Search Results (2,413)

This paper presents a hybrid 1D–3D computational framework for the dynamic analysis of lattice metamaterials for impact protection. Periodic and stochastic lattices are generated automatically; slender members are modeled with beams, and selected regions are locally enriched with 3D solids, with an interface strategy ensuring kinematic compatibility. A PA12 octagonal lattice (30 × 30 × 25 mm) is compressed in Abaqus/Explicit at a high strain rate. Two hybrid configurations, differing by the placement of a 3D unit cell, are compared to a beam-only reference. Global responses (modulus, densification strain, absorbed energy) are consistent across models, while the hybrid scheme recovers local stress concentrations and failure. Full article

Multi-task learning (MTL) is essential for satellite internet systems requiring simultaneous optimization of beam management, interference mitigation, resource allocation, and traffic prediction. However, existing evaluation methods rely predominantly on external performance metrics, neglecting internal dynamics governing task interactions. We propose TDS-Mamba (Task-Aware Decoupled State-Space Model), integrating selective state-space models with task-specific modulation for satellite networks. Our contributions include: (1) Task-Aware Decoupled S6 (TA-DS6) with hypernetwork-generated task-conditioned projection matrices; (2) Shared–Private State Decomposition disentangling cross-task representations from task-specific features; (3) Value-at-Risk (VaR) Gating for risk-sensitive optimization under varying orbital conditions; and (4) an internal diagnostic framework with Task-Specific Entropy and Interference Coefficient metrics. Experiments on LEO satellite constellation benchmarks show consistent improvements over the selected baselines and provide enhanced interpretability of multi-task dynamics via internal diagnostics. Full article

This study presents an analytical investigation of the dynamic behavior of concrete beams reinforced with different types of nano-clay (NC) particles and resting on a Winkler–Pasternak elastic foundation. The equivalent elastic properties of the nanocomposite were determined using an Eshelby-based homogenization model. An improved quasi-three-dimensional beam theory was applied to formulate the governing equations of motion, which were subsequently then analytically solved using Navier’s method. The analysis shows that NC reinforcement systematically elevates the natural frequencies of the beam, with the magnitude of improvement varying by particle type and concentration. Increasing the NC volume fraction to 30% leads to a significant rise in the fundamental frequency, reaching about 30% for hectorite (SHca-1) compared with the unreinforced beam, whereas montmorillonite (SWy-1) produces a more moderate increase of approximately 13%. This reinforcing effect remains consistent across different span-to-depth ratios, indicating that the influence of nano-clay content on the dynamic response is largely independent of beam slenderness. Furthermore, increasing the Winkler foundation stiffness results in an almost linear rise in frequency of approximately 18–22%, whereas the Pasternak shear parameter produces a stronger effect, reaching around 25% enhancement depending on the reinforcement type. These results indicate that incorporating nano-clay platelets can be an effective strategy for enhancing the vibrational stiffness of concrete beams and improving their dynamic performance when interacting with supporting soil media. Full article

To address the suboptimal radiometric calibration accuracy observed in specific beam codes of the GaoFen-3 (GF-3) series satellite for sea surface wind speed (SSWS) retrieval, this study introduces a calibration constant correction method based on the geophysical model function (GMF). This approach enables high-precision SSWS retrieval from GF-3B data. Conventional SAR-based SSWS retrieval models typically rely on pointwise mapping relationships, which overlook the spatial characteristics inherent in dynamic sea surface wind fields. To overcome this limitation, this study proposes an attention-guided dual-branch feature-fusion network (ADBFF-NET). The first branch, implemented as a backpropagation neural network (BPNN), learns nonlinear mappings between the normalized radar cross-section (NRCS, σ⁰), incidence angle, azimuth look direction, and wind vectors (speed and direction). The second branch, designed as a residual convolutional neural network, extracts spatial features of wind fields. An attention mechanism fuses the outputs of both branches, thereby enhancing retrieval accuracy. Experiments conducted with GF-3 series satellite data were validated against the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis V5 (ERA5), Advanced Scatterometer (ASCAT) wind fields, and altimeter-derived wind speeds. The results indicate that the SSWS retrieved from GF-3B SAR data using the corrected calibration constants achieve a root mean square error (RMSE) of 1 m/s against ERA5 wind speeds, representing an approximately 40% reduction compared with the RMSE obtained using the original calibration constant. Furthermore, compared to ERA5 and ASCAT data, the RMSE of the wind speeds retrieved by the ADBFF-NET model reaches 1.17 m/s and 1.03 m/s, respectively. Full article

In this study, a three-dimensional simulation of a walking-beam reheating furnace was developed to improve the steel slab reheating process and reduce surface oxidation kinetics using computational fluid dynamics (CFD). Combustion, heat transfer, fluid dynamics, and chemical reaction models were integrated into the numerical framework of this study. In addition, dynamic mesh remeshing was coupled through user-defined functions (UDFs), enabling the simultaneous simulation of slab movement and evolution of the involved transport phenomena. Turbulence was modeled with the realizable k-ε formulation, combustion with the Eddy Dissipation model, and radiation with the P-1 model coupled with WSGGM to include CO₂ and H₂O gas radiation. Scale formation was modeled using customized functions based on Arrhenius-type kinetics and Wagner’s oxidation model, evaluating its growth as a function of time, temperature, and furnace atmosphere. The predicted thermal evolution inside the furnace was validated using industrial data, yielding an average deviation of 5%. Furthermore, the proposed operating conditions led to an average slab temperature of 1289.77 °C at the exit of the homogenization zone, which was 16 °C higher than that under the current operation but still within the target range (1250 ± 50 °C). The reduction in combustion air decreased energy losses and improved product quality, lowering the molar oxygen content in the furnace atmosphere from 4.9 × 10² mol to 6.7 × 10¹ mol. Additionally, annual savings of 4,793,472 kg of natural gas and 13,884 tons of steel were estimated owing to reduced oxidation losses. The proposed air–fuel adjustment led to estimated annual energy savings (equivalent to 4,793,472 kg of natural gas) and a reduction in material loss due to oxidation from 4.5% to 3.75% (an absolute reduction of 0.75 percentage points; relative reduction ≈ 16.7%), which has a significant industrial impact on metal conservation and descaling cost reduction. Although there are CFD studies on plate overheating and scale growth separately, this work presents three main contributions: (1) the integration, within a single numerical framework, of combustion, radiation, species transport, oxidation kinetics, and actual plate movement using a dynamic mesh; (2) validation against continuous industrial records (16 thermocouples) and quantification of operational benefits such as fuel savings and reduced material loss; and (3) a comparative analysis between actual and optimized conditions, which standardize the air–methane ratio. Full article

More and more urban underpass tunnels are being constructed to alleviate traffic congestion; however, for this type of underground structure, the soil–structure interaction mechanisms under earthquake loading remain unclear, and dedicated advice and guidance for their seismic design are still lacking. This paper endeavors to investigate the dynamic interaction mechanisms of an underpass tunnel and surrounding soft ground using the finite element (FE) method. Firstly, the accuracy of the FE model in reproducing seismic responses of the layered half-space is validated by comparison with results of equivalent linear one-dimensional site response. Then, the dynamic response characteristics of 3D boat-shaped excavation are analyzed to determine the influence of potential local site amplification on the underpass tunnel. Finally, seismic behaviors of open and buried sections of the underpass tunnel are investigated in detail. The results show that under high-intensity rare earthquakes, severe damage occurs at the ceiling slab near the longitudinal beam and at the base of the side wall of the tunnel’s buried section; seismic underpass–site interactions might be influenced the most by the local topography effect of the 3D boat-shaped excavation, as well as a sudden stiffness change between the open and buried sections. Full article

Focusing on the problems of difficult alignment and low efficiency when coupling the spatially scattered light from 532 nm underwater LiDAR to a single-mode fiber, this paper presents an analysis and simulation of the coupling principle of spatially scattered light and its influencing factors based on the extended light source imaging model, and designs and develops a spatially scattered light adaptive coupling system. The system adopts a three-lens set to receive spatially scattered light, combines a fast steering mirror and displacement stage to adjust the beam position dynamically, and realizes the automatic and efficient coupling of spatially scattered light through a joint control strategy combining rough alignment and precise alignment (using the improved simulated annealing SPGD algorithm). The experimental results show that the best coupling efficiency reaches 88.18% of the theoretical value after program adjustment. This represents an approximate 88% improvement over the best coupling efficiency obtained after manual adjustment, whilst the algorithm effectively circumvents the issue of local optima. This study provides a feasible adaptive solution for underwater LiDAR and similar applications involving scattered light coupling. Full article

With the development of a photoelectric system in the aviation field, the requirements for airborne equipment have increased accordingly. The photoelectric aiming and tracking turntable as a crucial component in the photoelectric system has stringent requirements on weight and volume. A new type of structure with the coaxial dual-axis turntable has been researched, it adopts a structural form with two rotating axes connected in series and rotating Risley gratings by two independent mechanical shaft axes to complete pointing, capturing and tracking functions. This type of structure features compactness, small moments of inertia and fast response speed; this miniaturized aiming and tracking system with Risley grating is more suitable for airborne equipment. The Risley grating aiming and tracking system adjusts the optical axis angle using two rotating Risley gratings; it realizes beam pointing within a conical range through polarization diffraction. The aiming and tracking system based on Risley grating has small moving parts so it is lighter; it has more advantages than the traditional turntable. Although the tracking range is relatively limited, it still offers significant lightweight effects for certain special applications and can effectively reduce weight and volume. In this paper, we research the system of aiming and tracking with Risley gratings, the influence of mechanical turntable parameters on the system’s tracking accuracy is analyzed based on its working principle; error analysis and allocation of turntable errors are carried out. Subsequently, the decoupling model of the system is analyzed and system errors are compensated; the miniaturized tracking and calibration system based on Risley gratings is developed. Then, the photoelectric testing method based on dual reference mirrors proposed by us is used to test the coaxiality and axis jitter accuracy of the turntable. The system has an effective aperture > Φ120 mm, weight < 10 kg and volume < Φ190 × 155 mm. Pointing accuracy and dynamic tracking test show that the system’s pointing accuracy is ≯10″ and tracking accuracy is ≯380 μrad. Finally, a field tracking test is carried out and verify the system’s capability and performance. Full article

In this work, an accelerated non-uniform corrosion method controlled by time and current was employed to fabricate power-on accelerated corrosion specimens of hybrid steel fiber-reinforced concrete (HSFRC) gradient beams. Experimental research was conducted to investigate their impact resistance, revealing the dynamic response patterns of these gradient beams with varying steel fiber contents. By analyzing the evolutionary characteristics of impact load, displacement, energy dissipation, equivalent impact bearing capacity, and dynamic amplification factor, the influence of steel fibers with different sizes and contents on the bearing capacity degradation and mechanical properties of HSFRC gradient beams under the same corrosion conditions was clarified. The synergistic enhancement mechanism of multi-scale steel fibers in the beams was elucidated, highlighting the complementary effects of long fibers and short fibers at different stages of material damage. Results show that the incorporation of steel fibers can effectively improve the impact resistance of reinforced concrete gradient beams, with a maximum improvement of approximately 2.5 times. Compared with gradient beams reinforced with single long fibers, the peak impact force of HSFRC gradient beams increases by about 16%, and different steel fiber ratio plays a significant role in regulating impact resistance. Within the corrosion range of 3% to 5%, the equivalent impact bearing capacity of gradient beams is negatively correlated with the reinforcement corrosion rate. Full article

Neighbor discovery in underwater acoustic networks (UANs) faces challenges such as high propagation delay and limited spectrum resources. This study proposes a dynamic beam control-based multi-parallel transceiver neighbor discovery protocol (DBCB), which improves node discovery efficiency by dynamically matching transmission beams and optimizing spatiotemporal frequency resource allocation. During node initialization, the master node broadcasts omnidirectionally to quickly capture coarse-grained neighbor parameters. After obtaining these parameters, the master node dynamically allocates orthogonal frequency bands for directional multi-beam validation and optimizes beam alignment, resource allocation, and topology stability through real-time feedback. The protocol adaptively optimizes transmission power and continues the discovery task, while nodes that remain undiscovered for extended periods automatically adjust their receiving gain. The adaptive power control mechanism adjusts the transmission power based on node distance and azimuth, enabling the protocol to maintain low power consumption and enhance interference resilience. Simulation results show that the DBCB protocol outperforms similar neighbor discovery protocols based on directional transmission-reception (DTR) and random two-way (RTW) mechanisms, with improvements of 7.84% and 28.17% in average discovery rate, and reductions of 28.13% and 59.06% in average discovery delay, respectively. The anechoic tank experiment demonstrates that multi-beam parallel transmission effectively improves underwater node discovery efficiency, with simulation results aligning with experimental data, confirming the stability and high efficiency of the system. Full article

Microwave wireless power transfer (MWPT) for space solar power stations (SSPS) requires high-precision beam pointing in order to maintain effective aperture coupling and transmission efficiency under platform motion and disturbances. This paper proposes a dual-link beam pointing estimation framework that integrates guidance-link interferometric angle-of-arrival (AoA) measurements with power-link energy-field reconstruction. The interferometric chain provides high-rate azimuth and elevation observations for dynamic tracking, while the energy-field reconstruction estimates the energy-centroid displacement from the received-aperture power distribution to correct steady-state pointing bias. A Kalman filter (KF) is developed to fuse the asynchronous multi-rate measurements, yielding continuous and robust pointing estimates for closed-loop beam control. Simulation results show that the proposed fusion method achieves azimuth and elevation RMSEs of ${0.0069}^{°}$ and ${0.006}^{°}$ with interferometric and energy-centroid error levels of approximately ${0.05}^{°}$ and ${0.02}^{°}$, respectively, significantly reducing high-frequency fluctuations. In addition, a sensitivity model is established to quantify the impact of angular errors on capture efficiency. The expected efficiency improves from approximately 0.988 and 0.998 for the individual methods to nearly unity for the fusion output. Quantitative accuracy thresholds corresponding to different efficiency requirements are further derived, providing practical guidelines for SSPS MWPT system design. Full article

Foaming technology can effectively reduce the viscosity of polymer-modified asphalt and significantly decrease energy consumption during pavement construction, making it an effective approach for achieving low-carbon pavement construction and maintenance. However, mechanically foamed asphalt relies on specialized equipment and requires strict parameter control. Although water-based foaming methods using zeolites or ethanol can alleviate these issues to some extent, they still present disadvantages such as significant variability in foaming performance and potential risks during transportation and construction. Therefore, this study investigates the feasibility of using crystalline hydrates with high water of crystallization for micro-foamed asphalt. Three types of micro-foamed SBS-modified asphalt (MFPA) were prepared using hydrates with different contents of water of crystallization. Physical property tests, foaming characteristic parameters, viscosity–temperature analysis, Fourier transform infrared spectroscopy (FTIR), adhesion tensile tests, scanning electron microscopy (SEM), and fluorescence microscopy were conducted to evaluate their effects on the physical and chemical properties, viscosity reduction performance, adhesion, and compatibility of SBS-modified asphalt. Furthermore, dynamic shear rheometer (DSR) tests, bending beam rheometer (BBR) tests, fatigue life modeling, and morphological analysis were employed to investigate the rheological properties, fatigue life, and bubble evolution behavior of the MFPA system. The results indicate that utilizing the thermal decomposition characteristics of crystalline hydrates with high water of crystallization (Na₂SO₄·10H₂O, Na₂HPO₄·12H₂O, and Na₂CO₃·10H₂O) to release H₂O and CO₂ in SBS-modified asphalt for micro-foaming is a short-term reversible physical viscosity reduction process. The maximum expansion ratio (ERmax) of MFPA reaches 8–10, the half-life (HL) remains stable at approximately 180 s, and the foaming index (FI) peak is about 1160. The construction temperature can be reduced by 10–15%, and the viscosity reduction effect remains stable within 60 min. Compared with unfoamed SBS-modified asphalt, the compatibility, rutting resistance, and fatigue life of MFPA increase by approximately 65%, 32%, and 30%, respectively, while the low-temperature performance decreases by 18%. Under the same short-term and long-term aging conditions, MFPA exhibits better aging resistance. Specifically, its rutting resistance increases by 37%, and fatigue resistance improves by 30% compared with aged SBS-modified asphalt, while the low-temperature performance remains essentially unchanged. Full article

The integration of mechanics-based analysis and materials design procedures has become central to the development of multi-material structures with tailored mechanical and dynamic performance. In this study, the dynamic and flexural behaviour of multi-material FDM sandwich beams composed of PETG face sheets and an ABS core is experimentally investigated. Seven different infill patterns Grid, Line, Wavy, Honeycomb, Gyroid, Cubic, and Triangle were implemented in the core layer to assess their influence on damping and natural frequency behaviour. Experimental modal analysis was performed using impact testing to identify the first three vibration modes. Natural frequencies were extracted from Frequency Response Functions (FRFs), and modal damping ratios were determined using the half-power bandwidth method. The reliability of the damping results was evaluated through statistical analysis. Additionally, quasi-static three-point bending tests were conducted to assess flexural strength and load-carrying capacity. The results demonstrate that infill topology has a significant impact on both dynamic and mechanical responses. In particular, geometrically complex infill patterns exhibit enhanced stiffness, higher natural frequencies, and improved damping performance. Among the investigated designs, the Triangle infill exhibited the highest natural frequency values across the first three vibration modes (f₁ ≈ 24.910 Hz, f₂ ≈ 162.609 Hz, f ≈ 466.595 Hz), indicating its superior stiffness characteristics. In terms of damping behaviour, the Cubic infill showed the highest loss factor in the first vibration mode (0.0426), while the Line and Gyroid patterns exhibited the highest damping in the second (0.0439) and third modes (0.0354), respectively. Moreover, the force–displacement results revealed that the Triangle infill exhibited the highest load-bearing capacity, further confirming its superior structural stiffness among the investigated designs (SEA = 110.83 J/kg). These findings highlight the potential of multi-material FDM for designing polymer-based sandwich structures with tailored vibration and energy dissipation characteristics. Full article

Present and future rare isotope accelerator facilities provide new opportunities to explore the structure of unstable nuclei. We report the measurements of the elastic scattering angular distributions of ²¹Na and ²²Na on the doubly magic ⁴⁰Ca above the Coulomb barrier energies, using high-purity post-accelerated ISOL beams from Beijing Radioactive Ion Beam Facility (BRIF). Angular distributions were measured with a silicon detector telescope array, and relative cross sections were determined with a CaF₂ target on Au backing. The data were well reproduced by optical model calculations with Woods–Saxon and USNP potentials, the latter giving better agreement. These results confirm the stable operation and performance of the BRIF ISOL production and post-acceleration system, demonstrate its capability to provide radioactive beams of useful intensity and purity for future investigations of reaction dynamics and astrophysically relevant processes involving proton-rich nuclei, and simultaneously extend proton-rich elastic scattering studies to heavier systems. Full article

Real-time path planning for Unmanned Surface Vehicles (USVs) in complex marine environments remains challenging due to unstructured environments, ocean current disturbances, and dynamic obstacles. This paper proposes an improved Hybrid Safety and Reward-Sensitive Twin Delayed Deep Deterministic Policy Gradient (H_RS_TD3) algorithm and constructs a high-fidelity simulation environment based on GEBCO bathymetric data and CMEMS ocean current data. The path planning problem is formulated as a Markov Decision Process (MDP), where the state space incorporates multi-beam radar perception, ocean current disturbances, and relative goal information, while the action space outputs continuous thrust and rudder commands subject to vehicle dynamics constraints. The proposed framework integrates a risk-aware hybrid safety decision architecture, a Trajectory Predictor Network (TPN), a Curvature-driven Advantage-based Prioritized Experience Replay (CDA-PER) mechanism, and an uncertainty-aware conservative Q-learning strategy to enhance navigation safety, sample efficiency, and policy stability. Comprehensive simulations demonstrate that, compared with baseline deep reinforcement learning methods, the proposed approach achieves faster convergence, improved stability, and competitive path efficiency while consistently maintaining sufficient obstacle clearance and millisecond-level inference latency, validating its effectiveness and practical feasibility for safe USV navigation in realistic dynamic marine environments. Full article