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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DECOVALEX-2023: Task F2-Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2-(salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

DECOVALEX-2023: Task F2 Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2- (salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics. Thermal, hydrological, mechanical, and chemical properties of individual components of the engineered and natural system were chosen for relevance by participating teams. The salt reference case system was characterized using data and measurements collected at relevant underground research laboratories (URLs), field sites, and simulation results from teams with specialized modelling capability. Participating teams made a wide range of model assumptions from compartmentalized networks to full 3D models of the salt formation. No single contributed model includes full-fidelity representation of all the features, events, and processes (FEPs) detailed in the task specification, but almost all features and processes are represented in at least one model. Despite differences in the modelling strategies developed by participating teams, all models indicate that salt compaction and radionuclide diffusion are key processes in the repository, and for the FEPs and model scenario considered, little of the disposed radionuclides will migrate beyond the repository seal over the 100,000 year simulations. In general, the model output quantities have the largest differences over the short term and near the waste. The models tend to be more similar further from waste and at later time. Disparities between the models are believed to be due to differing simplifications from the task specification, some of which are chosen simplifications to reduce complexity, and some are restrictions imposed by the modelling tools. A second round of this task has been accepted for DECOVALEX-2027 in conjunction with Task F1 on crystalline PA modelling. The future round includes waste package heating, improved modelling of salt creep closure, additional comparisons of coupled-process sub-models, and the impact of repository engineering design on radionuclide migration in the repository. Participants will also propose and finalize a set of uncertain inputs for the reference case simulations, propagate these uncertainties in a set of realizations, and conduct sensitivity analyses on the simulation results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

WHOLESCALE - Water & Hole Observations Leverage Effective Stress Calculations And Lessen Expenses (Final Technical Report 2020 - 2024)

The WHOLESCALE acronym stands for Water & Hole Observations Leverage Effective Stress Calculations and Lessen Expenses. The goal of the WHOLESCALE project is to simulate the spatial distribution and temporal evolution of stress in the geothermal system at San Emidio in Nevada, United States. To reach this goal, the WHOLESCALE team has developed a methodology to incorporate and interpret data from four methods of measurement into a multi-physics model that couples thermal, hydrological, and mechanical (T H-M) processes. The WHOLESCALE team has applied this methodology at the San Emidio geothermal field, located ~100 km north of Reno, Nevada in the northwestern Basin and Range province. The WHOLESCALE team includes 30 individuals working at two universities, two national laboratories, and one industry partner. Two master-degree students and five post-doctoral researchers have gained professional experience and earned partial financial support via the WHOLESCALE project. The WHOLESCALE team has taken advantage of the perturbations created by changes in pumping operations during planned shutdowns in 2016, 2021, and 2022 to infer temporal changes in the state of stress in the geothermal system at San Emidio, Nevada, U.S. The WHOLESCALE results support the working hypothesis that increasing pore-fluid pressure reduces the effective normal stress acting across fault zones. During normal operations, pumping in deep production wells decreases fluid pressures and thus increases the effective normal stresses on faults, reducing microseismicity. During planned shutdowns, the cessation of production increases pore-fluid pressure and reduces effective normal stress. The WHOLESCALE products generated during the 4-year period between 2020 and 2024 include: three articles published in the open-access, peer-reviewed scientific literature, two master’s theses, 20 presentations or papers at scientific conferences, and 17 data sets available on public repositories. The WHOLESCALE project has been completed in two phases that included three performance periods separated by two Go/No-go Stage Gate Reviews. Tasks were classified by data type (i.e., Geologic Structure, Borehole, Geodesy, Hydrology, Seismology, and Modeling). The first phase of the project started July 31, 2020 and included ongoing project coordination (Task 1), a project kickoff (Task 2), analysis of existing data (Task 3), development of the initial stress model & deployment design (Task 4), and Go/No-go Decision Point #1 (Task 5). Phase II began with implementing the 2022 deployment (Task 6), followed by Go/No-go Decision Point #2 (Task 7) The remainder of Phase II consisted of analyzing data collected during deployment (Task 8), calibration of the stress model on all observations (Task 9), and the Final Review (August 23, 2024) & Reporting (Task 10).

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Accelerated Coupled Monte Carlo-Thermal Hydraulic Calculations using a Hybrid GTF-Diffusion-based Prediction Block: First Results

Accurate predictions of spatial power and temperature distributions require the coupling of a neutron transport solver with a thermal-hydraulic (TH) feedback. Nowadays, Monte Carlo (MC) codes are widely coupled to TH solvers, typically via a Picard iteration (PI) method, due to the higher fidelity that such frameworks can produce. To speed up a PI, a prediction step can produce an improved initial guess for a source distribution and feed it to the MC code. Recent work [1, 2] investigated a prediction step that uses generalized transfer functions (GTFs) to predict the macroscopic cross sections’ variations following a perturbation in TH properties, such as coolant density. The previous method also relied on first order perturbation (FOP) theory to predict perturbed power profiles, rather than using an expensive MC iterate. The implemented FOP method relied on generating a fission matrix from which the forward and adjoint eigenmodes were extracted and later used to for power calculations. The generation of the fission matrix can introduce a significant computational overhead, therefore undermining the performance of the proposed hybrid technique when applied to high-dimensional problems, e.g., full core calculations. This work attempts to improve the GTF-FOP prediction step by replacing the FOP solver with a nodal diffusion solver, thus eliminating the need to calculate a fission matrix. The GTF-diffusion step was tested for various moderator density perturbations. In each case, the predicted power distribution showed good agreement with the reference case. The latter is attributed to the generally good prediction of most spatially distributed macroscopic cross sections, except the transport cross section, which will become the focus of future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Stout Smearing on a Quantum Computer

Smearing of gauge-field configurations in lattice field theory improves the results of lattice simulations by suppressing high energy modes from correlation functions. In quantum simulations, high kinetic energy eigenstates are introduced when the time evolution operator is approximated such as Trotterization. While improved Trotter product formulae exist to reduce the errors, they have diminishing accuracy returns with respect to resource costs. Therefore having an algorithm that has fewer resources than an improved Trotter formula is desirable. In this work I develop a representation agnostic method for quantum smearing and show that it reduces the coupling to high energy modes in the discrete nonabelian gauge theory $D_4$

Gustafson, Erik J.↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
DOE OSTI2021

Local Explosion Detection and Infrasound Localization by Reverse Time Migration Using 3-D Finite-Difference Wave Propagation

Infrasound data are routinely used to detect and locate volcanic and other explosions, using both arrays and single sensor networks. However, at local distances (< km) topography often complicates acoustic propagation, resulting in inaccurate acoustic travel times leading to biased source locations when assuming straight-line propagation. Here we present a new method, termed Reverse Time Migration-Finite-Difference Time Domain (RTM-FDTD), that integrates numerical modeling into the standard RTM back-projection process. Travel time information is computed across the entire potential source grid via FDTD modeling to incorporate the effects of topography. The waveforms are then back-projected and stacked at each grid point, with the stack maximum corresponding to the likely source. We apply our method to three volcanoes with different network configurations, source-receiver distances, and topography. At Yasur Volcano, Vanuatu, RTM-FDTD locates explosions within ~20 m of the source and differentiates between multiple vents. RTM-FDTD produces a more accurate location for the two Yasur subcraters than standard RTM and doubles the number of detected events. At Sakurajima Volcano, Japan, RTM-FDTD locates the source within 50 m of the active vent despite notable topographic blocking. The RTM-FDTD location is similar to that from the Time Reversal Mirror method, but is more computationally efficient. Lastly, at Shishaldin Volcano, Alaska, RTM and RTM-FDTD both produce realistic source locations (<50 m) for ground-coupled airwaves recorded on a four-station seismic network. We show that RTM is an effective method to detect and locate infrasonic sources across a variety of scenarios, and by integrating numerical modeling, RTM-FDTD produces more accurate source locations and increases the detection capability.

58 GEOSCIENCES↗
DOE OSTI2023

Tensor renormalization group study of 3D principal chiral model

We study the three-dimensional SU(2) principal chiral model using different tensor renormalization group methods based on the triad and anisotropic decomposition of the tensor. The tensor network representation is formulated based on the character expansion of the Boltzmann weight. We compare the average action obtained using these two tensor network algorithms and confirm that the resulting critical coupling and exponent are comparable with the recent estimations from the Monte Carlo methods.

Unmuth-Yockey, Judah↗
DOE OSTI2023

Tensor renormalization group study of 3D principal chiral model

We study the three-dimensional $SU(2)$ principal chiral model (PCM) using different tensor renormalization group methods based on the triad and anisotropic decomposition of the tensor. The tensor network representation is formulated based on the character expansion of the Boltzmann weight. We compare the average action obtained using these two tensor network algorithms and confirm that the resulting critical coupling and exponent are comparable with the recent estimations from the Monte Carlo methods.

Akiyama, Shinichiro↗
DOE OSTI2019

Synchronous and asynchronous optimized Schwarz methods for one-way subdivision of bounded domains

Convergence of both synchronous and asynchronous optimized Schwarz algorithms for the shifted Laplacian operator on a bounded rectangular domain, in a one-way subdivision of the computational domain, with overlap, is shown. Convergence results are obtained under very mild conditions on the size of the subdomains and on the amount of overlap. A couple of results are also given, relating the convergence rate of the asynchronous method to changes in the size of the domain. Numerical experiments illustrate the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Analytical derivatives of the individual state energies in ensemble density functional theory. II. Implementation on graphical processing units (GPUs)

Conical intersections control excited state reactivity, and thus, elucidating and predicting their geometric and energetic characteristics are crucial for understanding photochemistry. Locating these intersections requires accurate and efficient electronic structure methods. Unfortunately, the most accurate methods (e.g., multireference perturbation theories such as XMS-CASPT2) are computationally challenging for large molecules. The state-interaction state-averaged restricted ensemble referenced Kohn–Sham (SI-SA-REKS) method is a computationally efficient alternative. The application of SI-SA-REKS to photochemistry was previously hampered by a lack of analytical nuclear gradients and nonadiabatic coupling matrix elements. We have recently derived analytical energy derivatives for the SI-SA-REKS method and implemented the method effectively on graphical processing units. We demonstrate that our implementation gives the correct conical intersection topography and energetics for several examples. Furthermore, our implementation of SI-SA-REKS is computationally efficient, with observed sub-quadratic scaling as a function of molecular size. This demonstrates the promise of SI-SA-REKS for excited state dynamics of large molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Electrochemical Nickel-Catalyzed Asymmetric Hydrogenation of C═C Bonds Facilitated by a Proton-Coupled Electron Transfer Mediator

Enantioselective hydrogenation of C═C bonds is foundational to asymmetric synthesis, yet its adaptation to electrochemical methods has been limited by challenges in achieving chemoselectivity versus the hydrogen evolution reaction (HER). In this article, we present a modular electrochemical strategy that merges chiral nickel catalysis with a cobaltocene-derived proton-coupled electron transfer (PCET) mediator to enable the asymmetric hydrogenation of α,β-unsaturated carbonyl compounds. Under optimized conditions, a range of substrates featuring diverse amide functionalities and substitution patterns are hydrogenated in high yields (up to 95%) and enantioselectivities (up to 98% ee). The results described highlight the potential benefits of mediator-assisted, fixed-potential electrocatalysis in selective, stereocontrolled hydrogenation under mild conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrated Process Testing of MSR Salt Spill Accidents

Part of the licensing process for new nuclear reactors requires vendors to assess the potential consequences of identified accident scenarios using accident progression modeling. The accident scenario that will likely be evaluated by all molten salt reactor (MSR) developers is a spill of radionuclide-bearing fuel salt onto the reactor containment floor (i.e., a salt spill accident). The development of accident progression models requires experimental data to inform which processes to incorporate, to enable the calculation of parameters to model these processes, and to validate the model predictions. The data should quantify the sensitivities of key processes (e.g., molten salt spreading, heat transfer, containment structure corrosion, radionuclide vaporization, and aerosol generation) towards the initial conditions of the spill, the ambient environment, and the features of the containment. In addition, results from integrated process tests that quantify coupled processes are required to validate systems-level models. This report documents results from integrated process tests conducted on simulated molten salt spill accidents. The generated experimental data simultaneously quantify the heat transfer behavior of the spilled salt, compositional changes to the bulk salt, and the release of surrogate fission products from the spilled salt as aerosol particles. All tests that were conducted used FLiNaK doped with surrogate fission products, and the variables that were evaluated included the initial salt temperature and the concentration of surrogate fission products present in the salt. The major accomplishments of this work include identifying surrogate fuel salt compositions that provide insight into the dispersal behavior of radionuclides of potential significance to the source term, employing previously developed methods and measurement techniques to simultaneously measure key processes, generating data on the coupled processes of molten salt heat transfer and surrogate fission product release as aerosol particles, demonstrating new test methods for real-time monitoring of the flow rate of the spill and aerosol size quantification in an argon atmosphere, and developing a mass transfer model for cesium and iodine release from molten FLiNaK to provide insight into aerosol formation by vapor condensation. The same methodology applied herein can be employed to study different salt compositions of interest to MSR developers, different environmental conditions, and other variables that are relevant to postulated accident scenarios. The insights gained from these integrated process tests conducted at a laboratory scale will be incorporated into future integral effects tests conducted at an engineering scale.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Tuning the Dimensionality of Excitons in Colloidal Quantum Dot Molecules

Electrically coupled quantum dots (QDs) can support unique optoelectronic properties arising from the superposition of single-particle excited states. Experimental methods for integrating colloidal QDs within the same nano-object, however, have remained elusive to the rational design. Here, we demonstrate a chemical strategy that allows for the assembling of colloidal QDs into coupled composites, where proximal interactions give rise to unique optoelectronic behavior. The assembly method employing “adhesive” surfactants was used to fabricate both homogeneous (e.g., CdS–CdS, PbS–PbS, CdSe–CdSe) and heterogeneous (e.g., PbS–CdS, CdS–CdSe) nanoparticle assemblies, exhibiting quasi-one-dimensional exciton fine structure. In addition, tunable mixing of single-particle exciton states was achieved for dimer-like assemblies of CdSe/CdS core–shell nanocrystals. The nanoparticle assembly mechanism was explained within the viscoelastic interaction theory adapted for molten-surface colloids. Furthermore, we expect that the present work will provide the synthetic and theoretical foundation needed for building assemblies of many inorganic nanocrystals.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Deployment of the Finite Volume Method in Pronghorn for Gas and Salt cooled Pebble Bed Reactors

This report summarizes the activities related to ”Complete FHR and HTGR pebble bed simulator, including initial validation” funded by the NEAMS thermal-hydraulics focus area. The activity revolves around the coarse-mesh thermal-hydraulics code Pronghorn and its application to gas and salt cooled Pebble bed reactor (PBR). The main difference between gas and salt cooled PBR from a thermal-hydraulics perspective is the fluid. To address the difference in fluid behavior, two separate approaches are implemented in the MOOSE Navier Stokes module: 1) a Boussinesq approximation and 2) a fully compressible formulation. The developed finite volume method capabilities are used for improving pre-existing gas-cooled and salt-cooled pebble-bed reactor models. A steady-state, multiphysics gas-cooled pebble-bed reactor model is created that couples the equilibrium core depletion capability developed in previous work, and the finite volume method capability developed for this report. The salt-cooled pebble-bed reactor model is upgraded to use the incompressible finite volume method capability and then extended to three spatial dimensions. Finally, several verification-and-validation exercises performed with Pronghorn are documented using the verification-and-validation report of the MooseDoc system. The goal of this effort to document the verification-and-validation level of Pronghorn and improve stakeholder confidence in the results obtained with Pronghorn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Three-dimensional coupling of electron cyclotron drift instability and ion–ion two stream instability

Electron cyclotron drift instability (ECDI) and ion–ion two stream instability (IITSI) are both kinetic instabilities that can be present in low-temperature, partially magnetized plasmas. The coupling of instabilities in a three-dimensional configuration leads to the existence of more than one unstable roots to the kinetic dispersion relation. In this paper, a generalized method has been developed for numerically evaluating solutions to the three-dimensional dispersion relation for coupled ECDI and IITSI, assuming cold singly and doubly charged ions and a Maxwellian velocity distribution function for the electrons. The present study demonstrates the coupling between ECDI and IITSI that affects the most unstable mode as a function of the wavenumbers in three dimensions and various plasma properties, including the applied electric field, magnetic field, electron temperature, ion velocities, and plasma density. One of the most notable results is that, while the most unstable mode with the largest growth rate is in the direction of the E×B drift in the two-dimensional cases, the most unstable mode for the three-dimensional configuration occurs in the oblique direction between the applied electric field and the E×B drift. Here, this agrees with experimental observations in cross field plasma sources using coherent Thomson scattering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗