Hasil untuk "Dynamic and structural geology"

Yue Chen, Yinsheng Wang, Yongqiang Li et al.

To investigate the shear behavior of rock mass joint surfaces with varying roughness and lithology, this study introduces a novel experimental framework that combines high-precision 3D printing and direct shear testing. Ten artificial joint surfaces were fabricated using Barton standard profiles with different joint roughness coefficients (JRC) and were cast using two representative rock-like materials simulating soft and hard rocks. The 3D printing technique employed significantly reduced the staircase effect and ensured high geometric fidelity of the joint morphology. Shear tests revealed that peak shear strength increases with JRC, but the underlying failure mechanisms vary depending on the lithology. Experimental results were further used to back-calculate JRC values and validate the empirical JRC–JCS (joint wall compressive strength) model. Numerical simulations using FLAC3D captured the shear stress–displacement evolution for different lithologies, revealing that rock strength primarily influences peak shear strength and fluctuation characteristics during failure. Notably, despite distinct lithologies, the post-peak degradation behavior tends to converge, suggesting universal residual shear mechanisms across rock types. These findings highlight the critical role of lithology in joint shear behavior and demonstrate the effectiveness of 3D-printing-assisted model tests in advancing rock joint characterization.

Mahdis Rabbani, Navid Mojahed, Shima Nazari

Dynamic games are powerful tools to model multi-agent decision-making, yet computing Nash (generalized Nash) equilibria remains a central challenge in such settings. Complexity arises from tightly coupled optimality conditions, nested optimization structures, and poor numerical conditioning. Existing game-theoretic solvers address these challenges by directly solving the joint game, typically requiring explicit modeling of all agents' objective functions and constraints, while learning-based approaches often decouple interaction through prediction or policy approximation, sacrificing equilibrium consistency. This paper introduces a conceptually novel formulation for dynamic games by restructuring the equilibrium computation. Rather than solving a fully coupled game or decoupling agents through prediction or policy approximation, a data-driven structural reduction of the game is proposed that removes nested optimization layers and derivative coupling by embedding an offline-compiled best-response map as a feasibility constraint. Under standard regularity conditions, when the best-response operator is exact, any converged solution of the reduced problem corresponds to a local open-loop Nash (GNE) equilibrium of the original game; with a learned surrogate, the solution is approximately equilibrium-consistent up to the best-response approximation error. The proposed formulation is supported by mathematical proofs, accompanying a large-scale Monte Carlo study in a two-player open-loop dynamic game motivated by the autonomous racing problem. Comparisons are made against state-of-the-art joint game solvers, and results are reported on solution quality, computational cost, and constraint satisfaction.

Song-Ju Kim

Decision making often exhibits context dependence that challenges classical probability theory. While quantum cognition has successfully modeled such phenomena, it remains unclear whether quantum probability is merely a convenient assumption or a necessary consequence of decision dynamics. Here we present a theoretical framework in which contextuality arises generatively from physically grounded constraints on decision making. By developing a quantum extension of the Tug-of-War (TOW) model, we show that conservation-based internal state updates and measurement-induced disturbance preclude any non-contextual classical description with a single, unified internal state. Contextuality therefore emerges as a structural consequence of adaptive learning dynamics. We further show that the resulting measurement structure admits Klyachko-Can-Binicioglu-Shumovsky (KCBS)-type contextuality witnesses in a minimal single-system setting. These results indicate that quantum probability is not merely a descriptive convenience, but an unavoidable effective theory for adaptive decision dynamics.

Reza Sedghi, Robin Schiewer, Anand Subramoney et al.

At typical context lengths, the feed-forward MLP block accounts for a large share of a transformer's compute budget, motivating sparse alternatives to dense MLP blocks. We study sparse, tree-structured feed-forward layers as drop-in replacements for MLP blocks in deep transformer architectures, enabling conditional computation via hard hierarchical routing without a separate router network. We demonstrate for the first time that this form of tree-structured conditional sparsity can be applied for autoregressive language modeling and downstream question answering, including zero- and few-shot settings, and its scalability beyond 1B parameters. Despite activating fewer than 5% of the feed-forward block's units per token, our models match dense baselines under controlled training and fine-tuning protocols. We further analyze training dynamics and identify an emergent auto-pruning effect: the interaction of hard routing with asymmetric nonlinearities progressively deactivates unused paths, yielding partial conversion of dynamic routing into static structural sparsity. We show that simple architectural choices can modulate this behavior and recover balanced trees without auxiliary losses. Overall, our work demonstrates that tree-structured feed-forward layers provide a scalable and controllable mechanism for sparsifying large transformer models.

Shabnam Jalalat, Kambiz Shahroodi, Mehdi Fadaei et al.

The Iranian insurance industry is a system in which each of the population segments, customers and their types, revenue management, various investment methods, and advertising methods have nonlinear and bidirectional relationships with each other. Analyzing this industry requires a tool to consider all the essential variables and incorporate the relationships between them in the analysis and simulation. System dynamics is a powerful approach for modeling and simulation that has shown its applicability in analyzing and predicting the behavior of complex systems. Therefore, this article used this tool to model and simulate the impact of advertising on the behavior of life insurance customers and its relationship with revenue and asset management. The system dynamics model was drawn, formulated, and validated with the help of the Vensim software. The model extraction process consisted of a comprehensive review of existing studies on customer behavior, identification of key variables related to life insurance purchasing behavior, consulting with insurance industry experts to validate the initial variables and identify factors specific to the Iranian context, drawing causal loop diagrams, and converting them into stock and flow diagrams. Statistical data were collected using the annual reports of the Iran Insurance Company, the Statistical Center of Iran, the statistical yearbooks of the Central Insurance of Iran, and semi-structured interviews with experts. After optimizing the structure and parameters of the model, simulation was performed over a 10-year horizon, and the results were analyzed in three scenarios. The first scenario showed that of continuing the current conditions would lead to an increase in the gap between life insurance expenses and revenue. In the second scenario, the effect of increasing the advertising budget was examined, which prevented the increase in this gap but the existence of a difference. The third scenario showed that a 10% improvement in the rate of word-of-mouth advertising dissemination, while compensating for the costs, will lead to the company's profitability.

A. L. Wild, A. L. Wild, J. Braun et al.

<p>Within the stratigraphic record, grain size fining has been commonly used to infer subsidence, rate and its variability has been interpreted as a signature of external forcing events. We have recently developed a model <span class="cit" id="xref_paren.1">(<a href="#bib1.bibx56">Wild et al.</a>, <a href="#bib1.bibx56">2025</a><a href="#bib1.bibx56">b</a>)</span> that predicts grain size fining within a two-dimensional Landscape Evolution Model to predict the effect of autogenic processes on grain size fining. Here, we couple it to a flexural model to predict the stratigraphic evolution of a foreland basin, the distribution of grain size fining, and which of subsidence or autogenic processes dominates in controlling the fining. We show that, throughout its evolution, the foreland basin experiences a gradual increase in the bypass ratio, <span class="inline-formula"><i>F</i></span>, that provokes a gradual shift from subsidence-dominated to autogenically dominated grain size fining but also progressively alters stratigraphic preservation. The amplitude, and therefore efficiency, of autogenic processes in controlling grain size fining processes is modulated by the shape of the surface topography that we control by changing the rainfall gradient and extent of the basin confinement compared to the orogen. We also show how the evolution of the basin can be mapped in the framework we recently developed <span class="cit" id="xref_paren.2">(<a href="#bib1.bibx57">Wild et al.</a>, <a href="#bib1.bibx57">2025</a><a href="#bib1.bibx57">c</a>)</span> to interpret grain size fining data. Finally, we demonstrate how the model results and our findings can be used to interpret the stratigraphy and grain size information stored in a real foreland basin, namely the Alberta Basin of Western Canada.</p>

Long Hu, Zhiheng Wang, Yichen Wang et al.

Global coastal reclamation areas face significant land subsidence, threatening infrastructure and sustainable development. China’s large-scale projects show particularly severe subsidence. For example, Tianjin’s Binhai New Area contains 413.6 km² of reclaimed land, and subsidence is driven by soft soil consolidation, industrial loads, and dynamic land use changes. This study addresses the unique geology of coastal reclamation zones: thick, soft clay layers; high porosity; and low soil strength. We employed optimized Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology using 48 Sentinel-1A radar images (2019–2022), which generated high-resolution annual deformation rate maps revealing a north-high, south-low subsidence gradient. Crucially, validation against leveling data confirmed reliability. The systematically quantified results demonstrate built areas and the bare ground intensifies subsidence through structural loads and soil compression. Land use transitions also exacerbate differential settlement. For coastal cities and reclamation zones, key strategies emerge, including regulating structural loads in high-subsidence areas, managing soft soil consolidation, and implementing dynamic monitoring. Aligning development intensity with geological capacity is essential, and adopting adaptive spatial planning can mitigate subsidence hazards. This approach offers a scientific framework for enhancing global coastal resilience.

Sychev, Vladimir N., Bogomolov, Leonid M.

The values of dynamic parameters (DP) for 110 earthquakes with magnitudes MW = 4.7–7.7 that occurred on Sakhalin in 1978–2024 were obtained. A scalar seismic moment was previously determined for these earthquakes. To estimate the other DP: the radii of the foci, the shear stress drop, and the reduced seismic energy a phenomenological approach was used based on the presence of regression, which links the source radius and the values of the scalar seismic moment for earthquakes within the Sakhalin-Kuril region. The results of the study were summarized in a data table. Distribution maps of the averaged values of these DP across the studied region were constructed. Thus, the amount of data on the stress drop and reduced seismic energy for Sakhalin earthquakes has been significantly increased.

Inbazhagan Ravikumar, Ram Sundhar, Narendhiran Vijayakumar

Micro aerial vehicles are becoming increasingly important in search and rescue operations due to their agility, speed, and ability to access confined spaces or hazardous areas. However, designing lightweight aerial systems presents significant structural, aerodynamic, and computational challenges. This work addresses two key limitations in many low-cost aerial systems under two kilograms: their lack of structural durability during flight through rough terrains and inability to replan paths dynamically when new victims or obstacles are detected. We present a fully customised drone built from scratch using only commonly available components and materials, emphasising modularity, low cost, and ease of assembly. The structural frame is reinforced with lightweight yet durable materials to withstand impact, while the onboard control system is powered entirely by free, open-source software solutions. The proposed system demonstrates real-time perception and adaptive navigation capabilities without relying on expensive hardware accelerators, offering an affordable and practical solution for real-world search and rescue missions.

Mingyuan Zhou, Haoze Song, Wenjing Ye et al.

Parameter estimation in structural dynamics generally involves inferring the values of physical, geometric, or even customized parameters based on first principles or expert knowledge, which is challenging for complex structural systems. In this work, we present a unified deep learning-based framework for parameterization, forward modeling, and inverse modeling of structural dynamics. The parameterization is flexible and can be user-defined, including physical and/or non-physical (customized) parameters. In the forward modeling, we train a neural operator for response prediction -- forming a surrogate model, which leverages the defined system parameters and excitation forces as inputs to the model. The inverse modeling focuses on estimating system parameters. In particular, the learned forward surrogate model (which is differentiable) is utilized for preliminary parameter estimation via gradient-based optimization; to further boost the parameter estimation, we introduce a neural refinement method to mitigate ill-posed problems, which often occur in the former. The framework's effectiveness is verified numerically and experimentally, in both interpolation and extrapolation cases, indicating its capability to capture intrinsic dynamics of structural systems from both forward and inverse perspectives. Moreover, the framework's flexibility is expected to support a wide range of applications, including surrogate modeling, structural identification, damage detection, and inverse design of structural systems.

Clément Vella, Pierre Gosselet, Serge Prudhomme

We propose in this paper a Proper Generalized Decomposition (PGD) solver for reduced-order modeling of linear elastodynamic problems. It primarily focuses on enhancing the computational efficiency of a previously introduced PGD solver based on the Hamiltonian formalism. The novelty of this work lies in the implementation of a solver that is halfway between Modal Decomposition and the conventional PGD framework, so as to accelerate the fixed-point iteration algorithm. Additional procedures such that Aitken's delta-squared process and mode-orthogonalization are incorporated to ensure convergence and stability of the algorithm. Numerical results regarding the ROM accuracy, time complexity, and scalability are provided to demonstrate the performance of the new solver when applied to dynamic simulation of a three-dimensional structure.

Taozhe Li, Wei Sun

The Visual Simultaneous Localization and Mapping (V-SLAM) system has seen significant development in recent years, demonstrating high precision in environments with limited dynamic objects. However, their performance significantly deteriorates when deployed in settings with a higher presence of movable objects, such as environments with pedestrians, cars, and buses, which are common in outdoor scenes. To address this issue, we propose a Multilayer Perceptron (MLP)-based real-time stereo SLAM system that leverages complete geometry information to avoid information loss. Moreover, there is currently no publicly available dataset for directly evaluating the effectiveness of dynamic and static feature classification methods, and to bridge this gap, we have created a publicly available dataset containing over 50,000 feature points. Experimental results demonstrate that our MLP-based dynamic and static feature point discriminator has achieved superior performance compared to other methods on this dataset. Furthermore, the MLP-based real-time stereo SLAM system has shown the highest average precision and fastest speed on the outdoor KITTI tracking datasets compared to other dynamic SLAM systems.The open-source code and datasets are available at https://github.com/TaozheLi/MLP-SLAM.

A. R. Jönsson, A. R. Jönsson, F. A.-M. Bender et al.

<p>The Earth's albedo is observed to be symmetric between the hemispheres on the annual mean timescale, despite the clear-sky albedo being asymmetrically higher in the Northern Hemisphere due to more land area and aerosol sources; this is because the mean cloud distribution currently compensates for the clear-sky asymmetry almost exactly. We investigate the evolution of the hemispheric difference in albedo in the Coupled Model Intercomparison Project Phase 6 (CMIP6) coupled model simulations following an abrupt quadrupling of <span class="inline-formula">CO₂</span> concentrations, to which all models respond with an initial decrease of albedo in the Northern Hemisphere (NH) due to loss of Arctic sea ice. Models disagree over whether the net effect of NH cloud responses is to reduce or amplify initial NH albedo reductions. After the initial response, the evolution of the hemispheric albedo difference diverges among models, with some models remaining stably at their new hemispheric albedo difference and others returning towards their pre-industrial difference primarily through a reduction in SH cloud cover. Whereas local increases in cloud cover contribute to negative shortwave cloud feedback, the cross-hemispheric communicating mechanism found to be primarily responsible for restoring hemispheric symmetry in the models studied implies positive shortwave cloud feedback.</p>

P. Allemand, E. Lajeunesse, O. Devauchelle et al.

<p>Bedload transport, entrainment of coarse sediment by a river, is inherently a stochastic and intermittent process whose monitoring remains challenging. Here, we propose a new method to characterize bedload transport in the field. Using an uncrewed aerial vehicle (UAV) equipped with a high-resolution camera, we recorded yearly images of a bar of the Grande Rivière des Vieux-Habitants, a gravel bed river located on Basse-Terre Island (Guadeloupe, French West Indies). These images, combined with high-frequency measurements of the river discharge, allow us to monitor the evolution of the population of sediments of a diameter between 0.5 and 0.75 m on the riverbed. Based on this dataset, we estimate the smallest discharge that can move these boulders and calculate the duration of effective transport. We find that the transport of boulders occurs for approximately 10 h yr<span class="inline-formula">⁻¹</span>. When plotted as a function of the effective transport time, a given population of boulders decreases exponentially with an effective residence time of approximately 17 h. This exponential decay suggests that the probability of dislodging a grain from the bed is proportional to the number of grains at repose on the bed, an observation consistent with laboratory experiments. Finally, the residence time of bedload particles on a riverbed can be used to evaluate bedload discharge.</p>

Ophélie Rohmer, Maria Paola Santisi d’Avila, Etienne Bertrand et al.

This research investigates the convenience of structural identification tools to detect the rocking motion tendency, using as input the structural response to ambient vibrations. The rocking ratio and rocking spectrum are proposed as original tools to highlight the rocking motion and its frequency content. The proposed procedure allows the detection and quantification of rocking using only building vertical motion records in both cases of ambient vibration and earthquake. First, three-dimensional finite element models of reinforced concrete buildings are adopted to simulate the structural response to white noise vibration. Different low- and high-rise buildings are studied, having framed structure and frame–wall system, regular and irregular structure, shallow foundation and underground floors. The structural response obtained numerically is analyzed using different signal processing tools to obtain the dynamic features of buildings, and the rocking motion tendency is identified by comparison with a reference fixed base condition. Then, the reliability of the proposed methodology to detect rocking motion attitude, using only the structural motion, is verified and quantified using the proposed tools. Finally, the same approach is applied to real structural motion records of a high-rise reinforced concrete building.

Rebecca M. Chambers, Gareth Johnson, Adrian J. Boyce et al.

Usage of thermal energy contained in abandoned, flooded, coal mines has the potential to contribute to low carbon heating or cooling supply and assist in meeting net-zero carbon emission targets. However, hazardous ground gases, such as CH4 and CO2, can be found naturally in superficial deposits, coal bearing strata and abandoned mines. Determining the presence, magnitude, and origin of subsurface gases, and how their geochemical fingerprints evolve within the shallow subsurface is vital to developing an understanding of how to manage the risk posed by ground gases in geoenergy technology development. Here, we present the first CH4 and CO2 concentration-depth profiles and stable isotope (δ13CCH4, δ13CCO2, and δDCH4) profiles obtained from UK mine workings, through analysis of headspace gas samples degassed from cores and chippings collected during construction of the Glasgow Observatory. These are used to investigate the variability of gas fingerprints with depth within unmined Carboniferous coal measures and Glasgow coal mine workings. Stable isotope compositions of CH4 (δ13CCH4 = −73.4‰ to −14.3‰; δ13CCO2 = −29‰ to −6.1‰; δDCH4 = −277‰ to −88‰) provide evidence of a biogenic source, with carbonate reduction being the primary pathway of CH4 production. Gas samples collected at depths of 63–79 m exhibit enrichments in 13CCH4 and 2H, indicating the oxidative consumption of CH4. This correlates with their proximity to the Glasgow Ell mine workings, which will have increased exposure to O2 from the atmosphere as a result of mining activities. CO2 gas is more abundant than CH4 throughout the succession in all three boreholes, exhibiting high δ13CCO2 values relative to the CH4 present. Gases from unmined bedrock exhibit the highest δ13CCO2 values, with samples from near-surface superficial deposits having the lowest δ13CCO2 values. δ13CCO2 values become progressively lower at shallower depths (above 90 m), which can be explained by the increasing influence of shallow groundwaters containing a mixture of dissolved marine carbonate minerals (∼0‰) and soil gas CO2 (−26‰) as depth decreases. Our findings provide an insight into the variability of mine derived gases within 200 m of the surface, providing an important ‘time-zero’ record of the site, which is required in the design of monitoring approaches.

I. Movchan, A. Yakovleva, V. Frid et al.

A new approach to seismic analysis has been introduced and demonstrated for a sequence of recent seismic events recorded in the Blackpool region of Lancashire, UK. The seismic activity, induced by an industrial hydraulic fracturing at a depth exceeding 2 km, had the extent of registered surface elastic vibrations reaching a distance exceeding 15 km. The analysis is based on the study of elastic fields, three-dimensional extrapolations of the landscape and the novel reconstruction of a three-dimensional digital model of seismic map boundaries and vertical profiles. The verification of the proposed approach is carried out via the comparison with published data of the Blackpool seismic events, combined with the new spectral analysis linked to the identified regions of seismic activity. The latter was accompanied by a finite-element simulation of vibrations for an elastic layer of variable thickness, approximating the test region. The analysis and numerical modelling have demonstrated consistency with the dynamic nature of structural stratification of the geological systems, and in addition, the predictive nature of the modelling work was demonstrated by the comparison of the model eigenmodes with the published parameters of registered earthquakes in the Blackpool area. This article is part of the theme issue ‘Wave generation and transmission in multi-scale complex media and structured metamaterials (part 1)’.

Zhijian Wang, Shujie Zhou, Qinmei Yao et al.

Game dynamics theory, as a field of science, the consistency of theory and experiment is essential. In the past 10 years, important progress has been made in the merging of the theory and experiment in this field, in which dynamics cycle is the presentation. However, the merging works have not got rid of the constraints of Euclidean two-dimensional cycle so far. This paper uses a classic four-strategy game to study the dynamic structure (non-Euclidean superplane cycle). The consistency is in significant between the three ways: (1) the analytical results from evolutionary dynamics equations, (2) agent-based simulation results from learning models and (3) laboratory results from human subjects game experiments. The consistency suggests that, game dynamic structure could be quantitatively predictable, observable and controllable in general.

Jędrzej Olkowski, Michał Pilipczuk, Mateusz Rychlicki et al.

We revisit classic string problems considered in the area of parameterized complexity, and study them through the lens of dynamic data structures. That is, instead of asking for a static algorithm that solves the given instance efficiently, our goal is to design a data structure that efficiently maintains a solution, or reports a lack thereof, upon updates in the instance. We first consider the Closest String problem, for which we design randomized dynamic data structures with amortized update times $d^{\mathcal{O}(d)}$ and $|Σ|^{\mathcal{O}(d)}$, respectively, where $Σ$ is the alphabet and $d$ is the assumed bound on the maximum distance. These are obtained by combining known static approaches to Closest String with color-coding. Next, we note that from a result of Frandsen et al.~[J. ACM'97] one can easily infer a meta-theorem that provides dynamic data structures for parameterized string problems with worst-case update time of the form $\mathcal{O}(\log \log n)$, where $k$ is the parameter in question and $n$ is the length of the string. We showcase the utility of this meta-theorem by giving such data structures for problems Disjoint Factors and Edit Distance. We also give explicit data structures for these problems, with worst-case update times $\mathcal{O}(k2^{k}\log \log n)$ and $\mathcal{O}(k^2\log \log n)$, respectively. Finally, we discuss how a lower bound methodology introduced by Amarilli et al.~[ICALP'21] can be used to show that obtaining update time $\mathcal{O}(f(k))$ for Disjoint Factors and Edit Distance is unlikely already for a constant value of the parameter $k$.

V. Aakash

Structurally dynamic, youthful collapsed mountains; The Himalayas are loaded with full of geological surprises, involving issues, folds, shear zones and so forth that shows their quality because of progressing structural exercises in the Himalayas. In feature of Atal tunnel, these issues increments multifold due to high overburden of the material and also careful topographical and geotechnical investigations at different scales. This makes vulnerability in planning a specific emotionally supportive network and requests for "structure as you go" approach for whole passage length (8.8km). DRESS (Drainage-Reinforcement-Excavation-Support-Solution) philosophy of excavation is very powerful in water bearing issue zones of delicate Himalayan district. DRESS includes pre-seepage of ground in front of face with long waste gaps and adjustment of the crown in front of passage face by steel pipe umbrella curve, up to a foreordained length, trailed by exhuming in little strides by mechanical methods and backing thereof. Numerous troublesome issues have been experienced during construction which was unpredicted initially. One such issue is an experience of Seri Nala. Due to differing conduct of rock mass, continuous update of rock mass is constantly required. NATM is dependent on disfigurement observing information to assess amount and nature of emotionally supportive network, has end up being a fitting apparatus for tunneling in the youthful Himalayas. This paper depicts the consolidation of NATM as well as DRESS method in the unearthing of Atal Tunnel, Himachal Pradesh, India