Search Results (7,437)

Time-Sensitive Networking (TSN) with Cyclic Queuing and Forwarding (CQF) is a critical mechanism for ensuring deterministic forwarding. However, existing incremental schedulers typically rely on single-dimensional heuristics, which fail to address the coupled impact of traffic characteristics and spatiotemporal resource distribution. This limitation leads to suboptimal scheduling success, especially under complex topologies and high network loads. To address this, we propose TMCOA–MFS, a joint incremental scheduling framework that integrates the Triple-Mode Cooperative Optimization Algorithm (TMCOA) with a Multi-Feature Scheduling (MFS) strategy. The logic of our approach is twofold: First, to balance spatial resource distribution, we introduce the TMCOA—inspired by table-tennis offensive–defensive behaviors—to optimize path selection by minimizing port-load variance and escaping local optima through a three-mode population partition. Second, building upon the optimized spatial paths, the MFS strategy is employed to resolve temporal scheduling conflicts. By computing a composite priority score that accounts for path hops, offset configuration difficulty, and flow size, MFS enables a robust incremental offset search with integrated feasibility checking. Extensive simulations on benchmark functions and diverse TSN scenarios demonstrate that the TMCOA offers superior convergence and stability. More importantly, the integrated TMCOA–MFS framework significantly enhances scheduling success rates and load balancing, effectively overcoming the bottlenecks of high-load and topologically complex environments. Full article

Cracking in reinforced concrete beam bridges severely compromises their durability and structural integrity. Although external prestressed CFRP plate reinforcement technology has emerged as an effective repair solution, current design codes primarily rely on idealized crack-free or simplified single-crack assumptions, leading to inadequate precision in prestressing application for real-world structures with complex crack networks. This study investigated the reinforcement effectiveness of externally prestressed CFRP plates on three pre-cracked reinforced concrete T-beams with varying reinforcement ratios (1.20%, 2.41%, and 3.61%). A comprehensive experimental program was conducted to monitor crack closure behavior, strain distributions, and deflection changes during tensioning and loading phases. A three-dimensional finite element model was developed using Midas FEA NX 2022, and theoretical formulas for crack closure prestressing were derived under the plane-section assumption, supplemented by engineering correction factors. Results demonstrated that calculation errors for both crack closure prestressing and secondary cracking loads were below 5%, while correlation coefficients between finite element simulations and experimental data ranged from 0.93 to 0.99. External prestressing significantly enhanced the stiffness of cracked beams, with stiffness recovery rates reaching up to 156.2%, and exhibited excellent synergistic performance among CFRP plates, steel reinforcement, and concrete. These findings provide a theoretical foundation and technical support for the precision design of external prestressing reinforcement in cracked reinforced concrete beams. Full article

Understanding grout diffusion behavior in rough-walled rock fractures is essential for optimizing grouting design in mining and geotechnical engineering. This study couples fractal surface reconstruction with three-dimensional volume-of-fluid (VOF) simulation to systematically investigate grout diffusion in fractures characterized by the Weierstrass–Mandelbrot fractal function. Twelve simulation cases, comprising four JRC profiles and three grout viscosities, are analyzed to elucidate the spatiotemporal evolution of grout filling. The results reveal a consistent three-stage diffusion pattern—initial filling, rapid diffusion, and stable equilibrium—across all conditions. Fracture fractal dimension emerges as the dominant factor controlling seepage velocity and diffusion zoning, while grout viscosity plays a secondary, roughness-modulated regulatory role. The equivalent hydraulic aperture is identified as the core parameter governing zone proportions. Engineering guidelines for viscosity selection and injection strategy under different roughness conditions are proposed. Full article

Three-dimensional (3D)-printed dentures are often fabricated from a single tooth-colored resin and externally characterized using stains and glaze coatings to enhance gingival esthetics and surface properties. However, routine toothbrushing may degrade these coatings, potentially affecting surface gloss and roughness. This study evaluated the effects of stain timing and glaze application on the gloss and surface roughness of a 3D-printed denture resin following simulated toothbrushing. Eighty disc-shaped specimens (12 mm × 3 mm) were fabricated and assigned to two staining systems (OPTIGLAZE Color and Palette 2.0), with subgroups based on stain timing (before or after post-curing) and glaze application (with or without glaze) (n = 10). Specimens underwent 20,000 cycles of simulated toothbrushing, and gloss and surface roughness were measured before and after brushing. Data were analyzed using two-way ANOVA (α = 0.05). Glaze application significantly improved gloss retention for both staining systems (p < 0.001), while stain timing had no independent effect. Glaze application with Palette 2.0 demonstrated improved gloss retention when post-cured in a post-curing unit. Toothbrushing increased surface roughness in all groups, with no significant effects of stain timing or glaze. Within the limitations of this study, glaze improves gloss stability, whereas stain timing has minimal influence and does not affect surface roughness. Full article

Background: In tennis, the volley is an important shot; however, studies describing its movement characteristics have been limited to the forehand volley (FV). In this study, we analyzed the characteristics of upper-limb movement during FV and backhand volley (BV) in skilled and less-skilled tennis players. Methods: Twelve tennis players with experience (skilled group) and eight with little experience (less-skilled group) were included. The participants stood in front of a simulated net and volleyed balls were fed toward the target. Movements were recorded using three video cameras, and three-dimensional coordinates were obtained using the direct linear transformation method. The measured variables were bilateral shoulder rotation angle, pelvic rotation angle, shoulder–pelvis twist angle, and the racket–forearm angle. A two-way analysis of variance (ANOVA) was conducted with player level (skilled vs. less skilled) and time point (backswing event vs. impact event) as factors. Results: In the FV, a significant main effect of time point was observed for the bilateral shoulder rotation angle (F1,18 = 7.471, p = 0.014, η² = 0.293). In the BV, significant main effects at both player level and time point were observed for the pelvic rotation (player level; F_1,18 = 8.759, p = 0.008, η² = 0.327, time point; F_1,18 = 13.351, p = 0.002, η² = 0.426). Also, significant main effects at both player level and time point were observed for racket–forearm angles (player level; F_1,18 = 6.752, p = 0.018, η² = 0.273, time point; F_1,18 = 10.213, p = 0.005, η² = 0.362). However, a significant main effect of the player level was observed for the shoulder–pelvis twist angle (F_1,18 = 12.124, p = 0.003, η² = 0.402). Conclusions: In contrast to FV, BV prioritizes ball control by maintaining the shoulder–pelvis angular relationship without releasing the twist. These results suggest that skill-related differences in volleying are more pronounced in the BV than in the FV. Full article

A novel robot behavior generation method combining imitation learning with diffusion models elegantly addresses multi-modal action distributions, adapts to high-dimensional action spaces, and demonstrates impressive training stability. It significantly improves success rates across nine diverse tasks on three different robot simulation benchmarks, but comes with longer training times and slower inference speed. This paper proposes a novel architecture, DiT1dLnet, applied to DDPM for training and inference. DiT1dLnet improves accuracy across various robotic simulation tasks while accelerating training and inference speed by 50–100%. We benchmarked its performance on nine different tasks using three distinct robots. Full article

This study presents an AI-assisted thermodynamic and computational fluid dynamics (CFD) evaluation of a β-type Stirling engine to improve its thermal efficiency and indicated power output. The engine performance was investigated using Restricted Dimensions Thermodynamics (RDT), the Schmidt thermodynamic model, and three-dimensional CFD simulations under various operating and geometric conditions. Key parameters including rotational speed, phase angle, piston diameter, displacer stroke, porosity, and charged pressure were systematically analyzed to determine their influence on engine behavior. A feed-forward artificial neural network (ANN) trained using the Levenberg–Marquardt optimization algorithm was integrated with CFD-generated datasets to predict engine performance and accelerate the optimization process. The AI-assisted optimization was coupled with the Variable Step-size Simplified Conjugate Gradient Method (VSCGM) to identify near-optimal operating conditions while reducing computational cost. Simulation results demonstrated that the optimization process improved the indicated power from 180.33 W to 185.44 W and increased thermal efficiency from 10.32% to 11.54%. The results also showed close agreement between predicted and experimental pressure–temperature profiles, confirming the reliability of the proposed methodology. Furthermore, CFD analyses revealed that increasing piston diameter and optimizing porosity enhanced heat transfer and pressure distribution within the engine chambers, resulting in improved thermodynamic performance. The proposed AI-driven framework provides a reliable and computationally efficient approach for the design and optimization of advanced β-type Stirling engines operating under realistic thermal conditions. Full article

Quantitative characterization of permeability in porous media represents a central problem in filtration theory, geosciences, and materials engineering. Standard numerical approaches, including finite element methods and Lattice Boltzmann simulations, typically require extensive domain-specific expertise together with specialized computational software. This motivates the development of computationally simpler and more accessible geometric approaches applicable directly to binary volumetric data. We introduce a novel algorithmic framework for the analysis of porous structures that reformulates permeability-related characterization in terms of discrete geometry and graph-based computation. The method combines parallel raster-grid and graph representations of a binarized three-dimensional CT image. The principal transport-limiting feature of the pore network, interpreted as the minimal constriction governing connectivity, is identified through iterative morphological dilation coupled with a three-dimensional scanline seed-fill procedure. In addition, a dichotomous bisection strategy is proposed to accelerate the determination of the critical bottleneck scale. The proposed methodology was evaluated on five volumetric datasets of size 100 × 100 × 100 voxels obtained from CT-derived porous structures. Experimental results demonstrate that dilation- and erosion-based formulations yield equivalent estimates of the bottleneck parameter in four of the five investigated samples. Furthermore, incorporation of the bisection optimization reduces computational time in three-dimensional experiments by approximately 50% relative to sequential iteration. The presented approach provides a computationally efficient and fully open-source alternative to conventional physics-based permeability solvers for binary porous media. The resulting bottleneck parameter b should be interpreted as a discrete geometric invariant characterizing the pore-network connectivity and minimal transport cross-section. It is not intended to replace the absolute permeability coefficient K appearing in Darcy’s law, but rather to serve as an independent structural descriptor suitable for comparative and topological analysis of porous systems. Full article

Surface orientation can influence the aerodynamic response of modern soccer balls, particularly in the drag crisis regime. This study quantified the orientation-dependent aerodynamic characteristics of the FIFA World Cup match ball Trionda using a single specimen and examined how these differences affect simulated flight at sea level and 1500 m altitude. Two reproducible reference orientations were defined: a red-panel-centered orientation (Series A) and a seam-junction-centered orientation (Series B). Each reference orientation was rotated by 0°, 90°, and 180°, resulting in six fixed-orientation conditions. Wind tunnel measurements were repeated three times per condition to obtain drag, lift, and side-force coefficients, and two-dimensional non-spinning flight simulations were performed for representative long-kick and free-kick conditions. All six orientations exhibited drag crisis behavior, but the transition response magnitude, subcritical drag level, and supercritical drag state differed among conditions. The representative transition region occurred at approximately Re = 2.0 × 10⁵ to 2.5 × 10⁵. Among the tested conditions, B-90 showed the lowest full-range mean drag coefficient (0.231), whereas A-90 showed the highest (0.266). In the simulations, lower drag orientations consistently produced longer flight ranges, and the B-90 > A-90 ordering was preserved across representative launch conditions and the expanded parametric comparison. These findings indicate that the aerodynamic response of Trionda cannot be represented adequately by a single mean drag coefficient and that surface orientation should be considered in aerodynamic characterization and flight prediction. Full article

Accurately estimating leaf area index (LAI) is vital for evaluating crop growth and predicting yields. Conventional approaches, however, often struggle due to the limited representativeness of available data and the complex structure of plant canopies, which reduce their reliability across diverse canopy architectures and observation conditions. To overcome these challenges, this work introduces an LAI retrieval framework that combines a three-dimensional radiative transfer model (3D RTM) with deep learning techniques. Representative 3D maize canopy scenarios were generated using the LESS model, producing synthetic LiDAR point clouds constrained by realistic structural parameters. A deep learning model based on PointNet++ was trained, and transfer learning (TL) was employed to facilitate knowledge transfer from simulated to actual measured data. The TL-enhanced model demonstrated significant improvement, with R² rising from 0.537 to 0.842 and RMSE dropping from 0.541 to 0.288 m²·m⁻². Moreover, retrieval performance was notably affected by scanning mode, angle, and stem diameter, achieving optimal results under TLS acquisition, moderate scanning angles, and intermediate stem widths. These findings suggest that integrating 3D RTM-generated synthetic point clouds with transfer learning is an effective strategy for enhancing the robustness and generalization of LiDAR-based LAI retrieval. Full article

Iron-based shape memory alloy (Fe–SMA) rebars can generate internal prestress in cement-based members after restrained thermal activation; however, the temperature actually reached by embedded rebars in cracked UHPFRC is difficult to infer from exposed bar segments. This study investigates electrical resistance activation of 4% prestrained Fe–SMA rebars embedded in pre-cracked UHPFRC beams and clarifies the activation-control problem by combining thermocouple measurements with a calibrated two-dimensional electro-thermal simulator. Twelve beams (150 × 150 × 600 mm) containing either Dramix 3D or Dramix 4D hooked steel fibers were first loaded in three-point bending to a mid-span displacement of 4 mm. The 4D series reached a 9.47% higher average pre-cracking load, confirming that fiber geometry modified the cracked state before heating. During activation, the exposed rebar segment reached 200 °C after approximately 77 s, whereas the embedded working segment reached the same target only after approximately 213 s; at that moment, the exposed segment was already close to 350 °C. The calibrated simulator reproduced the target activation time with an error of approximately 3 s and visualized the localized heat transfer from Fe–SMA to UHPFRC. The results demonstrate that activation control based only on exposed-bar temperature may cause under-activation of the embedded reinforcement, and that direct internal temperature monitoring is required for reliable Fe–SMA activation in cracked UHPFRC members. Full article

To investigate the resin infusion molding process for novel dry fiber-reinforced epoxy composite wing skin, dry fiber preforms were fabricated via an automated fiber placement (AFP) system, and the out-of-plane permeability of the preforms at different lay-up speeds was measured using the ultrasonic transmission method to determine the optimal lay-up parameters. A scaled-down composite wing skin structure was modeled and meshed via numerical simulation, and different resin infusion schemes were simulated and analyzed using PAM-RTM software. The optimal infusion scheme was determined by comparing the infusion time, infusion pressure and defect formation during resin flow for different schemes, and the wing skin component was fabricated through the vacuum-assisted resin infusion (VARI) process. Results indicate that the infusion time predicted by PAM-RTM simulation is 3883 s, while the actual measured value in the VARI process is 3611 s with an error of approximately 7% within a reasonable range. Both simulation and actual wing skin fabrication exhibited no significant defects, validating the accuracy of the three-dimensional permeability measurement of dry fiber preforms as well as the reliability of the simulation results. Full article

Fluid flow in fractured-vuggy carbonate reservoirs is characterized by extreme multiscale heterogeneity, where the coexistence of tight matrix rock and macroscopic cave challenges traditional Darcy-based continuum models. This paper presents a semi-analytical solution for two-phase immiscible displacement in a one-dimensional composite porous–cavernous–porous (PCP) system. The main feature of the model is that the cave region is treated separately from the porous domains: classical Darcy flow is used in the surrounding matrix, whereas an idealized free-flow representation is introduced for open caves based on a simplified one-dimensional treatment of the cave momentum balance. To elucidate the impact of distinct flow regimes on displacement dynamics, three physical models are compared for the cave region: (1) an open-cave model represented by a simplified free-flow formulation; (2) a filled-cave non-Darcy model governed by the Forchheimer equation using the Ergun correlation; and (3) a creeping-flow model governed by Darcy’s law. A piecewise semi-analytical solution procedure is established to enforce flux continuity, characterize interfacial state remapping, and determine the downstream front under global water-balance closure. The results show that both cave geometry and internal cave-flow mechanism critically control water-front advancement. While the open-cave model exhibits piston-like displacement behavior with high local displacement efficiency but stronger preferential flow, the Forchheimer model shows that inertial resistance can modify the saturation profile and delay breakthrough relative to the Darcy prediction. The proposed framework provides an idealized theoretical reference for benchmarking numerical simulators and for interpreting waterflooding behavior in complex vuggy reservoirs under one-dimensional, incompressible, gravity-free, and capillarity-free conditions. Full article

Full-waveform hyperspectral LiDAR offers a new approach for precise forest ecological monitoring by simultaneously acquiring the three-dimensional structure and continuous spectral information of targets. However, uncertainty in the backscattering cross-section and the inseparability of the reflectance coefficient lead to systematic underestimation of multi-echo reflectance retrieved using traditional methods. This limitation significantly hinders quantitative applications. The existing multi-echo reflectance correction using neighborhood single-echo reflectance (MCNS) method provides an effective solution by establishing proportional models between similar targets, laying an important foundation for the extraction of multi-echo reflectance. However, its applicability in complex forest scenes is limited due to its dependence on specific vegetation single-echo samples. To address this, an iterative correction method based on ground reflectance baseline, namely Bare-Ground-Echo-Based Iterative Correction of Multi-Echo Reflectance for Hyperspectral LiDAR (BGE-ICMER), is proposed. Using ground single-echo reflectance as a stable baseline, a multi-target energy distribution model is constructed based on energy conservation, and backscattering cross-section proportions for each echo are iteratively solved to recover true reflectance. Validation using a high-fidelity dataset generated by the Large-Scale remote sensing data and image Simulation framework (LESS) confirmed the effectiveness of the proposed method. This dataset encompasses three typical tree species with vegetation layers ranging from two to four, incorporates micro-topographic ground surfaces and ten spectral channels from 500 to 1000 nm, thereby capturing the structural and spectral complexity of real forests. The results showed that coefficients of determination (R²) between the corrected and true reflectance exceeded 0.9560, with an RMSE below 0.0418 and MAE below 0.0360. The average relative error was reduced from 26.66% to 10.07%, representing a 62.22% improvement in accuracy. Even in the most challenging scenarios with four-layer vegetation occlusion within this dataset, no significant error accumulation occurred. These results demonstrate the robustness and effectiveness of the proposed method for multi-echo reflectance extraction. This study lays a foundation for more accurate forest biochemical attribute assessment and enables the vertical characterization of multiple targets using high-resolution spectral reflectance. Full article

To mitigate safety risks such as tunnel collapse and water inrush induced by fault fracture zones during urban shield tunneling, this study investigates the application mechanisms and identification characteristics of the surface transient electromagnetic (TEM) method for ahead-of-face geological prediction, using a shallow metro tunnel (30–50 m burial depth) in Qingdao as a case study. Departing from conventional empirical threshold approaches, a three-dimensional geological model incorporating a fault fracture zone is constructed. Guided by electromagnetic diffusion theory, the transient field response evolution is numerically simulated to obtain time-domain electromagnetic decay curves at various observation points. By integrating these simulations with field measurements, quantitative criteria for fault identification are extracted. The results demonstrate that the electric field response attenuation rate at measurement points directly overlying the fault fracture zone is significantly faster than that in the intact host rock. This accelerated decay behavior is jointly governed by the fault scale, degree of water saturation in the fracture zone, and source–receiver offset, serving as a primary indicator for fault identification. In the apparent resistivity profiles, the fault-intersecting zones exhibit distinct abrupt transitions between low and high resistivity. The water-saturated fracture zone manifests as a well-defined low-resistivity anomaly, generating a pronounced electrical contrast with the high-resistivity host rock. Field validation confirms that the identified low-resistivity anomaly aligns closely with the actual location of the water-bearing fault, which was subsequently verified during tunnel excavation. This study elucidates the physical mechanism of electromagnetic diffusion distortion induced by faults under shallow urban conditions. The proposed integrated criterion, combining the response attenuation rate with abrupt apparent resistivity boundaries, effectively mitigates the non-uniqueness inherent in single-parameter geophysical interpretations. These findings provide theoretical support and a reproducible engineering criterion for ahead-of-face fault prediction in metro tunnels. Future research should further incorporate the effects of geological anisotropy and dynamic groundwater seepage on the electromagnetic diffusion process. Full article