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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

Nuclear magnetic resonance dark-matter searches are sensitive to dark photons and the axion-photon coupling

We demonstrate that nuclear magnetic resonance based searches for dark matter (DM) have intrinsic and powerful sensitivity to dark photons and the axion-photon coupling. The reason is conceptually straightforward. An instrument such as CASPEr-Gradient begins with a large sample of nuclear spins polarized in a background magnetic field. In the presence of axion DM coupled to nucleons, the spin ensemble feels an effective magnetic field 𝐁 ∝ ∇𝑎 that tilts the spins, generating a potentially observable precession. If the magnetic field is real rather than effective, the system responds identically. A real field can be generated by a kinetically mixed dark photon within the shielded region the sample is placed or an axion coupled to photons through its interaction with the background magnetic field. We show that all three signals are detectable and distinguishable. If CASPEr-Gradient were to reach the QCD axion prediction of the axion-nucleon coupling, it would simultaneously be sensitive to kinetic mixings of 𝜀 ≃ 3 × 10 −16 and axion-photon couplings of 𝑔 𝑎⁢𝛾⁢𝛾 ≃ 2 × 10 −16 GeV −1 for 𝑚 ≃ 1 𝜇⁢eV. Our analysis demonstrates that CASPEr-Gradient has the tantalizing possibility of simultaneously measuring two separate couplings of axion dark matter, thereby providing a unique window into the axion’s UV completion.

Beadle, Carl [University of Geneva (Switzerland)] ↗

Geometric origin of the intrinsic transverse spin transport in a canted-antiferromagnet/heavy-metal heterostructure

We theoretically study the conditions under which an intrinsic spin Nernst effect–a transverse spin current induced by an applied temperature gradient–can occur in a canted-antiferromagnet insulator, such as LaFeO 3 and other materials of the same family. The spin Nernst effect may provide a microscopic mechanism for an experimentally observed anomalous thermovoltage in LaFeO 3 /Pt heterostructures, where spin is transferred across the insulator/metal interface when a temperature gradient is applied to LaFeO 3 parallel to the interface. We find that LaFeO 3 exhibits an intrinsic spin Nernst effect when inversion symmetry is broken on the axes parallel to both the applied temperature gradient and the direction of spin transport, which can result in a spin injection across the insulator/metal interface. Furthermore, our paper provides a general derivation of a symmetry-breaking-induced spin Nernst effect, which may open a path to engineering a finite spin Nernst effect in systems where it would otherwise not arise.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Chemomechanics in alloy phase stability

We describe a first-principles statistical mechanics method to calculate the free energies of crystalline alloys that depend on temperature, composition, and strain. The approach relies on an extension of the alloy cluster expansion to include an explicit dependence on homogeneous strain in addition to site occupation variables that track the degree of chemical ordering. The method is applied to the Si-Ge binary alloy and is used to calculate free energies that describe phase stability under arbitrary epitaxial constraints. We find that while the incoherent phase diagram (in which coexisting phases are not affected by coherency constraints) hosts a miscibility gap, coherent phase equilibrium predicts ordering and negative enthalpies of mixing. Instead of chemical instability, the chemomechanical free energy exhibits instabilities along directions that couple the composition of the alloy with a volumetric strain order parameter. Furthermore, this has fundamental implications for phase field models of spinodal decomposition as it indicates the importance of gradient energy coefficients that couple gradients in composition with gradients in strain.

Materials Science↗

Exploring composition mixing in kilonova ejecta with ray-by-ray simulations

Binary neutron star merger (BNSM) ejecta are considered a primary repository of r-process nucleosynthesis and a source of the observed heavy-element abundances. We implement composition mixing into ray-by-ray radiation-hydrodynamic simulations of BNSM ejecta, coupled with an online nuclear network (NN). We model mixing via a gradient-based mixing approximation that evolves simultaneously with the hydrodynamics. Here, we find that mixing occurs in regions where the electron fraction changes rapidly. While mixing smooths composition gradients in transition regions, it has a negligible impact on the heavy-element yields. This is because the primary r-process site (the equatorial ejecta) is initially homogeneous in free neutrons, leaving no strong gradients for mixing to act upon. In each angular ray, the abundances of the most produced elements are robust under mixing, while the less abundant ones are more affected. The total global abundances change only slightly from mixing, since each angular ray contributes its most abundant elements. Furthermore, the predicted kilonova light curves show only minor reddening, with differences below the detectability of state-of-the-art telescopes. In general, we do not observe significant effects from mixing in the time span of the r-process. Consequently, mixing only leads to minor variations in abundances and light curves in ray-by-ray simulations.

Explosive burning↗

Leveraging differentiable programming in the inverse problem of neutron stars

Neutron stars (NSs) probe the high-density regime of the nuclear equation of state (EOS). However, inferring the EOS from observations of NSs is a computationally challenging task. Here, in this work, we efficiently solve this inverse problem by leveraging differential programming in two ways. First, we enable full Bayesian inference in under one hour of wall time on a GPU by using gradient-based samplers, without requiring pretrained machine learning emulators. Moreover, we demonstrate efficient scaling to high-dimensional parameter spaces. Second, we introduce a novel gradient-based optimization scheme that recovers the EOS of a given NS mass-radius curve. We demonstrate how our framework can reveal consistencies or tensions between nuclear physics and astrophysics. First, we show how the breakdown density of a metamodel description of the EOS can be determined from NS observations. Second, we demonstrate how degeneracies in EOS modeling using nuclear empirical parameters can influence the inverse problem during gradient-based optimization. Looking ahead, our approach opens up new theoretical studies of the relation between NS properties and the EOS, while effectively tackling the data analysis challenges brought by future detectors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Aridity and forest age mediate landscape scale patterns of tropical forest resistance to cyclonic storms

Abstract Cyclonic storms, or hurricanes, are expected to intensify as ocean heat energy rises due to climate change. Ecological theory suggests that tropical forest resistance to hurricanes should increase with forest age and wood density. However, most data on hurricane effects on tropical forests come from a limited number of well‐studied long‐term monitoring sites, restricting our capacity to evaluate the resistance of tropical forests to hurricanes across broad environmental gradients. In this study, we assessed whether forest age and aridity mediate the effects of hurricanes Irma and Maria in Puerto Rico, Vieques and Culebra islands. We leveraged functional trait data for 410 tree species, remotely sensed measurements of canopy height and cover, along with data on forest stand characteristics of 180 of 338 forest monitoring plots, each covering an area of 0.067 ha. The plots represent a broad mean annual precipitation (MAP) gradient from 701 to 4598 mm and a complex mosaic of forest age from 5 to around 85 years since deforestation. Hurricanes resulted in a 25% increase in basal area mortality rates, a 45% decrease in canopy height and a 21% reduction in canopy cover. These effects intensified with forest age, even after considering proximity to the hurricane path. The links between forest age and hurricane disturbances were likely due the prevalence of tall canopies. Tall forest canopies were strongly linked with low community‐weighted wood density (WD). These characteristics were on average more common in moist and wet forests (MAP >1250 mm). Conversely, dry forests were dominated by short species with high wood density (WD > 0.6 g cm −3 ) and did not show significant increases in basal area mortality rates after the hurricanes. Synthesis . Our findings show that selection towards drought‐tolerant traits across aridity gradients, such as short stature and dense wood, enhances resistance to hurricanes. However, forest age modulated responses to hurricanes, with older forests being less resistant across the islands. This evidence highlights the importance of considering the intricate links between ecological succession and plant function when forecasting tropical forests’ responses to increasingly strong hurricanes.

Vargas G., German↗

Rooting for function: community‐level fine‐root traits relate to many ecosystem functions

Humans are driving biodiversity change, which also alters community functional traits. However, how changes in the functional traits of the community alter ecosystem functions—especially belowground—remains an important gap in our understanding of the consequences of biodiversity change. We test hypotheses for how the root traits of the root economics space (composed of the collaboration and conservation gradients) are associated with proxies for ecosystem functioning across grassland and forest ecosystems in both observational and experimental datasets from 810 plant communities. First, we assessed whether community-weighted means of the root economics space traits adhered to the same trade-offs as species-level root traits. Then, we examined the relationships between community-weighted mean root traits and aboveground biomass production, root standing biomass, soil fauna biomass, soil microbial biomass, decomposition of standard and plot-specific material, ammonification, nitrification, phosphatase activity, and drought resistance. We found evidence for a community collaboration gradient but not for a community conservation gradient. Yet, links between community root traits and ecosystem functions were more common than we expected, especially for aboveground biomass, microbial biomass, and decomposition. These findings suggest that changes in species composition, which alter root trait means, will in turn affect critical ecosystem functions.

54 ENVIRONMENTAL SCIENCES↗

Finding MIDDLE Ground: Scalable and Secure Distributed Learning

Edge computing methods allow devices to efficiently train a high-performing, robust, and personalized model for predictive tasks. However, these methods succumb to privacy and scalability concerns such as adversarial data recovery and expensive model communication. Furthermore, edge computing methods unrealistically assume that all devices train an identical model. In practice, edge devices have varying computational and memory constraints which may not allow certain devices to have the space or speed to train a specific model. To overcome these issues, we propose MIDDLE: a model independent distributed learning algorithm which allows heterogeneous edge devices to assist each other’s training while communicating only non-sensitive information. MIDDLE unlocks the ability for edge devices, regardless of computational or memory constraints, to assist each other even with completely different model architectures. Furthermore, MIDDLE does not require model or gradient communication which greatly reduces communication size and time. We prove that MIDDLE attains the optimal convergence rate O(1/sqrt(TM)) of stochastic gradient descent for convex and non-convex smooth optimization (for total iterations T and batch size M). Finally, our experimental results demonstrate that MIDDLE (even in non-IID data settings) attains robust and high-performing models without model or gradient communication.

Bornstein, Marc I.↗

Semantic Stealth: Crafting Covert Adversarial Patches for Sentiment Classifiers Using Large Language Models

Deep learning models have been shown to be vulnerable to adversarial attacks, in which perturbations to their inputs cause the model to produce incorrect predictions. As opposed to adversarial attacks in computer vision, where small changes introduced to pixel values can drastically alter a model's output while remaining imperceptible to humans, text-based attacks are difficult to conceal due to the discrete nature of tokens. Consequently, unconstrained gradient-based attacks often produce adversarial examples that lack semantic meaning, rendering them detectable through visual inspection or perplexity filters. In contrast to methods that rely on gradient-based optimization in the embedding space, we propose an approach that leverages a Large Language Model's ability to generate grammatically correct and semantically meaningful text to craft adversarial patches that seamlessly blend in with the original input text. These patches can be used to alter the behavior of a target model, such as a text classifier. Since our approach does not rely on gradient backpropagation, it only requires access to the target model's confidence scores, making it a grey-box attack. We demonstrate the feasibility of our approach using open-source LLMs, including Intel's Neural Chat, Llama2, and Mistral-Instruct, to generate adversarial patches capable of altering the predictions of a distilBERT model fine-tuned on the IMDB reviews dataset for sentiment classification.

Roa Carvajal, Maria↗

Toward Establishing Uniqueness of Experimentally Determined Transference Numbers

The passage of current through a battery results in the development of concentration gradients in the electrolytic phase. For a fully characterized binary electrolyte, where the conductivity, salt diffusion coefficient, cation transference number, and the thermodynamic factor are known, concentration and potential gradients in the electrolytic phase can be modeled using Newman’s concentrated solution theory. We report two methods for measuring the transference number: the standard method based on electrochemical measurements ( t + , echem 0 ) and electrophoretic NMR ( t + , eNMR 0 ). The electrochemical approach requires combining measurements from multiple experiments; the equations used to determine the cation transference number and the thermodynamic factor are coupled, nonlinear algebraic equations. In the electrophoretic-NMR-based approach, however, the equations used to determine the cation transference number and the thermodynamic factor are decoupled. We find for a liquid electrolyte comprised of a lithium salt dissolved in tetraglyme, the values of the transference numbers obtained by these two methods are distinct. For example, at 30 °C, t + , echem 0 = −1.02 ± 1.11 and t + , eNMR 0 = 0.25 ± 0.04. The corresponding thermodynamic factors are also different. While the magnitude of the predicted concentration gradients based on the two sets of parameters are different, the predicted current-voltage relationships are similar.

Hickson, Darby T. (ORCID:0000000251339755)↗

Hydroxide Exchange Membrane Carbon Capture (HEMCC) Using Nickel Hydroxide Batteries and Flow-through Membranes

Proposed is an electrochemical nickel hydroxide based hydroxide exchange membrane carbon capture (HEMCC) device for Direct Air Capture (DAC) of CO2. DAC has been identified as one of the key net negative carbon technologies to achieve net zero carbon emissions. Net negative carbon technologies are required to offset continued emissions from dilute CO2 sources such as agriculture and construction. The majority of current DAC technologies at scale (>1 KT∙yr-1) are adsorbent based technologies with significant energy cost. The traditional DAC energy cost is primarily driven by the temperature swing required to regenerate the sorbent and has been shown to be 1.8 MWh·ton-1 at the system level. Electrochemical pH swing devices are a growing research area for carbon capture devices with the goal of lowering the energy cost required for DAC. A pH gradient is built by generating OH- at the cathode and consuming OH- at the anode. An acid-base equilibrium with CO2 allows for the capture of CO2 at the cathode and release at the anode. This extends from other electrochemical CO2 capture devices based on pKa shifts of an electrochemically active organic species allowing for the capture and release of CO2. Electrochemical CO2 capture is considered promising based on potentially low energy costs to capture CO2 in comparison with current temperature swing adsorption technologies. This work explores Ni(OH)2 electrodes to produce the pH gradient for CO2 capture and release. At the cathode NiOOH is reduced to Ni(OH)2 while at the anode Ni(OH)2 is oxidized to NiOOH. The symmetrical electrodes allow for a low voltage requirement; the thermodynamic potential difference of standard electrochemical reactions is zero. Most of the voltage observed is to produce the pH gradient with the remainder driving the polarization of the electrodes. There is a resistance component as well, but this is small in comparison due to the low current densities used in the device, nominally 2 mA·cm-1. Two similar devices are presented, a traditional MEA (membrane electrode assembly) and a flow-through MEA. The traditional MEA separates the two Ni(OH)2 electrodes with an 80μm Piperion® membrane. While the flow-through membrane separates the electrodes with a three piece membrane consisting of two 80μm Piperion® membranes with a porous membrane between them. In the traditional MEA system air is passed over the cathode for capture, while the flow-through MEA the air is passed through the porous membrane isolated from the electrodes. The traditional MEA has been used to establish a baseline performance of the device and has been shown to capture CO2 at an energy cost of 1 MWh·ton-1 at the device level. An understanding has been built around the components of that energy cost including the relationship of flux to current density, effect of a regeneration process, transient battery behavior, and gas losses coinciding with changing the polarization of the batteries. The flow-through MEA looks to address of transient battery behavior and gas losses. It allows for denser, higher capacity electrodes, which can lean on traditional Ni-MH battery technology used in alkaline batteries used today. The higher capacities, limit the transient battery effect on flux in the device. Gas losses are addressed by having a continuous inlet air stream to the device and continuous outlet product.

Buchen, James↗

Characterizing Near-Surface Moisture Increase during the Clear-Sky Afternoon-to-Evening Transition Using a Single-Column Model

The afternoon-to-evening transition is the period when the atmospheric boundary layer transitions from convective to stable conditions. One noticeable feature during this transition period is the rapid increase in water vapor concentration near the surface. However, the mechanism behind the increase in water vapor remains poorly understood. This study investigated the processes contributing to the water vapor increase and the impacts of the land cover and horizontal advection on the water vapor increase using a single-column model for the clear-sky condition. Numerical experiments were conducted on three cases at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. Evapotranspiration was found to be the main moisture source to the water vapor increase, and that change of the near-surface vertical temperature gradient from negative to positive is the trigger for this increase during the afternoon-to-evening transition. This is because the near-surface turbulence divergence term decreases due to the change in the buoyancy profile caused by vertical temperature gradient change. The impact of horizontal advection on water vapor varies, and it can either lead to an increase or a decrease in water vapor, depending on the spatial horizontal water vapor gradient. This study also found that land cover can influence the timing of the water vapor increase since different land covers may have different Bowen ratios. Water vapor increases earlier under conditions with smaller Bowen ratios compared to those with larger values.

Atmosphere-land interaction↗

A Unified Interpretation of Variability in Precipitation Isotope Ratios

Abstract Several mechanisms have been proposed to explain why the isotope ratios of precipitation vary in space and time and why they correlate with other climate variables like temperature and precipitation. Here, we argue that this behavior is best understood through the lens of radiative transfer, which treats the depletion of atmospheric vapor transport by precipitation as analogous to the attenuation of light by absorption or scattering. Building on earlier work by Siler et al., we introduce a simple model that uses the equations of radiative transfer to approximate the two-dimensional pattern of the oxygen isotope composition of precipitation ( δ p ) from monthly mean hydrologic variables. The model accurately simulates the spatial and seasonal variability in δ p within a state-of-the-art climate model and permits a simple decomposition of δ p variability into contributions from gradients in evaporation and the length scale of vapor transport. Outside the tropics, δ p is mostly controlled by gradients in evaporation, whose dependence on temperature explains the positive correlation between δ p and temperature (i.e., the temperature effect). At low latitudes, δ p is mostly controlled by gradients in the transport length scale, whose inverse relationship with precipitation explains the negative correlation between δ p and precipitation (i.e., the amount effect). This suggests that the temperature and amount effects are both mostly explained by the variability in upstream rainout, but they reflect distinct mechanisms governing rainout at different latitudes. Significance Statement The isotopic composition of precipitation has long been used to make inferences about past climates based on its observed relationship with precipitation in the tropics and with temperature at higher latitudes. These relationships—known as the “amount effect” and “temperature effect,” respectively—have been attributed to many different mechanisms, most of which are thought to operate at either high or low latitudes but not both. Here, we present a unified framework for interpreting the isotope variability that can explain the latitude dependence of the temperature and amount effects despite making no distinction between high and low latitudes. Although our results are generally consistent with certain interpretations of the amount effect, they suggest that the temperature effect is widely misunderstood.

54 ENVIRONMENTAL SCIENCES↗

Decadal Spiciness Variability in the Subtropical-Tropical Pacific in the CESM2 Large Ensemble

Tropical Pacific decadal variations impact weather and climate around the world and are also connected to variations in the global warming trend. The mechanisms driving these long-term modulations, particularly the role of subsurface ocean dynamics, are still debated. Here, we investigate the dynamics of spiciness (density-compensated temperature and salinity) anomalies in the tropical and subtropical Pacific, which are hypothesized as a possible driving mechanism of decadal climate variability. Based on the analysis of 100 realizations from the Community Earth System Model Version 2 Large Ensemble (CESM2-LE), we demonstrate a coupling between the subtropics and the equatorial Pacific by propagating spiciness anomalies at decadal time scales. The CESM2-LE simulates spiciness variability along a subduction path from the subtropics to the equator with frequency spectra that show the highest power at low frequencies and a power decay proportional to a −4 slope for frequencies greater than 0.01 cycles per months, corresponding to periods smaller than ∼8.5 years. Signals that originate in the Southern Hemisphere (SH) dominate and arrive with a larger magnitude at the equator compared to spiciness anomalies from the Northern Hemisphere (NH). Spiciness anomalies from the SH have shorter propagation times and are strengthened along their pathway as stochastic wind stress curl forcing generates anomalous baroclinic ocean pressure gradients. These pressure gradients generate spiciness anomalies via anomalous advection across climatological spiciness gradients in the SH. We conclude that the observed spiciness variance at decadal time scales is consistent with a forcing by stochastic wind variations that are low-pass filtered by ocean dynamics.

54 ENVIRONMENTAL SCIENCES↗

COMPASS-FME Synoptic Site Characterization

This dataset contains soil biogeochemical and physicochemical characterization data for the COMPASS-FME synoptic sites.This dataset also contains data for the paper Patel et al. 2025 "Transition zones at the changing coastal terrestrial-aquatic interface", https://doi.org/10.1029/2025JG008978.Coastal soils are a significant but highly uncertain component of global biogeochemical cycles. These systems experience unique spatial and temporal variability in biogeochemical processes, driven by wetland-to-upland gradients and hydrological fluctuations. We studied drivers of coastal soil variability (a) at regional scales and (b) across transects from upland forest to wetland, in two contrasting regions — Lake Erie, a freshwater lacustrine system, and Chesapeake Bay, a saltwater estuarine system. Salinity-related analytes were a key driver of soil variability, not just in the saltwater system, but surprisingly, also in the freshwater system. We had hypothesized linear trends in biogeochemical parameters along the TAI – however, contrary to expectations, transition soils were not consistently intermediate between upland and wetland endmembers; the non-monotonic trends of carbon, phosphorus, iron along our transects suggest that these are key analytes to study in our regions. Rapidly changing soil factors across coastal gradients provide insights into which soil processes may act as precursors to ecosystem shifts. Our comprehensive soil characterization across the coastal transects provides essential data for mechanistic modeling of ecosystem dynamics.The data are provided as processed, csv files. Raw data and processing scripts can be accessed on GitHub (https://github.com/COMPASS-DOE/cmps-soil_characterization).A note on the nomenclature: the experimental design represents three points along the coastal gradient -- upland, transition, and wetland. "wetland" is referred to as "marsh" in the corresponding paper. The two terms can be used interchangeably for the sites in this study.

54 ENVIRONMENTAL SCIENCES↗

Final Report on Predictive Analyses of PRD as Function of Anomalies

This report summarizes the work completed in FY-2024 to analyze the power reactivity decrement (PRD) concepts of the ARC-100 core. The PRD has been traditionally defined by the reactivity change from a hot zero power (HZP) to a particular power. Consequently, the PRD accounts for the core reactivity changes due to increase coolant temperature gradient axially and radially across the core, and increased fuel temperature. The coolant temperature gradient leads to sodium and structure density changes, to radial core expansion from assembly flowering and bowing (due to axial and radial temperature gradients within the assemblies), and to control rod driveline thermal expansion. The fuel temperature increase associated with coolant temperature and power increases leads to Doppler effect and axial thermal expansion. In this work, the normal operating Hot Full Power (HFP) state is the only power level of interest, so analyses focus on the PRD calculated from HZP to HFP. The PRD has been used to assess the reactor safety features asymptotically in unprotected accident scenarios, including the loss of heat sink (LOHS), loss of flow (LOF), and transient overpower (TOP) without scram. The PRD concept relies on the “global” reactivity coefficients A, B, and C that are estimated based on “individual” reactivity effects (Doppler, sodium density, etc.). The objectives of this work are: 1) to improve and verify the methodology used to calculate the ABC coefficients used in the PRD, 2) to assess if the PRD can be used to reliably identify abnormal events. This report fulfills the FY-2024 scope of WBS#1.15.8.3 activity, “ANL0120 – Predictive Analyses of PRD as function of deformation”. The PRD concept is described in Sections 2. Additional effort in refining the methodology for core bowing modeling is performed in Sections 3. Then, two verification exercises are proposed in Section 4 to benchmark these coefficients based on direct neutronic-only calculations and on dynamic core transient simulations. Finally, the PRD approach is assessed for the detection of several unexpected events, such as primary flow perturbation or improper fuel loading, in Section 5.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Salt Tank Testbed: a Test Site Designed to Replicate Floor Buckles Observed in Commercial TES Tanks

A test site has been designed and is under construction to replicate the buckling failure ob-served in several in-service storage tanks for nitrate salts operating up to 565°C. In commercial tanks multiple factors have been identified that influence the floors susceptibility to buck-ling, including: the as-manufactured shape of the floor, high compressive stresses due to thermal gradients and/or friction, fluid inventory and absolute temperature. Based on exten-sive modeling analysis it was determined that similar buckles can be reproduced in a scaled test tank (approximately 9x smaller than a representative commercial tank design). To buckle the scaled tank a radial thermal gradient is generated in the tank with a low fluid level, the fluid level is then increased while maintaining the thermal gradient; based on the modeling results just one of these cycles can plastically deform the tank floor. The test site which is under construction is designed to replicate this damaging cycle at lower temperatures. The goal of testing will be to reproduce this damaging cycle and buckle the scaled test tank floor, allowing proper model validation and a methodology for comparing different tank designs at a smaller (and less costly) scale.

25 ENERGY STORAGE↗

Characterizing Stress Roughness at Utah FORGE Through Simulation of Hydraulic Fracture Growth During 16A Stage 3 Stimulation

In most geologic formations, the vertical gradient of the minimum horizontal stress (𝜎 h ) exceeds the hydrostatic gradient, often driving hydraulic fractures to propagate upward. However, observations indicate that the upward growth of real hydraulic fractures is less pronounced than theoretical predictions based on smoothly varying 𝜎 h fields. In fact, the layered structure of sedimentary rocks hinders fracture propagation across layers, partially explaining the limited height growth observed in practice (Zoback et al., 2022). While crystalline rocks lack the pervasive layered fabric of sedimentary formations, they still possess structural fabric formed over their geologic history, resulting in inherently "rough" in situ stress fields. Recent studies have identified another key factor: the "roughness" of in situ stress, characterized by temporal, relatively short-wavelength fluctuations superimposed on the overall stress gradient. This stress roughness leads to apparent toughness anisotropy, where the vertical toughness appears significantly larger than the horizontal toughness (P. Fu et al., 2019; Dontsov & Suarez-Rivera, 2021). Neglecting the effects of rock fabric and stress roughness can yield inaccurate predictions of hydraulic fracture geometry and growth rates at larger length scales.

58 GEOSCIENCES↗