Search Results (206)

Predicting tunnel seepage field is a critical challenge in the construction of underground engineering projects. While traditional analytical solutions and numerical methods struggle with complex geometric boundaries, standard Physics-Informed Neural Networks (PINNs) encounter additional challenges in tunnel seepage problems, including training instability, boundary handling difficulties, and low sampling efficiency. This paper develops an enhanced PINN framework designed specifically for predicting tunnel seepage field by integrating Exponential Moving Average (EMA) weight stabilization, Residual Adaptive Refinement with Distribution (RAR-D) sampling, and Bayesian optimization for collaborative training. The framework introduces a trial function method based on an approximate distance function (ADF) to address the precise handling of circular tunnel boundaries. The results demonstrate that the enhanced PINN framework achieves an exceptional prediction accuracy with an overall average relative error of 5 × 10⁻⁵. More importantly, the method demonstrates excellent practical applicability in data-scarce scenarios, maintaining acceptable prediction accuracy even when monitoring points are severely limited. Bayesian optimization reveals the critical insight that loss weight configuration is more important than network architecture in physics-constrained problems. This study is a systematic application of PINNs to prediction of tunnel seepage field and holds significant value for tunnel construction monitoring and risk assessment. Full article

Deep learning-based methods have shown great promise for synthetic aperture radar (SAR) automatic target recognition (ATR) in recent years. These methods demonstrate superior performance compared to traditional approaches across various recognition tasks. However, these methods often face significant challenges due to the limited availability of labeled samples, which is a common issue in SAR image analysis owing to the high cost and difficulty of data annotation. To address this issue, a variety of few-shot learning approaches have been proposed and have demonstrated promising results under data-scarce conditions. Nonetheless, a notable limitation of many existing few-shot methods is that their performance tends to plateau when more labeled samples become available. Most few-shot methods are optimized for scenarios with extremely limited data. As a result, they often fail to leverage the advantages of larger datasets. This leads to suboptimal recognition performance compared to conventional deep learning techniques when sufficient training data is available. Therefore, there is a pressing need for approaches that not only excel in few-shot scenarios but also maintain robust performance as the number of labeled samples increases. To this end, we propose a novel method, termed relation-guided embedding transductive propagation network with residual correction (RGE-TPNRC), specifically designed for few-shot SAR ATR tasks. By leveraging mechanisms such as relation node modeling, relation-guided embedding propagation, and residual correction, RGE-TPNRC can fully utilize limited labeled samples by deeply exploring inter-sample relations, enabling better scalability as the support set size increases. Consequently, it effectively addresses the plateauing performance problem of existing few-shot learning methods when more labeled samples become available. Firstly, input samples are transformed into support-query relation nodes, explicitly capturing the dependencies between support and query samples. Secondly, the known relations among support samples are utilized to guide the propagation of embeddings within the network, enabling manifold smoothing and allowing the model to generalize effectively to unseen target classes. Finally, a residual correction propagation classifier refines predictions by correcting potential errors and smoothing decision boundaries, ensuring robust and accurate classification. Experimental results on the moving and stationary target acquisition and recognition (MSTAR) and OpenSARShip datasets demonstrate that our method can achieve state-of-the-art performance in few-shot SAR ATR scenarios. Full article

This article discusses contemporary strategies to deal with immersed boundary (IB) frameworks useful for analyzing flow–structure interaction in complex settings. It focuses on immense advancements in various fields: biology, oscillation of structures due to fluid flow, deformable materials, thermal processes, settling particles, multiphase systems, and sound propagation. The discussion also involves a review of techniques addressing moving boundary conditions at complex interfaces. Evaluating practical examples and theoretical challenges that have been addressed by these frameworks are another focus of the article. Important results highlight the integration of IB methods with adaptive mesh refinement and high-order accuracy techniques, which enormously improve computational efficiency and precision in modeling complex solid–fluid interactions. The article also describes the evolution of IB methodologies in tackling problems of energy harvesting, bio-inspiration propulsion, and thermal-fluid coupling, which extends IB methodologies broadly in many scientific and industrial areas. More importantly, by bringing together different insights and paradigms from across disciplines, the study highlights the emerging trends in IB methodologies towards solving some of the most intricate challenges within the technical and scientific domains. Full article

The Diaoyu Islands Folded-Uplift Belt consists of metamorphic basement, magmatic rocks and Paleogene series in the Eastern Depression Zone of the East China Sea Basin which was deformed and uplifted by magma emplacement. The emplacement of the magma resulted in an unclear understanding of the Paleogene geomorphy in the paleo-uplift, further affecting the analysis of the eastern boundary and the sedimentary environment of Paleogene prototype basin in the Eastern Depression Zone. To explore the Paleogene geomorphy and magma emplacement process of the Diaoyu Islands Folded-Uplift Belt, we conducted a detailed interpretation of 2-D seismic profiles and identified nearshore subaqueous fans and fan deltas within the deformed strata. The development scale of them helps to determine the approximate location of the Paleogene eastern boundary of the Eastern Depression Zone. We integrated the boundary location with gravity, magnetic, and well data to obtain the Paleogene geomorphy of the Diaoyu Islands Folded-Uplift Belt. Our results indicate that the subduction direction of the Pacific Plate was almost perpendicular to the Eurasian Plate during the late Eocene, leading to the development of numerous left-lateral strike-slip faults within the East China Sea Basin, further forming channels within the paleo-uplift, which connected the Eastern Depression Zone and the ocean. In the Early Oligocene, the subduction rate of the Pacific Plate abruptly increased, resulting in large-scale and significant exhumation of the paleo-uplift, and the Eastern Depression Zone had transformed into a lacustrine sedimentary environment. Furthermore, due to the continuous retreat of the Pacific Plate, the extension center of the back-arc basin moved to the eastern margin of the Eastern Depression Zone in the late Oligocene. This work provides a method for recovering the geomorphology of complex tectonic units in back-arc basins based on fine seismic interpretation, solving the key problem that constrained the recovery of boundaries and sedimentary environment of the prototype basin. Full article

Energy generation from renewable sources has increased exponentially worldwide, particularly wind energy, which is converted into electricity through wind turbines. The growing demand for renewable energy has driven the development of horizontal-axis wind turbines with larger dimensions, as the energy captured is proportional to the area swept by the rotor blades. In this context, the dynamic loads typically observed in wind turbine towers include vibrations caused by rotating blades at the top of the tower, wind pressure, and earthquakes (less common). In offshore wind farms, wind turbine towers are also subjected to dynamic loads from waves and ocean currents. Vortex-induced vibration can be an undesirable phenomenon, as it may lead to significant adverse effects on wind turbine structures. This study presents a two-dimensional transient model for a rigid body anchored by a torsional spring subjected to a constant velocity flow. We applied a coupling of the Fourier pseudospectral method (FPM) and immersed boundary method (IBM), referred to in this study as IMERSPEC, for a two-dimensional, incompressible, and isothermal flow with constant properties—the FPM to solve the Navier–Stokes equations, and IBM to represent the geometries. Computational simulations, solved at an aspect ratio of $\varphi =4.0$, were analyzed, considering Reynolds numbers ranging from $Re=150$ to Re = 1000 when the cylinder is stationary, and $Re=250$ when the cylinder is in motion. In addition to evaluating vortex shedding and Strouhal number, the study focuses on the characterization of space–time symmetry during the galloping response. The results show a spatial symmetry breaking in the flow patterns, while the oscillatory motion of the rigid body preserves temporal symmetry. The numerical accuracy suggested that the IMERSPEC methodology can effectively solve complex problems. Moreover, the proposed IMERSPEC approach demonstrates notable advantages over conventional techniques, particularly in terms of spectral accuracy, low numerical diffusion, and ease of implementation for moving boundaries. These features make the model especially efficient and suitable for capturing intricate fluid–structure interactions, offering a promising tool for analyzing wind turbine dynamics and other similar systems. Full article

The entanglement entropy of a random tensor network (RTN) is studied using tools from free probability theory. Random tensor networks are simple toy models that help in understanding the entanglement behavior of a boundary region in the anti-de Sitter/conformal field theory (AdS/CFT) context. These can be regarded as specific probabilistic models for tensors with particular geometry dictated by a graph (or network) structure. First, we introduce a model of RTN obtained by contracting maximally entangled states (corresponding to the edges of the graph) on the tensor product of Gaussian tensors (corresponding to the vertices of the graph). The entanglement spectrum of the resulting random state is analyzed along a given bipartition of the local Hilbert spaces. The limiting eigenvalue distribution of the reduced density operator of the RTN state is provided in the limit of large local dimension. This limiting value is described through a maximum flow optimization problem in a new graph corresponding to the geometry of the RTN and the given bipartition. In the case of series-parallel graphs, an explicit formula for the limiting eigenvalue distribution is provided using classical and free multiplicative convolutions. The physical implications of these results are discussed, allowing the analysis to move beyond the semiclassical regime without any cut assumption, specifically in terms of finite corrections to the average entanglement entropy of the RTN. Full article

In order to improve the uniformity of microwave heating, moving components are often added to the cavity. For higher uniformity or greater industrial processing capacity, samples often perform large-scale movements such as rotating and lifting motion or translational motion on a conveyor belt. The microwave heating algorithm based on the ray-casting method (RCM), as proposed in previous studies, can calculate moving complex-shaped samples, but the calculation efficiency is low when the sample moves on a large scale due to the large refined mesh area. To solve this problem, this study introduced a moving mesh combined with the RCM for calculation purposes. A microwave oven model with a rotating and lifting turntable was selected for the analysis. First, the calculation area was divided into a sliding mesh and a telescopic mesh area. The telescopic mesh area was stretched or compressed at different times, which was equivalent to the translational motion of the sample. Then, the electromagnetic parameters were assigned to each mesh point in combination with the boundary recognition algorithm based on the ray-casting method, and the horizontal motion was calculated while calculating the large-scale translation. The proposed method only needs to refine the mesh in the horizontal motion area, which reduces the number of overall meshes. The electromagnetic field distribution obtained by the model during the heating process was verified by the discrete position method. The surface temperature distribution and the real-time curve of the center point temperature were further compared with the RCM. The results show that the average error of the sample center temperature is 2.5% and the calculation time was reduced to 9.8%, which verified the accuracy and efficiency of the proposed method. Finally, the influence of different lifting and rotating speeds on the heating effect was further explored. Full article

This paper presents a meshless Galerkin method for analyzing the nonlinear behavior of corrugated sandwich plates. A corrugated sandwich plate is a composite structure comprising two flat face sheets and a corrugated core, which can be approximated as an orthotropic anisotropic plate with distinct elastic properties in two perpendicular directions. The formulation is based on the first-order shear deformation theory (FSDT), where the shape functions are constructed using the moving least-square (MLS) approximation. Nonlinear stress and strain expressions are derived according to von Kármán’s large deflection theory. The virtual strain energy functionals of the individual plates are established, and their nonlinear equilibrium equations are formulated using the principle of virtual work. The governing equations for the entire corrugated sandwich structure are obtained by incorporating boundary conditions and displacement continuity constraints. A Newton–Raphson iterative scheme is employed to solve the nonlinear equilibrium equations. The computational program is implemented in C++, and extensive numerical examples are analyzed. The accuracy and reliability of the proposed method are validated through comparisons with ANSYS finite element solutions using SHELL181 elements. The method used in this paper can avoid the problems of mesh reconstruction and mesh distortion in the finite element method. In practical application, it simplifies the simulation calculation and understands the mechanical behavior of sandwich plates closer to actual engineering practice. Full article

This paper studies numerical simulations of the input-output behavior of a geothermal energy storage used in residential heating systems. There, under or aside of a building a certain domain is filled with soil and insulated from the surrounding ground. Thermal energy is stored by raising the temperature of the soil inside the storage, and pipe heat exchangers filled with a moving fluid are used to charge and discharge the storage. Numerical simulations are required for the design, operation and optimal management of heating systems that are equipped with such a thermal storage system. They help to understand the storage response to charging and discharging processes, which depend crucially on the dynamics of the spatial temperature distribution in the storage medium. The latter is modeled mathematically by an initial boundary value problem for a linear heat equation with convection. The problem is solved numerically by finite difference discretization. Finally, the results of computer simulations are presented, which show the properties of the temperature distribution in the storage and its aggregated characteristics. Full article

In this paper, we consider the unsteady flow of a compressible micropolar fluid between two moving, thermally isolated parallel plates. The fluid is characterized as viscous and thermally conductive, with polytropic thermodynamic properties. Although the mathematical model is inherently three-dimensional, we assume that the variables depend on only a single spatial dimension, reducing the problem to a one-dimensional formulation. The non-homogeneous boundary conditions representing the movement of the plates lead to moving domain boundaries. The model is formulated in mass Lagrangian coordinates, which leads to a time-invariant domain. This work focuses on numerical simulations of the fluid flow for different configurations. Two computational approaches are used and compared. The first is based on the finite difference method and the second is based on the Faedo–Galerkin method. To apply the Faedo–Galerkin method, the boundary conditions must first be homogenized and the model equations reformulated. On the other hand, in the finite difference method, the non-homogeneous boundary conditions are implemented directly, which reduces the computational complexity of the numerical scheme. In the performed numerical experiments, it was observed that, for the same accuracy, the Faedo–Galerkin method was approximately 40 times more computationally expensive compared to the finite difference method. However, on a dense numerical grid, the finite difference method required a very small time step, which could lead to an accumulation of round-off errors. On the other hand, the Faedo–Galerkin method showed the convergence of the solutions as the number of expansion terms increased, despite the higher computational cost. Comparisons of the obtained results show good agreement between the two approaches, which confirms the consistency and validity of the numerical solutions. Full article

Suction is an important control method in the shock wave and boundary layer interaction (SWBLI). Aimed at the problem of separation bubbles induced at the expansion corners, this study investigates the influence of suction on both the dimensions of bubble and the structure of the flow field at varying positions and back pressures under Ma = 2.73. As the upstream suction hole moves to the shoulder point, the size of the separation bubble decreases slightly. The decrease in back pressure leads to an increase in flow deflection angle α_h. The low-kinetic-energy fluid in the boundary layer is removed and the thickness of the boundary layer decreases. Suction downstream of the shoulder point leads to an obvious change in separation bubble size. When the bleed position is upstream of the actual location of incident shock (D_down = 2δ), the separation zone is located at the trailing edge of the hole, and the convergence of the separation shock wave (SS) and the barrier shock wave (BSW) leads to a large increase in the pressure plateau. At the downstream of the incident shock (D_down = 5δ), the separation zone is situated at the leading edge of the hole, resulting in a substantial reduction in the size of the separation bubble. The flow reaches 88.5% of the theoretical expansion value at the shoulder point and directly turns into the bleeding area at the leeward side of the separation bubble. The deflection angle α_h reaches the maximum of 46°, and the sonic flow coefficient Q_sonic increases significantly. At the theoretical incident shock position (D_down = 7δ), the separation zone is far from the suction hole position; the two are almost decoupled. The size of the bubble increases rapidly and the reattachment shock wave (RS) appears. Full article

This study investigates the dynamics of two oscillating rigid spheres moving through an infinite porous medium saturated with Stokes fluid flow, addressing the problem of how fluid properties, permeability, frequency, and slip length influence the system. The objective is to model the interactions between the spheres, which differ in size and velocity as they move along the axis connecting their centers while applying slip boundary conditions to their surfaces. We derive the governing field equations using a semi-analytical method and solve the resulting system of equations numerically through a collocation technique. Our novel quantitative results include insights into the drag force coefficients for both in-phase and out-of-phase oscillations of each hydrophobic sphere, considering parameters such as diameter ratio, permeability, frequency, velocity ratios, slip lengths, and the distances between the spheres. Notably, when the spheres are sufficiently far apart, the normalized drag force coefficients behave as if each sphere is moving independently. Additionally, we present streamlines that illustrate the interactions between the spheres across a range of parameters, highlighting the novelty of our findings. A purely viscous medium and no-slip conditions are used to validate the numerical approach and results. Full article

This study addresses the diffusion of oxygen in a spherical geometry with simultaneous absorption at a constant rate. The analytical method assumes a polynomial representation of the oxygen concentration profile, leading to a system of differential equations through mathematical manipulation. A numerical scheme is then employed to solve this system, linking the moving boundary and its velocity to determine the unknown functions within the assumed polynomial. An approximate analytical solution is obtained and compared with other methods, demonstrating very good agreement. This approach provides a novel method for addressing oxygen diffusion in spherical geometries, combining analytical techniques with numerical computations to efficiently solve for oxygen concentration profiles and moving boundary dynamics. Full article

We introduce a circle rolling method (CRM) for boundary extraction from 2D point clouds. The core idea is to create a circle that performs pure rolling on the perimeter of the point cloud to obtain the boundary. For a 3D point cloud, a plane adsorbs points on both sides to create a 2D point cloud, and the CRM is used to extract the boundary points and map them back into space to obtain 3D boundary points. Continuously moving this plane can obtain a complete boundary, which is called the moving adsorption rolling method (MARM). In this paper, we solve the interference problems in our method caused by unidirectional overlapping points and porous structures and successfully validate the solutions in practical examples. Our point cloud boundary extraction method is faster in 2D and better for surface concavities extracted in 3D compared to existing methods, and it is unaffected by sparse points within the point cloud. Full article

An efficient approximation is developed for the Laplacian operator by merging the advances of finite difference and finite element approximations. This approach is applicable to a general quadrilateral grid. The optimal coefficients for the approximation are computed using a pointwise optimization process. In this process, an overdetermined system is solved in the least-square sense using weighted polynomial approximation. The proposed algorithm is a vectorized procedure, keeping the computational time at a low level. The performance of this method is demonstrated on a model problem involving the numerical solution of a Poisson problem. Its true potential is evident when applied to moving boundary problems, which typically require a dynamic grid for efficient simulation. Within the framework of the proposed algorithm, we can compute the spatial discretization on the new grid quickly. This procedure is tested in the Stefan problem. For this, we give the simulation algorithm in detail utilizing the quadrilateral grid geometry. The performance is again demonstrated in a series of numerical experiments. Full article