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At least 595 records · Page 33

Efficient Monte Carlo With Graph-Based Subsurface Flow and Transport Models

Simulating flow and transport in fractured porous media frequently involves solving numerical discretizations of partial differential equations with a large number of degrees of freedom using discrete fracture network (DFN) models. Uncertainty in the properties of the fracture network that controls flow and transport requires a large number of DFN simulations to statistically describe quantities of interest. However, the computational cost of solving more than a few realizations of a large DFN can be intractable. As a means of circumventing this problem, we utilize both a high-fidelity DFN model and a graphbased model of flow and transport in combination with a multifidelity Monte Carlo (MC) method to reduce the number of high-fidelity simulations that are needed to obtain an accurate estimate of the quantity of interest. We demonstrate the approach by estimating quantiles of the breakthrough time for a conservative tracer in an ensemble of fractured porous media. Our results demonstrate that a multifidelity MC estimate, whose computational cost is equal to the cost of 10 DFN simulations, can be as accurate as a standard MC estimate that utilizes 1,000 DFN simulations. Thus the combination of our graphbased model with multifidelity MC estimates effectively reduces the computational cost of the problem by a factor of approximately 100.

58 GEOSCIENCES↗

Global tropical cyclone precipitation scaling with sea surface temperature

Understanding the relationship between tropical cyclone (TC) precipitation and sea surface temperature (SST) is essential for both TC hazard forecasting and projecting how these hazards will change in the future due to climate change. This work untangles how global TC precipitation is impacted by present-day SST variability (known as apparent scaling) and by long-term changes in SST caused by climate change (known as climate scaling). A variety of datasets are used including precipitation and SST observations, realistic climate model simulations, and idealized climate model simulations. The apparent scaling rates depend on precipitation metric; examples shown here have ranges of 6.1 to 9.5% per K versus 5.9 to 9.8% per K for two different metrics. The climate scaling is estimated at about 5% per K, which is slightly less than the atmospheric moisture scaling based on thermodynamic principles of about 7% per K (i.e., the Clausius–Clapeyron scaling). The apparent scaling is greater than the climate scaling, which implies that the relationship between TC precipitation and present-day SST variability should not be used to project the long-term response of TC precipitation to climate change.

54 ENVIRONMENTAL SCIENCES↗

Extension of Virtual Test Bed Advanced Modeling and Simulation Capabilities for Fusion Energy

The National Reactor Innovation Center (NRIC) was established to accelerate the deployment of novel reactor concepts. This is achieved by providing physical and virtual spaces for building and testing reactor experiments. The Virtual Test Bed (VTB) represents the virtual counterpart to the physical test beds. It is a collaboration with the Department of Energy’s (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program with the mission to accelerate the deployment of advanced reactors by facilitating the adoption of advanced modeling and simulation (M&S) tools developed by the DOE. This mission has been carried out by the VTB since 2020 by hosting and featuring dozens of advanced fission nuclear reactor models developed by national laboratories and academia. The charter of the NRIC’s definition of advanced reactors also includes fusion nuclear reactors. As the tools developed by the NEAMS program are increasingly used for modeling fusion energy devices, there is an increasing need to host fusion reactor models on the VTB repository. The VTB will be extended in 2024 to support fusion energy modeling and simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A hybrid finite volume method and smoothed particle hydrodynamics approach for efficient and accurate blast simulations

Modeling strong shock waves in fluids remains a persistent challenge in computational physics. Essential to research efforts in industry and defense, numerous methods have been devised to improve the accuracy and efficiency of shock simulations. A novel, hybrid Finite Volume Method (FVM)-Smoothed Particle Hydrodynamics (SPH) approach is capable of further improving efficiency and retaining accuracy by exploiting the favorable characteristics of each respective method. This hybrid approach is presented for shock capturing in compressible fluids. The Python framework Pyro2 is employed to simulate a coarse FVM mesh, while the Python framework PySPH is utilized to model the fluid in regions with high gradients through SPH particles. The performance of the hybrid FVM-SPH scheme, compared to the individual FVM and SPH methods, is assessed in 1 kt and 10 kt blast simulations. Our results indicate that the hybrid approach offers higher computational efficiency than SPH while preserving its accuracy and characteristics. The hybrid approach had a relative speedup of 11.3x and 22.3x over the FVM and SPH approaches for the 1 kt simulation and a relative speedup of 14.7x and 20.9x over the FVM and SPH approaches for the 10 kt simulation. The hybrid SPH algorithm enables future compressible fluid simulations with more extensive capabilities than grid-based methods alone, presenting potential applications in modeling fluid-structure interactions and solid deformation and fracturing in blast simulations.

Myers, Conner↗

Capturing the run-in of a pebble-bed reactor by using thermal feedback and high-fidelity neutronics simulations

Modeling the run-in of a pebble-bed reactor (PBR) can be challenging as a result of changes in the power, fuel type, and temperatures that occur throughout the run-in period. Previous work utilized high-fidelity neutronics simulations or lower-fidelity coupled neutronics/thermal-hydraulics models to capture the general characteristics of the run-in process. Here, the present work employs high-fidelity neutronics simulations (using Serpent) coupled with thermal-hydraulics simulations (using Griffin–Pronghorn) to capture the thermal feedback present during the run-in and approach to equilibrium for a PBR. Incorporating thermal feedback enables important distinctions to be made about conditions occurring inside the core, as the power distribution, discharge burnup, and isotopic compositions are all affected by the temperature distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A comparison of simple global kinetic models for coal devolatilization with the CPD model

Simulations of coal combustors and gasifiers generally cannot incorporate the complexities of advanced pyrolysis models, and hence there is interest in evaluating simpler models over ranges of temperature and heating rate that are applicable to the furnace of interest. In this paper, six different simple model forms are compared to predictions made by the Chemical Percolation Devolatilization (CPD) model. The model forms included three modified one-step models, a simple two-step model, and two new modified two-step models. These simple model forms were compared over a wide range of heating rates (5 × 10 3 to 10 6 K/s) at final temperatures up to 1600 K. Comparisons were made of total volatiles yield as a function of temperature, as well as the ultimate volatiles yield. Advantages and disadvantages for each simple model form are discussed. In conclusion, a modified two-step model with distributed activation energies seems to give the best agreement with CPD model predictions (with the fewest tunable parameters).

01 COAL, LIGNITE, AND PEAT↗

Analysis of permeability change in dissolving rough fractures using depth-averaged flow and reactive transport models

Many geophysical problems and engineering applications involve fluid flow through evolving faults and fractures. These situations are typical in CO 2 injection scenarios where supercritical CO 2 or CO 2 –saturated fluids are able to dissolve the solid matrix. Dissolution or precipitation within a fracture could lead to self-reinforcing or self-limiting behavior due to feedbacks from changes in permeability (k). There is limited predictive understanding of this phenomenon. Here, we investigated the case of fracture dissolution using a two-dimensional depth-averaged reactive transport model. The model simulated an acidic fluid dissolving a three-dimensional rough fracture. We observed different dissolution patterns across a wide range of geometric properties and different Peclet and Damkohler numbers (960 cases total). Despite this variation, a persistent linear increase in k with time (t) roughly manifested once the dissolution front advanced through the fracture. The time rate of change of k (k/t) is roughly constant for all simulations. The modeled rate is consistent with a theoretical value based on the parallel plates model and with experimentally derived values. Finally, the results confirm the common presence of linear time-dependence of fracture k due to self-reinforcement.

58 GEOSCIENCES↗

Incorporating an Interactive Fire Plume-Rise Model in the DOE's Energy Exascale Earth System Model Version 1 (E3SMv1) and Examining Aerosol Radiative Effect

The vertical distribution of biomass burning aerosol (BBA) is important in regulating their impacts on weather and climate. The plume-rise process affects the injection height of BBA and interacts with the air parcel lifting and cloud processes. However, these processes are not represented in most global climate models. In this study, we replaced the fixed vertical profiles of monthly BBA emissions in the Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume-rise model. The vertical distribution of BBA emissions was calculated as a function of ambient thermodynamic conditions from the host E3SMv1, with distributions of fire sizes and sensible heat fluxes derived from the observations. The maximum fire radiative power (FRP) technique was used to determine the fire size. Scaling-FRP technique is used to calculate the wildfire heat release. Daily BBA emission, superimposed with a fire diurnal cycle retrieved from the satellite observation, was included in model simulations. The model shows improved agreement with satellite retrievals and in situ measurement during the National Oceanic and Atmospheric Administration Wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen campaign. The model-observation comparison demonstrates the importance of the plume-rise model and fire diurnal cycle assumption in determining the BBA fields. We also find that E3SMv1 with new features produces a larger carbonaceous aerosol burden, leading to 0.13 W m –2 warming at the top of atmosphere compared to the default E3SMv1. This highlights the importance of accurately representing the BBA injection height and indicates a no-linear nature in the BBA-induced radiative effect.

54 ENVIRONMENTAL SCIENCES↗

Allometric scaling laws linking biomass and rooting depth vary across ontogeny and functional groups in tropical dry forest lianas and trees

There are two theories about how allocation of metabolic products occurs. The allometric biomass partitioning theory (APT) suggests that all plants follow common allometric scaling rules. The optimal partitioning theory (OPT) predicts that plants allocate more biomass to the organ capturing the most limiting resource. In this work, whole-plant harvests of mature and juvenile tropical deciduous trees, evergreen trees, and lianas and model simulations were used to address the following knowledge gaps: (1) Do mature lianas comply with the APT scaling laws or do they invest less biomass in stems compared to trees? (2) Do juveniles follow the same allocation patterns as mature individuals? (3) Is either leaf phenology or life form a predictor of rooting depth? It was found that: (1) mature lianas followed the same allometric scaling laws as trees; (2) juveniles and mature individuals do not follow the same allocation patterns; and (3) mature lianas had shallowest coarse roots and evergreen trees had the deepest. It was demonstrated that: (1) mature lianas invested proportionally similar biomass to stems as trees and not less, as expected; (2) lianas were not deeper-rooted than trees as had been previously proposed; and (3) evergreen trees had the deepest roots, which is necessary to maintain canopy during simulated dry seasons.

59 BASIC BIOLOGICAL SCIENCES↗

Use of a Reduced Order Model (ROM) to Simulate SOFC Performance in System Models

Numerical models for design and optimization of fuel cell-based power generation systems require an accurate representation of the SOFC stack performance over a wide range of operating conditions. Response surface techniques were used with detailed SOFC stack model results to create a computationally efficient reduced order model (ROM) of the stack that retains desirable information about its internal state, which can be important in system optimization studies to preclude operation under off-design conditions that can adversely impact overall reliability. A tool was developed to randomly sample selected input parameters, obtain stack solutions for these sampled cases, perform regression to obtain response surfaces for stack performance and other metrics of interest, and export the response surfaces as a ROM. The ROM was then successfully implemented in an Aspen Plus® system model for a natural gas fuel cell (NGFC) power system. Additional work to characterize the ROM’s approximation error is ongoing.

Modeling & Simulation↗

An Assessment of Geological Carbon Storage Options in the Illinois Basin: Validation Phase

The Midwest Geological Sequestration Consortium (MGSC) assessed the options for geological carbon dioxide (CO 2 ) storage in the 155,400 km 2 (60,000 mi 2 ) Illinois Basin, which underlies most of Illinois, western Indiana, and western Kentucky. The region has annual CO 2 emissions of about 265 million metric tonnes (292 million tons), primarily from 122 coal-fired electric generation facilities, some of which burn almost 4.5 million tonnes (5 million tons) of coal per year (U.S. Department of Energy, 2010). Validation Phase (Phase II) field tests gathered pilot data to update the Characterization Phase (Phase I) assessment of options for capture, transportation, and storage of CO 2 emissions in three geological sink types: coal seams, oil fields, and saline reservoirs. Four small-scale field tests were conducted to determine the properties of rock units that control injectivity of CO 2 , assess the total storage resources, examine the security of the overlying rock units that act as seals for the reservoirs, and develop ways to control and measure the safety of injection and storage processes. The MGSC designed field test operational plans for pilot sites based on the site screening process, MVA program needs, the selection of equipment related to CO 2 injection, and design of a data acquisition system. Reservoir modeling, computational simulations, and statistical methods assessed and interpreted data gathered from the field tests. Monitoring, Verification, and Accounting (MVA) programs were established to detect leakage of injected CO 2 and ensure public safety. Public outreach and education remained an important part of the project; meetings and presentations informed public and private regional stakeholders of the results and findings. A miscible (liquid) CO 2 flood pilot project was conducted in the Clore Formation sandstone (Mississippian System, Chesterian Series) at Mumford Hills Field in Posey County, southwestern Indiana, and an immiscible CO 2 flood pilot was conducted in the Jackson sandstone (Mississippian System Big Clifty Sandstone Member) at the Sugar Creek Field in Hopkins County, western Kentucky. Up to 12% incremental oil recovery was estimated based on these pilots. A CO 2 huff puff (HNP) pilot project was conducted in the Cypress Sandstone in the Loudon Field. This pilot was designed to measure and record data that could be used to calibrate a reservoir simulation model. A pilot project at the Tanquary Farms site in Wabash County, southeastern Illinois, tested the potential storage of CO 2 in the Springfield Coal Member of the Carbondale Formation (Pennsylvanian System), in order to gauge the potential for large-scale CO 2 storage and/or enhanced coal bed methane recovery from Illinois Basin coal beds. The pilot results from all four sites showed that CO 2 could be injected into the subsurface without adversely affecting groundwater. Additionally, hydrocarbon production was enhanced, giving further evidence that CO 2 storage in oil reservoirs and coal beds offers an economic advantage. Results from the MVA program at each site indicated that injected CO 2 did not leave the injection zone. Topical reports were completed on the Middle and Late Devonian New Albany Shale and Basin CO 2 emissions. The efficacy of the New Albany Shale as a storage sink could be substantial if low injectivity concerns can be alleviated. CO 2 emissions in the Illinois Basin were projected to be dominated by coal-fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

Great Lakes O shore Wind Project: Utility and Regional Integration Study

This project aims to identify transmission system upgrades needed to facilitate offshore wind projects as well as operational impacts of offshore generation on operation of the regional transmission system in the Great Lakes region. A simulation model of the US Eastern Interconnection was used as the test system as a case study for investigating the impact of the integration of a 1000MW offshore wind farm operating in Lake Erie into FirstEnergy/PJM service territory. The findings of this research provide recommendations on offshore wind integration scenarios, the locations of points of interconnection, wind profile modeling and simulation, and computational methods to quantify performance, along with operating changes and equipment upgrades needed to mitigate system performance issues introduced by an offshore wind project.

17 WIND ENERGY↗

Optimizing and Quantifying CO 2 Storage Resource in Saline Formations and Hydrocarbon Reservoirs

In an effort to reduce carbon dioxide (CO 2 ) emissions from large stationary sources, carbon capture and storage (CCS) is being investigated as one approach. This work assesses CO 2 storage resource estimation methods for deep saline formations (DSFs) and hydrocarbon reservoirs undergoing CO 2 enhanced oil recovery (EOR). Project activities were conducted using geologic modeling and simulation to investigate CO 2 storage efficiency. CO 2 storage rates and efficiencies in DSFs classified by interpreted depositional environment were evaluated at the regional scale over a 100-year time frame. A focus was placed on developing results applicable to future widespread commercial-scale CO 2 storage operations in which an array of injection wells may be used to optimize storage in saline formations. The results of this work suggest future investigations of prospective storage resource in closed or semiclosed formations need not have a detailed understanding of the depositional environment of the reservoir to generate meaningful estimates. However, the results of this work also illustrate the relative importance of depositional environment, formation depth, structural geometry, and boundary conditions on the rate of CO 2 storage in these types of systems. CO 2 EOR occupies an important place in the realm of geologic storage of CO 2 , as it is likely to be the primary means of geologic CO 2 storage during the early stages of commercial implementation, given the lack of a national policy and the viability of the current business case. This work estimates CO 2 storage efficiency factors using a unique industry database of CO 2 EOR sites and 18 different reservoir simulation models capturing fluvial clastic and shallow shelf carbonate depositional environments for reservoir depths of 1219 and 2438 meters (4000 and 8000 feet) and 7.6-, 20-, and 64-meter (25-, 66,- and 209-foot) pay zones. The results of this work provide practical information that can be used to quantify CO 2 storage resource estimates in oil reservoirs during CO 2 EOR operations (as opposed to storage following depletion) and the uncertainty associated with those estimates.

54 ENVIRONMENTAL SCIENCES↗

EVI-Equity

EVI-Equity (Electric Vehicle Infrastructure for Equity) is a $200k project, started around in June of 2021, with a funding from the Vehicle Technologies Office (VTO). The motivation was to create a new analytical capability that can enable us to quantify and investigate equitable access to and distribution of existing and future deployment of PEVs and EVSEs in neighborhoods, cities, states, and the nation. EVI-Equity is a bottom-up equity-focused analysis model, built upon individual (synthetic) households, aggregated by census block groups. It consists of four core components - community engagement, environmental profiling, household expenditures, and network design. Although there are some commonalities, EVI-Equity is not a vehicle choice model, charging simulation model, or transportation demand model. EVI-Equity is rather a cross-cutting analysis tool, dedicated for evaluating equitable EV adoption and EVSE deployment, encompassing and bridging a wide variety of related tools, models, and frameworks. Some of the results indicate the importance of used vehicle market for low-income households. The presentation also highlights similarities and variations as to preferred public charging locations. For example, regardless of household income, retail spots are the most preferred location for public charging, followed by curbside/street. However, the results also imply that the importance of workplace charging may vary with income - the lower the income, the less important. Environmental profiling results, with an example of ground-level ozone in Atlanta area, show that the contrast between the haves and the have nots of plug-in electric vehicles depends on location. The assessment of household expenditures illustrates the economic impact of home charging access on an individual household level - the lower the income, the greater the impact is. Lastly, Denver metro area and the state of South Dakota are used to showcase the impact of different network design of charging infrastructure, as well as alternative (vs. baseline/existing) electric vehicle adoption pattern.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

CAMPUS: Fully Coupled Multiphysics Modeling and Simulation of LWR and FBR Nuclear Fuel Behavior

Nuclear fuels operate in an environment that involves complex multiphysics phenomena, and the multiphysics behavior is often tightly coupled. The prediction of fuel behavior under irradiation involves very complex material behavior that is not seen in any other engineering discipline. Understanding and predicting the evolving material properties and phenomenal behaviors of nuclear fuels are major challenges for fuel design and behavior prediction. The multiphysics behavior is often a tightly coupled thermal, mechanical and chemical phenomenon associated with a large number of control parameters and uncertainties, which requires an advanced fuel performance modeling and simulation capability to improve the existing reactors performance, to address environmental and reactor safety concerns. Nuclear fuel performance modeling and simulation capability is necessary as a result of the high cost and difficulty in experimental measurements. So, a fuel performance code called CityU Advanced Multiphysics Nuclear Fuels Performance with User-defined Simulations (CAMPUS) was developed to predict both light water reactor and fast reactor fuel behavior. An effective approach was developed using self-defined multiphysics models based on the framework of COMSOL Multiphysics to manage the nonlinearities associated with light water reactor and fast reactor fuels performance analysis. The modelling and simulations approach is of particular importance since it demonstrates highly interrelated and nonlinear fuel performance models can be developed and implemented into a multiphysics platform, and thus more efforts can be put into physics model development and improvement. The modelling results can be used to identify the important phenomena and parameters, to direct and design experiments and to assist in post analysis of expensive nuclear experiments for light water reactor and fast reactor nuclear fuel performance analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗

Terry Turbopump Expanded Operating Band Modeling and Simulation Efforts in Fiscal Year 2020 - Progress Report

The Terry Turbine Expanded Operating Band Project is currently conducting testing at Texas A&M University as part of a revised experimental program meant to supplant previous full-scale testing plans under the headings of Milestone 5 and Milestone 6. In consultation with Sandia National Laboratories technical staff and with modeling and simulation support from the same, the hybrid Milestone 5&6 plan is moving forward with experiments aimed at addressing knowledge gaps regarding scale, working fluid, and turbopump self-regulation. Modeling and simulation efforts at Sandia National Laboratories in FY20 fell under the broad umbrella of Milestone 7 and consisted exclusively of MELCOR-related tasks aimed at: 1) Constructing/improving input models of Texas A&M University experiments, 2) Constructing a generic boiling water reactor input model according to best practices with systems-level Teny turbine capabilities, and 3) Adding code capability in order to leverage experimental data/findings, address bugs, and improve general code robustness Project impacts of the Covid-19 pandemic have fortunately been minimal thus far but are mentioned as necessary when discussing the hybrid Milestone 5&6 progress as well as the corresponding Milestone 7 modeling and simulation progress.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗