designed to assure a capacity to capture, store, and utilize at least 1,000,000 metric tons (tonnes) of CO2 from the atmosphere annually 1 metric tonnes per annum (MTA), starting from an initial capacity of 200,000 tonnes of CO2 per annum (KTA). The Hub also included:(1) clean energy providers to supply renewable energy to the DAC units; (2) geological storage facilities to inject and sequestrate the captured CO2; (3) CO2 utilization facilities that would uptake the captured CO2 and convert it into products; and (4) small business organizations that would assist in workforce development efforts for the region. This closeout report consolidates the tasks undertaken and accomplished as deliverables for the project. The project team had successfully completed all required tasks of phase 0a, confirming that the project is feasible based on the preliminary conceptual designs and operational requirements of the DAC systems. Of particular interest, the hub ownership structure was identified and was implemented in follow on projects that would transition the hub infrastructure to a build/operate phase.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fire, dust, air and water: Improving aerosol biogeochemistry interactions in ACME. Final report

Aerosol-biogeochemistry interactions will have important consequences for human health, ecosystem services, and climate feedbacks over the next several decades. In this proposal we seek to link how human activities on land, including direct industrial emissions and landscape fires, impact the atmosphere and the biogeochemistry of the ocean and land. Our overall goal was to complement existing work at DOE labs to improve the capability and performance of the E3SM model in short-term, high-resolution projections of climate. Projections of ocean uptake of anthropogenic carbon are highly dependent on the details of the ocean physical and biogeochemistry parameterizations. Potentially equally important are the estimates of increases in iron and soluble nitrogen deposition in aerosols to the open ocean, but there are substantial uncertainties in these feedbacks. The E3SM land model simulates natural and anthropogenic fires, but improvement is needed to more accurately simulate fire responses to climate variability as well as fire contributions to terrestrial climate feedbacks. This proposal addressed four of the six priorities within the ACME/E3SM call by improving the representation of fire, industrial combustion sources, and desert dust and adding iron and soluble iron to the atmospheric chemistry (1). Our work focused on improving ocean biogeochemistry and the response of the oceans to anthropogenic atmospheric iron and nitrogen (3). We also improved the representation of land disturbance on fires and fire mediated carbon cycle feedbacks in the land model (4). Finally we had planned to couple the land, atmosphere and ocean biogeochemical systems (6) and explore how this coupling changes the feedbacks in the climate system. Our work under this proposal was separated into the following 5 tasks: i) improve representation of fire dynamics in both boreal and tropical ecosystems, ii) improve estimates of industrial emissions of iron and phosphorus, iii) improve representation of atmospheric iron, phosphorus and nitrogen transport, chemistry and deposition, iv) improve representation of iron, phosphorus and nitrogen deposition impacts on ocean biogeochemistry, and v) couple emissions into atmosphere, to deposition onto land and ocean biogeochemistry. For all 5 tasks, we conducted offline experiments of the historical period to enable comparison with available aerosol and land surface observations. We had planned to conduct fully coupled simulations, however, these will be conducted as part of the coupling in version 3 and 4 of the E3SM model, and thus have not been completed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

TrustDER: Trusted, Private and Scalable Coordination of Distributed Energy Resources

In this project, the Stanford and SLAC Teams have developed a Trusted, Private and Scalable platform for coordinating Coordination of Distributed Energy Resources (TrustDER). This is a layered system that ensures private, trusted and scalable coordination and monitoring of DERs. It accommodates a variety of resources, such as solar generation, gensets and loads, with a particular focus on battery systems-based resources, as they are a transformational technology experiencing fast growth in adoption by large critical facilities. The platform can be used as standalone or added to existing aggregation systems to enable trust, privacy and resilience. TrustDER consists of layers that address each of the shortcomings of the existing state of the art. Each layer in the platform can operate independently but provides information to the layers above it to enable a novel form of overall coordination architecture. The project consists of several tasks, with each task dedicated to the design of each layer. Task 2 Resource Virtualization defined a software abstraction layer for distributed energy resources (DERs). The goal of this abstraction was to simplify the implementation of algorithms utilizing cooperation of DERs resources in a variety of use cases. Task 3 is on Secure ID for Asset Authentication. Identity Management Systems (IDMS) are a foundational infrastructure for interactions between entities (organizations, users, devices, and services). Secure ID is blockchain-based a distributed identity management system allowing (1) identity provisioning, (2) authentication, (3) authorization, and (4) identity data sharing for IoT-enabled assets on the electricity grid. In this project, the SLAC team focused on designing and testing Keymaker, a protocol for authenticating device identity managed by Secure ID. Task 5 Private and Safe Integration is focused on the design and evaluation of a DER cooperation scheme which allows for the aggregation of DERs without impacting network reliability. The approach is designed based on realistic assumptions regarding data availability, communication infrastructure limitations, and privacy. Task 6 Scalable Distributed Privacy for Information explored how virtualized batteries could be managed privately. Specifically, it examined the case in which a principal provides a partitioned battery to multiple clients. Task 7 Use Cases was to ensure that this technology was applied in relevant situations and scenarios. Primarily, this means that virtualization needed to be employed in a manner that either improved flexibility, bolstered security or privacy, or decreased costs.

25 ENERGY STORAGE↗
DOE OSTI2024

AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation (Workshop Report)

The Artificial Intelligence Enhanced Co-Design for Next Generation Microelectronics virtual workshop was held April 4-5, 2023, and attended by subject matter experts from universities, industry, and national laboratories. This was the third in a series of workshops to motivate the research community to identify and address major challenges facing microelectronics research and production. The 2023 workshop focused on a set of topics from materials to computing algorithms, and included discussions on relevant federal legislation and such as the Creating Helpful Incentives to Produce Semiconductors and Science Act (CHIPS Act) which was signed into law in the summer of 2022. Talks at the workshop included edge computing in radiation environments, new materials for neuromorphic computing, advanced packaging for microelectronics, and new AI techniques. We also received project updates from several of the Department of Energy (DOE) microelectronics co-design projects funded in the fall of 2021, and from three of the Energy Frontier Research Centers (EFRCs) that had been funded in the fall of 2022. The workshop also conducted a set of breakout discussions around the five principal research directions (PRDs) from the 2018 Department of Energy workshop report: 1) define innovative material, device, and architecture requirements driven by applications, algorithms, and software; 2) revolutionize memory and data storage; 3) re-imagine information flow unconstrained by interconnects; 4) redefine computing by leveraging unexploited physical phenomena; 5) reinvent the electricity grid through new materials, devices, and architectures. We tasked each breakout group to consider one primary PRD (and other PRDs as relevant topics arose during discussions) and to address questions such as whether the research community has embraced co-design as a methodology and whether new developments at any level of innovation from materials to programming models requires the research community to reevaluate the PRDs developed back in 2018.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

AstroCLIP: a cross-modal foundation model for galaxies

ABSTRACT We present AstroCLIP, a single, versatile model that can embed both galaxy images and spectra into a shared, physically meaningful latent space. These embeddings can then be used – without any model fine-tuning – for a variety of downstream tasks including (1) accurate in-modality and cross-modality semantic similarity search, (2) photometric redshift estimation, (3) galaxy property estimation from both images and spectra, and (4) morphology classification. Our approach to implementing AstroCLIP consists of two parts. First, we embed galaxy images and spectra separately by pre-training separate transformer-based image and spectrum encoders in self-supervised settings. We then align the encoders using a contrastive loss. We apply our method to spectra from the Dark Energy Spectroscopic Instrument and images from its corresponding Legacy Imaging Survey. Overall, we find remarkable performance on all downstream tasks, even relative to supervised baselines. For example, for a task like photometric redshift prediction, we find similar performance to a specifically trained ResNet18, and for additional tasks like physical property estimation (stellar mass, age, metallicity, and specific-star-formation rate), we beat this supervised baseline by 19 per cent in terms of R2. We also compare our results with a state-of-the-art self-supervised single-modal model for galaxy images, and find that our approach outperforms this benchmark by roughly a factor of two on photometric redshift estimation and physical property prediction in terms of R2, while remaining roughly in-line in terms of morphology classification. Ultimately, our approach represents the first cross-modal self-supervised model for galaxies, and the first self-supervised transformer-based architectures for galaxy images and spectra.

Parker, Liam (ORCID:0009000749521674)↗
DOE OSTI2022

QuantumNAT: quantum noise-aware training with noise injection, quantization and normalization

Parameterized Quantum Circuits (PQC) are promising towards quantum advantage on near-term quantum hardware. However, due to the large quantum noises (errors), the performance of PQC models has a severe degradation on real quantum devices. Take Quantum Neural Network (QNN) as an example, the accuracy gap between noise-free simulation and noisy results on IBMQ-Yorktown for MNIST-4 classification is over 60%. Existing noise mitigation methods are general ones without leveraging unique characteristics of PQC; on the other hand, existing PQC work does not consider noise effect. To this end, we present QuantumNAT, a PQC-specific framework to perform noise-aware optimizations in both training and inference stages to improve robustness. We experimentally observe that the effect of quantum noise to PQC measurement outcome is a linear map from noise-free outcome with a scaling and a shift factor. Motivated by that, we propose post-measurement normalization to mitigate the feature distribution differences between noise-free and noisy scenarios. Furthermore, to improve the robustness against noise, we propose noise injection to the training process by inserting quantum error gates to PQC according to realistic noise models of quantum hardware. Lastly, post-measurement quantization is introduced to quantize the measurement outcomes to discrete values, achieving the denoising effect. Extensive experiments on 8 classification tasks using 6 quantum devices demonstrate that QuantumNAT improves accuracy by up to 43%, and achieves over 94% 2-class, 80% 4-class, and 34% 10-class classification accuracy measured on real quantum computers. The code for construction and noise-aware training of PQC is available in the TorchQuantum library.

Wang, Hanrui↗
DOE OSTI2024

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends with Washed and Unwashed Legacy Coals and Other Waste Fuels to Generate White Hydrogen

The objective of this effort, primarily funded by the United States Department of Energy (DOE), and led by the Electric Power Research Institute, Inc. (EPRI), with support by Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), has been to qualify coal, biomass, and plastic waste blends based on performance testing of selected fuel pellet compositions in a pilot-scale updraft moving-bed (UDMB) gasifier. The testing provided relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are the focus. The gasifier used for testing is HMI’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips (biomass). However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The three feedstocks were densified and pelletized by California Pellet Mill (CPM) to meet the feedstock size required by Sotacarbo’s 30mm ID UDMB gasifier, under contract to HMI. The technical tasks and results from this two-year research project included: (1) Feed Procurement and Preparation: Nine different tri-fuel pellets were prepared from varying compositions of fresh mined PRB coal, corn stover biomass, and car fluff waste plastics. Tri-fuel pellets were produced by CPM and shipped to Sotacarbo’s test facility in Carbonia, Sardinia, Italy. (2) Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different UDMB gasification tests to be performed in Sotacarbo’s 12-inch ID pilot scale gasifier, the process monitoring instrumentation used, and the extractive samples recovered for analysis of the total gasification process mass and energy balance. (3) Gasifier Testing: Nine different gasification runs were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstock compositions generated from varying mixtures of PRB coal, biomass, and plastic wastes. The testing generated performance data on gasification reaction efficiency and performance, yielding relevant data for models used to scale up the gasifier design. This task also included work to refurbish and reassemble the pilot gasifier at Sotacarbo and perform a baseline 100% PRB coal run. (4) Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results are reported in the project’s final report, published in March 2024. The results show that all tri-fuel pellets gasified well and maintained structural integrity throughout the gasification process. The syngas generated can be shifted to hydrogen by using commercial syngas shifting technologies. (5) High Fidelity computational fluid dynamics (CFD) Simulation: The National Energy Technology Laboratory (NETL) team performed CFD simulations of the UDMB gasifier for two of the tri-fuel pellets gasified in Sotacarbo’s pilot scale gasifier. The kinetic mechanisms for the pyrolysis of each constituent, PRB coal, corn stover biomass, and waste plastics are based on thermogravimetric analysis performed by Sotacarbo. The gasification model was validated by comparing the predicted syngas composition at the exit of the gasifier with the measured syngas composition. In addition, the reactor’s measured internal temperature profile agreed well with the predicted internal reactor temperature profile. These results validate that the model can be used to predict the performance of the updraft moving bed gasifier for different feedstocks and operating conditions. This paper summarizes the results of the completed work in which the pelletizing procedure was validated to ensure the viability of the tri-fuel pellets for the gasification runs performed at Sotacarbo’s 30 mm UDMB gasifier. The gasification performance data from this series of nine runs will enable modeling of a full-scale HMI industrial scale gasifier supporting both combined heat and power, and Hydrogen production from coal (both fresh mined and legacy) combined with various biomass and waste plastics. Additionally, plans and progress on a follow-up project, being executed by the same project team, will be presented. In this project, a total of twenty (20) different feedstocks are being prepared from varying compositions of biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste, and refuse-derived fuel (RDF). The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design to 50 megawatt electric (MWe) (equivalent hydrogen production). Tests will also be performed on a bench-scale fluidized-bed gasifier for comparison purposes. The results of this testing will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends.

08 HYDROGEN↗
DOE OSTI2021

Charge Condensation and Lattice Coupling Drives Stripe Formation in Nickelates

Revealing the predominant driving force behind symmetry breaking in correlated materials is sometimes a formidable task due to the intertwined nature of different degrees of freedom. This is the case for La 2–x Sr x NiO 4+δ , in which coupled incommensurate charge and spin stripes form at low temperatures. Here, we use resonant x-ray photon correlation spectroscopy to study the temporal stability and domain memory of the charge and spin stripes in La 2–x Sr x NiO 4+δ . Although spin stripes are more spatially correlated, charge stripes maintain a better temporal stability against temperature change. More intriguingly, charge order shows robust domain memory with thermal cycling up to 250 K, far above the ordering temperature. Furthermore, these results demonstrate the pinning of charge stripes to the lattice and that charge condensation is the predominant factor in the formation of stripe orders in nickelates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Coupled Neutronic and Thermal Hydraulic Analysis of a Natural Circulation Based Small Modular Reactor (SMR) Using VERA-CS

As part of the work supported by a US Department of Energy (DOE) Office of Nuclear Energy Gateway for Accelerated Innovation in Nuclear FY 2020 Voucher, Holtec International subsidiary SMR LLC (hereinafter referred to as Holtec) and Oak Ridge National Laboratory entered into a cooperative research and development agreement (CRADA) to develop coupled multiphysics core models of the Holtec developed small modular reactor (SMR), SMR-160. The scope of the 1 year project was to use the DOE–developed tool set, VERA, to analyze several aspects of a representative SMR-160 core design. The goals of the project were to perform the code-to-code benchmarking and to provide Holtec with a confirmatory calculations to compare against the results with the codes used in the SMR-160 design, identify and resolve areas of discrepancy between the two models to give Holtec a basis for selecting certain tool and model options, and develop a workflow so that the VERA model could be adapted easily to any future changes in the design of the SMR-160 core. The work proceeded in four phases: 1. Developing the initial VERA model based on Holtec-provided core design information; 2. Comparing VERA results with Holtec-provided calculations for the first five cycles; 3. Developing a VERA transient model based on the prior model; and 4. Training Holtec personnel on VERA and hand-off the developed models. This report summarizes at a high level the completed tasks. Details of the tasks and results are reserved for the full report, which will not be publicly released for 5 years per the terms of the CRADA. The report is titled “Coupled Neutronic and Thermal Hydraulic Analysis of a Natural Circulation Based Small Modular Reactor (SMR) using VERA-CS” and has the ORNL technical report number ORNL/TM 2021/2303 (NFE-20-08305)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Alternative Hanford ETF Grout Evaluation Report

The Hanford Effluent Treatment Facility (ETF) ammonia tolerant grout waste form was developed by the Vitreous State Laboratory (VSL) to stabilize ammonium and thereby prevent emission of ammonia vapor during processing of a final cementitious waste form. This ETF evaporator bottom waste is a concentrated sodium sulfate aqueous solution that also contains dissolved ammonium. The VSL waste form was produced in a two-step process in which struvite (MgNH 4 PO 4.6 H 2 O) is precipitated and then the resulting slurry is solidified in a cementitious matrix. SRNL researchers were tasked to evaluate the effect of compositional and struvite stability in simulated ETF evaporator brine. In 2022 to 2023, samples prepared by SRNL experienced significant expansion (up to 20 volume %) which was not observed by VSL.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

NRC Multiphysics Analysis Capability Deployment FY2020 - Part 4

This report details progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Sup- port for Advanced Non-Light Water Reactors.” The tasks completed for this report are: • Task 3a: This task demonstrates the effectiveness of Griffin’s methods for interpolating cross sections and SPH correction factors as a function of control drum rotation. The Monte Carlo code Serpent is used to generate reference results. The accuracy of Griffin-calculated eigenvalues and reaction rates are studied as a function of control drum rotation for cross section and SPH factor libraries of varying fidelity. Higher-fidelity libraries require less interpolation and are therefore inherently more accurate; however, they require more computational resources to create. Overall, Griffin is able to accurately model eigenvalue and reaction rates over the full range of drum rotation using a library generated from three to five discrete drum rotations for a particular microreactor design. • Task 3c: This preliminary task successfully demonstrates the performance of a coupled neutron-photon transport calculation with Griffin using the spherical harmonics approximation. The Griffin solutions are compared to reference solutions from the continuous energy Monte Carlo codes MCNP and Serpent. Furthermore, this work also demonstrates how to prepare the neutron and photon libraries using NJOY, MCNP, and Serpent with the latest ENDF/B-VIII data for 235 U and graphite. The Griffin total energy deposition in the active core region is calculated within 0.3% of the reference, but it degrades in the reflector regions with a maximum difference of -1.5%. Overall, the results look promising and future analysis should use an improved data stream and focus on determining the potential cancellation of error within each energy group.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Shelter Island, New York, Energy Reliability Assessment and Local Generation Options

Shelter Island's Green Options Committee (GOC), an all-volunteer committee tasked with considering all environmental conservation issues, requested technical assistance under the U.S. Department of Energy (DOE)-funded Energy Technology Innovation Partnership Project (ETIPP). The primary goals of this technical assistance project included: 1. Informing the GOC about energy use trends within the community as well as distributed solar, wind and storage opportunities; 2. Providing additional resources and technical feasibility information for geothermal, agrivoltaics and tidal energy; 3. Supporting the development of a community engagement plan; and 4. Supporting collaboration between the GOC and PSEG in order to find mutually beneficial follow-on projects. Assistance from NLR to help the GOC meet these overall project goals was provided through the following primary tasks: 1. Collaborate with the local utility in order to collect energy use data and inform the community on energy use patterns through a baseline assessment; 2. Technical analysis of distributed renewable and resiliency opportunities (solar, wind and storage) that best align with the community's energy priorities; 3. Provide high level feasibility support for future renewable energy scenarios that include agrivoltaic solutions, tidal energy, and geothermal projects on Shelter Island, and 4. Integrate all findings into a Community Outreach presentation to help the GOC engage with community stakeholders to build support and awareness of chosen resilience strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

GR-Athena++: Puncture Evolutions on Vertex-centered Oct-tree Adaptive Mesh Refinement

Numerical relativity is central to the investigation of astrophysical sources in the dynamical and strong-field gravity regime, such as binary black hole and neutron star coalescences. Current challenges set by gravitational-wave and multimessenger astronomy call for highly performant and scalable codes on modern massively parallel architectures. We present GR-Athena++, a general-relativistic, high-order, vertex-centered solver that extends the oct-tree, adaptive mesh refinement capabilities of the astrophysical (radiation) magnetohydrodynamics code Athena++. To simulate dynamical spacetimes, GR-Athena++ uses the Z4c evolution scheme of numerical relativity coupled to the moving puncture gauge. We demonstrate stable and accurate binary black hole merger evolutions via extensive convergence testing, cross-code validation, and verification against state-of-the-art effective-one-body waveforms. GR-Athena++ leverages the task-based parallelism paradigm of Athena++ to achieve excellent scalability. We measure strong-scaling efficiencies above 95% for up to ~1.2 × 10 4 CPUs and excellent weak scaling is shown up to ~10 5 CPUs in a production binary black hole setup with adaptive mesh refinement. GR-Athena++ thus allows for the robust simulation of compact binary coalescences and offers a viable path toward numerical relativity at exascale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining

Transformers are considered one of the most important deep learning models since 2018, in part because it establishes state-of-the-art (SOTA) records and could potentially replace existing Deep Neural Networks (DNNs). Despite the remarkable triumphs, the prolonged turnaround time of Transformer models is a widely recognized roadblock. The variety of sequence lengths imposes additional computing overhead where inputs need to be zero-padded to the maximum sentence length in the batch to accommodate the parallel computing platforms. This paper targets the field-programmable gate array (FPGA) and proposes a coherent sequence length adaptive algorithm–hardware co-design for Transformer acceleration. Particularly, we develop a hardware-friendly sparse attention operator and a length-aware hardware resource scheduling algorithm. The proposed sparse attention operator brings the complexity of attention-based models down to linear complexity and alleviates the off-chip memory traffic. The proposed length-aware resource hardware scheduling algorithm dynamically allocates the hardware resources to fill up the pipeline slots and eliminates bubbles for NLP tasks. Experiments show that our design has very small accuracy loss and has 80.2 × and 2.6 × speedup compared to CPU and GPU implementation, and 4 × higher energy efficiency than state-of-the-art GPU accelerator optimized via CUBLAS GEMM.

Peng, Hongwu↗