Hasil untuk "Dynamic and structural geology"

Patrick BarAvi

Radiation reaction in classical electrodynamics is traditionally described by the Lorentz Abraham Dirac equation (LAD), whose point particle formulation leads to well known difficulties including runaway solutions, pre acceleration, and the ambiguous status of the Schott term. We analyze radiation reaction within the framework of Extended Structural Dynamics (ESD), in which charged particles are modeled as finite systems possessing internal dynamical structure. In the present formulation the particle is represented as a finite, deformable sphere with a single radial breathing mode describing internal charge redistribution. This internal degree of freedom introduces a finite response time and ensures that changes in the charge distribution propagate at finite speed. Starting from the full particle field Hamiltonian, we derive the retarded self force for such a deformable charge and obtain a delay kernel that depends on both the past motion and the past internal configuration. In the adiabatic regime the kernel reduces to an effective causal form that is free of pre acceleration and exhibits a band pass frequency response, suppressing high frequency instabilities associated with runaway behavior. The Schott term is shown to correspond to reversible energy stored in the internal deformation mode, providing a direct mechanical interpretation of this contribution. The LAD dynamics are recovered only in the double limit of vanishing spatial extent and frozen internal dynamics, where the causal delay structure collapses to the familiar point particle approximation. Within this framework radiation reaction arises as the leading order effective dynamics of a finite deformable charge, while higher order corrections encode finite size and internal structural effects without modifying Maxwell's equations or introducing ad hoc regularization.

Rambod Azimi, Yuri Grinberg, Dan-Xia Xu et al.

Silicon photonic devices often exhibit fabrication-induced variations such as over-etching, underetching, and corner rounding, which can significantly alter device performance. These variations are non-uniform and are influenced by feature size and shape. Accurate digital twins are therefore needed to predict the range of possible fabricated outcomes for a given design. In this paper, we introduce Gen-Fab, a conditional generative adversarial network (cGAN) based on Pix2Pix to predict and model uncertainty in photonic fabrication outcomes. The proposed method takes a design layout (in GDS format) as input and produces diverse high-resolution predictions similar to scanning electron microscope (SEM) images of fabricated devices, capturing the range of process variations at the nanometer scale. To enable one-to-many mapping, we inject a latent noise vector at the model bottleneck. We compare Gen-Fab against three baselines: (1) a deterministic U-Net predictor, (2) an inference-time Monte Carlo Dropout U-Net, and (3) an ensemble of varied U-Nets. Evaluations on an out-of-distribution dataset of fabricated photonic test structures demonstrate that Gen-Fab outperforms all baselines in both accuracy and uncertainty modeling. An additional distribution shift analysis further confirms its strong generalization to unseen fabrication geometries. Gen-Fab achieves the highest intersection-over-union (IoU) score of 89.8%, outperforming the deterministic U-Net (85.3%), the MC-Dropout U-Net (83.4%), and varying U-Nets (85.8%). It also better aligns with the distribution of real fabrication outcomes, achieving lower Kullback-Leibler divergence and Wasserstein distance.

Shiyao Jia, Qiang Xu, Wanlin Chen et al.

Michael Kendall, Toshiko Terakawa, Martha Savage et al.

The interaction of faults, fractures, and hydromagmatic systems of volcanoes can lead to complicated stress patterns that vary over short spatial and temporal scales. Here we study stress-induced anisotropy using observations of shear-wave splitting at 12 stations across Ontake volcano, Japan. The results reveal a complicated pattern of anisotropy indicating that the volcano perturbs the local stress field. In 2007, a minor phreatic eruption (VEI 0) occurred at Ontake, but there is little evidence of changes in splitting parameters during this eruption. In contrast, the much large eruption of 2014  (VEI 3) shows clear temporal changes in splitting parameters following the eruption. The average background magnitude of anisotropy, as described by the delay time between the fast and slow shear wave, doubles to nearly 0.2 second at the onset of the 2014 eruption, but the percent anisotropy increases dramatically from 3% to 20%. Contemporaneously, the polarisation of the fast shear wave rotates towards sHmax. We interpret these observations in terms of basal heating of the hydrothermal system. We suggest that a lack of temporal variation in anisotropy parameters during the 2007 eruption indicates that a critical stress or crack density threshold must be overcome to exhibit a change in anisotropy, which may be indicative of a more significant eruption.

Nastaran Siahchehreh Soraki, Mohammadreza Bagherzadeh, Yousef Gholipour Kanaani et al.

Strategic planning is one of the important and effective concepts that organisations have always paid attention to in order to survive, improve competitiveness, adapt to changing environmental conditions and finally provide better services. This issue requires close attention, especially considering the current conditions in important and influential organisations such as the Forensic Medicine Organisation. The purpose of this research is to explain the strategic planning model of the country's forensic medicine organisation through a futures research approach. The research method employed in this study is qualitative. The current research is career-oriented in its purpose and employs both qualitative and survey methodologies. The method of data collection was library studies and semi-structured interviews, and MAXQDA version 20 software was used for data analysis. The statistical population included 15 experts (directors, managers organisation, and supervisors of the organisation's human resource strategy projects, as well as business experts and academic experts in the field of management). The research findings showed that the strategic planning model Forensic Medicine Organisation includes organisational  factors, support factors, and individual factors. Organisational factors include cultural, structural, and process criteria. The support dimension includes motivation criteria, an extroverted management team, and a focused management team. Individual factors include interpersonal communication criteria, creativity, and general skills. The results of the research have also shown that strategic futures research operates at two levels of organisation and product employing two approaches: perception and prediction (interpretation). From the perspective of product innovation management, futures research is conducted at both the organisational and product levels. At both levels, environmental monitoring activities, data interpretation and learning are conducted separately.

G. G. Roberts

<p>The use of Fourier Neural Operators (FNOs) to learn how landscapes evolve is introduced. The approach makes use of recent developments in deep learning to learn the processes involved in evolving landscapes (e.g., erosion). An example is provided in which FNOs are developed using input–output pairs (elevations at different times) in synthetic landscapes generated using the stream power model (SPM). The SPM takes the form of a non-linear partial differential equation that advects slopes headwards. The results indicate that the learned operators can reliably and very rapidly predict subsequent landscape evolution at large scales. These results suggest that FNOs could be used to rapidly predict landscape evolution without recourse to the (slow) computation of flow routing and time stepping needed when generating numerical solutions to the SPM. More broadly, they suggest that neural operators could be used to learn the processes that evolve actual and analogue landscapes. Interesting future work could involve assessment of whether learned operators can be applied to other settings or model parametrizations.</p>

Yang Zhang, Chunguang Fan, Chenglong Yu

This study proposes a semi-analytic harmonic modeling method that significantly improves the accuracy and efficiency of complex magnetic field modeling by integrating numerical and analytical approaches. Compared to traditional methods such as the equivalent charge method and finite element method, this approach optimizes the distribution of surface and body charges in the magnetic dipole model and introduces a finite and variable permeability model to accommodate material non-uniformity. Through harmonic expansion and analytical optimization, the method more accurately reflects the characteristics of real magnets, providing an efficient and precise solution for complex magnetic field problems, particularly in the design of high-performance magnets such as Halbach arrays. In this study, the effectiveness of the new modeling method is verified through the combination of simulation and experiment: the magnetic field distribution of the new Halbach array is accurately simulated, and the applicability of the model in the description of complex magnetic fields is analyzed. The dynamic response ability of the optimized model is verified by modeling and simulating the variation of the permeability under actual conditions. The distribution of scalar potential energy with permeability was simulated to evaluate the adaptability of the model to the real physical field. Through the comparative analysis of simulation and experimental results, the advantages of the new method in modeling accuracy and efficiency are clearly pointed out, and the effectiveness of the semi-analytic harmonic modeling method and its wide application potential in the design of new magnetic fields are proved. In this study, a semi-analytic harmonic modeling method is proposed by combining numerical and analytical methods, which breaks through the efficiency bottleneck of traditional modeling methods, and achieves the unity of high precision and high efficiency in the magnetic field modeling of the new Halbach array, providing a new solution for the study of complex magnetic field problems.

Satoru Hayami

We study unconventional multipole moments arising from noncollinear magnetic structures within an augmented framework encompassing electric, magnetic, magnetic toroidal, and electric toroidal multipoles. Employing a tight-binding model for an <i>s</i>-<i>p</i> hybridized orbital system, we analyze two spiral magnetic textures and classify the resulting multipoles according to magnetic point group symmetry. Different spiral wave types, such as cycloidal and proper-screw forms, activate distinct multipole components, with odd-parity multipoles emerging from local <i>s</i>-<i>p</i> parity mixing induced by magnetically driven inversion-symmetry breaking. Calculated multipole structure factors reveal finite-<i>q</i> peaks originating from higher-order magnetic-dipole-scattering processes and their characteristic couplings between Fourier components of the magnetic dipole texture. Our results demonstrate that magnetic ordering can generate parity-mixed states without intrinsic structural inversion asymmetry, offering new pathways to realize cross-correlation phenomena in functional magnetic materials.

Edgar Sucar, Zihang Lai, Eldar Insafutdinov et al.

DUSt3R has recently shown that one can reduce many tasks in multi-view geometry, including estimating camera intrinsics and extrinsics, reconstructing the scene in 3D, and establishing image correspondences, to the prediction of a pair of viewpoint-invariant point maps, i.e., pixel-aligned point clouds defined in a common reference frame. This formulation is elegant and powerful, but unable to tackle dynamic scenes. To address this challenge, we introduce the concept of Dynamic Point Maps (DPM), extending standard point maps to support 4D tasks such as motion segmentation, scene flow estimation, 3D object tracking, and 2D correspondence. Our key intuition is that, when time is introduced, there are several possible spatial and time references that can be used to define the point maps. We identify a minimal subset of such combinations that can be regressed by a network to solve the sub tasks mentioned above. We train a DPM predictor on a mixture of synthetic and real data and evaluate it across diverse benchmarks for video depth prediction, dynamic point cloud reconstruction, 3D scene flow and object pose tracking, achieving state-of-the-art performance. Code, models and additional results are available at https://www.robots.ox.ac.uk/~vgg/research/dynamic-point-maps/.

Marios Impraimakis

The response-only model class selection capability of a novel deep convolutional neural network method is examined herein in a simple, yet effective, manner. Specifically, the responses from a unique degree of freedom along with their class information train and validate a one-dimensional convolutional neural network. In doing so, the network selects the model class of new and unlabeled signals without the need of the system input information, or full system identification. An optional physics-based algorithm enhancement is also examined using the Kalman filter to fuse the system response signals using the kinematics constraints of the acceleration and displacement data. Importantly, the method is shown to select the model class in slight signal variations attributed to the damping behavior or hysteresis behavior on both linear and nonlinear dynamic systems, as well as on a 3D building finite element model, providing a powerful tool for structural health monitoring applications.

Sina Sabermahani, Andrew Frederiksen

This paper introduces DeepRFQC, an automated method for quality control in P-wave receiver function analysis. Leveraging a U-Net inspired deep learning model, which has previously shown promise in denoising and phase detection, DeepRFQC efficiently distinguishes usable from noisy receiver functions. We examine a Proterozoic Trans-Hudson Orogen dataset from northern Canada, including seismic events from 1990 to 2023, which is expanded for training purposes by data augmentation techniques. With 1,508,449 trainable parameters, the DeepRFQC model attains a commendable 96.6% validation accuracy, on a test dataset from the X5 seismic network; tests on stations from different tectonic environments indicate that the model is effective even in environments very different from the training set. Validation through the H-κ stacking method shows consistent and plausible results. As manual quality control is a major bottleneck in receiver-function processing, automated methods such as this one will allow for efficient examination of large data sets.

Andrey O. Leonov

The structure of skyrmion and spiral solutions, investigated within the phenomenological Dzyaloshinskii model of chiral magnets near the ordering temperatures, is characterized by the strong interplay between longitudinal and angular order parameters, which may be responsible for experimentally observed precursor effects. Within the precursor regions, additional effects, such as pressure, electric fields, chemical doping, uniaxial strains and/or magnetocrystalline anisotropies, modify the energetic landscape and may even lead to the stability of such exotic phases as a square staggered lattice of half-skyrmions, the internal structure of which employs the concept of the “soft” modulus and contains points with zero modulus value. Here, we additionally alter the stiffness of the magnetization modulus to favor one- and two-dimensional modulated states with large modulations of the order parameter magnitude. The computed phase diagram, which omits any additional effects, exhibits stability pockets with a square half-skyrmion lattice, a hexagonal skyrmion lattice with the magnetization in the center of the cells parallel to the applied magnetic field, and helicoids with propagation transverse to the field, i.e., those phases in which the notion of localized defects is replaced by the picture of a smooth but more complex tiling of space. We note that the results can be adapted to metallic glasses, in which the energy contributions are the same and originate from the inherent frustration in the models, and chiral liquid crystals with a different ratio of elastic constants.

Abolfazl Eslami, Masoud Nobahar, Mohammad Esmailzade

Field tests are the most suitable method to determine geotechnical parameters. Owing to some restrictions in field tests, physical modeling has been widely accepted as a proper method to define mathematical correlations among geotechnical parameters. This study investigates correlations between parameters derived from cone penetrometer tests. The tests were performed in a cylindrical chamber with a height and diameter of 1000 mm to minimize the boundary effect. Coastal poorly graded sand sampled from the Babolsar region, adjacent to the Caspian Sea, was used. Some correlations among geotechnical parameters, including cone resistance, dynamic cone resistance, dynamic penetration index, modulus of elasticity, internal friction angle, and relative density, are presented. All correlations were categorized into three main categories: soil stiffness, penetration strength, and geotechnical parameters. The results had reasonable accuracy and precision. The average R² value of the obtained results was approximately 94. The investigations into the inherent CPT also indicated that the strength parameter had more accuracy than stiffness and other sand parameters. Specifically, the R² value for the correlation between the results of various penetration tests, considered strength parameters, averaged 97. In contrast, the R² value for the correlation between the elasticity modulus and cone penetration test results was 86.

Ru Lei, Lin Li, Rustam Stolkin et al.

This paper addresses the challenge of dynamic multi-objective optimization problems (DMOPs) by introducing novel approaches for accelerating prediction strategies within the evolutionary algorithm framework. Since the objectives of DMOPs evolve over time, both the Pareto optimal set (PS) and the Pareto optimal front (PF) are dynamic. To effectively track the changes in the PS and PF in both decision and objective spaces, we propose an adaptive prediction strategy that incorporates second-order derivatives to predict and adjust the algorithms search behavior. This strategy enhances the algorithm's ability to anticipate changes in the environment, allowing for more efficient population re-initialization. We evaluate the performance of the proposed method against four state-of-the-art algorithms using standard DMOPs benchmark problems. Experimental results demonstrate that the proposed approach significantly outperforms the other algorithms across most test problems.

William Yang, Michael Posa

Non-prehensile manipulation enables fast interactions with objects by circumventing the need to grasp and ungrasp as well as handling objects that cannot be grasped through force closure. Current approaches to non-prehensile manipulation focus on static contacts, avoiding the underactuation that comes with sliding. However, the ability to control sliding contact, essentially removing the no-slip constraint, opens up new possibilities in dynamic manipulation. In this paper, we explore a challenging dynamic non-prehensile manipulation task that requires the consideration of the full spectrum of hybrid contact modes. We leverage recent methods in contact-implicit MPC to handle the multi-modal planning aspect of the task. We demonstrate, with careful consideration of integration between the simple model used for MPC and the low-level tracking controller, how contact-implicit MPC can be adapted to dynamic tasks. Surprisingly, despite the known inaccuracies of frictional rigid contact models, our method is able to react to these inaccuracies while still quickly performing the task. Moreover, we do not use common aids such as reference trajectories or motion primitives, highlighting the generality of our approach. To the best of our knowledge, this is the first application of contact-implicit MPC to a dynamic manipulation task in three dimensions.

Adriana Amieva, Agustín G. Bonifacio, Pablo Neme

We examine the problem of assigning teachers to public schools over time when teachers have tenured positions and can work simultaneously in multiple schools. To do this, we investigate a dynamic many-to-many school choice problem where public schools have priorities over teachers and teachers hold path-independent choice functions selecting subsets of schools. We introduce a new concept of dynamic stability that recognizes the tenured positions of teachers and we prove that a dynamically stable matching always exists. We propose the Tenure-Respecting Deferred Acceptance (TRDA) mechanism, which produces a dynamically stable matching that is constrained-efficient within the class of dynamically stable matchings and minimizes unjustified claims. To improve efficiency beyond this class, we also propose the Tenure-Respecting Efficiency-Adjusted Deferred Acceptance (TREADA) mechanism, an adaptation of the Efficiency-Adjusted Deferred Acceptance mechanism to our dynamic context. We demonstrate that the outcome of the TREADA mechanism Pareto-dominates any dynamically stable matching and achieves efficiency when all teachers consent. Additionally, we examine the issue of manipulability, showing that although the TRDA and TREADA mechanisms can be manipulated, they remain non-obviously dynamically manipulable under specific conditions on schools' priorities.

S. M. Smith, A. J. Hughes, T. A. Dardeno et al.

Population-based structural health monitoring (PBSHM), aims to share information between members of a population. An offshore wind (OW) farm could be considered as a population of nominally-identical wind-turbine structures. However, benign variations exist among members, such as geometry, sea-bed conditions and temperature differences. These factors could influence structural properties and therefore the dynamic response, making it more difficult to detect structural problems via traditional SHM techniques. This paper explores the use of a hierarchical Bayesian model to infer expected soil stiffness distributions at both population and local levels, as a basis to perform anomaly detection, in the form of scour, for new and existing turbines. To do this, observations of natural frequency will be generated as though they are from a small population of wind turbines. Differences between individual observations will be introduced by postulating distributions over the soil stiffness and measurement noise, as well as reducing soil depth (to represent scour), in the case of anomaly detection.

R. Bossis, V. Regard, S. Carretier

<p>Long-term coastal erosion is not yet well studied given that it is difficult to quantify. The quantification of long-term coastal erosion requires reconstruction of the coast's initial geometry and the determination of where and when the erosion started. Volcanic islands fulfill these two conditions: their initial shape is roughly conical and the age of the lavas that generated this geometry is easily measured. We have developed a method to reconstruct the initial shape of simple volcanic edifices from aerial and submarine topographic data. The reconstructed initial shape and associated uncertainties allow us to spatially quantify the coastal erosion since the building of the island. This method is applied to Corvo Island in the Azores archipelago. We calculated that, due to coastal erosion, the island has lost a volume of 6.5 <span class="inline-formula">±</span> 2.7 km<span class="inline-formula">³</span> and roughly 80 % of its surface area since it first came into being. Taking the large uncertainty in the age of the topmost lava flows (0.43 <span class="inline-formula">±</span> 0.34 Myr) into account, we have estimated that Corvo Island has lost an average of 5000 to 100 000 m<span class="inline-formula">³</span> yr<span class="inline-formula">⁻¹</span> of its volume due to coastal erosion. Lastly, we show a strong correlation between long-term coastal erosion and the spatial distribution of the waves. Specifically, we highlight a stronger control on erosion by smaller and more frequent waves than by storm waves. The next step will be to apply this method to other volcanic islands in order to (i) streamline and improve the method and (ii) verify the correlations observed in the present study.</p>

Zezhang Song, Xiaoheng Ding, Benjian Zhang et al.

The evolution mechanism of hydrocarbons in ultra-deeply-buried and ultra-old strata is the core issue of petroleum geology moving towards Deep Earth. Reconstructing the evolutionary history of ultra-deeply-buried hydrocarbons is the key to shedding light on deep hydrocarbon accumulation and evolution mechanisms. Furthermore, it can help point out directions for oil and gas exploration in Deep Earth. Anyue gas field in the central Sichuan Basin is the Frontier of deep natural gas exploration in China. This study selected the natural gas reservoirs of the Upper Sinian Dengying Formation in the central Sichuan Basin as the research object. By integrating analysis of natural gas geochemical characteristics, source rock evaluation, reservoir bitumen-source correlation, inclusion analysis, one-dimensional and two-dimensional hydrocarbon accumulation simulations, the generation and evolution of hydrocarbons in different structural regions, namely the inherited paleo-uplift and slope area in central Sichuan Basin, have been dynamically restored and compared. The results show that: 1) The natural gas of the ultra-deeply-buried Sinian Dengying formation in central Sichuan is typical oil-cracking gas from the paleo-oil reservoir. The Sinian gas is mainly sourced from the Qiongzhusi/Maidiping Formation. 2) The formation of Sinian gas reservoirs includes three stages: the formation of paleo-oil-reservoirs; the cracking of paleo-oil-reservoirs into paleo-gas-reservoirs; the adjustment of the paleo-gas-reservoirs. 3) Source rock and reservoir evaluation, quantitative solid bitumen analysis, and hydrocarbon accumulation simulation show that the natural gas accumulation conditions in the slope area are better than in the inherited uplift area. The scale of the paleo-oil-reservoirs in the slope area may be greater than that in the inherited uplift area.

Zhongnian Yang, Zhaochi Lu, W. Shi et al.