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DOE OSTI2022

2D Magnetohydrodynamic Simulations of the Electrothermal Instability in Metallic Liners

The Virginia Tech (VT) Plasma Dynamics Laboratory Computational (PDCL) and Lawrence Livermore National Laboratory (LLNL) are performing two dimensional (2D) simulations of the electrothermal instability (ETI) using the LLNL multi-physics code Ares. Ares is a multi-physics arbitrary–Lagrangian-Eulerian (ALE) code developed by LLNL and is of particular use in studying magnetohydrodynamic (MHD) instabilities like the ETI due to its resistive MHD, magnetic diffusion, and radiative-hydrodynamics packages. Among its capabilities, it has the ability to model material strength, perform adaptive mesh refinement (AMR), and incorporate a wide variety of equations of state models and conductivity models. The 2D Ares simulation model created by VT-LLNL for studying the development and growth of the electrothermal instability has been configured with initial conditions based on the Mykonos Electrothermal Instability II (METI-II) experiments described by this grant and conducted by team members at the University of Nevada (UNR), the University of New Mexico (UNM), and Sandia National Laboratories. Previously, preliminary 2D Ares simulations of the ETI had been run to approximately 80ns. The rods in these simulations were initiated with sinusoidal perturbations at a similar order of magnitude to those measured on the aluminum rods used for the Mykonos experiment. This model has been improved by increasing the spatial resolution of the simulations and running the simulations further in time. In addition to the simulation run-times extending, the preliminary sinusoidal perturbation has been replaced with a perturbation derived from amplitude measurements by the experimental team, thereby correlating the simulation inputs better to the experimental runs. These new runs are capable of reaching 120ns of simulated time for the uncoated cases and to 200ns the 41 μm coated cases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing will provide 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 the 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 a focus. The gasifier is Hamilton Mauer International, Inc. (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. However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The feedstocks will be prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks and current status for this two-year research project are: Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill and shipped to Sotacarbo’s test facility in Italy. Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. Gasifier Testing: Tests are currently being performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also include work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results to be reported. The results 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. This paper will be summarize the pelletizing procedure that insures the viability of the tri-fuel pellets for the gasification runs that are being performed at Sotacarbo’s 30mm up draft moving bed gasifier. Initial gasification tests have been conducted, and all the lab scale tri-fuel pellet gasification runs will be completed by the fall of 2022. Performance data will enable modeling of a full-scale HMI industrial scale gasifier supporting both CHP and Hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Enhanced Component Performance Study: Turbine-Driven Pumps 1998-2020

This report presents an enhanced performance evaluation of turbine-driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The TDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR≤1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. No increasing trends were identified for TDPs for the most recent 10-year period: The following decreasing trends were identified for TDPs for the most recent 10-year period: • Standby TDP FTR>1H failure rate • Standby TDP unavailability • Standby MDP total unreliability (8-hour mission) • Standby TDP frequency of FTR>1H events (failures per reactor year) • Normally running TDP frequency of start demands (demands per reactor year) • Normally running TDP frequency of run hours (hours per reactor year).

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Overview of the Muon 𝑔 − 2 Experiment at Fermilab

Searching for anomalies is one of the most interesting approaches to physics research. Many particle physicists look for discrepancies between experimental measurements and theoretical predictions because we know that identifying and understanding anomalies can be a major component of building a more fundamental description of nature. The Muon g-2 experiment at Fermilab measures the magnetic anomaly of the muon with extremely high precision. In 2021, the Muon g-2 Collaboration reported its first result at a precision of 460 ppb based on the first data-taking run comprising 6% of the total data set to be collected. This result is in good agreement with the previous measurement from Brookhaven National Laboratory, giving greater certainty to the world average of the experimental value. The next even higher precision Muon g-2 result will play an important role given the recent tensions between data-driven dispersive and lattice QCD calculations to predict the hadronic vacuum polarization contribution. I begin this talk with a review of muon g-2 physics and the experimental technique. Then I present a timeline including the past Run 1 result milestone, current status of Runs 2/3 analysis, and projections to finalize work on the final data from Runs 4/5/6. I conclude with a brief discussion of new ideas and future plans for the Muon g-2 experiment after the completion of Run 6.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

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 OSTI2025

FY-25 Progress on Computational Modeling of the Water Based NSTF

This report summarizes the system level modeling using RELAP5-3D of the Natural Convection Shutdown Heat Removal Test Facility (NSTF) completed in FY25. This year’s work focuses on a new tank configuration where the inlet of the tank was lowered in elevation by 45”. The stability boundaries of the NSTF are thoroughly studied and stability maps are constructed based on the stability and the oscillation patterns of the system. Five distinct operational modes are identified, namely single-phase liquid, uniform double peak oscillations, uniform sinusoidal oscillations, stable two-phase flow, and non-uniform oscillations. Next, the riser inlet throttling case of experimental test Run-104 is simulated with the RELAP5 model where good agreement is obtained between the model and the experimental data. The simulation also highlights the effects of backflow of water from the tank to the upper region of the chimney. Additionally, the decay heat removal test of Run-99 is simulated with the RELAP5 model. Comparison is carried out between this run and a similar run with the mid-tank inlet of Run-74 performed in FY22. With the lower tank inlet, the RELAP5 model is able to predict the experimental data more accurately than the previous mid tank inlet configuration. The discrepancy in model prediction accuracy highlights the non-symmetrical spatial effects in the tank that would otherwise be more easily captured with higher fidelity models. Lastly, two exploratory studies are conducted to investigate the behaviors of the NSTF when 1) heating is provided to the downcomer and 2) a bypass channel is added between the horizontal chimney section to the downcomer.

42 ENGINEERING↗

DOE OSTI2025

Develop Accurate Techniques for Passive SiC Temperature Monitoring of Miniature Samples for Cross-Cutting Applications

Passive thermometry is critically important because most fuels and materials irradiation experiments are not instrumented, and it is necessary to understand the irradiation temperature to properly interpret any post-irradiation examination data, including evolving properties and/or microstructures. The standard passive thermometry approach uses continuous dilatometry to evaluate changes in the instantaneous coefficient of thermal expansion during post-irradiation thermal annealing. This approach has limitations in terms of sample size (minimum length requirements) and the maximum irradiation temperature that can be accurately determined, which is limited by the reduced swelling (and therefore recovery) following higher temperature irradiation and limitations on the furnaces used with push-rod dilatometers. This work evaluates two new proposed techniques for post-irradiation evaluation of passive SiC temperature monitors: differential scanning calorimetry (DSC) and Raman spectroscopy. DSC is an extremely sensitive technique that can be used for any specimen geometry and is capable of higher temperature operation. Raman spectroscopy is similar in that it is a surface technique capable of examining extremely small samples (submillimeter), can be used with a heated stage up to 1,500°C (planned for future work), and is capable of mapping local irradiation temperatures throughout a sample. Existing SiC samples that were previously irradiated over a wide range of temperatures were cut into multiple pieces to allow for annealing studies using multiple different techniques: dilatometry, DSC, and Raman spectroscopy. This approach mitigates the concern that samples analyzed using one technique may have a slightly different irradiation history than those analyzed using a different technique. Recovery was clearly observed during annealing using both DSC and dilatometry. In some cases, a direct comparison could not be made due to some of the DSC runs accidentally including material from multiple specimens and issues with using an alternative DSC sample holder for the highest temperature annealing studies. Nevertheless, one trend was clear: the DSC runs resulted in higher irradiation temperatures compared to those of the dilatometry runs. Part of this could be attributed to the higher temperature ramp rates used during the DSC runs, which are often preferred to reduce noise in the measurements. By comparison, dilatometry has previously been shown to produce better data at lower ramp rates. Future work should further investigate the ideal ramp rate for both techniques to produce consistent results. Additional work should evaluate the best holder material to use for DSC runs exceeding 1,000°C to provide reliable data while preventing interactions between SiC and the holder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Develop Accurate Techniques for Passive SiC Temperature Monitoring of Miniature Samples for Cross-Cutting Applications

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Distribution of Lanthanides, Yttrium, and Scandium in the Pilot-Scale Beneficiation of Fly Ashes Derived from Eastern Kentucky Coals

In this study, Central Appalachian coal-derived fly ashes from two power plants were beneficiated in a pilot-scale facility in order to produce a product with a relatively consistent concentration of rare earth elements (REE). The <200-mesh final fly ash product was produced by removing the carbon- and Fe-rich particles prior to screening at 200 mesh (75 µm). The Plant D fly ash had high concentrations of CaO and SO3, which were diminished through the two months when the ash was being beneficiated, representing a consequence of the heat, humidity, and excessive rainfall in the Kentucky summer. The high CaO and SO3 concentrations through the early runs likely contributed to the lower REE in the <200-mesh products of those runs. Of the non-REE minor elements, Ba, V, Mn, Zn, and As showed the greatest between-run variations within the runs for each plant. The overall REE concentrations proved to be similar, both on a between-run basis for the individual fly ash sources and on a between-plant basis. Variations in fly ash quality will occur in larger-scale operations, so on-going attention to the fly ash quality and the response of the fly ash to beneficiation is necessary. Changes in the Plant D fly ash with time imply that both the freshness of the original ash and the length and conditions of its storage at the site of beneficiation could be factors in the quality and consistency of the processed fly ash.

58 GEOSCIENCES↗

DOE OSTI2025

Synthesis and characterization of uranium trichloride in alkali-metal chloride media

Given a growing interest in uranium salts for pyrochemical processing of used fuel and uranium-fueled molten salt reactors, the synthesis of uranium trichloride in alkali-metal chloride media was investigated in a series of four experiments. Specifically, uranium metal powder and uranium hydride powder were prepared and separately blended with ammonium chloride and lithium chloride – potassium chloride eutectic in two runs, while the same powders were separately blended with ammonium chloride and sodium chloride in two additional runs. Each of the lithium chloride – potassium chloride containing blends was slowly heated to 923 K, while those containing sodium chloride were heated to 1123 K. During each heat up, the ammonium chloride sublimed into gaseous ammonia and hydrogen chloride, leading to the chlorination of uranium metal or uranium hydride and the formation of molten salt solutions of the respective chlorides. Experimental conditions were incorporated in the runs to promote formation of uranium trichloride over uranium tetrachloride in the respective media. Molten samples of each run product were taken and characterized via chemical analyses, diffractometry, and microscopy. The final products from each run were dark dense ingots of the respective salt systems with uranium concentrations ranging from 44 to 51 wt%. Chemical analyses and diffractometry identified the predominant presence of uranium trichloride in these systems; however, a possible minor presence of uranium tetrachloride could not be conclusively dismissed.

D Herrmann, Steven↗

DOE OSTI2023

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Search for Lepton Flavor Violation in Two Body Muon and Pion Decay at Rest

The ability of the Mu2e experiment to probe, or discover beyond the Standard Model physics in direct Charged Lepton Flavor Violation $\mu^+$ and $\pi^+$ decay modes is estimated. These direct modes are searched for simultaneously with proposed Mu2e detector validation runs, and are complementary to the Mu2e main search goal, an indirect search for $\mu^- \to e^-$ conversion at the sensitivity level of $\sim 10^{-17}$. The $\mu^+$ validation run will operate at 50% nominal magnetic field and reduced proton beam intensity to less than 1/100th nominal, in order to observe the e+ spectrum from $\mu^+$ decay, at and below the Michel edge Ee . 53 MeV. The $\pi^+$ validation run, based on measuring the mono-energetic e+ emission in the decay $\pi^+ \to e+\nu$, at 76% of nominal magnetic field and reduced beam intensity less than 1/5th nominal. Both of these runs can be used to fix the momentum scale for the Mu2e conversion search. In addition the muon validation dataset can be used to correct for systematic errors in the detector response by mapping the well known to O(\u03B13) corrected theoretical Michel spectrum, to the observed spectrum. One direct search is for two-body Charged Lepton Flavor Violation $\mu^+ \to e^+X$ decay, where $X$ is a light new physics particle. This allows Mu2e to explore well motivated models including axion like particles with flavor violating couplings and massive $Z^0$ bosons with more sensitivity then present astrophysical and laboratory constraints. In two weeks of data-taking, Mu2e can achieve direct mode 90% confidence level branching ratio limits of $10^{-7}$ over the mass range $20 \le m_X \le 50$ MeV, improving the current experimental limit at $10^{-5}$ by two orders of magnitude. In the mass range $m_X \le 20$ MeV, assuming systematic error corrections can be made by correcting the Monte Carlo mapping, the achievable search sensitivity is found to be $2.3\times 10^{-7}$ for $m_X =0$, an order of magnitude improvement over the current best limit at $2.6\times 10^{-6}$, when assuming $V+A$ or isotropic coupling. The $\pi^+$ validation run, allows searching for $\pi^+ \to e^+N$ decay, where $N$ is a heavy neutral lepton such as a heavy sterile neutrino, in the mass region $20 \le m_N \le 65$ MeV. A branching ratio limit at 90% confidence level of $3\times 10^{-8}$ can be achieved in two weeks, an improvement of the current search sensitivity limit by an order of magnitude.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Local Power Impact Experiment Design for a New Fuel Type for use in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. Reactor physics safety evaluations currently use Monte Carlo for the 21st Century (MC21), a continuous-energy Monte Carlo radiation transport code [3]. Existing MC21 models of the ATR and ATRC cores have a validation basis for use in neutronics analyses with HEU fuel. The models are used to support safety analyses that include comparisons to the safety requirements for the reactors. However, the use of the LOWE element in the ATR and ATRC is not currently covered by the current model validation basis. To deploy the new fuel type, extensive computational reactor physics support is necessary to support the use of LOWE in the ATR and ATRC. Therefore, LOWE requires a rigorous validation basis, aligned with that of HEU fuel, that takes advantage of the existing software tools and processes currently used for the ATR and ATRC. The experiment to validate of the MC21 models for determining power, the Power Impact Validation Experiment, will consist of two flux runs in the ATRC, one with fully HEU loading and one with a single LOWE element. Both flux runs will be instrumented with 20 sets of azimuthal fission wires and 3 sets of axial fission wires, as shown in Figure 4. Standard flux run methodology will be used [4]. Power Impact Validation Experiment data will be compared against MC21 calculated data, both for absolute fission rate accuracy and to determine the relative change in fission rates between the two runs. The results of the Power Impact Validation Experiment and subsequent evaluations will provide the validation basis for MC21 for use with LOWE elements. Key features of the Power Impact Validation Experiment include: (1) Two flux runs to allow for LOWE perturbed measurements to be compared to already validated measurements taken from a full core of HEU fuel, (2) Optimization of instrumentation to balance analytical needs with practical considerations (e.g., limited time window to count beta particles from fission products), and (3) Standard ATRC core loading, including both driver positions and flux traps, to minimize cost while remaining representative of typical ATR core loading.

42 ENGINEERING↗

DOE OSTI2024

Evaluating integration and performance of containerized climate applications on a Hewlett Packard Enterprise Cray system

Containers have taken over large swaths of cloud computing as the most convenient way of packaging and deploying applications. The features that containers offer for packaging and deploying applications translate to high performance computing (HPC) as well. At The National Oceanic and Atmospheric Administration, containers provide an easy way to build and distribute complex HPC applications, allowing faster collaboration, portability, and experiment computer environment reproducibility amongst the scientific community. The challenge arises when applications rely on message passing interface (MPI). This necessitates investigation into how to properly run these applications with their own unique requirements and produce performance on par with native runs. We investigate the MPI performance for benchmarks and containerized climate models for various containers covering selection of compiler and MPI library combinations from the Cray provided programming environments on the Cray XC supercomputer GAEA. Performance from the benchmarks and the climate models shows that for the most part containerized applications perform on par with the natively built applications when the system optimized Cray MPICH libraries are bound into the container, and the hybrid model containers have poor performance in comparison. We also describe several challenges and our solutions in running these containers, particularly challenges with heterogeneous jobs for the containerized model runs.

Abraham, Subil↗

DOE OSTI2022

Flood hazard model calibration using multiresolution model output

Riverine floods pose a considerable risk to many communities. Improving flood hazard projections has the potential to inform the design and implementation of flood risk management strategies. Current flood hazard projections are uncertain, especially due to uncertain model parameters. Calibration methods use observations to quantify model parameter uncertainty. With limited computational resources, researchers typically calibrate models using either relatively few expensive model runs at high spatial resolutions or many cheaper runs at lower spatial resolutions. This leads to an open question: is it possible to effectively combine information from the high and low resolution model runs? We propose a Bayesian emulation–calibration approach that assimilates model outputs and observations at multiple resolutions. As a case study for a riverine community in Pennsylvania, we demonstrate our approach using the LISFLOOD-FP flood hazard model. Here, the multiresolution approach results in improved parameter inference over the single resolution approach in multiple scenarios. Results vary based on the parameter values and the number of available models runs. Our method is general and can be used to calibrate other high dimensional computer models to improve projections.

multiresolution↗

DOE OSTI2021

Methods for a blind analysis of isobar data collected by the STAR collaboration

In 2018, the STAR collaboration collected data from $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ at $\sqrt{s_\text {NN}}=200$ GeV to search for the presence of the chiral magnetic effect in collisions of nuclei. The isobar collision species alternated frequently between $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ . In order to conduct blind analyses of studies related to the chiral magnetic effect in these isobar data, STAR developed a three-step blind analysis procedure. Analysts are initially provided a “reference sample” of data, comprised of a mix of events from the two species, the order of which respects time-dependent changes in run conditions. After tuning analysis codes and performing time-dependent quality assurance on the reference sample, analysts are provided a species-blind sample suitable for calculating efficiencies and corrections for individual $\approx 30$-min data-taking runs. For this sample, species-specific information is disguised, but individual output files contain data from a single isobar species. Only run-by-run corrections and code alteration subsequent to these corrections are allowed at this stage. Following these modifications, the “frozen” code is passed over the fully un-blind data, completing the blind analysis. As a check of the feasibility of the blind analysis procedure, analysts completed a “mock data challenge,” analyzing data from Au + Au collisions at $\sqrt{s_\text {NN}}=27$ GeV, collected in 2018. The Au + Au data were prepared in the same manner intended for the isobar blind data. Finally, the details of the blind analysis procedure and results from the mock data challenge are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Designing a repository in domal salt: The influence of design variants in different modelling environments

To understand the long-term environmental impact of disposing radioactive waste of in a deep geological repository and to optimise its design, performance assessments are used. In this study, four teams (COVRA, GRS, Quintessa, and DOE) modified the previously developed generic repository of DECOVALEX task F2 to identify commonalities and differences between the teams for specific changes in repository design. The teams tested six design modifications: (1) Replacing concrete abutments with run-of-mine salt; (2) Replacing the salt seal with a concrete abutment and using run-of-mine salt instead for the two concrete abutments in each drift seal; (3) Halving the size of the infrastructure area; (4) Using run-of-mine salt instead of gravel for backfilling the infrastructure area; (5) Disposal of spent nuclear fuel without the POLLUX-10 containers (6); Lower initial saturation of the spent nuclear fuel and vitrified waste disposal drifts. Despite different modelling strategies used, models agreed that a smaller infrastructure area has a limited effect on radionuclide transport. Responses to the absence of the two concrete abutments in each seal, the use of single large concrete abutments (200 m each), or the use of run-of-mine salt in the infrastructure area differ between teams due to differing modelling assumptions. Based on these results, the estimated efficacy of containment depends strongly on the model assumptions of each team. More specifically, it appears to depend on the compaction model used and therefore on the backfill material used in different areas of the repository. However, the drift seal appears to be a critical design element in all models, effectively limiting radionuclide transport by hydrologically disconnecting sections of the repository. Additional beneficial design choices include the use of dry salt in disposal drifts to limit radionuclide transport and reducing the infrastructure area costs and minimizing host rock damage.

DECOVALEX↗

DOE OSTI2023

Model to inform the expansion of hydrogen distribution infrastructure

A growing hydrogen economy requires new hydrogen distribution infrastructure to link geographically distributed hubs of supply and demand. The Hydrogen Optimization with Deployment of Infrastructure (HOwDI) Model helps meet this requirement. The model is a spatially resolved optimization framework that determines location-specific hydrogen production and distribution infrastructure to cost-optimally meet a specified location-based demand. While these results are useful in understanding hydrogen infrastructure development, there is uncertainty in some costs that the model uses for inputs. Thus, the project team took the modeling effort a step further and developed a Monte Carlo methodology to help manage uncertainties. Seven scenarios were run using existing infrastructure and new demand in Texas exploring different policy and tax approaches. The inclusion of tax credits increased the percentage of runs that could deliver hydrogen at <$\$4$ /kg from 31% to 77% and decreased the average dispensed cost from $\$4.35$ /kg to $\$3.55$ /kg. However, even with tax credits there are still some runs where unabated SMR is deployed to meet new demand as the low-carbon production options are not competitive. Every scenario, except for the zero-carbon scenario (without tax credits), resulted in at least 20% of the runs meeting the $\$4$ /kg dispensed fuel cost target. This indicates that multiple pathways exist to deliver $\$4$ /kg hydrogen.

08 HYDROGEN↗