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At least 685 records · Page 38

Simulation study of chemo-mechanical impacts of CO 2 injection in morrow b sandstone reservoir

Here, this study investigates the impacts of geomechanical and geochemical changes on carbon storage in a partially depleted oil reservoir, using results from four different coupled simulation models. Models were used to examine the relative importance of storage mechanisms, and how changing reservoir parameters might affect these mechanisms through time. The study uses data from a Morrowan sandstone reservoir in the Farnsworth Unit (FWU), Ochiltree County, Texas which is currently undergoing CO 2 enhanced oil recovery (EOR). Partially depleted oil reservoirs such as the FWU offer attractive carbon utilization and/or storage targets because of existing infrastructure and economic benefits from incremental oil recovery as well as tax credits. However, prediction of storage capacity or long-term fluid migration in these fields can be difficult because of the wide variation in formation fluids and operational histories that may have undergone. CO 2 injection can cause complex geomechanical and geochemical responses in a reservoir as a result of interplay between dynamic changes in pore pressure, reservoir temperature, fluid composition, and interactions between formation fluids, CO 2 , and reservoir rock. Thus, multiple coupled numerical simulation models must be developed and used to more precisely understand what CO 2 storage mechanisms are most significant, as well as the long-term fate of the stored CO 2 . Our study used results from hydrodynamic, coupled hydro-geomechanical, coupled hydro-geochemical, and coupled hydro-geomechanical-geochemical models to examine how changes in geomechanical and geochemical properties can impact the injectivity or storage capacity of CO 2 . Models simulated historical field operations and then forward-modeled a water-alternate-gas (WAG) operation for 20 years, followed by a 1000-year post-injection monitoring. The work demonstrates that in this specific reservoir, geomechanical impacts appear to be more significant than any geochemical processes, which showed minimal impact on reservoir properties. Furthermore, these simulation scenarios corroborated other studies showing more than 90% of CO 2 injected are being stored and will remain stored in the reservoir. The study was able to draw on a rich set of data from this currently operational project for the work. Because the Morrow is a widespread oil-bearing reservoir in the midcontinent of the United States and is fairly typical of many sandstone reservoirs elsewhere, the study has significance beyond the boundaries of our field area.

58 GEOSCIENCES↗

Utility of near‐surface phenology in estimating productivity and evapotranspiration across diverse ecosystems

Abstract Agroecosystems, which include row crops, pasture, and grass and shrub grazing lands, are sensitive to changes in management, weather, and genetics. To better understand how these systems are responding to changes, we need to improve monitoring and modeling carbon and water dynamics. Vegetation Indices (VIs) are commonly used to estimate gross primary productivity (GPP) and evapotranspiration (ET), but these empirical relationships are often location and crop specific. There is a need to evaluate if VIs can be effective and, more general, predictors of ecosystem processes through time and across different agroecosystems. Near‐surface photographic (red‐green‐blue) images from PhenoCam can be used to calculate the VI green chromatic coordinate (G CC ) and offer a pathway to improve understanding of field‐scale relationships between VIs and GPP and ET. We synthesized observations spanning 76 site‐years across 15 agroecosystem sites with PhenoCam G CC and GPP or ET estimates from eddy covariance (EC) to quantify interannual variability (IAV) in the relationship between GPP and ET and G CC across. We uncovered a high degree of variability in the strength and slopes of the G CC ∼ GPP and ET relationships (R 2 = 0.1 ‐ 0.9) within and across production systems. Overall, G CC is a better predictor of GPP than ET (R 2 = 0.64 and 0.54, respectively), performing best in croplands (R 2 = 0.91). Shrub‐dominated systems exhibit the lowest predictive power of G CC for GPP and ET but have less IAV in slope. We propose that PhenoCam estimates of G CC could provide an alternative approach for predictions of ecosystem processes.

Environmental Sciences & Ecology↗

Step-loaded creep testing of Zircaloy-4 cladding at higher temperatures in the α-phase

A refined understanding of zirconium-based cladding thermomechanical performance during rapid transients is essential for enhancing the safety and operation of light-water reactors. Traditional models for zirconium alloys under accident conditions generally assume that creep dominates fuel cladding performance. Here, these historic models have largely remained unchanged and serve as the basis for safety criteria development. As the U.S. nuclear industry pursues higher burnup levels, the increased release of fission gases during transients raises the risk of cladding failure in the low-temperature hcp α-phase, making the fidelity of these models of greater importance. Creep testing was conducted from 550–700°C with 25–120 MPa applied hoop stresses to investigate Zircaloy-4 deformation at accident-relevant temperatures in the α-phase. Step-loading was employed to capture creep behavior across a wide stress range from a single sample. The stress-strain rate data at higher temperatures (650 and 700°C) were well-described by isotropic versions of the Erbacher and Kaddour models, while the lower temperature data (550 and 600°C) were underpredicted by both anisotropic and isotropic model variants. Greater strain rates during the initial loading step at 650 and 700°C were attributed to recrystallization and grain growth of sub-micron crystallites. Yet, texture analysis revealed the basal split texture remained after testing. These observations produced results suggesting Zircaloy-4 claddings experience higher creep rates across the α-phase than previously thought, possibly related to dynamic anisotropy due to temperature dependent activation of deformation mechanisms, effects of biaxial loading, and variation in material condition between the current testing used in previous model development.

36 MATERIALS SCIENCE↗

Feature extraction for subtle anomaly detection using semi-supervised learning

The demand for automated and effective monitoring techniques has soared with the increased digitization of industrial monitoring systems. State-of-the-art machine learning methods are effectively detecting abrupt changes in system states. However, these methods lack comparable maturity in detecting subtle changes that may be signs of incipient faults. This manuscript argues that the current anomaly detection methods can be enhanced by exploring weak patterns to enable subtle variation detection. Specifically, the concept of semi-supervised learning is employed, with labels representing knowledge about some anomalous conditions of a system. The basic idea is to extract a candidate set of weak patterns discarded by state-of-the-art baselining algorithms. With few labeled anomalous data, the algorithm selects the weak patterns and allows for their possible fusion using the highest sensitivity to the labeled anomalies. Here, the method’s applicability is demonstrated using a representative pressurized water reactor (PWR) model simulated by Dymola.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multiphysics analysis of fuel fragmentation, relocation, and dispersal susceptibility–Part 1: Overview and code coupling strategies

The US nuclear energy industry is investigating strategies to increase the reactor operating cycle to 24 months, resulting in peak rod average burnups exceeding the current limit of 62 GWd/tU. This increase will in turn increase the probability of fuel fragmentation, relocation, and dispersal (FFRD) in the event of a loss-of-coolant accident (LOCA). This effort couples multiple codes to (1) evaluate full-core power histories for high-burnup fuel operated in a Westinghouse 4-loop pressurized water reactor, (2) model a postulated large-break LOCA, and (3) calculate the mass of fuel susceptible to FFRD. This paper, the first of three describing the work, focuses on code coupling strategies and FFRD susceptibility calculations. The other two companion papers focus on code-specific designs and analyses. Three codes were used in this work. VERA was used to calculate steady-state power histories, TRACE was used to model the transient thermal hydraulics, and BISON was used to model steady-state and transient fuel performance and cladding failure. Herein, several fuel pulverization models were used to calculate FFRD susceptibility in failed rods. Depending on the cladding failure/fuel pulverization model combination, the core-wide FFRD susceptibility during the postulated LOCA range from 0 to over 5,000 kg.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance study of the cross-flow Maisotsenko cycle in humid climate conditions

This paper presents a first numerical analysis of the cross-flow Maisotsenko cycle (M-Cycle) below dew-point evaporative cooler for humid climates with model including the water vapor condensation phenomenon. Proposed solution allows to cool ambient air below its dew-point temperature, by utilizing cooling energy in air extracted from the building, due to that it can be used as effective pre-cooling solution for traditional systems. Proposed unit has significant advantage over traditional counter and cross-flow units operating in heat recovery mode, hence it is almost insensitive on temperature of exhaust air. This is caused by effective pre-cooling of the exhaust air in its initial part. Operation in humid climates using cold extracted air results in condensation occurrence in the primary air channels, and hence partial dehumidification of the primary airflow (which allows to cool the air before its dew- point temperature). The Maisotsenko cycle exchanger used to recover heat in the air-conditioning system is compared with Maisotsenko exchanger that operates only on the ambient airflow and does not allow to recover heat from the exhaust airflow from a conditioned space. Achieved results showed that M-Cycle below dew-point air cooler can operate more effectively in humid climates than traditional cross-flow Maisotsenko cycle exchanger.

Condensation↗

Numerical implementation of the MOOSE subchannel module (SCM) algorithm

The subchannel module of moose (SCM), previously referred to as Pronghorn-SC, is a subchannel code designed to resolve single-phase flow fields and calculate the relevant flow variables, in nuclear reactor fuel-pin assemblies. The assemblies it models are: water-cooled, with bare fuel-pins in a square ducted, quadrilateral lattice and liquid-metal/water-cooled, with bare/wire-wrapped fuel pins in a hexagonal ducted, triangular lattice. Previous publications have presented the development, validation and verification of SCM. This work presents an comparative overview of the different solvers implemented within SCM. This includes the solver algorithm description, and a performance comparison. The two test cases chosen to demonstrate the solver performance were taken from the PSBT enthalpy mixing benchmark and the ORNL-19 pin benchmark.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Sequence Modulates Polypeptoid Hydration Water Structure and Dynamics

We use molecular dynamics simulations to investigate the effect of polypeptoid sequence on the structure and dynamics of its hydration waters. Polypeptoids provide an excellent platform to study small-molecule hydration in disordered polymers, as they can be precisely synthesized with a variety of sidechain chemistries. We examine water behavior near a set of peptoid oligomers in which the number and placement of nonpolar versus polar sidechains are systematically varied. To do this, we leverage a new computational workflow enabling accurate sampling of polypeptoid conformations. We find that the hydration waters are less dense, are more tetrahedral, and have slower dynamics compared to bulk water. The magnitude of these shifts increases with the number of nonpolar groups. Here, we also find that shifts in the water structure and dynamics are strongly correlated, suggesting that experimental insight into the dynamics of hydration water obtained by Overhauser dynamic nuclear polarization (ODNP) also contains information about water structural properties. We then demonstrate the ability of ODNP to probe site-specific dynamics of hydration water near these model peptoid systems.

36 MATERIALS SCIENCE↗

Harnessing Photoelectrochemistry for Wastewater Nitrate Treatment Coupled with Resource Recovery

Wastewater is a misplaced resource well suited to recover nutrients, value-added chemicals, energy, and clean water. A photoelectrochemical device is proposed to transform wastewater nitrates to ammonia and nitrous oxide, coupled with water oxidation. Numerical models were developed to quantify the dependence of process efficiencies and nitrogen-removal rates on light absorber band gaps, electrocatalytic kinetic parameters, competing oxygen reduction and hydrogen evolution reactions, and the reacting nitrate species concentrations that affect the mass-transfer limited current densities. With a single light-absorber and state-of-the-art catalysts, optimal solar-to-chemical efficiencies of 7% and 10% and nitrogen-removal rates of 260 and 395 gN m -2 day -1 are predicted for nitrate reduction to ammonia and nitrous oxide, respectively. The influence of competing reactions on the performance depends on the nitrate concentration and band gap of the light absorber modeled. Oxygen reduction is more dominant than hydrogen evolution to compete with the nitrate reduction reaction, but it is mass-transfer limited. Even with kinetic parameters that enhanced the driving forces for the competing reactions, the performance is only minimally affected by these reactions for optimally selected band gaps and nitrate concentrations larger than 100 mM. Here, theoretically predicted peak nitrogen removal rates and specific energy intensities are competitive with reported estimates for electrochemical and Sharon-Anammox processes for ammonia recovery and nitrogen removal, respectively. This result, together with the added benefit of harnessing sunlight to produce value-added products, indicates promise in the photoelectrochemical approach as a tertiary pathway to recover nutrients and energy from wastewater nitrates.

25 ENERGY STORAGE↗

Multilevel Computational Studies Reveal the Importance of Axial Ligand for Oxygen Reduction Reaction on Fe–N–C Materials

The systematic improvement of Fe–N–C materials for fuel cell applications has proven challenging, due in part to an incomplete atomistic understanding of the oxygen reduction reaction (ORR) under electrochemical conditions. Herein, a multilevel computational approach, which combines ab initio molecular dynamics simulations and constant potential density functional theory calculations, is used to assess proton-coupled electron transfer (PCET) processes and adsorption thermodynamics of key ORR intermediates. These calculations indicate that the potential-limiting step for ORR on Fe–N–C materials is the formation of the Fe III –OOH intermediate. They also show that an active site model with a water molecule axially ligated to the iron center throughout the catalytic cycle produces results that are consistent with the experimental measurements. In particular, reliable prediction of the ORR onset potential and the Fe(III/II) redox potential associated with the conversion of Fe III –OH to Fe II and desorbed H 2 O requires an axial H 2 O co-adsorbed to the iron center. The observation of a five-coordinate rather than four-coordinate active site has significant implications for the thermodynamics and mechanism of ORR. Importantly, these findings highlight the importance of solvent–substrate interactions and surface charge effects for understanding the PCET reaction mechanisms and transition-metal redox couples under realistic electrochemical conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Leaf Wax Hydrogen Isotopes Reflect Storm Track Position Over Western North America

Proxy records of past climates have yielded powerful insights into regional hydroclimate dynamics. Novel insights may be gained by reconstructing spatiotemporal changes in precipitation isotopologues in past climate states that cannot be gleaned from individual site‐level studies. In this paper, we ask whether latitudinal gradients in the stable hydrogen isotopic composition of precipitation, as inferred from sedimentary leaf wax biomarkers, reflect aspects of large‐scale climate conditions in western North America (WNA). Modern coretop samples from offshore WNA show that leaf wax hydrogen isotopes broadly track the hydrogen isotopic composition of rainfall between 20 and 40N, but with an offset corresponding to a relatively constant “apparent fractionation” value. Poleward of 40N, the leaf wax signal may be complicated by fluvial transport of leaf waxes from the continental interior. Leaf wax‐inferred precipitation hydrogen isotopes show a shift to more negative values between 30 and 40N. We use modern observational data to show that this latitudinal range marks a major transition between the subtropical arid zone and the location of the midlatitude storm tracks over the northeast Pacific. Nudged water isotope‐enabled models capture the location of the arid to mesic climate transition with fidelity. This modern data set suggests that reconstructions of the latitudinal gradient of precipitation hydrogen isotopes can constrain the sensitivity of the storm tracks to shifts in climatic boundary conditions in past climate states. This approach can yield novel insights into past, present, and future hydroclimate variability in this arid region.

54 ENVIRONMENTAL SCIENCES↗

Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs

Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. Trade-offs are often assumed to be bidirectional, where opposite ends of a gradient in trait values confer advantages in different environments. However, unidirectional benefits could be widespread if extreme trait values confer advantages at one end of an environmental gradient, whereas a wide range of trait values are equally beneficial at the other end. Here, we show that root traits explain species occurrences along broad gradients of temperature and water availability, but model predictions only resembled trade-offs in two out of 24 models. Forest species with low specific root length and high root tissue density (RTD) were more likely to occur in warm climates but species with high specific root length and low RTD were more likely to occur in cold climates. Unidirectional benefits were more prevalent than trade-offs: for example, species with large-diameter roots and high RTD were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Directional selection for traits consistently occurred in cold or dry climates, whereas a diversity of root trait values were equally viable in warm or wet climates. Explicit integration of unidirectional benefits into ecological theory is needed to advance our understanding of the consequences of trait variation on species responses to environmental change.

54 ENVIRONMENTAL SCIENCES↗

DFT-based QM/MM with Particle-Mesh Ewald for Direct, Long-Range Electrostatic Embedding

In this work, we present a DFT-based, QM/MM implementation with long-range electrostatic embedding achieved by direct real-space integration of the particle mesh Ewald (PME) computed electrostatic potential. The key transformation is the interpolation of the electrostatic potential from the PME grid to the DFT quadrature grid, from which integrals are easily evaluated utilizing standard DFT machinery. We provide benchmarks of the numerical accuracy with choice of grid size and real-space corrections, and demonstrate that good convergence is achieved while introducing nominal computational overhead. Furthermore, the approach requires only small modification to existing software packages, as is demonstrated with our implementation in the OpenMM and Psi 4 software. After presenting convergence benchmarks, we evaluate the importance of long-range electrostatic embedding in three solute/solvent systems modeled with QM/MM. Water and BMIM/BF 4 ionic liquid were considered as "simple" and "complex" solvents respectively, with water and p-phenylenediamine (PPD) solute molecules treated at QM level of theory. While electrostatic embedding with standard real-space truncation may introduce negligible error for simple systems such as water solute in water solvent, errors become more significant when QM/MM is applied to complex solvents such as ionic liquids. An extreme example is the electrostatic embedding energy for oxidized PPD in BMIM/BF 4 for which real-space truncation produces severe error even at 2-3 nm cutoff distances. This latter example illustrates that utilization of QM/MM to compute redox potentials within concentrated electrolytes/ionic media requires carefully chosen long-range electrostatic embedding algorithms, with our presented algorithm providing a general and robust approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of Timber Mountain Recharge and Groundwater Flow in Relation to Pahute Mesa-Oasis Valley Flow System

The purpose of this study was to evaluate the effect of Timber Mountain recharge on groundwater flow in the surrounding Pahute Mesa-Oasis Valley groundwater basin using several different methodologies. These methodologies included examining climatic and soil moisture data, estimating groundwater recharge by chloride mass balance, interpreting water chemical and isotopic data, and modeling groundwater flow along faults.

54 ENVIRONMENTAL SCIENCES↗

Summary of Development for Structural Component Modeling in Fiscal Year 2022

This report summarizes efforts performed during Fiscal Year 2022 to develop capabilities for modeling structural component degradation in support of the U.S. Department of Energy's Nuclear Energy Advanced Modeling and Simulation Program. These efforts were centered around development of capabilities for the Grizzly code. Efforts focused both on foundational engineering-scale analysis capabilities for damage and shell formulations and on material-scale tools for accounting for irradiation effects in Grade 91 steel. A major outcome of this effort was the development of a general-purpose tool for nonlocal averaging of material properties, which enabled nonlocal damage models. In addition, the applicability of the shell elements in MOOSE has been expanded to allow modeling a wider range of component geometries and using a wide variety of material models. For irradiation effects on materials, a previously developed cluster dynamics model for light water reactor pressure vessel steels has been adapted for application to Grade 91 alloy. This work builds on prior efforts to build a flexible, capable code for addressing a variety of aging and component performance issues in nuclear power plant structural components.

36 MATERIALS SCIENCE↗

Semi-Annual Report for Horizontal Compact High Temperature Gas Reactor (HC-HTGR) Development during Performance Period October 2022-March 2023

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary heat transport system to ensure temperatures in the reactor systems, structures and components with significant safety margins during normal operation and design basis accident scenarios. This third semi-annual report summarized the progress made at Argonne on the two tasks during the first half of FY23. As a part of the RCCS design task, a design process for the water panel and the system configuration was performed to improve the thermal performance of the RCCS. The updated water panel design had achieved enhanced thermal performance with 0.96 MWth capability with major design updates made in structural interfaces with the RPV and initial configuration of the water tanks. The loop configuration of the RCCS has been proposed to have two independently working loops for system redundancy. A water panel material study was performed focusing on the use of carbon steel in water systems. Additional modeling strategies of primary system thermal fluids analyses were developed to meet modeling needs that are not well suited for the 1D-3D assembly level approach. The first of these is a reduced order assembly model, in which fuel centered unit cells are used to represent a fuel assembly. The 2D approach used in this model is much more computationally efficient, making this model useful for full core transient scenarios where fuel to coolant heat transfer is still the dominant flow path. The next model is the 3D core conduction model to be used to analyze decay heat removal in loss of primary system flow scenarios. Because these scenarios require a large domain to be modeled, a homogenized core model is being pursued to reduce the required computational costs. To accurately model decay heat scenarios it is necessary to couple a RCCS model to the 3D core conduction model. A simplified case is presented to demonstrate how the coupling methodology will be applied to the full core 3D conduction model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Examples of Mission-driven Data Science from Jefferson Lab and ACES

This presentation details mission-driven data science initiatives at Jefferson Lab and the Joint Institute for Advanced Computing on Environmental Studies (ACES). JLab, a U.S. Department of Energy Office of Science national laboratory, operates the Continuous Electron Beam Accelerator Facility (CEBAF), and is the lead institute for the new High Performance Data Facility (HPDF) Hub. The Joint Institute for ACES brings together interdisciplinary teams in health informatics, climate modeling, computer science, and physics to address environmental challenges, including flood modeling. The Hampton Roads region, particularly Norfolk and Virginia Beach, faces increasing flood risks, motivating the need for rapid, reliable, and risk-aware decision support. ACES’s flooding work has a focus on uncertainty quantification (UQ) and machine learning (ML) for coastal flood management. The work is motivated by the increasing vulnerability of communities such as Norfolk and Virginia Beach, Virginia, to frequent coastal flooding events, and the need for rapid, reliable decision support. The research develops computationally efficient ML surrogate models to forecast water levels and flooding risk. A central theme is the quantification and calibration of predictive uncertainty, especially for out-of-distribution (OOD) scenarios, using techniques such as Monte Carlo Dropout, Deep Ensembles, Gaussian Processes, and Deep Quantile Regression (DQR). The study demonstrates that distance-aware UQ is critical for reliable scientific AI, particularly in high-dimensional, safety-critical, and real-time applications.

McSpadden, Diana [Thomas Jefferson National Accele↗