Abstract:The deformation and failure of rock masses in cold regions due to repeated freeze-thaw cycles present critical challenges that demand thorough investigation. This study examines the mechanical properties and crack propagation characteristics of fractured limestone subjected to varying numbers of freeze-thaw cycles and crack inclination angles. Uniaxial compression tests were conducted, and corresponding stress-strain responses and macroscopic failure patterns were obtained. The fracture surfaces were further analyzed using scanning electron microscopy. Results indicate that repeated freeze-thaw cycles induce pronounced brittle failure in fractured limestone. Peak stress and elastic modulus increase with crack inclination but decrease with the number of freeze-thaw cycles, while peak strain shows positive correlation with both variables. Macroscopic failure is primarily governed by crack-induced breakage, with spalling as a secondary mode. Fracture surfaces predominantly exhibit tensile cracks influenced by pre-existing flaws, but not by the number of freeze-thaw cycles. Microscopically, freeze-thaw action promotes the development of internal microcracks-evidenced by increased crack length, width and density-while pre-existing cracks exert minimal influence on microstructural features. Increasing crack inclination angles suppresses freeze-thaw damage, thus improving rock durability. These findings provide valuable insights for improving the stability and longevity of rock structures in cold-region mining engineering.

Abstract:Plum-blossom pile is a novel kind of new cross-sectional shaped pile, and at present, there is no relevant research on the bearing characteristics of plum-blossom pile under lateral load. Based on the theory of circular hole expansion, the calculation method of soil displacement around plum-blossom pile in sand during pile sinking is established. With considering the special-shaped effect of plum-blossom pile section, the soil squeezing displacement in the positive direction of coordinate axis is obtained by using the principle of coordinate transformation and superposition on the basis of Hooke’s law. The differential equation of pile deflection curve is derived by using m method and its difference solution, and the reliability of the established theoretical method is verified by comparing with the experimental results. The results show that the horizontal displacement of soil between plum-blossom pile and circular pile with equal cross-section is similar. With the increase of horizontal load, the horizontal displacement first increases and then decreases, and the horizontal displacement of soil near plum-blossom pile is about 73.5% of that of circular pile with equal cross-section. The vertical squeezing force of plum-blossom pile on the soil facing surface under horizontal load is small, and the vertical displacement fluctuates with the increase of horizontal load. With the increase of horizontal load, the horizontal displacement of soil in the middle of plum-blossom pile first increases and then decreases, and the maximum horizontal displacement is about 75% of that of circular pile with equal cross section.

Abstract:Post-construction settlement of roadbeds is a critical factor influencing the long-term safety and performance of highways. Accurate prediction of creep behavior is of great significance for ensuring the structural integrity of roadbed systems. However, conventional finite element simulations of creep behavior require extensive meshing for complex structural models, leading to high computational costs and time consumption. To address these challenges, this paper proposes a novel arbitrary polygonal hybrid stress element method (PHSEM) that incorporates creep effects for roadbed settlement analysis. Based on the hybrid stress finite element method and the time-dependent deformation characteristics of roadbed soil, the theoretical formulation of the PHSEM is derived. This element introduces a higher-order stress field, improving computational accuracy. A numerical creep model is further established and validated against results obtained from MARC software. The simulation results show that the PHSEM achieves good agreement with benchmark solutions, with deviations within acceptable limits. Furthermore, the element accommodates polygons with variable edge counts, offering flexible meshing for complex, heterogeneous roadbed models and enabling realistic stress distribution analysis. The proposed PHSEM provides a promising approach for creep modeling in practical geotechnical engineering applications.

Abstract:To more accurately capture vehicle-following behavior in freeway diversion areas, this study proposes an enhanced car-following model by incorporating a lane-changing pressure gain factor into the full velocity difference model (FVDM). The proposed model accounts for both lane-changing pressure and lane-changing behavior. First, a linear stability analysis reveals that the stability region of the freeway diversion area diminishes as the lane-changing pressure gain factor increases. Second, using trajectory data from 92 lane-changing vehicles extracted from the NGSIM dataset, the improved car-following model is calibrated and validated. Simulation results demonstrate that the improved model more accurately reproduces vehicle speed and position. Compared with the original FVDM, the simulation error of the proposed pressure-based FVDM (P-FVDM) is reduced by 16%. Compared with the lane pressure FVDM(LP-FVDM), the proposed pressure-lane pressure FVDM(PLP-FVDM) reduces error by 12%. Finally, the improved model is used to simulate traffic oscillation in the diversion area. Results show that lane changing behavior can trigger traffic oscillations. Higher driving speeds attenuate oscillation amplitudes, while lower speeds result in a concave growth pattern of speed standard deviation along the vehicle platoon in the upstream direction. Furthermore, lane changes occurring closer to the exit ramp exacerbate oscillations, whereas shorter lane-changing duration help suppress them.

Abstract:This study proposes a numerical modeling method based on the cohesive zone model to investigate the mechanical response and fracture mechanism of steel fiber reinforced concrete (SFRC) structures. In the proposed model, cohesive elements are used to stimulate potential fracture surfaces and rebar-concrete interfaces. A constitutive model for SFRC fracture surfaces is developed by considering mixed-mode damage evolution, interfacial friction, and the fiber bridging effect. Additionally, a modified bond-slip constitutive model for the rebar-concrete interface is proposed, accounting for normal separation. To validate the proposed model, a series of four-point bending experiments on SFRC specimens are conducted. The simulation results closely align with experimental observation, confirming the model’s ability to accurately capture both mechanical response and fracture behavior. Parametric analysis reveals that inadequate fiber content or improper friction coefficients significantly reduce structural bearing capacity and ductility.

Abstract:To enhance the quality of service (QoS) in named data mobile ad hoc network (NDMANET), this paper proposes a novel node activeness-based packet forwarding (NAPF) strategy designed to mitigate performance degradation caused by the network’s time-varying topology. The proposed NAPF strategy periodically calculates and updates the activeness levels of all participating nodes, prioritizing nodes with higher activeness for forwarding and caching interest and data packets. A simulation platform is developed using the open-source NS-3/ndnSIM framework to conduct comparative performance evaluations among default flooding, shortest path routing, and the proposed NAPF strategy. Experimental results indicate that in medium-to high-mobility scenarios, the NAPF strategy significantly reduces average request delay, improves response ratios, and decreases bandwidth consumption, with only a modest increase in node storage usage.

Abstract:BEV (bird’s eye view)-based multi-sensor fusion perception algorithms for autonomous driving have made significant progress in recent years and continue to contribute to the development of autonomous driving. In the research of multi-sensor fusion perception algorithms, multi-view image-to-BEV conversion and multi-modal feature fusion have been the key challenges in BEV perception algorithms. In this paper, we propose MSEPE-CRN, a fusion sensing algorithm of camera and millimeter-wave radar for 3D target detection, which utilizes edge features and point clouds to improve the accuracy of depth prediction, and then realizes the accurate conversion of multi-view images to BEV features. Meanwhile, a multi-scale deformable large kernel attention mechanism is introduced for modal fusion to solve the misalignment problem due to the excessive difference of features from different sensors. Experimental results on the nuScenes open-source dataset show that compared to the baseline network, the proposed algorithm achieves improvements of 2.17% in mAP, 1.93% in NDS, 2.58% in mATE, 8.08% in mAOE, and 2.13% in mAVE. This algorithm can effectively improve the vehicle’s ability to perceive moving obstacles on the road, and has practical value.

Abstract:With the proliferation of diverse service characteristics in the internet of vehicles (IoV) under the mobile edge computing (MEC) paradigm, evaluating server-to-end transmission performance presents a significant challenge, particularly due to the complex modeling requirements that must account for service-specific traits in offload feedback strategies. To address this, a cache scheduling evaluation framework is proposed, incorporating time-varying and multi-type services based on queuing theory and a Markov-modulated service process. The proposed framework supports flexible adjustments to service characteristics, bidirectional processing rates, and offload feedback strategies, enabling it to adapt to various communication environments. Within this framework, an offload feedback strategy based on statistical prediction is proposed. Numerical simulations show that the the proposed strategy improves transmission performance by approximately 50% compared with traditional approaches. These findings indicate that the proposed framework provides a valuable reference for designing adaptive strategies under diverse network conditions and hardware configurations.

Abstract:This study presents a machine learning-based intelligent cabin alert filtering system for vehicles aiming to address safety risks caused by excessive and redundant alarm sources. To overcome limitations in current systems, such as alarm redundancy and inaccurate classifications, a hybrid selection strategy is proposed that combines manual expert filtering with a convolutional neural network (CNN) model. The system integrates operational data from various devices, applying manual heuristics to eliminate likely false signals and employing the CNN model for robust feature extraction and precise classification. Experimental results show that the CNN model achieves a classification accuracy of 89.07% on the test dataset. When combined with manual filtering, the overall selection accuracy of alarm signals reaches 99.998%, significantly surpassing the conventional VAS system (90%). These results validate the proposed method’s effectiveness in filtering alarm information. Future research will focus on expanding training datasets, optimizing model parameters, and improving text pre-processing techniques to further enhance the overall system performance.

Abstract:The digital image correlation (DIC) method currently suffers from inadequate systematic calibration methods and an underdeveloped metrological traceability system. To address these challenges, this study proposes a novel calibration methodology based on laser interferometry, integrated with a custom-designed optical system for local deformation measurements. Finite element simulations are employed to analyze the stress stiffening effect in strain plates under tensile loading. A coupled thermo-mechanical model is developed via theoretical analysis and experimental validation to quantitatively assess the influence of convective heat transfer on surface strain measurement accuracy. Furthermore, an Abbe error compensation mechanism is implemented to effectively mitigate nonlinear measurement errors induced by microscale bending during loading. A comprehensive uncertainty analysis is conducted to evaluate both standard uncertainty components and the overall measurement uncertainty. Experimental results demonstrate that the proposed calibration device reduces the uncertainty in standard strain field measurements to the range of 1.9% to 0.83%, offering a critical advancement toward establishing a traceable calibration framework for DIC-based strain measurement systems.