Hasil untuk "Dynamic and structural geology"

A. H. Towers, M. Attal, S. M. Mudd et al.

<p>The grain sizes of sediments in channels have been linked to landscape characteristics, such as flow distance from headwaters, topographic relief, lithology and climate, in landscapes with little past or present glacial influence. Few studies have explored the controls on sediment characteristics in formerly glaciated landscapes. In this study, we document river surface grain sizes at 279 localities across Scotland. We collect photographs of gravel bars through a citizen science survey, Scotland's Big Sediment Survey. Grain sizes distributions are extracted from the photographs using both manual and automated techniques. We investigate whether grain sizes can be correlated and predicted from environmental variables (e.g., basin slope, flow distance from headwaters) through Spearman's correlation statistics and random forest regression modelling. In contrast to other studies that have primarily focused on non-glaciated landscapes, we find no apparent controls on surface grain sizes in channels across Scotland. Specifically, we find no significant Spearman's relationships between d84 and environmental variables; the strongest relationship was found between d84 and average basin aridity with a weak <span class="inline-formula"><i>r</i>²</span> value of 0.34. We also find that the predictability of our random forest model is poor and only captures 20 % of the variance of d84. We find no correlation between grain size and flow competence, which suggests that sediment is both transport-limited and supply-limited. We propose that Scotland's post-glacial legacy drives the lack of sedimentological trends documented in this study, and that changes in landscape morphology and sediment sources caused by glacial processes lead to a complete decoupling between fluvial sediment grain size and environmental variables. This interpretation aligns with other studies that have highlighted the ongoing role of the post-glacial legacy on landscape evolution in tectonically quiescent terrains, both in Scotland and globally. Our results suggest that fluvial sediment grain size cannot be predicted by a global model based on environmental variables in post-glacial landscapes.</p>

Dezhi Yang, Qiaoyu Tan, Carlotta Domeniconi et al.

Learning the dynamic causal structure of time series is a challenging problem. Most existing approaches rely on distributional or structural invariance to uncover underlying causal dynamics, assuming stationary or partially stationary causality. However, these assumptions often conflict with the complex, time-varying causal relationships observed in real-world systems. This motivates the need for methods that address fully dynamic causality, where both instantaneous and lagged dependencies evolve over time. Such a setting poses significant challenges for the efficiency and stability of causal discovery. To address these challenges, we introduce DyCausal, a dynamic causal structure learning framework. DyCausal leverages convolutional networks to capture causal patterns within coarse-grained time windows, and then applies linear interpolation to refine causal structures at each time step, thereby recovering fine-grained and time-varying causal graphs. In addition, we propose an acyclic constraint based on matrix norm scaling, which improves efficiency while effectively constraining loops in evolving causal structures. Comprehensive evaluations on both synthetic and real-world datasets demonstrate that DyCausal achieves superior performance compared to existing methods, offering a stable and efficient approach for identifying fully dynamic causal structures from coarse to fine.

José Martín-Roca, Alberto Zaragoza, Frédéric Caupin et al.

Water shows numerous thermodynamic, dynamic, and structural anomalies. Recent experiments [Eichler et al. Phys. Rev. Lett. 134, 134101 (2025)], based on measurements of shear and bulk viscosities of liquid water up to 1.6 GPa, have reported the existence of a minimum in the variation of the structural relaxation time τα with pressure at room temperature. Here we investigate this and related properties with molecular dynamics simulations of the TIP4P/2005 water model, performed at extreme pressures commensurate with the experiments. Specifically, we compute dynamic (self-diffusion, shear and bulk viscosities, and structural relaxation time) and structural (oxygen-oxygen radial distribution function and structure factor, translational order parameter) properties down to 220 K and up to 2.7 GPa. We find good agreement with the experimental observations, and confirm the existence of a minimum in τα . The microscopic information obtained from the simulations suggests that this anomaly is connected with the sudden reorganization of the hydrogen bond network induced by pressurization.

O. Malcles, S. Mazzotti, P. Vernant et al.

<p>Elevated Plio-Pleistocene coastal and marine markers in stable continental regions are commonly explained by a combination of eustatic sea-level variations and large-scale geological processes (e.g., crustal or mantle dynamics). In this study, we test the role of erosion rates on the Late Pleistocene uplift and landform evolution of the Armorican Massif, western France. Denudation rates are estimated for 19 drainage basins using terrestrial cosmogenic nuclide (<span class="inline-formula">¹⁰</span>Be) measurements in quartz. They range between ca. 5 and 25 m Ma<span class="inline-formula">⁻¹</span>, with a factor of 2 difference between the western highland region and the central lowland region (<span class="inline-formula">13±6</span> m Ma<span class="inline-formula">⁻¹</span> vs. <span class="inline-formula">7±4</span> m Ma<span class="inline-formula">⁻¹</span>). Assuming a thin elastic plate model, the lithosphere flexural isostatic response to these denudation rates produces an overall uplift rate of the Armorican Peninsula from 4–8 m Ma<span class="inline-formula">⁻¹</span> in the central lowland region and along the coast to 8–14 m Ma<span class="inline-formula">⁻¹</span> in the western peninsula. We show that these erosion-driven uplift rates can explain the uplifted Late Pleistocene marine terraces along the Armorican Peninsula coastline and the elevated Quaternary marine deposits in the central lowland region, without necessitating additional geodynamic processes such as regional compression or local active faults. Our results suggest that, in stable continental regions, long-term erosion should be taken into account as a driver of uplift and deformation before trying to derive global or regional geodynamic or tectonic conclusions.</p>

K. Rainer Massarsch

The paper demonstrates how the concepts presented in the companion paper: “Determination of Constrained Modulus of Granular Soil from In Situ Tests—Part 1 Analyses” can be applied in practice. A settlement design based on the tangent modulus method is described. Extensive in situ tests were performed on a well-documented test site consisting of sand with silt and clay layers. The field tests comprised different types of penetration tests, such as the cone penetration test, the flat dilatometer, and the seismic down-hole test. The modulus number and the constrained tangent modulus were derived from the cone penetration test with pore water pressure measurement and the flat dilatometer test. In addition, the shear wave speed was determined from two seismic down-hole tests, from which the small-strain shear modulus could be evaluated. The constrained modulus obtained from the cone penetration test with pore water pressure measurement (CPTU) and the flat dilatometer (DMT) was compared with that from the seismic down-hole tests. The importance of the stress history on the constrained modulus was demonstrated. The range of modulus numbers, derived from different in situ tests, compares favorably with empirical values reported in the literature.

Emily J. Diaz-Vallejo, Ken Keefover-Ring, Elizabeth Hennessy et al.

The geosciences continue to grapple with the exclusion of Black, Indigenous, Latinx, and other students of Color. These patterns can be understood in the discipline’s roots in colonialism and extractivism. Furthermore, training of the scientific process as objective and race-neutral results in scientists who do not recognize how science can perpetuate inequities in society. Using a U.S. university biogeography course as a case study, we describe an innovative framework for teaching equity through a critical historical lens that interrogates: 1) biases in the processes and forms of knowledge production, legitimization, and exclusion; 2) the source of inequities in representation in the discipline; and 3) how societal benefits and harms of scientific practices are felt disproportionately demographically and geographically. Students were encouraged to critically analyze the historical context of scientific theories and their proponents and challenge assumptions about the representativeness of data supporting those theories into the present day. Engaging with these questions broadened students’ understanding of changing paradigms in the field and of links between colonialism and modern science. We provide recommendations for instructors seeking to use similar approaches to enhance student learning.

Satoru Hayami

We report our numerical results on the stability of the skyrmion crystal phase in an external magnetic field for both in-plane and out-of-plane directions in a centrosymmetric host. We analyze a spin model with the two-spin symmetric anisotropic exchange interaction that arises from relativistic spin–orbit coupling on a triangular lattice. By performing simulated annealing, we construct magnetic phase diagrams when the magnetic field is tilted from the out-of-plane field direction to the in-plane field direction. We find a different stability tendency of the skyrmion crystal phase according to the directions of the in-plane field, which provides a signal of the two-spin symmetric anisotropic exchange interaction for stabilizing the skyrmion crystal phase. Our results indicate that the mechanism of the skyrmion crystal phase triggered by the two-spin symmetric anisotropic exchange interaction can be experimentally tested by applying the in-plane magnetic field.

Meng (Matt) Wei, Lingchao He, Bridget Smith-Konter

The Gofar oceanic transform fault at the East Pacific Rise has one of the best seismic cycles recorded by modern instruments. The timing, location, and magnitude of major earthquakes (Mw>5.5) have been well constrained by data from global seismic networks for the past 30 years. The earthquake interval is short, about 3-5 years. Several segments have already experienced 5 cycles since 1995, when the seismic network was good enough for surface wave relocation. Two ocean bottom seismometer deployments (2008-2009, 2021-2023) also provide constraints on the seismic properties on the fault. This makes Gofar an ideal place to study earthquake cycles. Here, we developed a model for the seismic cycle along the Gofar transform fault using a semi-analytical approach for rapidly calculating 3D time-dependent deformation and stress caused by screw dislocations embedded within an elastic layer overlying a Maxwell viscoelastic half-space. The 160-km long fault is divided into three major segments with six asperities. Our model simulates the earthquake pattern on this fault for the past 30 years. Most of the time, each asperity ruptured as a large earthquake every 3-5 years. Most segments have a nearly constant Coulomb stress threshold of 2-3 MPa, providing optimal conditions for the forecasting of future earthquakes along Gofar. For three cases that deviated from this simple regular pattern, a large earthquake occurred with a centroid location between two asperities. This is likely due to concurrent rupture that involved both asperities. We also modeled surface deformation with different elastic layer thicknesses and mantle viscosities. Even though most deformation is in the horizontal direction, the difference in both horizontal and vertical directions between models can be as large as a few centimeters per year. Several seafloor geodesy methods can be used to differentiate between models, and seafloor pressure might be the most appropriate one at this remote location.

Idowu Itiola, Usama El Shamy

This study presents a microscale framework for investigating the seismic stability of bridge-pier structures using the discrete element method (DEM), with a focus on rocking isolation mechanisms. The piers and the deck are modeled as rigid blocks that follow rigid body dynamics. The rigid block is modeled as a collection of glued particles with geometrical arrangement and physical properties that mimic an actual block. To facilitate numerical contact points between the base of the block and the flat base wall, smaller particle sizes were introduced at the base of the block. A Hertz contact model was employed to model the interaction between contacting entities for better estimation of the contact constitutive parameters. Validation was performed using well-documented experimental data featuring the free-rocking of a granite stone block as well as existing analytical techniques. DEM simulations were performed on single blocks as well as on a bridge deck-pier system subjected to dynamic and seismic loadings. The study shows the effectiveness of rocking isolation through a comparative analysis of acceleration and angular velocity under varying seismic intensities, with acceleration reduction up to 70% for piers and 60% for the deck in a high-intensity scenario, affirming the potential of rocking isolation as a viable seismic mitigation strategy. The study monitors the structural response, contact mechanics, and energy dissipation of the pier–deck system. The application of the DEM model advances the analysis of bridge pier and deck interactions under seismic loads, providing new insights into the detailed behavior of rocking bridge piers and their potential for seismic isolation.

Dicong Qiu, Wenzong Ma, Zhenfu Pan et al.

Open-Vocabulary Mobile Manipulation (OVMM) is a crucial capability for autonomous robots, especially when faced with the challenges posed by unknown and dynamic environments. This task requires robots to explore and build a semantic understanding of their surroundings, generate feasible plans to achieve manipulation goals, adapt to environmental changes, and comprehend natural language instructions from humans. To address these challenges, we propose a novel framework that leverages the zero-shot detection and grounded recognition capabilities of pretraining visual-language models (VLMs) combined with dense 3D entity reconstruction to build 3D semantic maps. Additionally, we utilize large language models (LLMs) for spatial region abstraction and online planning, incorporating human instructions and spatial semantic context. We have built a 10-DoF mobile manipulation robotic platform JSR-1 and demonstrated in real-world robot experiments that our proposed framework can effectively capture spatial semantics and process natural language user instructions for zero-shot OVMM tasks under dynamic environment settings, with an overall navigation and task success rate of 80.95% and 73.33% over 105 episodes, and better SFT and SPL by 157.18% and 19.53% respectively compared to the baseline. Furthermore, the framework is capable of replanning towards the next most probable candidate location based on the spatial semantic context derived from the 3D semantic map when initial plans fail, keeping an average success rate of 76.67%.

Z. Tariq, B. Yan, Shuyu Sun

Geological Carbon Sequestration (GCS) in deep geological formations, like saline aquifers and depleted oil and gas reservoirs, brings enormous potential for large-scale storage of carbon dioxide (CO2). The successful implementation of GCS requires a comprehensive risk assessment of the confinement of plumes at each potential storage site. The accurate prediction of the flow, geochemical, and geomechanical responses of the formation is essential for the management of GCS in long-term operations because excessive pressure buildup due to injection can potentially induce fracturing of the cap-rock, or activate pre-existing faults, through which fluid can leak. In this study, we build a Deep Learning (DL) workflow to effectively infer the storage potential of CO2 in deep saline aquifers. Specifically, a reservoir model is built to simulate the process of CO2 injection into deep saline aquifers, which considers the coupled phenomenon of flow and hydromechanics. Further, the reservoir model was sampled to account for a wide range of petro-physical, geological, and operational parameters. These samples generated a massive physics-informed simulation database (about 1500 simulated data points) that provides training data for the DL workflow. The ranges of varied parameters were obtained from an extensive literature survey. The DL workflow consists of Fourier Neural Operator (FNO) to take the input of the parameterized variables used in the simulation database and jointly predict the temporal-spatial responses of pressure and CO2 saturation plumes at different periods. Average Absolute Percentage Error (AAPE) and coefficient of determination (R2), Structural similarity index (SSIM), and Peak Signal to Noise Ratio (PSNR) are used as error metrics to evaluate the performance of the DL workflow. Through our blind testing experiments, the DL workflow offers predictions as accurate as our physics-based reservoir simulations, yet 300 times more efficient than the latter. The developed workflow shows superior performance with an AAPE of less than 5% and R2 score of more than 0.99 between actual and predicted values. The workflow can predict other required outputs that numerical simulators can typically calculate, such as solubility trapping, mineral trapping, and injected fluid densities in supercritical and aqueous phases. The proposed DL workflow is not only physics informed but also driven by inputs and outputs (data-driven) and thus offers a robust prediction of the carbon storage potential in deep saline aquifers with considering the coupled physics and potential fluid leakage risk.

D. Draebing, D. Draebing, T. Gebhard et al.

<p>Landslides are important agents of sediment transport, cause hazards and are key agents for the evolution of scarplands. Scarplands are characterized by high-strength layers overlying low-inclined landslide-susceptible layers that precondition and prepare landsliding on geological timescales. These landslides can be reactivated, and their role in past hillslope evolution affected geomorphometry and material properties that set the framework for present-day shallow landslide activity. To manage present-day landslide hazards in scarplands, a combined assessment of deep-seated and shallow landsliding is required to quantify the interaction between geological conditions and vegetation that controls landslide activity. For this purpose, we investigated three hillslopes affected by landsliding in the Franconian scarplands. We used geomorphic mapping to identify landforms indicating landslide activity, electrical resistivity to identify shear plane location and a mechanical stability model to assess the stability of deep-seated landslides. Furthermore, we mapped tree distribution and quantified root area ratio and root tensile strength to assess the influence of vegetation on shallow landsliding. Our results show that deep-seated landslides incorporate rotational and translational movement and suggest that sliding occurs along a geologic boundary between permeable Rhätolias sandstone and impermeable Feuerletten clays. Despite low hillslope angles, landslides could be reactivated when high pore pressures develop along low-permeability layers. In contrast, shallow landsliding is controlled by vegetation. Our results show that rooted area is more important than species-dependent root tensile strength and basal root cohesion is limited to the upper 0.5 m of the surface due to geologically controlled unfavourable soil conditions. Due to low slope inclination, root cohesion can stabilize landslide toes or slopes undercut by forest roads, independent of potential soil cohesion, when tree density is sufficient dense to provide lateral root cohesion. In summary, geology preconditions and prepares deep-seated landslides in scarplands, which sets the framework of vegetation-controlled shallow landslide activity.</p>

Ahmed Bukhary, Shahid Azam

Severe climatic and environmental conditions warrant the use of stabilization agents in aid of compaction for sustainable improvement in engineering properties of clays. Physicochemical agents are a viable option because they are cost effective, environmentally friendly, and offer improved long-term performance of treated soils. This research developed a fundamental understanding of the clay–water–electrolyte admixtures relations. Based on a comprehensive literature review, the effect of nanomaterials, biopolymers, and geopolymers on the behavior of compacted clays was investigated. It was found that all of these admixtures facilitate the development of an aggregated soil microstructure through unique mechanisms. Biopolymers have the highest water adsorption capacity followed by geopolymers and then by nanomaterials. The effect of admixtures on optimum compaction properties follows a decreasing trend similar to untreated clays (<i>S</i> = 80% ± 20%). The variation of hydraulic conductivity, compression index, and compressive strength are largely within the family of curves identified by typical relationships for compacted clays. These preliminary findings indicate that not all engineering properties are improved to the same level by the different types of physicochemical admixtures. The specific nature of geotechnical engineering (soil type and site conditions) as well as the wide range of admixture types and potential biodegradation of some of the reagents are the major shortcoming of using this class of materials.

Frank Denk, Tobias Hofbauer

This document presents the process flow and the experimental conditions for calculating the static magnetic intermediate permeability of a specimen with a dedicated geometrical contour and surface for simulation parameter of metal detection systems. In this case, intermediate is explained and defined as probes with a magnetic permeability between 10 and 1000. An analysis of recent and current measurement standards as well as similar simulation principles leads to the contribution value of this new hybrid process flow. To calculate the permeability value in a first step, an electromagnetic circuit was constructed and excited with a defined electrical DC current with a dedicated tolerance for generating a static approximated homogenic magnetic field in a defined air gap space sector. Additionally, to the H-field generation part double copper coil, two magnetic ferrite cylinders with known permeability were used. The electrical and magnetic circuit has been modeled by an Ansys FEM Electronic Desktop software; the solver is magnetic static. Specifically, the simulated magnetic field distribution of the airgap was evaluated by using different Hall sensor elements with different tolerances. Subsequently, the electromagnetic circuit was expanded by implementing different cylindrical and cube shaped probes on a defined position inside the air gap sector with homogenic magnetization. Moreover, based on the analysis of the air gap structure without the probes, a detailed 3D-FEM model of the air gap magnetic field with special probes was established, which provides the environmental field distribution of the probes. The simulation models were compared with the corresponding Hall sensor measurements, which proved the high accuracy experimental validity of the models established in this paper. Finally, some key features related to parameter variations in the electromagnetic circuit were extracted, which can significantly reflect the characteristics of the robustness of the measurement principle. The main findings reported in this paper will be beneficial for magnetic parameter settings in electromagnetic simulation.

Georgios Diamantopoulos, Nikos Tziritas, Rami Bahsoon et al.

In recent years, we have seen an increase in the adoption of blockchain-based systems in non-financial applications, looking to benefit from what the technology has to offer. Although many fields have managed to include blockchain in their core functionalities, the adoption of blockchain, in general, is constrained by the so-called trilemma trade-off between decentralization, scalability, and security. In our previous work, we have shown that using a digital twin for dynamically managing blockchain systems during runtime can be effective in managing the trilemma trade-off. Our Digital Twin leverages DDDAS feedback loop, which is responsible for getting the data from the system to the digital twin, conducting optimisation, and updating the physical system. This paper examines how leveraging DDDAS feedback loop can support the optimisation component of the trilemma benefiting from Reinforcement Learning agents and a simulation component to augment the quality of the learned model while reducing the computational overhead required for decision-making.

Annika King, Dallas Smith, Benjamin Webb

The changing topology of a network is driven by the need to maintain or optimize network function. As this function is often related to moving quantities such as traffic, information, etc. efficiently through the network the structure of the network and the dynamics on the network directly depend on the other. To model this interplay of network structure and dynamics we use the dynamics on the network, or the dynamical processes the network models, to influence the dynamics of the network structure, i.e., to determine where and when to modify the network structure. We model the dynamics on the network using Jackson network dynamics and the dynamics of the network structure using minimal specialization, a variant of the more general network growth model known as specialization. The resulting model, which we refer to as the integrated specialization model, coevolves both the structure and the dynamics of the network. We show this model produces networks with real-world properties, such as right-skewed degree distributions, sparsity, the small-world property, and non-trivial equitable partitions. Additionally, when compared to other growth models, the integrated specialization model creates networks with small diameter, minimizing distances across the network. Along with producing these structural features, this model also sequentially removes the network's largest bottlenecks. The result are networks that have both dynamic and structural features that allow quantities to more efficiently move through the network.

Zhijian Wu, Dan Zhang, Shengnian Wang et al.

Abstract The Loess Plateau is one of the most seismically and geologically active regions in China. The related catastrophic earthquakes and geological disasters have caused more than 1.4 million deaths in the plateau. In this study, the slopes on the edge of the loess tableland in Pingliang City, Gansu Province—the core area of the Loess Plateau—are investigated. Based on large-scale shaking-table model tests and discrete-element numerical simulation—particle flow code (PFC 2D), the dynamic-response characteristics and deformation evolution process of fissured and non-fissured loess slopes under different seismic loads are studied. The test results show that with increasing seismic load input, the peak ground displacement (PGD) of the loess slopes increases gradually with increasing slope height. For the two types of slopes, the acceleration amplification effects in the slope with horizontal direction load are larger than those of the vertical direction load. The amplification factor of the peak ground acceleration (PGA) at the shoulder of the fissured slope is significantly larger than that of the non-fissured slope. According to the numerical simulation results of the fissured slope, when the seismic load is small, the bond-failures are distributed densely in the initial fissured structural plane and at the model bottom. Regarding the non-fissured slope, the bond-failures in the slope are mainly distributed at the bottom of the model. With increasing acceleration amplitude, the number of bond-failures in the slopes increases rapidly. When the input load increases to 0.40 g, two potential slip surfaces occur in the shallow surface of the fissured slope and a potential slip surface appears at the back edge of the non-fissured slope.

Prateek Roshan, S. Pal

Mario J. Pinheiro

Combining a current source involving vortical surface currents in the set of Maxwell’s equations offers a functional framework to address the complex phenomena of electromagnetic turbulence. The field structure equations exhibit fluid behavior with associated electromagnetic viscosity and reveal that the electromagnetic field, as a fluid, shows turbulent properties. This is an entirely new mechanism, investigated for the first time to the best of our knowledge. The fluidic–electromagnetic analogy implies that diffraction is the analog phenomenon of EM turbulence. The method clarifies the role of vortical surface currents in generating electromagnetic turbulence and classical fractal-like behavior in optical devices and suggests norms to design suitable plasmon circuity to control electromagnetic turbulence in stealth technology and propulsion machines.

M. Reckermann, A. Omstedt, T. Soomere et al.

<p><span id="page2"/>Coastal environments, in particular heavily populated semi-enclosed marginal seas and coasts like the Baltic Sea region, are strongly affected by human activities. A multitude of human impacts, including climate change, affect the different compartments of the environment, and these effects interact with each other. As part of the Baltic Earth Assessment Reports (BEAR), we present an inventory and discussion of different human-induced factors and processes affecting the environment of the Baltic Sea region, and their interrelations. Some are naturally occurring and modified by human activities (i.e. climate change, coastal processes, hypoxia, acidification, submarine groundwater discharges, marine ecosystems, non-indigenous species, land use and land cover), some are completely human-induced (i.e. agriculture, aquaculture, fisheries, river regulations, offshore wind farms, shipping, chemical contamination, dumped warfare agents, marine litter and microplastics, tourism, and coastal management), and they are all interrelated to different degrees. We present a general description and analysis of the state of knowledge on these interrelations. Our main insight is that climate change has an overarching, integrating impact on all of the other factors and can be interpreted as a background effect, which has different implications for the other factors. Impacts on the environment and the human sphere can be roughly allocated to anthropogenic drivers such as food production, energy production, transport, industry and economy. The findings from this inventory of available information and analysis of the different factors and their interactions in the Baltic Sea region can largely be transferred to other comparable marginal and coastal seas in the world.</p>