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This paper evaluates the seismic fragility of a two-span reinforced concrete (RC) bridge with shape memory alloy (SMA)-restrained rocking (SRR) columns through machine learning (ML) techniques. SRR columns incorporate a combination of replaceable superelastic NiTi (SMA) links and mild steel energy-dissipating links to achieve self-centering and energy dissipation, respectively, while their rocking joints are protected against compressive concrete damage through steel jacketing. To produce seismic fragility functions, initially, multi-parameter probabilistic seismic demand models (PSDMs) are generated for various engineering demand parameters through five different ML techniques (including neural network) and considering various sources of uncertainty, and the most accurate PSDMs are selected. The selected PSDMs are then interpreted using four different methods to investigate the effects of two key SRR column design parameters (self-centering coefficient and SMA link initial strain) and ambient temperature on the seismic performance of SRR columns. Subsequently, using neural networks, the PSDMs developed earlier, and appropriate capacity models, multi-parameter fragility functions are developed for various bridge damage states. After examining the effects of the two SRR column design parameters on the seismic fragility of the bridge, its seismic fragility is compared with those of the same bridge with monolithic RC and posttensioned (PT) rocking columns. It is shown that, in general, increasing the initial strain of the SMA links and decreasing the self-centering coefficient as possible (i.e., without compromising the self-centering) reduce the overall bridge damage. In addition, even considering the ambient temperature's uncertainty, SRR columns are proven, at least, as effective as PT columns in mitigating the seismic damage of the bridges of monolithic RC columns.

We conducted a TEM study of an unusual oxide-silicate composite presolar grain (F2-8) from the unequilibrated ordinary chondrite Semarkona. The presolar composite grain is relatively large, has an amoeboidal shape, and contains Mg-rich olivine, Mg-Al spinel, and Ca-rich pyroxene. The shape and phase assemblage are reminiscent of amoeboid-olivine-aggregates and add to the growing number of TEM observations of presolar refractory inclusion-like (CAIs and AOAs) grains. In addition to the dominant components, F2-8 also contains multiple subgrains, including an alabandite-oldhamite composite grain within the olivine and several magnetite subgrains within the Mg-Al spinel. We argue that the olivine, Mg-Al spinel, and alabandite-oldhamite formed by equilibrium condensation, whereas the Ca-rich pyroxene formed by non-equilibrium condensation, all in an M-type AGB star envelope. On the other hand, the magnetite subgrains are likely the result of aqueous alteration on the Semarkona asteroidal parent body. Additional evidence of secondary processing includes Fe-enrichment in the Mg-Al spinel and olivine, elevated Al contents in the olivine, and beam sensitivity and a modulated structure for the olivine. Compound presolar grains record condensation conditions over a wide range of temperatures. Additionally, the presence of several different presolar phases in a composite grain can impart information on the relative rates and effects of post-condensation processing in a range of environments, including the interstellar medium, solar nebula, and the host asteroid parent body. The TEM observations of F2-8 provide insights across the lifetime of the grain from its formation by condensation in an M-type AGB star envelope, its transit through the interstellar medium, and aqueous alteration during its residence on Semarkona's asteroidal parent body., 36 total pages, including 6 figures, 3 supplemental figures, 4 tables, and 2 supplemental tables

Presolar grains are trace components in chondrite matrices. Their abundances and compositions have been systematically studied in carbonaceous chondrites but rarely in situ in other major chondrite classes. We have conducted a NanoSIMS isotopic search for presolar grains with O- and C-anomalous isotopic compositions in the matrices of the unequilibrated ordinary chondrites Semarkona, Meteorite Hills 00526, and Northwest Africa 8276. The matrices of even the most primitive ordinary chondrites have been aqueously altered and/or thermally metamorphosed, destroying their presolar grain populations to varying extents. In addition to randomly placed isotope maps, we targeted recently reported, relatively pristine Semarkona matrix areas to better explore the original inventory of presolar grains. In all samples, we found a total of 122 O-anomalous grains (silicates + oxides), 79 SiC grains, and 22 C-anomalous carbonaceous grains (organics, graphites). Average matrix-normalized abundances are 151 ppm O-anomalous grains, 53 ppm SiC grains and 56 ppm carbonaceous grains in Semarkona, 55 ppm (O-anom.), 22 ppm (SiC) and 3 ppm (carb.) in MET 00526 and 12 ppm (O-anom.), 15 ppm (SiC) and 1 ppm (carb.) in NWA 8276. In relatively pristine ordinary chondrites and in primitive carbonaceous and C-ungrouped chondrites, the O and C isotopic composition of presolar grains and their matrix-normalized abundances are similar, despite the likely differences in chondrite-formation time and nebular location. These results suggest a relatively homogenous distribution of presolar dust across major chondrite-forming reservoirs in the solar nebula. Secondary asteroidal processes are mainly responsible for differences in presolar grain abundances between and within chondrites, highlighting the need to identify and target the most pristine chondrite matrices for such studies., Published in Geochimica et Cosmochimica Acta. Main text: 36 pp with 7 figures and 1 table. Supplement: 13 pp, 2 tables, 2 figures

A systematic study of ionospheric scintillation at the low-latitudes, especially around the Equatorial Ionization Anomaly (EIA) and the magnetic equator, is essential in understanding the dynamics of ionospheric variation and related physical processes. Our study involves NavIC $S_{4_C}$ observations over Indore and Hyderabad. Additionally, GPS $S_{4_C}$ observations over Indore were analyzed, under disturbed as well as quiet time ionospheric conditions from September 2017 through 2019, falling in the declining phase of the solar cycle 24. The $S_{4_C}$ observations were further analyzed using proxy parameters: ROT and ROTI. These results have been obtained from three satellites of the NavIC constellation (PRNs 2, 5, and 6). The onset times of scintillations \textbf{were} observed to be around 19:30 LT (h) and 20:30 LT (h) for Hyderabad and Indore respectively, while the $S_{4_C}$ peak values occurred between 22:00 LT (h) and 23:00 LT (h). The reliability of NavIC was evaluated using scattering coefficients that revealed a good correlation across the pair of signals during quiet time ionospheric conditions. The observations clearly show that the amplitude scintillation of the NavIC signal follows the Nakagami-m distribution along with the $\alpha-\mu$ distribution as a depiction of the deep power fades caused by scintillation on these signals. This paper shows the impact of such systematic studies near these locations for the first time, in improving the understanding of the dynamic nature of low-latitude ionosphere under low solar activity conditions.

We investigated six presolar grains from very primitive regions of the matrix in the unequilibrated ordinary chondrite Semarkona with TEM. These grains include one SiC, one oxide (Mg-Al spinel), and four silicates. Structural and elemental compositional studies of presolar grains located within their meteorite hosts have the potential to provide information on conditions and processes throughout the grains' histories. Our analyses show that the SiC and spinel grains are stoichiometric and well crystallized. In contrast, the majority of the silicate grains are non-stoichiometric and poorly crystallized. These findings are consistent with previous TEM studies of presolar grains from interplanetary dust particles and chondritic meteorites. We interpret the poorly crystalline nature, non-stoichiometry, more Fe- rather than Mg-rich compositions, and/or compositional heterogeneities as features of the formation by condensation under non-equilibrium conditions. Evidence for parent body alteration includes rims with mobile elements (S or Fe) on the SiC grain and one silicate grain. Other features characteristic of secondary processing in the interstellar medium, the solar nebula, and/or on parent bodies, were not observed or are better explained by processes operating in circumstellar envelopes. In general, there was very little overprinting of primary features of the presolar grains by secondary processes (e.g., ion irradiation, grain-grain collisions, thermal metamorphism, aqueous alteration). This finding underlines the need for additional TEM studies of presolar grains located in the primitive matrix regions of Semarkona, to address gaps in our knowledge of presolar grain populations accreted to ordinary chondrites., Comment: 50 pages including supplementary materials

Natural and engineered media usually involve combinations of solid, fluid and porous layers, and accurate and stable modelling of wave propagation in such complex multilayered media is fundamental to evaluating their properties with wave-based methods. Here we present a general stiffness matrix method for modelling waves in arbitrary multilayers. The method first formulates stiffness matrices for individual layers based on the governing wave equations for fluids and solids, and the Biot theory for porous materials. Then it utilises the boundary conditions considered at layer interfaces to assemble the layer matrices into a global system of equations, to obtain solutions for reflection and transmission coefficients at any incidence. Its advantage over existing methods is manifested by its unconditional computational stability, and its validity is proved by experimental validations on single solid sheets, porous layers, and porous-solid-porous battery electrodes. This establishes a powerful theoretical platform that allows us to develop advanced wave-based methods to quantitatively characterise properties of the layers, especially for layers of porous materials., Comment: 13 pages, 6 figures, 2 tables

International audience; Serpentinization and carbonation of ultramafic formations is a ubiquitous phenomenon, which deeply influences the biogeochemical cycles of water, hydrogen, carbon…while supporting the particular biosphere around the oceanic hydrothermal vents. Carbonation of peridotites and other mafic and ultramafic rocks is also a hot topic in the current energy landscape as the engineered sequestration of mineral CO2 in these formations could help reduce the atmospheric emissions and cope with climate change. In this study, we present two reactive percolation experiments performed on a natural serpentinite dredged from the ultraslow South-West Indian Oceanic Ridge. The serpentinite cores (length 3-4 cm and dia. 5.6 mm) were subjected for about 10 days to the continuous injection of a NaHCO3-saturated brine at respectively 160°C and 280°C. Petrographic and petrophysical results as well as outlet fluid compositions were compared to numerical batch simulations performed with the PHREEQC open software allowing to reconstruct the mineralogical evolution of both cores. The most striking observation is the fast and dramatic decrease of the permeability for both experiments principally due to the precipitation of carbonates. On the contrary, serpentine was found to be less impacting as it precipitates in low-flow zones, out of the main percolation paths. In total, about 5.6% of the total injected CO2 was retained in the core, at 280°C. In the same time, hydrogen was consistently produced with a total recovered H2 corresponding to 0.8% of the maximum H2 possible. The global behavior of the cores is interpreted as the result from an interplay between interacting spatio-temporal lengthscales controlled by the Damköhler number.

Carbon capture and storage (CCS) has emerged as the most effective method to curb the CO2 concentration in the atmosphere. It can store up to 5 billion tons of CO2 per year. To guarantee a safe and economical geological storage, the well cement degradation and wellbore integrity need to be studied thoroughly. This review paper is designed to provide a fundamental background of well cement degradation and wellbore integrity in geological CO2 storages to support the researchers in further investigation. The review mainly focuses on mechanical, thermal, chemical property changes and corrosion time for cement in experiments and simulation during geological CO2 storage. However, the debonding interface between casing/cement or cement/formation has not been addressed profoundly. A further investigation should inspect how pressure, temperature, and chemical reaction affect the micro-annuli of casing/cement or cement/formation. Also, a mathe-matical model should be established to predict the corrosion rate in geological CO2 storage., Comment: 17 pages

Seismic data processing involves techniques to deal with undesired effects that occur during acquisition and pre-processing. These effects mainly comprise coherent artefacts such as multiples, non-coherent signals such as electrical noise, and loss of signal information at the receivers that leads to incomplete traces. In the past years, there has been a remarkable increase of machine-learning-based solutions that have addressed the aforementioned issues. In particular, deep-learning practitioners have usually relied on heavily fine-tuned, customized discriminative algorithms. Although, these methods can provide solid results, they seem to lack semantic understanding of the provided data. Motivated by this limitation, in this work, we employ a generative solution, as it can explicitly model complex data distributions and hence, yield to a better decision-making process. In particular, we introduce diffusion models for three seismic applications: demultiple, denoising and interpolation. To that end, we run experiments on synthetic and on real data, and we compare the diffusion performance with standardized algorithms. We believe that our pioneer study not only demonstrates the capability of diffusion models, but also opens the door to future research to integrate generative models in seismic workflows.

This paper delivers a software -- libEMM -- for 3D controlled-source electromagnetics (CSEM) modelling in fictitious wave domain, based on the newly developed high-order finite-difference time-domain (FDTD) method on non-uniform grid. The numerical simulation can be carried out over a number of parallel processors using MPI-based high performance computing architecture. The FDTD kernel coded in C has been parallelized with OpenMP for speedup using local shared memory. In addition, the software features a GPU implementation of the same algorithm based on CUDA programming language, which can be cross-validated and compared in terms of efficiency. A perspective of libEMM on the horizon is its application to 3D CSEM inversion in land and marine environment.

Understanding rock shear failure behavior is crucial to gain insights into slip-related geohazards such as rock avalanches, landslides, and earthquakes. However, descriptions of the progressive damage on the shear surface are still incomplete or ambiguous. In this study, we use the hybrid finite-discrete element method (FDEM) to simulate a shear experiment and obtain a detailed comprehension of shear induced progressive damage and the associated seismic activity. We built a laboratory fault model from high resolution surface scans and micro-CT imaging. Our results show that under quasi-static shear loading, the fault surface experiences local dynamic seismic activities. We found that the seismic activity is related to the stress concentration on interlocking asperities. This interlocking behavior (i) causes stress concentration at the region of contact that could reach the compressive strength, and (ii) produces tensile stress up to the tensile strength in the region adjacent to the contact area. Thus, different failure mechanisms and damage patterns including crushing and sub-vertical fracturing are observed on the rough surface. Asperity failure creates rapid local slips resulting in significant stress perturbations that alter the overall stress condition and may trigger the slip of adjacent critically stressed asperities. We found that the spatial distribution of the damaged asperities and the seismic activity is highly heterogeneous; regions with intense asperity interactions formed gouge material, while others exhibit minimal to no damage. These results emphasize the important role of surface roughness in controlling the overall shear behavior and the local dynamic seismic activities on faults.

We present a novel method of using explainability techniques to design physics-aware neural networks. We demonstrate our approach by developing a convolutional neural network (CNN) for solving an inverse problem for shallow subsurface imaging. Although CNNs have gained popularity in recent years across many fields, the development of CNNs remains an art, as there are no clear guidelines regarding the selection of hyperparameters that will yield the best network. While optimization algorithms may be used to select hyperparameters automatically, these methods focus on developing networks with high predictive accuracy while disregarding model explainability (descriptive accuracy). However, the field of Explainable Artificial Intelligence (XAI) addresses the absence of model explainability by providing tools that allow developers to evaluate the internal logic of neural networks. In this study, we use the explainability methods Score-CAM and Deep SHAP to select hyperparameters, such as kernel sizes and network depth, to develop a physics-aware CNN for shallow subsurface imaging. We begin with a relatively deep Encoder-Decoder network, which uses surface wave dispersion images as inputs and generates 2D shear wave velocity subsurface images as outputs. Through model explanations, we ultimately find that a shallow CNN using two convolutional layers with an atypical kernel size of 3x1 yields comparable predictive accuracy but with increased descriptive accuracy. We also show that explainability methods can be used to evaluate the network's complexity and decision-making. We believe this method can be used to develop neural networks with high predictive accuracy while also providing inherent explainability., Comment: 26 pages, 14 figures, 4 tables

To explain Venus' young surface age and lack of plate tectonics, Venus' tectonic regime has often been proposed to be either an episodic-lid regime with global lithospheric overturns, or an equilibrium resurfacing regime with numerous volcanic and tectonic activities. Here, we use global 2-D thermochemical convection models with realistic parameters, including rheology (dislocation creep, diffusion creep, and plastic yielding), an experiment-based plagioclase (An$_{75}$) crustal rheology, and intrusive magmatism, to investigate the tectonics and mantle evolution of Venus. We find that surface tectonics is strongly affected by crustal rheology. With a ''weak'' plagioclase-rheology crust, models exhibit episodic overturns but with continuously high surface mobility and high distributed surface strain rates between overturns, leading to a new tectonic regime that we name ''deformable episodic lid''. On the other hand, olivine-crustal-rheology models exhibit either standard episodic-lid tectonics, i.e. with mobility that is high during overturns and near zero between overturns, or stagnant-lid tectonics, i.e. with near-zero mobility over the entire model time. Also, a combination of plagioclase crustal rheology and dislocation creep can weaken the lithosphere sufficiently to facilitate lithospheric overturns without applying plastic yielding. Internally, the composition-dependent density profile results in a ''basalt barrier'' at the mantle transition zone, which strongly affects Venus' mantle evolution. Only strong plumes can penetrate this basalt barrier and cause global lithospheric overturns. This basalt barrier also causes global internal episodic overturns that generate global volcanic resurfacing in stagnant-lid models, which suggests a new resurfacing mechanism (we name it ''stagnant episodic-volcanic-resurfacing'') that does not involve lithospheric overturns., Comment: Minor changes to previous version. Accepted by Icarus. Main text 54 pages, 17 figures, abstract abbreviated

A systematic model development for oil flow in quasi-3D (1D + 2D) is presented. Our approach provides a unified modeling scheme. Besides, additional terms are obtained, which allows for tubing area variation along the flow direction. The area variation can be modeled as analytic function or random fluctuation, as it could be the result of deposits or tubing internal surface roughness. The proposed approach can be used to obtain analytic solutions which provide physical insight into the phenomena under scrutiny, including the validation of software tools, sensor development and sensor placement. One starts from conservation laws as given by kinetic theory and applies the transverse averaging technique (TAT) to extract the one-dimensional approximation in formal grounds. To demonstrate its application, the steady-state Ramey's model, the Hasan's transient model and a simple two-phase model are generated from the obtained equations., Comment: 19 pages, 3 figures

The onset of frictional sliding between contacting bodies under shear load is nucleated by the quasi-static growth of localized slip patches. After reaching a certain critical size, known as the nucleation length, these patches become unstable and continue growing dynamically, eventually causing the sliding of the entire interface. Two different theories have been used to compute the nucleation length of such patches depending on the dominant process driving their growth. If it is only the yielding of contact asperities (large-scale yielding), a stress criterion is applied, based on linear stability analysis, whereas if fracture dominates (small-scale yielding), an energy criterion is applied (Griffith’s criterion), based on fracture mechanics and classical nucleation theory. Both approaches contain important underlying assumptions that are well-suited to describe either one situation or the other. However, what happens in-between is not captured by any of them. In this work, we use numerical simulations to study what is the dominant underlying process driving nucleation for different conditions of heterogeneity in the frictional strength of the interface and what are the implications for nucleation dynamics and the onset of frictional sliding. We show that large frictional heterogeneities enable a transition from a yielding-driven nucleation phase to a fracture-driven one. This transition occurs only above a certain level of heterogeneity and can either be quasi-static (stable) or dynamic (unstable), depending on the correlation length of frictional strength along the interface and the difference in strength between the strongest and the weakest point (the amplitude). Unstable transitions generate localized dynamic slip events, whose magnitude increases with higher correlation length and decreases with larger amplitude. Our work sheds new light on the role of heterogeneity and fracture in the nucleation of frictional slip, bridging the gap between the two main governing theories for nucleation., Journal of the Mechanics and Physics of Solids, 173, ISSN:0022-5096, ISSN:1873-4782

This paper emphasizes on NavIC's performance in ionospheric studies over the Indian subcontinent region. The study is performed using data of one year (2017-18) at IIT Indore, a location near the northern crest of Equatorial Ionization Anomaly (EIA). It has been observed that even without the individual error corrections, the results are within $\pm20\%$ of NavIC VTEC estimates observed over the 1\ensuremath{^{\circ}} x 1\ensuremath{^{\circ}} grid of IPP surrounding the GPS VTEC estimates for most of the time. Additionally, ionospheric response during two distinct geomagnetic storms (September 08 and 28, 2017) at the same location and other IGS stations covering the Indian subcontinent using both GPS and NavIC has also been presented. This analysis revealed similar variations in TEC during the geomagnetic storms of September 2017, indicating the suitability of NavIC to study space weather events along with the ionospheric studies over the Indian subcontinent., Comment: 38 Pages, 16 Figures, Accepted for publication in Advances in Space Research

This paper presents the response of the ionosphere during the intense geomagnetic storms of October 12-20, 2016 and May 26-31, 2017 which occurred during the declining phase of the solar cycle 24. Total Electron Content (TEC) from GPS measured at Indore, Calcutta and Siliguri having geomagnetic dips varying from 32.23{\deg}N, 32{\deg}N and 39.49{\deg}N respectively and at the International GNSS Service (IGS) stations at Lucknow (beyond anomaly crest), Hyderabad (between geomagnetic equator and northern crest of EIA) and Bangalore (near magnetic equator) in the Indian longitude zone have been used for the storms. Prominent peaks in diurnal maximum in excess of 20-45 TECU over the quiet time values were observed during the October 2016 storm at Lucknow, Indore, Hyderabad, Bangalore and 10-20 TECU for the May 2017 storm at Siliguri, Indore, Calcutta and Hyderabad. The GUVI images onboard TIMED spacecraft that measures the thermospheric O/N2 ratio, showed high values (O/N2 ratio of about 0.7) on October 16 when positive storm effects were observed compared to the other days during the storm period. The observed features have been explained in terms of the O/N2 ratio increase in the equatorial thermosphere, CIR-induced High Speed Solar Wind (HSSW) event for the October 2016 storm. The TEC enhancement has also been explained in terms of the Auroral Electrojet (AE), neutral wind values obtained from the Horizontal Wind Model (HWM14) and equatorial electrojet strength from magnetometer data for both October 2016 and May 2017 storms. These results are one of the first to be reported from the Indian longitude sector on influence of CME- and CIR-driven geomagnetic storms on TEC during the declining phase of solar cycle 24., Comment: 41 pages, 14 figures. Accepted for publication in Advances in Space Research

Anthropogenic emissions of CO2 must soon approach net zero to stabilize the global mean temperature. Although several international agreements have advocated for coordinated climate actions, their implementation has remained below expectations. One of the main challenges of international cooperation is the different degrees of socio-political acceptance of decarbonization.In this contribution, we interrogate a minimalistic model of the coupled human-natural system representing the impact of such socio-political acceptance on investments in clean energy and the path to net-zero emissions. Despite its simplicity, the model can reproduce complex interactions between human and natural systems, and it can disentangle the effects of climate policies from those of socio-political acceptance on the path to net zero. Although perfect coordination remains unlikely, as clean energy investments are limited by myopic economic strategies and a policy system that promotes free-riding, more realistic decentralized cooperation with partial efforts from each actor could still lead to significant emissions cuts.Since the socio-political feedback on the path to net zero could influence the trajectories of the Earth System for decades to centuries and beyond, climate models need to incorporate better the dynamical bi-directional interactions between socio-political groups and the environment. Our model represents a first step for incorporating this feedback in describing complex coupled human and natural systems.

This paper describes the wide-field three-color observations of an expanded field of noctilucent clouds modulated by a one-dimensional gravity wave. Long wave crests were aligned by a small angle to the solar vertical in the sky. This made possible separate determination of altitude and particle size at different wave phases based on three-color photometry of noctilucent clouds. Thereby, it is possible to use simple optical imaging to record the changes in the parameters of noctilucent clouds when a short-period gravity wave passes by., 8 pages, 6 figures, submitted to Planetary and Space Science

Based on a novel treatment of near resonances, we introduce a new approximation for the rotating stratified Boussinesq system on three-dimensional tori with arbitrary aspect ratios. The rotation and stratification parameters are arbitrary and not equal. We obtain global existence for the proposed nonlinear system for arbitrarily large initial data. This system is sufficiently accurate, with an important feature of coupling effects between slow and fast modes. The key to global existence is a sharp counting of the relevant number of nonlinear interactions. An additional regularity advantage arises from a careful examination of some mixed type interaction coefficients. In a wider context, the significance of our near resonant approach is a delicate balance between the inclusion of more interacting modes and the improvement of regularity properties, compared to the well-studied singular limit approach based on exact resonance.

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e., depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder. Estimation with uncertainty quantification (UQ) is performed on the low-dimensional latent space in a Bayesian setting. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

The complexity of geomodelling workflows is a limiting factor for quantifying and updating uncertainty in real-time during drilling. We propose Generative Adversarial Networks (GANs) for parametrization and generation of geomodels, combined with Ensemble Randomized Maximum Likelihood (EnRML) for rapid updating of subsurface uncertainty. This real-time ensemble method combined with a highly non-linear model arising from neural-network modeling sequences might produce inaccurate and/or biased posterior solutions. This paper illustrates the predictive ability of EnRML on several examples where we assimilate local extra-deep electromagnetic logs. Statistical verification with MCMC confirms that the proposed workflow can produce reliable results required for geosteering wells., Submitted to Journal of Computational Science. arXiv admin note: substantial text overlap with arXiv:2104.02550

The problem of a plane strain hydraulic fracture propagating in a layered formation is considered. Fracture toughness, in-situ stress, and leak-off coefficient are assumed to vary by layer, while the elastic properties are kept constant throughout the domain for simplicity. The purpose of this study is to develop a numerical algorithm based on a fixed mesh approach, which is capable to solve the above problem accurately using elements which can even be larger than the layer size. In order to do this, the concept of fictitious tip stress is first introduced for determining the fracture front location. In this technique, an additional stress is applied to the tip element with the purpose to suppress opening and to mimic width corresponding to the actual fracture front location. A theoretical basis for this concept has been established and it is further calibrated for piece-wise constant elements. Once the ability to track the crack front location is developed, the effect of layers is included by vary properties as a function of front location. Several numerical examples benchmarking the numerical solution, as well as highlighting capabilities of the algorithm to tackle multiple thin layers accurately are presented.

There is a need for computational models capable of predicting meltwater-assisted crevasse growth in glacial ice. Mass loss from glaciers and ice sheets is the largest contributor to sea-level rise and iceberg calving due to hydrofracture is one of the most prominent yet less understood glacial mass loss processes. To overcome the limitations of empirical and analytical approaches, we here propose a new phase field-based computational framework to simulate crevasse growth in both grounded ice sheets and floating ice shelves. The model incorporates the three elements needed to mechanistically simulate hydrofracture of surface and basal crevasses: (i) a constitutive description incorporating the non-linear viscous rheology of ice, (ii) a phase field formulation capable of capturing cracking phenomena of arbitrary complexity, such as 3D crevasse interaction, and (iii) a poro-damage representation to account for the role of meltwater pressure on crevasse growth. A stress-based phase field model is adopted to reduce the length-scale sensitivity, as needed to tackle the large scales of iceberg calving, and to adequately predict crevasse growth in tensile stress regions of incompressible solids. The potential of the computational framework presented is demonstrated by addressing a number of 2D and 3D case studies, involving single and multiple crevasses, and considering both grounded and floating conditions. The model results show a good agreement with analytical approaches when particularised to the idealised scenarios where these are relevant. More importantly, we demonstrate how the model can be used to provide the first computational predictions of crevasse interactions in floating ice shelves and 3D ice sheets, shedding new light into these phenomena. Also, the creep-assisted nucleation and growth of crevasses is simulated in a realistic geometry, corresponding to the Helheim glacier. The computational framework presented opens new horizons in the modelling of iceberg calving and, due to its ability to incorporate incompressible behaviour, can be readily incorporated into numerical ice sheet models for projecting sea-level rise.

Numerical models for predicting future ice-mass loss of the Antarctic and Greenland ice sheet requires accurately representing their dynamics. Unfortunately, ice-sheet models suffer from a very strict time-step size constraint, which for higher-order models constitutes a severe bottleneck since in each time step a nonlinear and computationally demanding system of equations has to be solved. In this study, stable time-step sizes are increased for a full-Stokes model by implementing a so-called free-surface stabilization algorithm (FSSA). Previously this stabilization has been used successfully in mantle-convection simulations where a similar, but linear, viscous-flow problem is solved. By numerical investigation it is demonstrated that instabilities on the very thin domains required for ice-sheet modeling behave differently than on the equal-aspect-ratio domains the stabilization has previously been used on. Despite this, and despite the nonlinearity of the problem, it is shown that it is possible to adapt FSSA to work on idealized ice-sheet domains and increase stable time-step sizes by at least one order of magnitude. The FSSA presented is deemed accurate, efficient and straightforward to implement into existing ice-sheet solvers.

We formulate a numerical method for solving the two-phase flow poroelasticity equations. The scheme employs the interior penalty discontinuous Galerkin method and a sequential time-stepping method. The unknowns are the phase pressures and the displacement. Existence of the solution is proved. Three-dimensional numerical results show the accuracy and robustness of the proposed method.

We present a procedure for assessing the urban exposure and seismic vulnerability that integrates LiDAR data with aerial images from the Spanish National Plan of Aerial Orthophotography (PNOA). It comprises three phases: first, we segment the satellite image to divide the study area into different urban patterns. Second, we extract building footprints and attributes that represent the type of building of each urban pattern. Finally, we assign the seismic vulnerability to each building using different machine-learning techniques: Decision trees, SVM, logistic regression and Bayesian networks. We apply the procedure to 826 buildings in the city of Lorca (SE Spain), where we count on a vulnerability database that we use as ground truth for the validation of results. The outcomes show that the machine learning techniques have similar performance, yielding vulnerability classification results with an accuracy of 77%–80% (F1-Score). The procedure is scalable and can be replicated in different areas. This is particularly relevant in Spain, where more than seven hundred towns have to develop seismic risk studies in the years to come, according to the General Direction of Civil Protection and Emergencies. It is especially interesting as a complement to conventional data gathering approaches for disaster risk applications in cities where field surveys need to be restricted to certain areas, dates or budget.

The potential complementarity between chondrules and matrix of chondrites, the Solar System's building blocks, is still a highly debated subject. Complementary superchrondritic compositions of chondrite matrices and subchondritic chondrules may point to formation of these components within the same reservoir or, alternatively, to mobilization of elements during secondary alteration on chondrite parent bodies. Zinc isotope fractionation through evaporation during chondrule formation may play an important role in identifying complementary relationships between chondrules and matrix and is additionally a mobile element during hydrothermal processes. In an effort to distinguish between primary Zn isotope fractionation during chondrule formation and secondary alteration, we here report the Zn isotope data of five chondrule cores, five corresponding igneous rims and two matrices of the relatively unaltered Leoville CV3.1 chondrite. The detail required for these analyses necessitated the development of an adjusted Zn isotope analyses protocol outlined in this study., Comment: in press

A new physically based method to estimate hemispheric-directional reflectance factor (HDRF) from lightweight multispectral cameras that have a downwelling irradiance sensor is presented. It combines radiometry with photogrammetric computer vision to derive geometrically and radiometrically accurate data purely from the images, without requiring reflectance targets or any other additional information apart from the imagery. The sky sensor orientation is initially computed using photogrammetric computer vision and revised with a non-linear regression comprising radiometric and photogrammetry-derived information. It works for both clear sky and overcast conditions. A ground-based test acquisition of a Spectralon target observed from different viewing directions and with different sun positions using a typical multispectral sensor configuration for clear sky and overcast showed that both the overall value and the directionality of the reflectance factor as reported in the literature were well retrieved. An RMSE of 3% for clear sky and up to 5 for overcast sky was observed.

Seismology is the main tool for inferring the deep interior structures of Earth and potentially also of other planetary bodies in the solar system. Terrestrial seismology is influenced by the presence of the ocean-generated microseismic signal, which sets a lower limit on the earthquake detection capabilities but also provides a strong energy source to infer the interior structure on scales from local to continental. Titan is the only other place in the solar system with permanent surface liquids and future lander missions there might carry a seismic package. Therefore, the presence of microseisms would be of great benefit for interior studies, but also for detecting storm-generated waves on the lakes remotely. We estimated the strength of microseismic signals on Titan, based on wind speeds predicted from modeled global circulation models interior structure. We find that storms of more than 2 m/s wind speed, would create a signal that is globally observable with a high-quality broadband sensor and observable to a thousand kilometer distance with a space-ready seismometer, such as the InSight instruments currently operating on the surface of Mars., 24 pages, 6 figures

A recent statistical analysis of the relationship between tides and seismic activity in Colombia has suggested the existence of correlation anomalies for the case of intermediate depth events in the Bucaramanga nest and the Cauca cluster (Moncayo et al., 2019). In this work, we explore in detail the hypothesis that tides may be triggering seismic activity in these regions and extend the analysis to two other seismic clusters in northern-central South America, specifically in the areas of El Puyo (Ecuador) and Pucallpa (Peru). For this purpose, we use the available focal mechanism information for seismic events at these locations, and calculate for each event the Tidal Coulomb Failure Stress (TCFS) as obtained from estimations of the tidal strain tensor. Tidal strains are computed considering the Earth body tides and the effect of the ocean tidal loading. Since our purpose is to elucidate the role of tides in earthquake nucleation, calculations of the TCFS are conducted not only for the time of earthquake, but also for the time of the closest maximum strain within a window of a few hours before the events. Our results tend to support the hypothesis that tidal stresses are contributing to earthquake generation in all the studied areas; this trend is especially stronger when TCFS are calculated at pre-earthquake times. The physical explanation for the positive contribution of tides to earthquake triggering in intermediate depth clusters may lie in the fact that a wide diversity of fault plane orientations is possible within a relatively small volume of subducted lithosphere, so making the tides more likely to help loosening up the blocks at the fault plane to promote slip., Comment: 46 pages, 11 figures, 8 tables, 2 supplementary figures. Submitted to Tectonophysics

Proximal gamma-ray spectroscopy supported by adequate calibration and correction for growing biomass is an effective field scale technique for a continuous monitoring of top soil water content dynamics to be potentially employed as a decision support tool for automatic irrigation scheduling. This study demonstrates that this approach has the potential to be one of the best space-time trade-off methods, representing a joining link between punctual and satellite fields of view. The inverse proportionality between soil moisture and gamma signal is theoretically derived taking into account a non-constant correction due to the presence of growing vegetation beneath the detector position. The gamma signal attenuation due to biomass is modelled with a Monte Carlo-based approach in terms of an equivalent water layer which thickness varies in time as the crop evolves during its life-cycle. The reliability and effectiveness of this approach is proved through a 7 months continuous acquisition of terrestrial gamma radiation in a 0.4 ha tomato (Solanum lycopersicum) test field. We demonstrate that a permanent gamma station installed at an agricultural field can reliably probe the water content of the top soil only if systematic effects due to the biomass shielding are properly accounted for. Biomass corrected experimental values of soil water content inferred from radiometric measurements are compared with gravimetric data acquired under different soil moisture levels, resulting in an average percentage relative discrepancy of about 3% in bare soil condition and of 4% during the vegetated period. The temporal evolution of corrected soil water content values exhibits a dynamic range coherent with the soil hydraulic properties in terms of wilting point, field capacity and saturation., 25 pages, 8 figures, 2 tables

The initiation and development of fractures in rocks is the key part of many problems from academic to industrial, such as faulting, folding, rock mass engineering, reservoir characterization, etc. Conventional ways of evaluating the fracture historical deformations depend on the geologists' visual interpretation of indicating structures such as fault striations, fault steps, plumose structures, etc. on the fracture surface produced by previous deformations, and hence suffer from problems like subjectivity and the absence of obvious indicating structures. In this study, we propose a quantitative method to derive historical shear deformations of rock fractures from digital outcrop models (DOMs) based on the analysis of effects of fault striations and fault steps on the shear strength parameter of the fracture surface. A theoretical model that combines effects of fault striations, fault steps and isotropic base shear strength is fitted to the shear strength parameter. The amount of fault striations and fault steps and their occurrences are estimated, and the historical shear deformations can be inferred. The validity and the effectiveness of the proposed method was proved by testing it on a constructed fracture surface with idealized striations and a fracture surface with clear fault steps. The application of this method on an example outcrop shows an intuitive idea of how the rock mass was deformed and that the distribution, occurrence and mode of new fractures are strictly controlled by preexisting fractures, and hence emphasizes the importance of preexisting fractures in modeling the development of fracture systems., Comment: 23 pages, 10 figures

In this work we propose a robust methodology to mitigate the undesirable effects caused by outliers to generate reliable physical models. In this way, we formulate the inverse problems theory in the context of Kaniadakis statistical mechanics (or $\kappa$-statistics), in which the classical approach is a particular case. In this regard, the errors are assumed to be distributed according to a finite-variance $\kappa$-generalized Gaussian distribution. Based on the probabilistic maximum-likelihood method we derive a $\kappa$-objective function associated with the finite-variance $\kappa$-Gaussian distribution. To demonstrate our proposal's outlier-resistance, we analyze the robustness properties of the $\kappa$-objective function with help of the so-called influence function. In this regard, we discuss the role of the entropic index ($\kappa$) associated with the Kaniadakis $\kappa$-entropy in the effectiveness in inferring physical parameters by using strongly noisy data. In this way, we consider a classical geophysical data-inverse problem in two realistic circumstances, in which the first one refers to study the sensibility of our proposal to uncertainties in the input parameters, and the second is devoted to the inversion of a seismic data set contaminated by outliers. The results reveal an optimum $\kappa$-value at the limit $\kappa \rightarrow 2/3$, which is related to the best results., Comment: 37 pages, 23 figures

The dynamic behavior of crystals in convecting fluids determines how magma bodies solidify. In particular, it is often important to estimate how long crystals stay in suspension in the host liquid before being deposited at its bottom (or top, for light particles). We perform a systematic 3D numerical study of particle-laden Rayleigh-Benard convection, and derive a robust model for the particle residence time. For Rayleigh numbers higher than 10^7, inertial particles' trajectories exhibit a monotonic transition from fluid tracer-like to free-fall dynamics, the control parameter being the ratio between particle Stokes velocity and the fluid velocity. The average settling rate is proportional to the particle Stokes velocity in both the end-member regimes, but the distribution of the residence times differs markedly from one to the other. For lower Rayleigh numbers (, To be submitted to Earth and Planetary Science Letters

The Azure Window was a natural arch situated in the west coast of Gozo (Maltese Archipelago) that collapsed in March 2017. We employ a Diver Propulsion Vehicle-mounted camera system to capture data for the 3D-modelling of this collapsed arch via photogrammetry. We demonstrate use of this method to document complex underwater geomorphology spread across a large area, and draw up a geomorphic assessment of the site and collapse event on the basis of this 3D-model. The methodology enables a reconstruction and understanding of the collapse event. On account of the high-resolution attained, we are able to cross-match the principal submerged components with their pre-collapse location; this enables an understanding of the dynamics of the collapse, confirmation of rock break-up along existing joints, and mapping the distribution of the rock and debris from the collapse event. We conclude that the key stages in the collapse of the Azure Window entailed erosion at the base of the pillar, leading to the latter's collapse in the southwest direction, breaking into two main sections that separated along the lithological boundary. We also find clear evidence that separation of some sections of the pillar followed pre-existing joints. The bridge collapsed vertically upon loss of support from the pillar, breaking into two main components and many other fragments. We also document further changes at the site post-collapse. We show that this approach can be utilised to understand and characterise such events even when significant time has elapsed since collapse, and rocks have already undergone erosion and significant marine growth., 33 pages, 14 figures, accepted for publication in Geomorphology

Mesosiderites are a type of stony-iron meteorites composed of a mixture of silicates and Fe-Ni metals. The mesosiderite silicates and metals are considered to have originated from the crust and metal core, respectively, of a differentiated asteroid. In contrast, mesosiderites rarely contain the olivine that is mainly included in a mantle. Although a giant impact onto a differentiated asteroid is considered to be a probable mechanism to mix crust and metal materials to form mesosiderites, it is not obvious how such a giant impact can form mesosiderite-like materials without including mantle materials. We conducted numerical simulations of giant impacts onto differentiated asteroids, using the smoothed particle hydrodynamics method, to investigate the detailed distribution of mixed materials on the resultant bodies. For the internal structure of a target body, we used a thin-crust model derived from the magma ocean crystallization model of the asteroid Vesta and a thick-crust and a large-core model suggested from the proximity observation of Vesta by the Dawn probe. In the simulations with the former model, excavation of the metal core requires nearly catastrophic impacts and mantle is exposed over large surface areas. Thus, stony-iron materials produced on its surface are likely to include mantle materials and it is difficult to produce mesosiderite-like materials. Conversely, in the simulations with the latter model, mantle materials are exposed only at impact sites, even when the impacts excavate the metal core, and the formation of a surface with little mantle material and the formation of mesosiderite-like materials are possible. Therefore, our simulations suggest that an internal structure with a thick crust and a large core is more likely as a mesosiderite parent body rather than the thin-crust internal structure inferred from the conventional magma ocean model., 21 pages, 8 figures, accepted for publication in Icarus

To enable fast uncertainty quantification of fluid flow in a discrete fracture network (DFN), we present two approaches to quickly compute fluid flow in DFNs using combinatorial optimization algorithms. Specifically, the presented Hanan Shortest Path Maxflow (HSPM) and Intersection Shortest Path Maxflow (ISPM) methods translate DFN geometries and properties to a graph on which a max flow algorithm computes a combinatorial flow, from which an overall fluid flow rate is estimated using a shortest path decomposition of this flow. The two approaches are assessed by comparing their predictions with results from explicit numerical simulations of simple test cases as well as stochastic DFN realizations covering a range of fracture densities. Both methods have a high accuracy and very low computational cost, which can facilitate much-needed in-depth analyses of the propagation of uncertainty in fracture and fracture-network properties to fluid flow rates.

The important question of absolute dating of seismic phenomena has been the study of several researchers over the past few decades. The relevant research has concentrated on 'energy traps' of minerals, such as quartz or feldspar, which may accumulate chronological information associated with tectonic deformations. However, the produced knowledge so far, is not sufficient to allow the absolute dating of faults. Today, Luminescence and Electron Spin Resonance (ESR) dating methods could be seen as offering high potential for dating past seismic deformed features on timescales ranging from some years to even several million years. This preliminary study attempts to establish the potential of three different carbonate fault zones hosting fault mirror-like structures, to be used in luminescence and ESR dating, based on their microstructural, mineralogical and palaeo-maximum temperatures analysis. The results indicated that the collected samples can be considered datable fault-rock materials, since they contain suitable minerals (quartz) for luminescence and ESR dating, have experienced repeated cataclastic deformation and have been subject to various physical and chemical processes as well as pressure and temperature conditions., This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 743607

The accurate and efficient modeling of granular flows and their interactions with external bodies is an open research problem. Continuum methods can be used to capture complexities neglected by terramechanics models without the computational expense of discrete element methods. Constitutive models and numerical solvers are the two primary aspects of the continuum methods. The viscoplastic size-dependent non-local granular fluidity (NGF) constitutive model has successfully provided a quantitative description of experimental flows in many different configurations in literature. This research develops a numerical approach, within a hyperelasticity framework, for implementing the dynamical form of NGF in three-dimensional material point method (3D MPM, an appropriate numerical solver for granular flow modeling). This approach is thermodynamically consistent to conserve energy, and the dynamical form includes the nonlocal effect of flow cessation. Excavation data, both quantitative measurements and qualitative visualization, are collected experimentally via our robotic equipment to evaluate the model with respect to the flow geometry as well as interaction forces. The results are further compared with the results from a recent modified plastic Drucker-Prager constitutive model, and in other configurations including wheel-soil interactions, a gravity-driven silo, and Taylor-Couette flow.

Fission-track annealing models aim to extrapolate laboratory annealing kinetics to the geological timescale for application to geological studies. Model trends empirically capture the mechanisms of track length reduction. To facilitate the interpretation of the fission-track annealing trends, a formalism, based on quantities already in use for the study of physicochemical processes, is developed and allows for the calculation of rate constants, Arrhenius activation energies, and transitivity functions for the fission-track annealing models. These quantities are then obtained for the parallel Arrhenius, parallel curvilinear, fanning Arrhenius, and fanning curvilinear models, fitted with Durango apatite data. Parallel models showed to be consistent with a single activation energy mechanism and a reaction order model of order ~ -4. However, the fanning curvilinear model is the one that results in better fits laboratory data and predictions in better agreement with geological evidence. Fanning models seem to describe a more complex picture, with concurrent recombination mechanisms presenting activation energies varying with time and temperature, and the reaction order model seems not to be the most appropriate. It is apparent from the transitivity analysis that the dominant mechanisms described by the fanning models are classical (not quantum) energy barrier transitions., This is not the accepted version of the paper. It only has some small corrections. The accepted version will be posted after the embargo period

It has recently been found that the evolution of the preparation of a strong earthquake (EQ), as it is monitored through fracture-induced electromagnetic emissions (EME) in the MHz band, presents striking similarity with the evolution of a thermal system as temperature drops, since distinct steps of the evolution of the phenomenon of spontaneous symmetry breaking (SSB) can be identified. Here, the study of fracture-induced EME in the MHz band in analogy to thermal systems is extended to the phase of local fracture structures that follow after the SSB (and the occurrence of the main EQ). By comparing fracture-induced MHz EME associated with the strongest EQs (Mw=6.9) that occurred in Greece during the last twenty years with the 3D Ising model, a way to distinguish whether a possible identification of post-SSB power-laws immediately after a very strong EQ is a sign for the preparation of a new strong EQ or not is provided. In the suggested approach, the time series analysis method known as the method of critical fluctuations is used, enhanced by the autocorrelation function, while the role of the latter proves to be decisive.

The link between the surface temperature of Mercury and the exosphere sodium content has been investigated. Observations show that, along the orbit of Mercury, two maxima of total Na content are present: one at aphelion and one at perihelion. Previous models, based on a simple thermal map, were not able to reproduce the aphelion peak. Here we introduce a new thermophysical model giving soil temperatures as an input for the IAPS exospheric model already used in the past with the input of a simple thermal map. By comparing the reference model output with the new one, we show that such improved surface temperature map is crucial to explain the temporal variability of Sodium along the orbit.

We study a three-dimensional fluid model describing rapidly rotating convection that takes place in tall columnar structures. The purpose of this model is to investigate the cyclonic and anticyclonic coherent structures. Global existence, uniqueness, continuous dependence on initial data, and large-time behavior of strong solutions are shown provided the model is regularized by a weak dissipation term.

The standard smooth electrical resistivity tomography inversion produces an estimate of subsurface conductivity that has blurred boundaries, damped magnitudes, and often contains inversion artifacts. In many problems the expected conductivity structure is well constrained in some parts of the subsurface, but incorporating prior information in the inversion is not a trivial task. In this study we developed an electrical resistivity tomography inversion algorithm that combines parametric and smooth inversion strategies. In regions where the subsurface is well constrained, the model was parameterized with only a few variables, while the rest of the subsurface was parameterized with voxels. We tested this hybrid inversion strategy on two synthetic models that contained a well constrained highly resistive or conductive near-surface horizontal layer and a target beneath. In each testing scenario, the hybrid inversion improved resolution of feature boundaries and magnitudes and had fewer inversion artifacts than the standard smooth inversion. A sensitivity analysis showed that the hybrid inversion successfully recovered subsurface features when a range of regularization parameters, initial models, and data noise levels were tested. The hybrid inversion strategy can potentially be expanded to a range of applications including marine surveys, permafrost/frozen ground studies, urban geophysics, or anywhere that prior information allows part of the model to be constrained with simple geometric shapes.

Dust emission mechanisms as one aspect of wind-driven particle motion on planetary surfaces are still poorly understood. The microphysics is important though as it determines dust sizes and morphologies which set sedimentation speeds and optical properties. We consider the effects of tribocharging in this context as grains in wind driven granular matter charge significantly. This leads to large electric fields above the granular bed. Airborne dielectric grains are polarized in these electric fields, which leads to attractive forces between grains. To simulate aggregation under these conditions we carried out drop tower experiments using tracer particles, mimicking the gas coupling behavior of small dust grains in terms of high surface to mass ratios and efficient gas drag. Under microgravity, the particles are released into an observation chamber in which an alternating electric field up to 80 kV/m is applied. Without electric field no aggregation can be observed on timescales of seconds. However, polarization instantly leads to aggregation of particles when the field is switched on and long chains aligned to the electric field form. Scaled to dust entrained into planetary atmospheres, fine and coarse grain fractions might readily form aggregates after being liberated. Under certain natural conditions, aggregates might therefore start chain-like or at least a chain-like appearance is favored. If atmospheric influences on their stability are small, aerodynamic and optical properties might depend on this.

Impacts between planetary-sized bodies can explain the origin of satellites orbiting large ( R > 500 km) trans-Neptunian objects. Their water rich composition, along with the complex phase diagram of water, make it important to accurately model the wide range of thermodynamic conditions material experiences during an impact event and in the debris disk. Since differences in the thermodynamics may influence the system dynamics, we seek to evaluate how the choice of an equation of state (EOS) alters the system’s evolution. Specifically, we compare two EOSs that are constructed by different approaches: either by a simplified analytic description (Tillotson), or by interpolation of tabulated data (Sesame). Approximately 50 pairs of Smoothed Particle Hydrodynamics impact simulations were performed, with similar initial conditions but different EOSs, in the parameter space in which the Pluto–Charon binary is thought to form (slow impacts between Pluto-size, water rich bodies). Generally, we show that impact outcomes (e.g., circumplanetary debris disk) are consistent between EOSs. Some differences arise, importantly in the production of satellitesimals (large intact clumps) that form in the post-impact debris disk. When utilizing an analytic EOS, the emergence of satellitesimals is highly certain, while when using the tabulated EOS it is less common. This is because for the typical densities and energies experienced in these impacts, the analytic EOS predicts very low pressure values, leading to particles artificially aggregating by a tensile instability.

Frictional sliding is an intrinsically complex phenomenon, emerging from the interplay between driving forces, elasto-frictional instabilities, interfacial nonlinearity and dissipation, material inertia and bulk geometry. We show that homogeneous rate-and-state dependent frictional systems, driven at a prescribed boundary velocity -- as opposed to a prescribed stress -- in a range where the frictional interface is rate-weakening, generically host self-healing slip pulses, a sliding mode not yet fully understood. Such velocity-driven frictional systems are then shown to exhibit coarsening dynamics saturated at the system length in the sliding direction, independently of the system's height, leading to steadily propagating pulse trains. The latter may be viewed as a propagating phase-separated state, where slip and stick characterize the two phases. While pulse trains' periodicity is coarsening-limited by the system's length, the single pulse width, characteristic slip velocity and propagation speed exhibit rich properties, which are comprehensively understood using theory and extensive numerics. Finally, we show that for sufficiently small system heights, pulse trains are accompanied by periodic elasto-frictional instabilities., 18 page, 9 figures (including appendices)

Fault zones are associated with multi-scale heterogeneities of rock properties. Large scale variations may be imaged with conventional seismic reflection methods that detect offsets in geological units, and tomographic techniques that provide average seismic velocities in resolved volumes. However, characterizing elementary localized inhomogeneities of fault zones, such as cracks and fractures, constitutes a challenge for conventional techniques. Resolving these small-scale heterogeneities can provide detailed information for structural and mechanical models of fault zones. Recently, the reflection matrix approach utilizing body wave reflections in ambient noise cross-correlations was extended with the introduction of aberration corrections to handle the actual lateral velocity variations in the fault zone [Touma et al., Geophys. J. Int. 226, 780-794, 2021]. Here this method is applied further to analyze the distribution of scatterers in the first few kilometers of the crust in the San Jacinto Fault Zone at the Sage Brush Flat (SGB) site, southeast of Anza, California. The matrix approach allows us to image not only specular reflectors but also to resolve the presence, location and intensity of scatterers of seismic waves starting with a simple homogeneous background velocity model of the medium. The derived three-dimensional image of the fault zone resolves lateral variations of scattering properties in the region within and around the surface fault traces, as well as differences between the Northwest (NW) and the Southeast (SE) parts of the study area. A localized intense damage zone at depth is observed in the SE section, suggesting that a geometrical complexity of the fault zone at depth induces ongoing generation of rock damage., 15 pages, 8 figures

Segmentation and analysis of individual pores and grains of mudrocks from scanning electron microscope images is non-trivial because of noise, imaging artifacts, variation in pixel grayscale values across images, and overlaps in grayscale values among different physical features such as silt grains, clay grains, and pores in an image, which make their identification difficult. Moreover, because grains and pores often have overlapping grayscale values, direct application of threshold-based segmentation techniques is not sufficient. Recent advances in the field of computer vision have made it easier and faster to segment images and identify multiple occurrences of such features in an image, provided that ground-truth data for training the algorithm is available. Here, we propose a deep learning SEM image segmentation model, MudrockNet based on Google's DeepLab-v3+ architecture implemented with the TensorFlow library. The ground-truth data was obtained from an image-processing workflow applied to scanning electron microscope images of uncemented muds from the Kumano Basin offshore Japan at depths < 1.1 km. The trained deep learning model obtained a pixel-accuracy about 90%, and predictions for the test data obtained a mean intersection over union (IoU) of 0.6591 for silt grains and 0.6642 for pores. We also compared our model with the random forest classifier using trainable Weka segmentation in ImageJ, and it was observed that MudrockNet gave better predictions for both silt grains and pores. The size, concentration, and spatial arrangement of the silt and clay grains can affect the petrophysical properties of a mudrock, and an automated method to accurately identify the different grains and pores in mudrocks can help improve reservoir and seal characterization for petroleum exploration and anthropogenic waste sequestration., 24 pages, 8 figures, submitted to Computers and Geosciences