Search Results (145)

This study presents a high-fidelity CFD-based optimization of a combined sacrificial-pile and collar (SPC) system designed to suppress local scour at circular bridge piers. Following rigorous validation against benchmark flume experiments (scour depth error < 3%), a systematic parametric study was conducted to quantify the influence of pile-to-pier spacing (d_p/D = 4–6) and collar elevation (h_c/D = 0–0.3). The optimal layout is found to be a sacrificial pile at d_p/D = 5 and a collar at h_c/D, which yields a 51.2% scour reduction relative to the unprotected case. Flow field analysis reveals that the pile wake deflects the lower approach flow, while the collar vertically displaces the horseshoe vortex; together, these mechanisms redistribute bed shear stress and prevent secondary undermining. Consequently, the upstream conical pit is virtually eliminated, lateral scour is broadened but markedly shallower, and the downstream dune tail bifurcates into two symmetrical ridges. To the best of the authors’ knowledge, this study presents the first high-fidelity CFD-based optimization of a combined sacrificial-pile and collar (SPC) system with a fully coupled hydrodynamic-morphodynamic model. The optimized layout yields a 51.2% scour reduction relative to the unprotected case and, more importantly, demonstrates a positive non-linear synergy that exceeds the linear sum of individual device efficiencies by 7.5%. The findings offer practical design guidance for enhancing bridge foundation resilience against scour-induced hydraulic failure. Full article

Traditional hybrid RANS/LES methods often struggle to accurately capture both the boundary layer transition and flow separation simultaneously due to their reliance on fully turbulent RANS models. To address this limitation, the present study first evaluates three transitional RANS models (γ-Re_θt-SST, γ-SST, and Kγ-SST) on the E387 airfoil. The results demonstrate that the γ-SST model offers the best balance of accuracy and computational efficiency in predicting laminar separation bubbles (LSBs) and transition points. Building on this, we implement the γ-SST-IDDES model into OpenFOAM-v2312, which integrates the γ-SST transitional RANS model with the Improved Delayed Detached Eddy Simulation (IDDES) approach. This coupling allows for the simultaneous prediction of the laminar-turbulent transition and high-fidelity resolution of separated flows. The γ-SST-IDDES model is rigorously validated across three airfoil cases with distinct separation characteristics: E387 (small separation), DBLN-526 (moderate separation), and NACA 0021 (massive separation). The results show that the γ-SST-IDDES model outperforms conventional methods, capturing leading-edge LSBs with high accuracy compared to fully turbulent IDDES. Additionally, it successfully resolves complex 3D vortical structures in separated regions, whereas unsteady URANS provides only quasi-2D results. Full article

In this study, we have performed 3D numerical simulations of the excitation and contraction of thin slab-like samples of myocardium tissue. The samples included a narrow region of almost non-excitable tissue simulating impaired myocardium. In the numerical experiments, we considered the heterogeneity of myocardium excitation and the ${\mathrm{Ca}}^{2+}$ activation of its contraction, as well as the orientation of the muscle fibers. Those characteristics varied throughout the thin wall of the sample. The simulations were performed in our numerical framework for the problems of cardiac electromechanics developed recently. The framework was previously tested for the benchmark problems in which formulations took into account only myocardium electrophysiology and passive mechanics. The study could be considered as an approbation of the framework performance with the fully coupled mathematical model of myocardium electromechanics. Here we dealt with the problems requiring a multiscale approach, taking into account cell-level electrophysiology, cell-level mechano-chemical processes, macromechanics (strain and stress) of the 3D sample, and interconnections between the levels. It was shown how the tissue heterogeneity and its strain affected the propagation of excitation–contraction waves in the sample, including, in particular, the formation of spiral waves. Full article

Rock creep, a key factor in the long-term stability of deep geotechnical engineering, remains challenging to study due to the complexity of its microscopic damage mechanisms. Laboratory creep tests are limited by long durations and scale effects, while phenomenological models cannot fully capture the underlying processes. This study employs the parallel-bonded stress corrosion (PSC) model in PFC2D to simulate sandy mudstone’s creep behavior, systematically correlating macroscopic creep deformation with microscopic damage evolution and energy conversion. The model reproduces the four stages of the idealized creep curve and quantifies the effects of axial stress level and confining pressure on creep lifetime, rate, and failure mode. Increasing axial stress shortens creep lifetime; every 10% increase raises the creep rate by a factor of 4–14, and high stress enhances nonlinear deformation, producing stair-stepping curves due to unstable microcrack propagation. In contrast, confining pressure prolongs lifetime; at 90% uniaxial compressive strength (UCS), 15 MPa extends it from 2.78 h to ~25 years. Confinement also enhances ductility by suppressing tensile stresses and delaying damage accumulation. This study reveals the coupling mechanism of stress-corrosion-induced subcritical crack propagation and energy dissipation, clarifies the microscopic origin of stepped creep curves, and provides a micromechanical framework for long-term stability evaluation in deep geotechnical engineering. Full article

This study numerically investigates the suitability of biomass particles of varying diameters as alternative reducing agents in the blast furnace raceway zone, where harsh conditions can create internal gradients affecting conversion. An internally resolved 1D Lagrangian particle model, fully integrated into the open-source CFD toolbox OpenFOAM^®, is used to model temperature and species gradients within thermally thick particles. The particle model is coupled with the surrounding Eulerian phase and includes drying, pyrolysis, oxidation, and gasification submodels. Results show that only biomass particles smaller than 250 μm fully convert in the raceway, while larger particles carry unconverted material beyond, potentially reducing blast furnace efficiency. Full article

Horizontal well fracturing is vital for low-permeability tight oil reservoirs, but multi-fracture effectiveness is hampered by stress shadowing and fluid-rock interactions, particuarly in optimizing fracture geometry and conductivity under different sequencing strategies. While previous studies have addressed aspects of pore pressure and stress effects, a comprehensive comparison of sequencing strategies using fully coupled models capturing the intricate seepage–stress–damage interactions remains limited. This study employs a novel 2D fully coupled XFEM model to quantitatively evaluate three fracturing approaches: simultaneous, sequential, and alternating. Numerical results demonstrate that sequential and alternating strategies alleviate stress interference, increasing cumulative fracture length by 20.6% and 26.1%, respectively, versus conventional simultaneous fracturing. Based on the research findings, fracture width reductions are 30.44% (simultaneous), 18.78% (sequential), and 7.21% (alternating). As fracture width directly governs conductivity—the critical parameter determining hydrocarbon flow efficiency—the alternating strategy’s superior width preservation (92.79% retention) enables optimal conductivity design. These findings provide critical insights for designing fracture networks with targeted dimensions and conductivity in tight reservoirs and offer a practical basis to optimize fracture sequencing design. Full article

Span-wise homogeneous supersonic cavity flows display complicated structures due to shear layer breakdown, flow acoustic resonance, and even non-linear hydrodynamic-acoustic interactions. In practical applications, such as aircraft bays, the cavity is of finite width and has doors, both of which introduce distinctive phenomena that couple with the shear layer at the cavity lip, further modulating shear layer bifurcations and tonal mechanisms. In particular, asymmetric states manifest as ‘tornado’ vortices with significant practical consequences on the design and operation. Both inward- and outward-facing leading-wedge doors, resulting in leading edge shocks directed into and away from the cavity, are examined at select opening angles ranging from $22.5°$ to $90°$ (fully open) at Mach 1.6. The computational approach utilizes the Reynolds-Averaged Navier–Stokes equations with a one-equation model and is augmented by experimental observations of cavity floor pressure and surface oil-flow patterns. For the no-doors configuration, the asymmetric results are consistent with a long-time series DDES simulation, previously validated with two experimental databases. When fully open, outer wedge doors (OWD) yield an asymmetric flow, while inner wedge doors (IWD) display only mildly asymmetric behavior. At lower door angles (partially closed cavity), both types of doors display a successive bifurcation of the shear layer, ultimately resulting in a symmetric flow. IWD tend to promote symmetry for all angles observed, with the shear layer experiencing a pitchfork bifurcation at the ‘critical angle’ ($67.5°$). This is also true for the OWD at the ‘critical angle’ ($45°$), though an entirely different symmetric flow field is established. The first observation of pitchfork bifurcations (‘critical angle’) for the IWD is at $67.5°$ and for the OWD, $45°$, complementing experimental observations. The back wall signature of the bifurcated shear layer (impingement preference) was found to be indicative of the 3D cavity dynamics and may be used to establish a correspondence between 3D cavity dynamics and the shear layer. Below the critical angle, the symmetric flow field is comprised of counter-rotating vortex pairs at the front and back wall corners. The existence of a critical angle and the process of door opening versus closing indicate the possibility of hysteresis, a preliminary discussion of which is presented. Full article

Hyperspectral image (HSI) classification faces challenges such as high dimensionality, spectral redundancy, and difficulty in modeling the coupling between spectral and spatial features. Existing methods fail to fully exploit first-order derivatives and frequency domain information, which limits classification performance. To address these issues, this paper proposes a Differential-Frequency Attention-based Band Selection Transformer (DFAST) for HSI classification. Specifically, a Differential-Frequency Attention-based Band Selection Embedding Module (DFASEmbeddings) is designed to extract original spectral, first-order derivative, and frequency domain features via a multi-branch structure. Learnable band selection attention weights are introduced to adaptively select important bands, capture critical spectral information, and significantly reduce redundancy. A 3D convolution and a spectral–spatial attention mechanism are applied to perform fine-grained modeling of spectral and spatial features, further enhancing the global dependency capture of spectral–spatial features. The embedded features are then input into a cascaded Transformer encoder (SCEncoder) for deep modeling of spectral–spatial coupling characteristics to achieve classification. Additionally, learnable attention weights for band selection are outputted for dimensionality reduction. Experiments on several public hyperspectral datasets demonstrate that the proposed method outperforms existing CNN and Transformer-based approaches in classification performance. Full article

This work deals with the catalytic steam reforming of raw syngas to increase the efficiency of coupling gasification with downstream processes (such as fuel cells and catalytic chemical syntheses) by producing high-temperature, ready-to-use syngas without cooling it for cleaning and conditioning. Such a combination is considered a key point for the future exploitation of syngas produced by steam gasification of biogenic solid fuel. The design and construction of an integrated gasification and gas conditioning system were proposed approximately 20 years ago; however, they still require further in-depth study for practical applications. A 3D model of the freeboard of a pilot-scale, fluidized bed gasification plant equipped with catalytic ceramic candles was used to investigate the optimal operating conditions for in situ syngas upgrading. The global kinetic parameters for methane and tar reforming reactions were determined experimentally. A fluidized bed gasification reactor (~5 kWth) equipped with a 45 cm long segment of a fully commercial filter candle in its freeboard was used for a series of tests at different temperatures. Using a computational fluid dynamics (CFD) description, the relevant parameters for apparent kinetic equations were obtained in the frame of a first-order reaction model to describe the steam reforming of key tar species. As a further step, a CFD model of the freeboard of a 100 kWth gasification plant, equipped with six catalytic ceramic candles, was developed in ANSYS FLUENT^®. The composition of the syngas input into the gasifier freeboard was obtained from experimental results based on the pilot-scale plant. Simulations showed tar catalytic conversions of 80% for toluene and 41% for naphthalene, still insufficient compared to the threshold limits required for operating solid oxide fuel cells (SOFCs). An overly low freeboard temperature level was identified as the bottleneck for enhancing gas catalytic conversions, so further simulations were performed by injecting an auxiliary stream of O₂/steam (50/50 wt.%) through a series of nozzles at different heights. The best simulation results were obtained when the O₂/steam stream was fed entirely at the bottom of the freeboard, achieving temperatures high enough to achieve a tar content below the safe operating conditions for SOFCs, with minimal loss of hydrogen content or LHV in the fuel gas. Full article

Extreme rainstorms are difficult to predict and often result in catchment-scale rainfall flooding, leading to substantial economic losses globally. Enhancing the numerical computational efficiency of flood models is essential for improving flood forecasting capabilities. This study presents an integrated hydrological–hydrodynamic model accelerated using GPU (Graphics Processing Unit) technology to perform high-efficiency and high-precision rainfall flood simulations at the catchment scale. The model couples hydrological and hydrodynamic processes by solving the fully two-dimensional shallow water equations (2D SWEs), incorporating GPU-accelerated parallel computing. The model achieves accelerated rainstorm flooding simulations through its implementation on GPUs with parallel computing technology, significantly enhancing its computational efficiency and maintaining its numerical stability. Validations are conducted using an idealized V-shaped catchment and an experimental benchmark, followed by application to a small catchment on the Chinese Loess Plateau. The computational experiments reveal a strong positive correlation between grid cell numbers and GPU acceleration efficiency. The results also demonstrate that the proposed model offers better computational accuracy and acceleration performance than the single-GPU model. This GPU-accelerated hydrological–hydrodynamic modeling framework enables rapid, high-fidelity rainfall flood simulations and provides critical support for timely and effective flood emergency decision making. Full article

The generation of high-quality mid-infrared free-electron laser (MIR-FEL) radiation depends critically on precise control of electron beam parameters, including energy, energy spread, transverse emittance, bunch charge, and bunch length. At the PBP-CMU Electron Linac Laboratory (PCELL), effective beam diagnostics are essential for optimizing FEL performance. However, dedicated systems for direct measurement of transverse emittance and bunch length at the undulator entrance have been lacking. This paper addresses this gap by presenting the design, simulation, and analysis of diagnostic stations for accurate characterization of these parameters. A two-quadrupole emittance measurement system was developed, enabling independent control of beam-focusing in both transverse planes. An analytical model was formulated specifically for this configuration to enhance emittance reconstruction accuracy. Systematic error analysis was conducted using ASTRA beam dynamics simulations, incorporating 3D field maps from CST Studio Suite and fully including space-charge effects. Results show that transverse emittance values as low as 0.15 mm·mrad can be measured with less than 20% error when the initial RMS beam size is under 2 mm. Additionally, quadrupole misalignment effects were quantified, showing that alignment within ±0.95 mm limits systematic errors to below 33.3%. For bunch length measurements, a transition radiation (TR) station coupled with a Michelson interferometer was designed. Spectral and interferometric simulations reveal that transverse beam size and beam splitter properties significantly affect measurement accuracy. A 6% error due to transverse size was identified, while Kapton beam splitters introduced additional systematic distortions. In contrast, a 6 mm-thick silicon beam splitter enabled accurate, correction-free measurements. The finite size of the radiator was also found to suppress low-frequency components, resulting in up to 10.6% underestimation of bunch length. This work provides a practical and comprehensive diagnostic framework that accounts for multiple error sources in both transverse emittance and bunch length measurements. These findings contribute valuable insight for the beam diagnostics community and support improved control of beam quality in MIR FEL systems. Full article

Understanding the coupled evolution mechanisms of stress, fracture, and seepage fields in overburden strata is critical for preventing water inrush disasters during fully mechanized mining in deep coal seams, particularly under complex hydrogeological conditions. To address this challenge, this study integrates laboratory experiments with FLAC3D numerical simulations to systematically investigate the multi-field coupling behavior in the Luotuoshan coal mine. Three types of coal rock samples—raw coal/rock (bending subsidence zone), fractured coal/rock (fracture zone), and broken rock (caved zone)—were subjected to triaxial permeability tests under varying stress conditions. The experimental results quantitatively revealed distinct permeability evolution patterns: the fractured samples exhibited a 23–48 × higher initial permeability (28.03 mD for coal, 13.54 mD for rock) than the intact samples (0.50 mD for coal, 0.21 mD for rock), while the broken rock showed exponential permeability decay (120.32 mD to 23.72 mD) under compaction. A dynamic permeability updating algorithm was developed using FISH scripting language, embedding stress-dependent permeability models (R² > 0.99) into FLAC3D to enable real-time coupling of stress–fracture–seepage fields during face advancement simulations. The key findings demonstrate four distinct evolutionary stages of pore water pressure: (1) static equilibrium (0–100 m advance), (2) fracture expansion (120–200 m, 484% permeability surge), (3) seepage channel formation (200–300 m, 81.67 mD peak permeability), and (4) high-risk water inrush (300–400 m, 23.72 mD stabilized permeability). The simulated fracture zone height reached 55 m, directly connecting with the overlying sandstone aquifer (9 m thick, 1 MPa pressure), validating field-observed water inrush thresholds. This methodology provides a quantitative framework for predicting water-conducting fracture zone development and optimizing real-time water hazard prevention strategies in similar deep mining conditions. Full article

China holds substantial coalbed methane resources, yet low single-well productivity persists. While horizontal well cavity completion offers a permeability-enhancing solution through stress release, its effectiveness remains limited by the incomplete knowledge of stress redistribution and permeability evolution during stress release. To bridge this gap, a fully coupled hydromechanical 3D discrete element model (FLC3D) was developed to investigate stress redistribution and permeability evolution in deep coalbed methane reservoirs under varying cavity spacings and fluid pressures, and a novel sequential cavity completion technique integrated with hydraulic fracturing was proposed to amplify stress release zones and mitigate stress concentration effects. Key findings reveal that cavity-induced stress release zones predominantly develop proximal to the working face, exhibiting radial attenuation with increasing distance. Vertical stress concentrations at cavity termini reach peak intensities of 2.54 times initial stress levels, forming localized permeability barriers with 50–70% reduction. Stress release zones demonstrate permeability enhancement directly proportional to stress reduction magnitude, achieving a maximum permeability of 5.8 mD (483% increase from baseline). Prolonged drainage operations reduce stress release zone volumes by 17% while expanding stress concentration zones by 31%. The developed sequential cavity hydraulic fracturing technology demonstrates, through simulation, that strategically induced hydraulic fractures elevate fluid pressures in stress-concentrated regions, effectively neutralizing compressive stresses and restoring reservoir permeability. These findings provide actionable insights for optimizing stress release stimulation strategies in deep coalbed methane reservoirs, offering a viable pathway toward sustainable and efficient resource development. Full article

Current weakly supervised salient object detection (SOD) methods for RGB-D images mostly rely on image-level labels and sparse annotations, which makes it difficult to completely contour object boundaries in complex scenes, especially when detecting objects with filamentary structures. To address the aforementioned issues, we propose a novel cross-modal weakly supervised SOD framework. The framework can adequately exploit the advantages of cross-modal weak labels to generate high-quality pseudo-labels, and it can fully couple the multi-scale features of RGB and depth images for precise saliency prediction. The framework mainly consists of a cross-modal pseudo-label generation network (CPGN) and an asymmetric salient-region prediction network (ASPN). Among them, the CPGN is proposed to sufficiently leverage the precise pixel-level guidance provided by point labels and the enhanced semantic supervision provided by text labels to generate high-quality pseudo-labels, which are used to supervise the subsequent training of the ASPN. To better capture the contextual information and geometric features from RGB and depth images, the ASPN, an asymmetrically progressive network, is proposed to gradually extract multi-scale features from RGB and depth images by using the Swin-Transformer and CNN encoders, respectively. This significantly enhances the model’s ability to perceive detailed structures. Additionally, an edge constraint module (ECM) is designed to sharpen the edges of the predicted salient regions. The experimental results demonstrate that the method shows better performance in depicting salient objects, especially the filamentary structures, than other weakly supervised SOD methods. Full article

The aviation industry currently faces several challenges in inspecting and diagnosing aircraft structures. Current aircraft inspection methods still need to be fully automated, making early detection and precise sizing of defects difficult. Researchers have expressed concerns about current aircraft inspections, citing safety, maintenance costs, and reliability issues. The next generation of aircraft inspection leverages semi-autonomous and fully autonomous systems integrating robotic technologies with advanced Non-Destructive Testing (NDT) methods. Active Thermography (AT) is an example of an NDT method widely used for non-invasive aircraft inspection to detect surface and near-surface defects, such as delamination, debonding, corrosion, impact damage, and cracks. It is suitable for both metallic and non-metallic materials and does not require a coupling agent or direct contact with the test piece, minimising contamination. Visual inspection using an RGB camera is another well-known non-contact NDT method capable of detecting surface defects. A newer option for NDT in aircraft maintenance is 3D scanning, which uses laser or LiDAR (Light Detection and Ranging) technologies. This method offers several advantages, including non-contact operation, high accuracy, and rapid data collection. It is effective across various materials and shapes, enabling the creation of detailed 3D models. An alternative approach to laser and LiDAR technologies is photogrammetry. Photogrammetry is cost-effective in comparison with laser and LiDAR technologies. It can acquire high-resolution texture and colour information, which is especially important in the field of maintenance inspection. In this proposed approach, an automated vision-based damage evaluation system will be developed capable of detecting and characterising defects in metallic and composite aircraft specimens by analysing 3D data acquired using an RGB camera and a IRT camera through photogrammetry. Such a combined approach is expected to improve defect detection accuracy, reduce aircraft downtime and operational costs, improve reliability and safety and minimise human error. Full article