CyberSec Research

This study examines the feasibility of carbon dioxide storage in shale rocks and the reliability of reactive transport models in achieving accurate replication of the chemo-mechanical interactions and transport processes transpiring in these rocks when subjected to CO2 saturated brine. Owing to the heterogeneity of rocks, experimental testing for adequate deductions and findings, could be an expensive and time-intensive process. Therefore, this study proposes utilization of reactive transport modeling to replicate the pore-scale chemo-mechanical reactions and transport processes occurring in silicate-rich shale rocks in the presence of CO2 saturated brine under high pressure and high temperature. For this study, Crunch Tope has been adopted to simulate a one-dimensional reactive transport model of a Permian rock specimen exposed to the acidic brine at a temperature of 100 {\deg}C and pressure of 12.40 MPa (1800 psi) for a period of 14 and 28 days. The results demonstrated significant dissolution followed by precipitation of quartz rich phases, precipitation and swelling of clay rich phases, and dissolution of feldspar rich phases closer to the acidic brine-rock interface. Moreover, porosity against reaction depth curve showed nearly 1.00% mineral precipitation occur at 14 and 28 days, which is insufficient to completely fill the pore spaces.

The Kefalonia Transform Fault Zone (KTFZ) is the most seismically active area in the Mediterranean and consists of two major branches, the Lefkada fault segment to the north and the Kefalonia fault segment to the south. KTFZ acts as an active boundary between the subduction zone of the remnants of the oceanic lithosphere of the Eastern Mediterranean that subducts under the Aegean microplate to the south and the continental collision between the Eurasian plate and the Adriatic Microplate to the north. The tectonic activity in the region is reflected in the rapid crustal deformation rates of the region and subsequently the frequent occurrence of strong earthquakes (Mw>6.0) that occurred during both the historical and instrumental era of seismology. Those strong earthquakes and their temporal distribution can be explained due to stress transfer between closely located fault segments (Papadimitriou, 2002) and as such, studying those stress interactions is an integral part of understanding the long-term tectonic loading in the region.

The M6.0 earthquakes recurrence times, Tr, exhibit high variability from 40 to 1500 years, with the southern Corinth Rift fault segments reaching values up to 350 years and their antithetic ones ranging from 400 to 1500 years. The fault segments in the Corinth Rift can be divided into three groups, according to their recurrence behaviour, with some of them exhibiting significantly lower renewal model probabilities than the Poisson model, others showing nearly equal probabilities, and one segment where the renewal model probabilities are much higher than the Poisson one.

In the past two decades, transit surveys have revealed a class of planets with thick atmospheres -- sub-Neptunes -- that must have completed their accretion in protoplanet disks. When planets form in the gaseous disk, the gravitational interaction with the disk gas drives their migration and results in the trapping of neighboring planets in mean motion resonances, though these resonances can later be broken when the damping effects of disk gas or planetesimals wane. It is widely accepted that the outer Solar System gas giant planets originally formed in a resonant chain, which was later disrupted by dynamical instabilities. Here, we explore whether the early formation of the terrestrial planets in a resonance chain (including Theia) can evolve to the present configuration. Using N-body simulations, we demonstrate that the giant planet instability would also have destabilized the terrestrial resonance chain, triggering moon-forming giant impacts in 20--50\% of our simulated systems, dependent on the initial resonance architecture. After the instability, the eccentricity and inclination of the simulated planets match their present-day values. Under the proposed scenario, the current period ratio of 3.05 between Mars and Venus -- devoid of any special significance in traditional late formation models -- naturally arises as a relic of the former resonance chain.

The recent breakthroughs in the distribution of quantum information and high-precision time and frequency (T&F) signals over long-haul optical fibre networks have transformative potential for physically secure communications, resilience of Global Navigation Satellite Systems (GNSS) and fundamental physics. However, so far these capabilities remain confined to isolated testbeds, with quantum and T&F signals accessible, for example in Germany, to only a few institutions. We propose the QTF-Backbone: a dedicated national fibre-optic infrastructure in Germany for the networked distribution of quantum and T&F signals using dark fibres and specialized hardware. The QTF-Backbone is planned as a four-phase deployment over ten years to ensure scalable, sustainable access for research institutions and industry. The concept builds on successful demonstrations of high-TRL time and frequency distribution across Europe, including PTB-MPQ links in Germany, REFIMEVE in France, and the Italian LIFT network. The QTF-Backbone will enable transformative R&D, support a nationwide QTF ecosystem, and ensure the transition from innovation to deployment. As a national and European hub, it will position Germany and Europe at the forefront of quantum networking, as well as time and frequency transfer.

The seismically active regions often correlate with fault lines, and the movement of these faults plays a crucial role in defining how stress is stored or released in these areas. To investigate the deformation and accumulation/release of stress and strain in seismically active regions during the aseismic period, a mathematical model has been developed by considering a finite, creeping dip-slip fault inclined in the viscoelastic half-space of a fractional Burger rheology. Laplace transformation for fractional derivatives, Modified Green's function technique, correspondence principle and finally, the inverse Laplace transformation have been used to derive analytical solutions for displacement, stress and strain components. The graphical representations were depicted using MATLAB to understand the effect on displacement, stresses and strains due to changes in inclinations and creep velocities of the fault, as well as orders of the fractional derivative. Our investigation indicates that a change in creep velocity and inclination of the fault has a significant effect, while a change in the order of fractional derivative has a moderate effect on displacement, stress, and strain components. Analysis of these results can provide insights into subsurface deformation and its impact on fault movement, which can lead to earthquakes.

Climate hazards can escalate into humanitarian disasters. Understanding their trajectories -- considering hazard intensity, human exposure, and societal vulnerability -- is essential for effective anticipatory action. The International Disaster Database (EM-DAT) is the only freely available global resource of humanitarian disaster records. However, it lacks exact geospatial information, limiting its use for climate hazard impact research. Here, we provide geocoding of 9,217 climate-related disasters reported by EM-DAT from 1990 to 2023, along with an open, reproducible framework for updating. Our method remains accurate even when only region names are available and includes quality flags to assess reliability. The augmented EM-DAT enables integration with other geocoded data, supporting more accurate assessment of climate disaster impacts and adaptation deficits.

The Fe pressure-temperature phase diagram and its melting line have a wide range of applications, including providing constraints for iron-core planetary models. We propose an equation of state (EOS) model based on the interstitial theory of simple condensed matter (ITCM), as suggested by A.V. Granato. When applied to Fe, this model enables the extrapolation of measured melting lines to the conditions of the Earth's inner core boundary (ICB). The ITCM describes the solid-liquid phase transition in metals as resulting from a strong structural perturbation due to a high concentration of interstitial-like defects. The strong nonlinearity of their self-interaction causes the stabilization of this interstitial-rich phase. The original model is expanded to describe melting over a wide range of pressures and temperatures rather than focusing on a specific isobaric transition. Using this model, we fit the measured melting data, extrapolate it to cover ICB conditions, and develop a multiphase equation of state that encompasses this regime. The model is used to explain contradictory data regarding the location of the melting line, resulting from a novel phase transition between two separate liquid phases, specifically between FCC-based and HCP-based liquids. This additional liquid phase offers a new interpretation of the previously suggested near-melting high-pressure phase and may also provide a solution to the inner core nucleation paradox.

This paper introduces Low-EFFourth (LEF4), a MATLAB-based computational framework designed for generating and studying multilevel model ensembles in continuous dynamical systems. Initially developed to address questions in climate modelling, LEF4 can also be used in other disciplines such as epidemiology, economics, and engineering, with minimal modifications to the code. The framework provides an efficient and flexible approach for investigating uncertainties arising from initial conditions, model parameters, numerical methods, and model formulation. This preprint serves as a formal reference for the LEF4 codebase and provides a concise technical and conceptual overview of its purpose, structure, applications and development pipeline.

In this work, we systematically investigate the similarities and differences observed between a hydraulically rough wall comprised of an array of cylinders, massive corals, and branching corals arranged in a staggered manner, along with a stochastically generated coral bed using a scale-resolving computational framework. Our data suggests that for all the flow parameters of interest, there is a substantial difference observed between the stochastic coral bed and the regularly arranged coral bed. By analysing the double-averaged statistics and time-averaged spatial heterogeneity in the hydrodynamic response, we explain the differences observed between the four cases that bring out significant local effects. These observations have important consequences for modelling coral-like roughness in numerical and experimental settings to better understand the mean flow statistics and the spatial heterogeneity induced as a consequence of the underlying coral geometry. Our results can help inform the coastal ocean modelling efforts to further improve the inclusion of coral heterogeneity within two-equation closure models by further investigating the impact of spatially stochastic, rough bottom boundary layers.

We present Gibbs free-energy phase diagrams for compressed iron within a pressure range of 20 to 300 GPa and electronic temperature up to 3 eV obtained using finite-temperature density functional and density functional perturbation theories. Our results for bcc, fcc, and hcp phases predict solid-solid phase transitions in iron driven purely by electronic entropy and temperature. We found a phase transition from hcp to bcc at pressures above 200 GPa, which depends on the electronic temperature. An experimental observation of the stability of the bcc phase above 200 GPa by X-ray Free Electron Laser has recently been reported.

In seismically active regions, the accumulation of geophysical stress during the aseismic period and its impact on faults is crucial for identifying which faults are more likely to undergo future fault movement. In this model, we consider an infinite non-planar fault located in a viscoelastic half-space of a fractional Maxwell medium representing the lithosphere-asthenosphere system comprising three interconnected planar sections. The problem is formulated as a two-dimensional boundary value problem with discontinuities along the fault plane. A numerical solution is obtained using a Laplace transformation, fractional derivative and the correspondence principle. The results have been illustrated graphically using suitable model parameters. The computational findings highlight the significant influence of fault movement and geometry on displacement, stress and strain components in the region surrounding the fault plane. A study has been carried out to investigate how non-planar faults influence displacement and the accumulation of stress and strain. Analysis of these results can provide insights into subsurface deformation and its impact on fault movement, which may contribute to the study of earthquake activity.

This work focuses on estimating soil properties from water moisture measurements. We consider simulated data generated by solving the initial-boundary value problem governing vertical infiltration in a homogeneous, bounded soil profile, with the usage of the Fokas method. To address the parameter identification problem, which is formulated as a two-output regression task, we explore various machine learning models. The performance of each model is assessed under different data conditions: full, noisy, and limited. Overall, the prediction of diffusivity $D$ tends to be more accurate than that of hydraulic conductivity $K.$ Among the models considered, Support Vector Machines (SVMs) and Neural Networks (NNs) demonstrate the highest robustness, achieving near-perfect accuracy and minimal errors.

Spherulites are complex polycrystalline structures that form through the self-assembly of small aggregated nanocrystals starting from a central point and growing radially outward. Despite their wide prevalence and relevance to fields ranging from geology to medicine, the dynamics of spherulitic crystallization and the conditions required for such growth remain ill-understood. Here, we report on the conditions to induce controlled spherulitic growth of sodium sulfate from evaporating aqueous solutions of sulfate salt mixtures at room temperature. We reveal that introducing divalent metal ions in the solution cause spherulitic growth of sodium sulfate. For the first time, we quantify the supersaturation at the onset of spherulitic growth from salt mixtures and determine the growth kinetics. Our results show that the nonclassical nucleation process induces the growth of sodium sulfate spherulites at high supersaturation in highly viscous solutions. The latter reaches approximately 111 Pa$\cdot$s, triggered by the divalent ions, at the onset of spherulite precipitation leading to a diffusion limited growth. We also show that spherulites, which are metastable structures formed under out-of-equilibrium conditions, can evolve into other shapes when supersaturation decreases as growth continues at different evaporation rates. These findings shed light on the conditions under which spherulites form and offer practical strategies for tuning their morphology.

Modeling seismic activity rates and clustering plays an important role in studies of induced seismicity associated with mining and other resource extraction operations. This is critical for understanding the physical and statistical characteristics of seismicity and assessing the associated hazard. In this work, we introduce the generalization of the Nearest-Neighbor Distance (NND) method by incorporating an arbitrary distribution function for the frequency-magnitude statistics of seismic events. Operating within a rescaled hyperspace that includes spatial, temporal, and magnitude domains, the NND method provides an effective framework for examining seismic clustering. By integrating a mixture of the two tapered Pareto distributions, the generalized NND approach accommodates deviations from standard frequency-magnitude scaling when studying the clustering properties of seismicity. In addition, the application of the temporal Hawkes process to model the mining seismicity rate reveals that the seismicity is primarily driven by external factors and lacks pronounced interevent triggering. A case study from a potash mine in Saskatchewan is presented to illustrate the application of the generalized NND method and the Hawkes process to estimate the clustering properties and occurrence rates of induced microseismicity. The implications of observed temporal variations and clustering behavior are discussed, providing insights into the nature of induced seismicity within mining environments.

Physics-informed neural networks (PINNs) offer a powerful framework for seismic wavefield modeling, yet they typically require time-consuming retraining when applied to different velocity models. Moreover, their training can suffer from slow convergence due to the complexity of of the wavefield solution. To address these challenges, we introduce a latent diffusion-based strategy for rapid and effective PINN initialization. First, we train multiple PINNs to represent frequency-domain scattered wavefields for various velocity models, then flatten each trained network's parameters into a one-dimensional vector, creating a comprehensive parameter dataset. Next, we employ an autoencoder to learn latent representations of these parameter vectors, capturing essential patterns across diverse PINN's parameters. We then train a conditional diffusion model to store the distribution of these latent vectors, with the corresponding velocity models serving as conditions. Once trained, this diffusion model can generate latent vectors corresponding to new velocity models, which are subsequently decoded by the autoencoder into complete PINN parameters. Experimental results indicate that our method significantly accelerates training and maintains high accuracy across in-distribution and out-of-distribution velocity scenarios.

We introduce a modular software framework designed to integrate distributed acoustic sensing (DAS) data into operational earthquake monitoring systems. Building on the infrastructure of the Advanced National Seismic System (ANSS) and the Southern California Seismic Network (SCSN), which employs the ANSS Quake Monitoring Software (AQMS), our solution supports real-time DAS waveform streaming and machine-learning-based traveltime picking to leverage the dense spatial sampling of DAS arrays. To enable seamless compatibility with the AQMS, our approach uses standardized seismic data formats to incorporate predetermined DAS channels. We demonstrate the integration of data from a 100-km-long DAS array deployed in Ridgecrest, California, and provide a detailed description of the software components and deployment strategy. This work represents a step toward incorporating DAS into routine seismic monitoring and opens new possibilities for real-time hazard assessment using fiber-optic networks.

Accurate depth estimation of magnetic sources plays a crucial role in various geophysical applications, including mineral exploration, resource assessments, regional hydrocarbon exploration, and geological mapping. Thus, this abstract presents a fast and simple method of estimating the depth of a magnetic body using the TDX derivative of the total magnetic field. TDX is a first-order derivative of the magnetic field that, in addition to edge detection, is less affected by noise, allowing for better depth resolution. The reduced sensitivity to noise enables a clearer estimation of depth and enhances the accuracy of the depth determination process. The TDX, as a variant of the phase derivative, is independent of magnetization and can be used to identify the edge of a magnetic body. In addition to excelling at edge detection, they can also estimate the depth of the magnetic source producing the anomalies. In this study, we explore the utilization of contour of the TDX derivative for estimating depth, assuming a vertical contact source. We demonstrate the effectiveness of the method using a two-prism block model and a simple bishop model with a uniform susceptibility of 0.001 cgs. The results agree with the known depth, providing evidence of the reliability of the method despite the restrictive nature of the assumption, especially for the Bishop model, where there are numerous fault structures.