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At least 541 records · Page 30

A review of thermo-hydro-mechanical modeling of coupled processes in fractured rock: From continuum to discontinuum perspective

Coupled thermo-hydro-mechanical (THM) processes in fractured rock are playing a crucial role in geoscience and geoengineering applications. Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling. This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions. By comparing various models, one can better assess the uncertainties in predictions, particularly those related to the conceptual models. The review explores how these methodologies have significantly enhanced the fundamental understanding of how fractures respond to fluid injection and production, and improved predictive capabilities pertaining to coupled processes within fractured systems. It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience. The selection and calibration of model parameters should be based on typical ranges and applied to the specific conditions of applications. The challenges arising from inherent heterogeneity and uncertainties, nonlinear THM coupled processes, scale dependence, and computational limitations in representing field scale fractures are discussed. Realizing potential advances on computational capacity calls for methodical conceptualization, mathematical modeling, selection of numerical solution strategies, implementation, and calibration to foster simulation outcomes that intricately reflect the nuanced complexities of geological phenomena. Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical field of study.

Coupling scheme↗

ED-cPSD: Fast Phase-Size Distribution via Sequential Erosion-Dilation

The Erosion-Dilation continuous Phase-Size Distribution, ED-cPSD, is an application for calculating continuous pore and particle-size distribution from digital reconstructions and/or image-based structural data. It is based on the erosion-dilation continuous phase-size distribution method. A continuous size distribution is a measure of the probability density of finding a particle or pore of a certain size. These distributions are of interest in any field of study involving porous media, including but not limited to electrochemistry, petroleum engineering, geology, and food science. The algorithm behind the software provides a computationally efficient way to calculate phase-size distributions for large domains. For a 3D battery electrode reconstruction with 1.3 x 10 8 voxels, the particle size distribution is derived in under 2 min on a desktop, while also retaining flexibility and computational efficiency for HPC-scale multi-threading. The software can handle structures with over 10 9 voxels. The algorithm is roughly 280 times faster than a previous version on the same task.

Characterization↗

Belowground allocation and dynamics of recently fixed plant carbon in a California annual grassland

Plant roots and the organisms that surround them are a primary source for stabilized soil organic carbon (SOC). While grassland soils have a large capacity to store organic carbon (C), few field-based studies have quantified the amount of plant-fixed C that moves into soil and persists belowground over multiple years. Yet this characteristic of the soil C cycle is critical to C storage, soil water holding capacity, nutrient provisions, and the management of soil health. Here, we tracked the fate of plant-fixed C following a five-day 13 CO 2 labeling of a Northern California annual grassland, measuring C pools starting at the end of the labeling period, at three days, four weeks, six months, one year, and two years. Soil organic carbon was fractionated using a density-based approach to separate the free-light fraction (FLF), occluded-light fraction (OLF), and heavy fraction (HF). Using isotope ratio mass spectrometry, we measured 13 C enrichment and total C content for plant shoots, roots, soil, soil dissolved organic carbon (DOC), and the FLF, OLF, and HF. The chemical nature of C in the HF was further analyzed by solid state 13 C nuclear magnetic resonance (NMR) spectroscopy.

13C-NMR↗

High-Temperature Ferrofluids Based on Molten Salts

Molten metal chloride salts are promising candidates for advanced heat transfer fluids in generation IV nuclear reactors and beyond. However, research on the magnetic properties of suspended metallic nanoparticles at elevated temperatures is scarce, and there have been no attempts to develop a high-temperature, molten salt based ferrofluid. Such a ferrofluid would enable in situ manipulation of both the physical and thermal properties of the fluid via an external magnetic field. This study examines molten salt based ferrofluids comprised of metallic cobalt nanoparticles dispersed in molten metal chloride salts. High-temperature magnetometry and magneto-thermogalvometric measurements were conducted to evaluate the magnetic characteristics of the ferrofluid. Further analysis was conducted through a combination of microscopy, spectroscopy, solubility tests, and diffraction measurements. Furthermore, the metallic cobalt nanoparticles exhibited a notable degree of chemical stability and sustained magnetism from 25 to 800 °C when suspended in NaCl–MgCl 2 and KCl–ZnCl 2 mixtures.

Cobalt↗

Exact-Two-Component Complete Active Space Method with Variational Treatment of Magnetic Field and Spin–Orbit Coupling: Application to X-ray Magnetic Circular Dichroism Spectroscopy

We introduce an exact-two-component complete active space self-consistent-field (X2C-CASSCF) method formulated under the restricted-magnetic-balance condition. This framework allows for the nonperturbative treatment of static magnetic fields using gauge-including atomic orbitals (GIAOs). The GIAO-X2C-CASSCF methodology effectively captures all microstates within the same 2J + 1-degenerate manifold and their splitting in a static magnetic field, which are not accessible through single-reference-based methods. We also present mathematical recursive expressions for evaluating one-electron relativistic integrals by using GIAOs in the presence of a finite magnetic field. Benchmark studies include oxygen and nitrogen K-edge X-ray magnetic circular dichroism spectroscopy (XMCD) for closed-shell organic compounds, as well as L-edge XMCD spectroscopy for the high-spin open-shell transition metal ion Mn 2+ and the tetrahedral Mn(II)O 4 6– complex.

Chemical calculations↗

Realistic Ion Dynamics through Charge Renormalization in Nonaqueous Electrolytes

While many practically important electrolytes contain lithium ions, interactions of these ions are particularly difficult to probe experimentally because of their small X-ray and neutron scattering cross sections and large neutron absorption cross sections. Molecular dynamics (MD) is a powerful tool for understanding the properties of nonaqueous electrolyte solutions from the atomic level, but the accuracy of this computational method crucially depends on the physics built into the classical force field. In this study, we demonstrate that several force fields for lithium bistriflimide (LiTFSI) in acetonitrile yield a solution structure that is consistent with the neutron scattering experiments, yet these models produce dramatically different ion dynamics in solution. Such glaring discrepancies indicate that inadequate representation of long-range interactions leads to excessive ionic association and ion-pair clustering. We show that reasonable agreement with the experimental observations can be achieved by renormalization of the ion charges using a “titration” method suggested herewith. This simple modification produces realistic concentration dependencies for ionic diffusion and conductivity in <2 M solutions, without loss in quality for simulation of the structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetics of Magnetic Skyrmion Crystal Formation from the Conical Phase

The particle-like magnetic skyrmion or skyrmion lattice (SkX) formation has promoted strong application and fundamental science interests. Despite extensive research, the kinetic of the SkX development is much less understood because of the ultrafast spin rotation and high sensitivity to external perturbations. In this work, using in situ Lorentz transmission electron microscopy, we successfully measured the dynamics of SkX formation from the conical phase with precise control of both the temperature and the magnetic field. We discovered that the Avrami equation can accurately describe the transition process with an initial Avrami constant around 1, suggesting that the rate-limiting step for the quasiparticle lattice formation is one-dimensional heterogeneous nucleation of individual skyrmions. A modified Arrhenius rate law is established, with an energy barrier that has a square-root dependence on temperature and a quadratic dependence on the magnetic field. This study paves the way toward precise and predictable manipulation of topological spin structures.

36 MATERIALS SCIENCE↗

Nanoparticle-Induced Disorder at Complex Liquid–Liquid Interfaces: Effects of Curvature and Compositional Synergy on Functional Surfaces

The self-assembly of surfactant monolayers at interfaces plays a sweeping role in tasks ranging from household cleaning to the regulation of the respiratory system. The synergy between different nanoscale species at an interface can yield assemblies with exceptional properties, which enhance or modulate their function. However, understanding the mechanisms underlying coassembly, as well as the effects of intermolecular interactions at an interface, remains an emerging and challenging field of study. Herein, we study the interactions of gold nanoparticles striped with hydrophobic and hydrophilic ligands with phospholipids at a liquid–liquid interface and the resulting surface-bound complexes. We show that these nanoparticles, which are themselves minimally surface active, have a direct concentration-dependent effect on the rapid reduction of tension for assembling phospholipids at the interface, implying molecular coassembly. Through the use of sum frequency generation vibrational spectroscopy, we reveal that nanoparticles impart structural disorder to the lipid molecular layers, which is related to the increased volumes that amphiphiles can sample at the curved surface of a particle. The results strongly suggest that hydrophobic and electrostatic attractions imparted by nanoparticle functionalization drive lipid–nanoparticle complex assembly at the interface, which synergistically aids lipid adsorption even when lipids and nanoparticles approach the interface from opposite phases. The use of tensiometric and spectroscopic analyses reveals a physical picture of the system at the nanoscale, allowing for a quantitative analysis of the intermolecular behavior that can be extended to other systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Contributions of Shear and Turbulence to Cloud Overlap for Cumulus Clouds

The causes of vertical cloud overlap, the ratio between the cloud fraction by area and the cloud fraction by volume, are studied for fields of cumulus convection. Using large-eddy simulations, the structure of individual clouds within the cloud field is inspected and connected to the overall cloud cover of the entire cloud field. First, it is shown that the cloud overlap of the entire field can be well approximated by the total cloud overlap of the individual clouds. It is then shown that a simple maximum overlap assumption, which is commonly used for cloud fields with small layer depth, can only account for roughly half of the overlap inefficiency. This is due to the fact that maximum overlap only represents variations in cloud width as a function of depth but does not take other factors into account, most notably shear or turbulence. The effects of turbulence and wind shear on the overlap of individual clouds are first estimated as a function of cloud depth, which closes the discrepancy between observed cloud overlap and the maximum overlap assumption. Then, an empirical model is developed for the shear and turbulence contributions on overlap as a function of cloud depth and of synoptic conditions. Finally, it is shown that our model is capable of accurately predicting overlap for a large number of cloud fields and under a variety of meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

Tearing Instability in Alfvén and Kinetic-Alfvén Turbulence

Recently, it has been realized that magnetic plasma turbulence and magnetic field reconnection are inherently related phenomena. Turbulent fluctuations generate regions of sheared magnetic field that become unstable to the tearing instability and reconnection, thus modifying turbulence at the corresponding scales. In this contribution, we give a brief review of some recent results on tearing-mediated magnetic turbulence. We illustrate the main ideas of this rapidly developing field of study by concentrating on two important examples—magnetohydrodynamic Alfvén turbulence and small-scale kinetic-Alfvén turbulence. Due to various potential applications of these phenomena in space physics and astrophysics, we specifically try not to overload the text by heavy analytical derivations but rather present a qualitative discussion accessible to a non-expert in the theories of turbulence and reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Observations and Simulations of Dropout Events and Flux Decays in October 2013: Comparing MEO Equatorial With LEO Polar Orbit

We compare ESA PROBA-V observations of electron flux at LEO with those from the NASA Van Allen Probes mostly at MEO for October 2013. Dropouts are visible at all energy during four storms from both satellites. Equatorially trapped electron fluxes are higher than at LEO by 10 2 (<1 MeV) to 10 5 (>2.5 MeV). We observe a quite isotropic structure of the outer belt during quiet times, contrary to the inner belt, and pitch angle dependence of high energy injection. We find a very good overlap of the outer belt at MEO and LEO at ~0.5 MeV. We use test-particle simulations of the energetic electrons trapped in the terrestrial magnetic field to study the outer radiation belt electron flux changes during geomagnetic storms. We show that the Dst (Disturbance storm time) effect during the main phase of a geomagnetic storm results in a betatron mechanism causing outward radial drift and a deceleration of the electrons. This outward drift motion is energy independent, pitch angle-dependent, and represents a significant distance (~1 L-shell at L = 5 for moderate storms). At fixed L-shell, this causes a decay of the LEO precipitating flux (adiabatic outward motion), followed by a return to the normal state (adiabatic inward motion) during main and recovery phases. Dst effect, associated with magnetopause shadowing and radial diffusion can explain the main characteristics of outer radiation belt electron dropouts in October 2013. We also use Fokker-Planck simulations with event-driven diffusion coefficients at high temporal resolution, to distinguish instantaneous loss from the gradual scattering that depopulates the slot region and the outer belt after storms. Simulations reproduce the slot formation and the gradual loss in the outer belt. The typical energy dependence of these losses leads to the absence of scattering for relativistic and ultra-relativistic electrons in the outer belt, oppositely to dropouts.

79 ASTRONOMY AND ASTROPHYSICS↗

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗

Agrivoltaic Grazing Systems for a Sustainable Future: A Multi‐Disciplinary Review & Gap Analysis

Solar photovoltaics (PV) is the fastest growing source of electricity in the world, however, its expansion has raised concerns about the displacement of agriculture and the degradation of rangeland ecosystems. This has prompted research and development of multi-land-use systems that co-prioritize energy production alongside agriculture, commonly referred to as agrivoltaics. Currently, agrivoltaic grazing (also called solar grazing) is one of the most common forms of these systems. However, peer-reviewed research on these systems is limited. This review synthesizes research on agrivoltaic grazing systems, drawing upon literature addressing agrivoltaics broadly and considering relevant literature in adjacent fields of study. Based on this review, we identify six key gaps and priority directions for future research. These include foundational fieldwork to characterize the layered ecological impacts of solar PV and grazing and understand PV-livestock integration from both an animal welfare and a PV infrastructure perspective. This will facilitate the development of biogeochemical and economic models that improve our predictive capacity and ability to compare system designs. We also identify gaps in understanding the human aspects of these systems and emphasize the importance of utilizing collaborative research methods and increasing research on the social dimensions of agrivoltaic grazing systems.

14 SOLAR ENERGY↗

Observation and Simulation of Methane Plumes During the Morning Boundary Layer Transition

Abstract Methane (CH 4 ) contributes significantly to global warming. However, accurate identification of CH 4 sources for reducing CH 4 emissions is often hampered by inadequate accuracy and spatiotemporal coverage of CH 4 detection, and lack of accurate CH 4 forward modeling used in top‐down inversion systems. In this study, a field experiment was conducted in Pampa, Texas using two CH 4 sensors (LI‐COR and OGI camera) to detect CH 4 releases. We investigated whether high‐resolution simulations using the Weather Research and Forecasting (WRF) model with greenhouse gases (WRF‐GHG) could accurately simulate the CH 4 plumes in the presence of evolving atmospheric boundary layer from sunrise to noon. CH 4 plumes showed substantial variation in time. At a release rate of ∼17.5 kg hr −1 , the maximum enhancement of CH 4 measured by LI‐COR was 2.6 ppm at sunrise (7:36 a.m.), 250 m from the release location. Within half an hour after sunrise, this enhancement decreased to 0.3–0.4 ppm. The enhancement was 0.2 ppm by 10:00 a.m. and further dropped to less than 0.1 ppm after 11:30 a.m. Due to the low temperature at sunrise, the OGI camera failed to detect the CH 4 plume. The WRF‐GHG large‐eddy simulation (LES) with 32 m grid spacing successfully reproduced these CH 4 enhancements. In situ measurements together with numerical simulations illustrate the impact of the transition from a stable boundary layer in the early morning to a convective boundary layer at noon on the dispersion of CH 4 plumes. Additionally, CH 4 plumes from a cattle farm in Oklahoma are briefly examined using the same modeling approach.

Hu, Xiao‐Ming [Center for Analysis and Prediction ↗

Warming induces unexpectedly high soil respiration in a wet tropical forest

Abstract Tropical forests are a dominant regulator of the global carbon cycle, exchanging more carbon dioxide with the atmosphere than any other terrestrial biome. Climate models predict unprecedented climatic warming in tropical regions in the coming decades; however, in situ field warming studies are severely lacking in tropical forests. Here we present results from an in situ warming experiment in Puerto Rico, where soil respiration responses to + 4 o C warming were assessed half-hourly for a year. Soil respiration rates were 42-204% higher in warmed relative to ambient plots, representing some of the highest soil respiration rates reported for any terrestrial ecosystem. While respiration rates were significantly higher in the warmed plots, the temperature sensitivity (Q 10 ) was 71.7% lower, pointing to a mechanistic shift. Even with reduced Q 10 , if observed soil respiration rates persist in a warmer world, the feedback to future climate could be considerably greater than previously predicted or observed.

Science & Technology - Other Topics↗

Laser cooling of antihydrogen atoms

The photon—the quantum excitation of the electromagnetic field—is massless but carries momentum. A photon can therefore exert a force on an object upon collision 1 . Slowing the translational motion of atoms and ions by application of such a force 2,3 , known as laser cooling, was first demonstrated 40 years ago 4,5 . It revolutionized atomic physics over the following decades 6–8 , and it is now a workhorse in many fields, including studies on quantum degenerate gases, quantum information, atomic clocks and tests of fundamental physics. However, this technique has not yet been applied to antimatter. Here we demonstrate laser cooling of antihydrogen 9 , the antimatter atom consisting of an antiproton and a positron. By exciting the 1S–2P transition in antihydrogen with pulsed, narrow-linewidth, Lyman-α laser radiation 10,11 , we Doppler-cool a sample of magnetically trapped antihydrogen. Although we apply laser cooling in only one dimension, the trap couples the longitudinal and transverse motions of the anti-atoms, leading to cooling in all three dimensions. We observe a reduction in the median transverse energy by more than an order of magnitude—with a substantial fraction of the anti-atoms attaining submicroelectronvolt transverse kinetic energies. We also report the observation of the laser-driven 1S–2S transition in samples of laser-cooled antihydrogen atoms. The observed spectral line is approximately four times narrower than that obtained without laser cooling. The demonstration of laser cooling and its immediate application has far-reaching implications for antimatter studies. A more localized, denser and colder sample of antihydrogen will drastically improve spectroscopic 11–13 and gravitational 14 studies of antihydrogen in ongoing experiments. Furthermore, the demonstrated ability to manipulate the motion of antimatter atoms by laser light will potentially provide ground-breaking opportunities for future experiments, such as anti-atomic fountains, anti-atom interferometry and the creation of antimatter molecules.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗