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DOE OSTI2021

Novel Geochemistry Determined from High Pressure, High Temperature Simulation Experiments of Hydraulic Fracture Test Site 2

A standard method in unconventional oil and gas production is the process of hydraulic fracturing followed by a shut-in period, during which the fracture fluid remains pressurized in the reservoir for up to three weeks before production begins. Despite this widely used process, very little is known about what occurs in the reservoir during this shut-in process. In order to properly delineate potential reservoir reactions that may occur during shut-in that would lead to corrosion and scaling events, experiments were conducted in high pressure, high temperature reactors to simulate conditions of the Wolfcamp Formation in the Delaware Basin. Experimental design allowed the assessment of the effect of proppant, microbiology, and time on the mineralogy and fluid chemistry in the reservoir. Results suggest the biggest impact on fluid chemistry and shale mineralogy during shut-in is time. Analyses demonstrate dissolution of the shale material, with maximum dissolved ions occurring after 7 days of the shut-in period. After 21 days, results suggest precipitation occurs. The Delaware Basin is demonstrated to be high in sulfate content, which further increases in the fluid due to dissolution reactions during shut-in. The pressure vessel experiments suggest there was no significant contribution to reactions from microbiology during the shut-in period. Furthermore, early production samples demonstrate a significant selection of the microorganism Caminicella, a genus of which has previously been correlated to corrosion and sulfide production. Results suggest shut-in conditions may provide high sulfate concentrations that could later be utilized by a shifted microbial community to drive potential well infrastructure failure. This is the first study to incorporate microbiology, mineralogy, and fluid chemistry to investigate the fundamental geochemical reactions that occur during shut-in and early phase production of the Delaware Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S032R001/2477425/urtec-2021-5219-ms.pdf/1 by Carol Worster on 28 February 2022 Basin. Results from this study can complement observations from the Hydraulic Fracture Test Site 2 observations

58 GEOSCIENCES↗

DOE OSTI2021

Simulations of Events for the LUX-ZEPLIN (LZ) Dark Matter Experiment

The LUX-ZEPLIN dark matter search aims to achieve a sensitivity to the WIMP-nucleon spin-independent cross-section down to (1–2) ×10−12 pb at a WIMP mass of 40 GeV/ c 2 . This paper describes the simulations framework that, along with radioactivity measurements, was used to support this projection, and also to provide mock data for validating reconstruction and analysis software. Of particular note are the event generators, which allow us to model the background radiation, and the detector response physics used in the production of raw signals, which can be converted into digitized waveforms similar to data from the operational detector. Inclusion of the detector response allows us to process simulated data using the same analysis routines as developed to process the experimental data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Mu2e experiment: Simulation of the Production Target

The Mu2e experiment will search for coherent, neutrinoless conversion of muons to elections in an aluminum stopping target. A simulation program is used to experiment and design the production target of the Mu2e experiment. The module uses programing languages and libraries to work. The program called the Offline uses C++ as the programing language in the module. To construct the simulation, the Geant4 library constructs shapes and uses them in the simulation program, ROOT. The offline program simplifies the creation of the tube by organizing them into parameter objects and nesting them with other variables required to construct the tube-like center point, material, or if it is allowed to conflict with other solids. The parameter varies for every solid tube. The geometry file uploads the parameters by declaring and organizing the parameters in C++ using the configuration tools. The author describes the development and the future of this project.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Mu2e experiment: Simulation of the Production Target

Szewczyk, Albert↗

DOE OSTI2023

Realistic large eddy and dispersion simulation experiments during project sagebrush phase 1

Typical dispersion simulations use mesoscale models at grid spacing greater than 1 km to simulate pollutant transport. Advances in computing power have allowed Large Eddy Simulations (LES), (grid spacing less than 100 m) to be run with boundary conditions in the grayscale regime (grid size of 1 km–100 m). We used the WRF mesoscale/LES model and the HYSPLIT particle dispersion model to simulate SF 6 transport from Project Sagebrush Phase 1, using a grayscale-aware scheme with 4 nests of 3 km, 1 km, 200 m, 67 m. The WRF/LES simulation was in satisfactory agreement with meteorological observations but the HYSPLIT SF6 simulations indicated insufficient sub-grid turbulence kinetic energy, especially in the lowest 100 m. This resulted in over predictions of the surface SF6 concentration and insufficient vertical transport. Best agreement with the Sagebrush observations was obtained with the WRF/LES large-scale and sub-grid turbulence, enhanced with a HYSPLIT parameterized turbulence profile.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Experiment Simulation Configurations Approximating DUNE TDR

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment consisting of a high-power, broadband neutrino beam, a highly capable near detector located on site at Fermilab, in Batavia, Illinois, and a massive liquid argon time projection chamber (LArTPC) far detector located at the 4850L of Sanford Underground Research Facility in Lead, South Dakota. The long-baseline physics sensitivity calculations presented in the DUNE Physics TDR, and in a related physics paper, rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the near and far detectors, fully automated event reconstruction and neutrino classification, and detailed implementation of systematic uncertainties. The purpose of this posting is to provide a simplified summary of the simulations that went into this analysis to the community, in order to facilitate phenomenological studies of long-baseline oscillation at DUNE. Simulated neutrino flux files and a GLoBES configuration describing the far detector reconstruction and selection performance are included as ancillary files to this posting. A simple analysis using these configurations in GLoBES produces sensitivity that is similar, but not identical, to the official DUNE sensitivity. DUNE welcomes those interested in performing phenomenological work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community.

Abi, B↗

DOE OSTI2023

Thermal insulation versus capacitance: A simulation experiment comparing effects of shade and hyporheic exchange on daily and seasonal stream temperature cycles

In streams where water temperatures stress native biota, management of riparian shade or hyporheic exchange are both considered viable management strategies for reducing the peaks of daily and seasonal stream channel temperature cycles. Although shade and hyporheic exchange may have similar effects on stream temperatures, their mechanisms differ. Improved understanding of the heat-exchange mechanisms influenced by shade and hyporheic exchange will aid in the appropriate application of either stream temperature management strategy. To illustrate a conceptual model highlighting shade as ‘thermal insulation’ and hyporheic exchange imparting ‘thermal capacitance’ to a stream reach, we conducted an in-silico simulation modelling experiment increasing shade or hyporheic exchange parameters on an idealized, hypothetical stream. We assessed the potential effects of increasing shade or hyporheic exchange on a stream reach using an established process-based heat-energy budget model of stream-atmosphere heat exchange and incorporated an advection-driven hyporheic heat exchange routine. The model tracked heat transport through the hyporheic zone and exchange with the stream channel, while including the effects of hyporheic water age distribution on upwelling hyporheic temperatures. Results showed that shade and hyporheic exchange similarly damped diurnal temperature cycles and differentially altered seasonal cycles of our theoretical stream. In winter, hyporheic exchange warmed simulated channel temperatures whereas shade had little effect. In summer, both shade and hyporheic exchange cooled channel temperatures, though the effects of shade were more pronounced. Our simple-to-grasp analogies of ‘thermal insulation’ for shade effects and ‘thermal capacitance’ for hyporheic exchange effects on stream temperature encourage more accurate conceptualization of complex, dynamic heat exchange processes among the atmosphere, stream channel, and alluvial aquifer.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Novel Geochemistry Determined from High P-T Simulation Experiments of HFTS 2

A standard method in unconventional oil and gas production is the process of hydraulic fracturing followed by a shut-in period, during which the fracture fluid remains pressurized in the reservoir for up to three weeks before production begins. Despite this widely used process, very little is known about what occurs in the reservoir during this shut-in process. In order to properly delineate potential reservoir reactions that may occur during shut-in that would lead to corrosion and scaling events, experiments were conducted in high pressure, high temperature reactors to simulate conditions of the Wolfcamp Formation in the Delaware Basin. Experimental design allowed the assessment of the effect of proppant, microbiology, and time on the mineralogy and fluid chemistry in the reservoir. Results suggest the biggest impact on fluid chemistry and shale mineralogy during shut-in is time. Analyses demonstrate dissolution of the shale material, with maximum dissolved ions occurring after 7 days of the shut-in period. After 21 days, results suggest precipitation occurs. The Delaware Basin is demonstrated to be high in sulfate content, which further increases in the fluid due to dissolution reactions during shut-in. The pressure vessel experiments suggest there was no significant contribution to reactions from microbiology during the shut-in period. However, early production samples demonstrate a significant selection of the microorganism Caminicella, a genus of which has previously been correlated to corrosion and sulfide production. Results suggest shut-in conditions may provide high sulfate concentrations that could later be utilized by a shifted microbial community to drive potential well infrastructure failure. This is the first study to incorporate microbiology, mineralogy, and fluid chemistry to investigate the fundamental geochemical reactions that occur during shut-in and early phase production of the Delaware Basin. Results from this study can complement observations from the Hydraulic Fracture Test Site 2 observations.

Gulliver, Djuna↗

DOE OSTI2022

Optimizing radar scan strategies for tracking isolated deep convection using observing system simulation experiments

Abstract. Optimizing radar observation strategies is one of the most important considerations in pre-field campaign periods. This is especially true for isolated convective clouds that typically evolve faster than the observations captured by operational radar networks. This study investigates uncertainties in radar observations of the evolution of the microphysical and dynamical properties of isolated deep convective clouds developing in clean and polluted environments. It aims to optimize the radar observation strategy for deep convection through the use of high-spatiotemporal cloud-resolving model simulations, which resolve the evolution of individual convective cells every 1 min, coupled with a radar simulator and a cell tracking algorithm. The radar simulation settings are based on the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field campaigns held in the Houston, TX, area but are generalizable to other field campaigns focusing on isolated deep convection. Our analysis produces the following four outcomes. First, a 5–7 m s−1 median difference in maximum updrafts of tracked cells is shown between the clean and polluted simulations in the early stages of the cloud lifetimes. This demonstrates the importance of obtaining accurate estimates of vertical velocity from observations if aerosol impacts are to be properly resolved. Second, tracking of individual cells and using vertical cross section scanning every minute capture the evolution of precipitation particle number concentration and size represented by polarimetric observables better than the operational radar observations that update the volume scan every 5 min. This approach also improves multi-Doppler radar updraft retrievals above 5 km above ground level for regions with updraft velocities greater than 10 m s−1. Third, we propose an optimized strategy composed of cell tracking by quick (1–2 min) vertical cross section scans from more than one radar in addition to the operational volume scans. We also propose the use of a single-RHI (range height indicator) updraft retrieval technique for cells close to the radars, for which multi-Doppler radar retrievals are still challenging. Finally, increasing the number of deep convective cells sampled by such observations better represents the median maximum updraft evolution with sample sizes of more than 10 deep cells, which decreases the error associated with sampling the true population to less than 3 m s−1.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data

Abstract Recent advances in machine learning, specifically transformer architecture, have led to significant advancements in commercial domains. These powerful models have demonstrated superior capability to learn complex relationships and often generalize better to new data and problems. This paper presents a novel transformer-powered approach for enhancing prediction accuracy in multi-modal output scenarios, where sparse experimental data is supplemented with simulation data. The proposed approach integrates transformer-based architecture with a novel graph-based hyper-parameter optimization technique. The resulting system not only effectively reduces simulation bias, but also achieves superior prediction accuracy compared to the prior method. We demonstrate the efficacy of our approach on inertial confinement fusion experiments, where only 10 shots of real-world data are available, as well as synthetic versions of these experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Human reliability analysis studies from simulator experiments using Bayesian inference

Probabilistic Safety Assessment (PSA) of complex facilities is performed to arrive at the risk posed by them. PSA also accounts for the contribution of the human errors towards the overall risk through Human Reliability Analysis (HRA) in terms of Human Error Probability (HEP). Human operators are part of the system and do not work in isolation. Their performance is influenced by the context in which the actions are performed. As a result, quantification of HEP requires operator performance data under the given context. Some good sources of operator performance data are plant‘s operation data, simulator data and expert judgement. The plant operation data pertaining to HRA is generally sparse. In this situation, a full scope plant simulator provides a good alternative for operator performance data generation. Many of the currently practiced HRA methods have been developed by combining the empirical evidence with expert judgement and contain a lot of uncertainty in their estimates. Bayesian inference is suitable for updating the prior HRA estimates with the simulator evidence to obtain the posterior HEP. Here, posterior HEP has been calculated for postulated accident scenarios in advanced reactor (first of its kind) at design stage, using plant simulator.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Quantifying automated vehicle benefits in reducing driving stress: a simulation experiment approach

Driving is a stressful activity because of the mental workload required to maneuver a vehicle in certain travel contexts, such as congested traffic, multi-modal networks requiring complex interaction with surrounding vehicles, and aggressive driving. Autonomous vehicles (AVs), on the other hand, can reduce the mental workload by performing most of the driving tasks and providing users with a comfortable ride. This study develops a pathway model to relate different health determinants, including travel reliability, safety, driving comfort, and value of time, to Autonomous vehicles driving and studies their impact on the value of driving stress. A case study example of Autonomous vehicles simulation is used to determine the impact of these health determinants. The value of driving stress in Autonomous vehicles is estimated as a function of the value of these individual health determinants. The results show that the perception of safe or unsafe driving in Autonomous vehicles is the most important factor in changing the perception of driving stress in Autonomous vehicles. Similarly, perceptions of comfortable driving in Autonomous vehicles and reduced workload with a higher value of time also reduce driving stress in Autonomous vehicles. These results allow Autonomous vehicles adoption models to explicitly consider driving stress reduction as a benefit and can improve understanding of Autonomous vehicles adoption, which may require quantitative analysis of underlying motivating benefits, including driving stress reduction.

Khattak, Zulqarnain H.↗

DOE OSTI2024

Automatic Multiple Experiment Simulation and Fitting (Ames-Fit)

AMES-Fit is a program used to automatically fit the multi-field solid-state NMR spectra of half-integer quadrupolar nuclei. Due to the high dimensional space, gradient algorithms have failed to address the fitting of such data, which is at present done manually. AMES-Fit diverges from these approaches by using an adaptive step size random search algorithm to fit the NMR spectra to consistently find the global best fit parameters.

Perras, Frederic↗

DOE OSTI2021

The Usage of Observing System Simulation Experiments and Reinforcement Learning to Optimize Experimental Design and Operation

Various organizations regularly conduct field campaigns across the globe designed to probe and improve atmospheric process understanding. However, these campaigns are mostly designed ad-hoc, and rely on anecdotes and knowledge of what was successful in previous campaigns. Such ad-hoc experiment design results in sub-optimal instrument siting and operation strategies. Inadequate targeted data collection of extreme weather is a major limitation to Earth and Environmental Systems Science Division (EESSD)’s goals of data model integration (4.5.3), which limits the knowledge gained through the collected observations, holding back significant advances in predictability. While advances in instrument design are always chipping away at these limitations, we are not optimally utilizing the instrumentation we currently possess.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Molten Salt Reactor Experiment Simulation using Shift/Griffin

The Department of Energy (DOE)’s NEAMS focuses its efforts on the development of advanced modeling and simulation (M&S) tools for light-water reactors (LWRs) and non–LWRs (i.e., molten salt reactors, high-temperature gas reactors, microreactors, and fast reactors). In the previous fiscal year, the Multiphysics Applications Driver Technical Area funded molten salt reactor (MSR) M&S at Oak Ridge National Laboratory (ORNL) to generate multigroup macroscopic cross sections with Shift for a MSRE 2D lattice model in Griffin. In addition, Shift’s capability to calculate gamma dose rates from activated components in the primary exchangers in a molten salt breeder reactor was also demonstrated. In fiscal year 2023, ORNL generated multigroup macroscopic cross sections using Shift for a 3D MSRE core model. MSRE depletion calculations using Griffin were also demonstrated in this fiscal year. For the depletion calculation, one-group microscopic cross sections for the 3D MSRE core were generated using Shift, and the decay transmutation library from ORIGEN was converted to an ISOXML file, which is required as input in Griffin. Several Monte Carlo codes, such as OpenMC and Serpent, were also used to benchmark and supplement multigroup cross sections generated by Shift. Multigroup libraries were generated with 8 and 20 group structures, and the study found the 8-group structure to be more accurate when comparing Griffin results to continuous energy (CE) Monte Carlo results. The average flux from CE Shift calculations is up to ~6% higher than the CE Serpent calculations because of different values applied for the energy released per fission (κ values). The average flux in the fuel salt calculated by Griffin using cross sections generated with Shift agrees well with the reference CE Shift solution; the same is valid for the corresponding Serpent results. The maximum relative error is ~6% and ~2% compared to the CE Shift and Serpent reference solutions, respectively. Meanwhile, the average flux calculated by Griffin in the graphite moderator shows a higher difference in the thermal range when compared to both reference Monte Carlo solutions; this result suggests a need for improvement in cross section generation for the graphite moderator in the thermal range in both Monte Carlo codes. Griffin depletion calculations using cross sections from Shift and Serpent were performed and compared against ORIGEN calculations, and the nuclide densities calculated by Griffin were found to be generally in agreement with those of ORIGEN. Because a different approach was taken to calculate the energy released per fission ( κ values) in Shift and Serpent, a difference in nuclide densities from differences in the average flux was observed between Griffin using Serpent and Shift cross sections. Griffin calculations with Shift cross sections produced higher average flux in the salt than with Serpent cross sections, leading to higher consumption of 235 U and higher production of 135 Xe. For time-dependent depletion calculations, cross sections were generated with Serpent, and Griffin’s results using these cross sections were compared to CE Serpent depletion results, demonstrating good agreement. The average difference in keff between Serpent and Griffin as a function of burnup is about 155 pcm. Similarly, good agreement with small differences up to ~0.5% was also noticed in the nuclide density of 235 U and 135 Xe. More details regarding the methodologies invoked to generate the cross section to make code-to-code comparisons are discussed further in this report. User feedback on Griffin and Shift capabilities that will enhance these calculations is provided in this report for future consideration. The work performed this fiscal year can be extended further for multiphysics coupling of Griffin-Pronghorn/SAM with Mole to study precursor flow and salt chemistry.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Integrating Experiments, Simulations, and Artificial Intelligence to Accelerate the Discovery of High-Performance Green Composites

The imperative for incorporating greener materials into the aerospace industry necessitates addressing significant challenges associated with the microstructural variability exhibited by recycled and sustainable feedstocks. In this study, we propose an integrated methodology that combines experimental investigations, finite element analysis, and artificial intelligence to develop sustainable composites with consistent properties. Our approach utilizes a pipeline comprising an automated mechanical tester, a finite element method simulator, and a convolutional neural network predictor to identify and optimize fabrication parameters for achieving desired mechanical characteristics in composites. By employing a nested-loop pipeline, our methodology improves sample efficiency, accuracy, and effectively bridges the gap between simulations and real-world performance. This unique methodology offers a promising avenue for facilitating the adoption of aerospace-appropriate green composites.

Athanasiou, Christos↗

DOE OSTI2026

X501 Experiment Simulation and PIE Data Comparison

Fuel performance simulations have been developed for X501 MA bearing fuel in BISON. The results of these simulations are compared with PIE results to assess the applicability of metallic fuel models in BISON to MA bearing metallic fuel.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Digital quantum simulation of NMR experiments

Simulations of nuclear magnetic resonance (NMR) experiments can be an important tool for extracting information about molecular structure and optimizing experimental protocols but are often intractable on classical computers for large molecules such as proteins and for protocols such as zero-field NMR. We demonstrate the first quantum simulation of an NMR spectrum, computing the zero-field spectrum of the methyl group of acetonitrile using four qubits of a trapped-ion quantum computer. We reduce the sampling cost of the quantum simulation by an order of magnitude using compressed sensing techniques. We show how the intrinsic decoherence of NMR systems may enable the zero-field simulation of classically hard molecules on relatively near-term quantum hardware and discuss how the experimentally demonstrated quantum algorithm can be used to efficiently simulate scientifically and technologically relevant solid-state NMR experiments on more mature devices. Our work opens a practical application for quantum computation.

74 ATOMIC AND MOLECULAR PHYSICS↗