Search Results (751)

This paper presents a systematic review of research investigating the effects of elevated temperatures on sedimentary rocks. The literature was selected using keyword-based searches of titles, abstracts, and keywords in the Scopus and Web of Science databases. In total, 107 relevant articles published between 2010 and 2024 were critically examined to address research questions on temperature-treated sedimentary rocks. Furthermore, both bibliometric analysis and systematic synthesis of experimental data were performed. The review identifies sandstone as the most-studied rock type, followed by limestone. It reveals that standard experimental methods include unconfined compressive strength (UCS), Brazilian tensile strength (BTS), and P-wave velocity tests. The study’s findings indicate that a temperature threshold of 400–600 °C governs deterioration in engineering properties, driven by the quartz α–β transition in sandstones and calcite decomposition in limestones. Normalized data show that UCS, BTS, and elastic modulus decline significantly beyond this threshold, while porosity increases. The study highlights the influence of fabric anisotropy, mineralogy, and heating conditions on rock behaviour, and identifies research gaps related to confined testing, real-fire scenarios, and anisotropic rocks. Based on a comprehensive analysis of the literature, the principal factors and processes occurring at different temperature ranges were identified and discussed. Full article

In this study, a three-dimensional (3D) model is developed based on an actual small forestry crawler tractor, to analyze its overturning and rollover behaviors, and a corresponding simulation model is constructed. The accuracy of the 3D model is validated by comparing its dimensions and center of gravity with those of the physical tractor, and the fidelity of the simulation model is verified using static sidelong falling angle, minimum turning radius, and driving tests. The developed simulation framework was employed to investigate the dynamic behavior of the small forestry crawler tractor, focusing on roll and pitch angular velocities across different obstacle heights, slope angles, and driving speeds. Backward rollover was not observed within the tractor’s realistic operating speed range, indicating that backward rollover is not the dominant risk mode. In contrast, lateral overturning occurs under all driving scenarios, and increases in driving speed and obstacle height lead to higher roll angular velocities, increasing the risk of lateral overturning. Across all conditions, the likelihood of lateral overturning surges when the roll angular velocity enters the 80–100°/s range, with obstacle height exerting the greatest influence. In conclusion, the small forestry crawler tractor is more prone to lateral overturning than backward rollover when driving on inclined surfaces. A distinct threshold roll angular velocity is identified as the onset point of lateral overturning, which will vary according to the tractor’s specifications. This study is a quantitative study of a small forestry crawler tractor and does not correlate with a full-scale tractor. While angular velocity values vary during lateral overturning and backward rollover, this study was conducted to identify trends under various driving conditions. Further work is required to apply the proposed analysis methodology to full-scale agricultural and forestry machinery and validate it with real-world operational data. Full article

Amid growing environmental concerns, resource depletion, and the pressing challenges of industrial waste management, this study investigates the potential of magnesium slag (MS) as a sustainable alternative binder in the production of one-part geopolymer concretes (OPGCs). The objective is to reduce reliance on conventional cementitious materials while promoting the valorization of industrial by-products in construction practices. For this purpose, ten different mixtures were designed by replacing ground granulated blast furnace slag (GGBS), the conventional aluminosilicate precursor, with MS, an innovative aluminosilicate precursor, at replacement levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% by weight, using a solid activator. The fresh and hardened properties of these mixtures were systematically evaluated through slump, setting time, density, ultrasonic pulse velocity (UPV), and strength tests, while microstructural characterization was also conducted using scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDX) to further investigate the geopolymerization process, elemental distribution, and the role of MS in binder formation in OPGC. The results revealed that MS incorporation significantly influenced both workability and mechanical performance, and it was confirmed that MS actively participates in geopolymerization and can be effectively utilized up to a certain threshold. Replacement levels up to 30% were found to maintain acceptable mechanical performance, providing evidence that MS is a promising precursor for developing sustainable OPGC. Full article

The pressure-gradient Micro-Electro-Mechanical Systems (MEMS) vector hydrophone is a novel type of sensor capable of simultaneously acquiring both scalar and vectorial information within an acoustic field. Conventional azimuth estimation methods struggle to achieve high-resolution localization using a single pressure-gradient MEMS vector hydrophone. In practical marine environments, the multiple signal classification (MUSIC) algorithm is hampered by significant resolution performance loss. Similarly, the complex acoustic intensity (CAI) method is constrained by a high-resolution threshold for multiple targets, often resulting in inaccurate azimuth estimates. Therefore, a cross-spectral model between the acoustic pressure and the particle velocity for the pressure-gradient MEMS vector hydrophone was established. Integrated with an improved particle swarm optimization (IPSO) algorithm, a high-resolution azimuth estimation method utilizing this hydrophone is proposed. Furthermore, the corresponding Cramér-Rao Bound is derived. Simulation results demonstrate that the proposed algorithm accurately resolves two targets separated by only 5° at a low signal-to-noise ratio (SNR) of 5 dB, boasting a root mean square error of approximately 0.35° and a 100% success rate. Compared with the CAI method and the MUSIC algorithm, the proposed method achieves a lower resolution threshold and higher estimation accuracy, alongside low computational complexity that enables efficient real-time processing. Field tests in an actual seawater environment validate the algorithm’s high-resolution performance as predicted by simulations, thus confirming its practical efficacy. The proposed algorithm addresses key limitations in underwater detection by enhancing system robustness and offering high-resolution azimuth estimation. This capability holds promise for extending to multi-target scenarios in complex marine settings. Full article

This paper presents a novel deep learning framework for traffic crash prediction that leverages graph-based representations to model complex interactions among road users. At its core is a dynamic Graph Attention Network (GAT), which abstracts road users and their interactions as evolving nodes and edges in a spatiotemporal graph. Each node represents an individual road user, characterized by its state as features, such as location and velocity. A node-wise Long Short-Term Memory (LSTM) network is employed to capture the temporal evolution of these features. Edges are dynamically constructed based on spatial and temporal proximity, existing only when distance and time thresholds are met for modeling interaction relevance. The GAT learns attention-weighted representations of these dynamic interactions, which are subsequently used by a classifier to predict the risk of a crash. Experimental results demonstrate that the proposed GAT-based method achieves 86.1% prediction accuracy, highlighting its effectiveness for proactive collision risk assessment and its potential to inform real-time warning systems and preventive safety interventions. Full article

In the diagnostics of plasmas heated by neutral beam injection (NBI), which serves as a fundamental heating technique, critical core parameters such as ion temperatures and rotational velocities can be measured through NBI’s associated diagnostic methods. However, conventional spectral analysis methods applied in NBI-based Beam Emission Spectroscopy diagnostics face a significant limitation: a relatively high false detection rate during characteristic peak detection and boundary determination. This issue stems from three primary factors: persistent noise interference, overlapping spectral peaks, and dynamic broadening effects. To address this critical issue, we propose a spectral feature extraction method based on morphological segmentation and optimized clustering, with three key innovations that work synergistically: (1) an adaptive chunking algorithm driven by gradient, Laplacian, and curvature features to dynamically partition spectral regions, laying a foundation for localized analysis; (2) a hierarchical residual iteration mechanism combining dynamic thresholding and Gaussian template subtraction to enhance weak peak signals; (3) optimized DBSCAN clustering integrated with morphological closure to refine peak boundaries accurately. Among them, the adaptive chunking technique is distinct from general adaptive methods: its chunking granularity can be dynamically adjusted according to peak structures and can accurately adapt to low signal-to-noise ratio (SNR) scenarios. Experimental results based on measured data from the EAST device demonstrate that the adaptive chunking strategy maintains a missed detection rate of 0–20% across the full signal-to-noise ratio (SNR) range, with false positive rates limited to 16.67–50.00%. Notably, it achieves effective peak detection even under extremely low SNR conditions. Full article

Background: Neoprene knee sleeves are commonly used to enhance joint stability and mechanical performance during resistance training. However, the specific influence of sleeve density on the force–velocity–power (F–V–P) profile during multi-joint lower-body exercises such as the back squat remains unclear. This study aimed to compare the theoretical F–V–P parameters derived from back squat performance while wearing low-density (LD) versus high-density (HD) knee sleeves. Methods: Fifteen resistance-trained males completed an incremental back squat test under both LD and HD conditions. A linear position transducer recorded barbell displacement and velocity. Individual force–velocity relationships were modelled to determine maximal theoretical force (F₀), velocity (V₀), power (Pmax), and the F–V slope. Paired-sample t-tests, linear mixed models, and Cohen’s d effect sizes were calculated. Clinical relevance was assessed using a threshold defined as 0.2 × the standard deviation of the HD condition. Bayesian analyses were conducted to estimate the probability and magnitude of the observed effects. Results: No statistically significant differences were observed between sleeve conditions for F₀, V₀, Pmax, or F–V slope (p > 0.05, d ≤ 0.37). Nonetheless, HD sleeves yielded slightly higher mean values for F₀, V₀, and Pmax, exceeding the predefined threshold for practical relevance. Bayesian models showed moderate probabilities (~0.80) that HD sleeves outperformed LD, though with limited chances of crossing the clinical significance threshold. Conclusions: Although HD sleeves do not produce systematic changes in F–V–P parameters, their increased material stiffness may provide small yet practically meaningful mechanical advantages in high-force resistance training contexts. Full article

Subsea pipelines are critical lifelines for marine resource development, yet they face severe threats from accidental ship anchor impacts. This study addresses the scientific challenge of quantifying the “protection margin” of artificial rock-dumping layers, moving beyond traditional passive structural response to a “Critical Failure Intervention” logic. Based on the energy criteria of DNV-RP-F107, a critical velocity required to trigger Concrete Weight Coating (CWC) failure for a bare pipe was derived and established as the Safety Factor baseline (S = 1). Two groups of scaled model tests (1:15) were conducted using a Hall anchor to simulate impact scenarios, where impact forces were measured via force sensors beneath the pipeline under varying backfill thicknesses and configurations. Results show that artificial backfill provides a significant protective redundancy; a 10 cm coarse rock layer increases the safety factor to 3.69 relative to the H₀ baseline, while a multi-layer configuration (sand bedding plus coarse rock) elevates S to 27. Analysis reveals a non-linear relationship between backfill thickness and cushioning efficiency, characterized by diminishing marginal utility once a specific thickness threshold is reached. These findings indicate that while thickness is critical for extreme impacts, the protection efficiency optimizes at specific depths, providing a quantifiable framework to reduce small-particle layers in engineering projects without compromising safety. Full article

Fish passes are essential hydraulic structures that maintain longitudinal connectivity in regulated rivers, but their hydraulic performance may be affected by debris accumulation at chamber openings. This study investigates the influence of partial and total inlet blockage by plant debris on flow conditions within a semi-natural fish pass under field conditions. Hydraulic measurements were conducted at multiple locations along the fish pass, and the effects of debris covering were evaluated using statistical and mixed-effects modeling approaches. Field measurements demonstrated that the Froude number decreases systematically with increasing distance from the inlet, indicating progressive longitudinal dissipation of flow energy along the chamber sequence. Partial debris accumulation caused only marginal changes in the Froude number, remaining close to the threshold of statistical significance. In contrast, mean flow velocity decreased markedly with increasing inlet blockage, by approximately 17% at 50% covering and by about 36% under full blockage, indicating that debris primarily acts as a hydraulic damper rather than inducing a change in flow regime. The highest variability in hydraulic conditions was observed in chambers associated with changes in flow direction and local geometry. These results highlight the dominant role of longitudinal layout and chamber geometry in shaping hydraulic conditions in semi-natural fish passes, while moderate debris accumulation affects local velocities without fundamentally compromising hydraulic functionality. From an ecological perspective, transition zones with elevated hydraulic variability may represent critical locations influencing the swimming effort and passage efficiency of migrating fish. Full article

Background: Microsaccades are small fixational eye movements tightly linked to attention and oculomotor control. Although diabetes mellitus is associated with retinal and neural alterations that may impair visuomotor function, the influence of physical activity on microsaccade behaviour in individuals with type 2 diabetes mellitus (T2DM) remains unknown. This study investigated whether habitual physical activity modulates microsaccade characteristics during fixation under different optic flow stimuli. Given that optic flow engages motion processing and gaze stabilisation pathways that may be affected by diabetes-related microvascular/neural changes, it can reveal subtle visuomotor alterations during fixation. Methods: Twenty-eight adults with T2DM and no diagnosed retinopathy performed a fixation task while viewing optic flow stimuli made of moving dots. Eye movements were recorded using an EyeLink system. Physical activity behaviour was assessed at baseline and at a 6-month follow-up after a low-threshold aerobic circuit training programme. Classification as physically active (≥600 MET-min/week) or inactive (<600 MET-min/week) was based on the 6-month assessment. Microsaccade characteristics were analysed by repeated-measures ANOVA. Results: Microsaccade rate was modulated by optic flow (p = 0.044, η²p = 0.106) and showed a significant stimulus × group × sex interaction (p = 0.005, η²p = 0.163), indicating sex-dependent differences in how optic flow modulated microsaccade rate across physically active and inactive participants. A time × stimulus interaction effect was found in peak velocity (p = 0.03, η²p = 0.114) and amplitude (p = 0.02, η²p = 0.127), consistent with modest context-dependent changes over time. Conclusions: These findings suggest that physical activity modulates microsaccade generation and supports the potential of microsaccade metrics as sensitive indicators of oculomotor function in diabetes. Full article

Biomimetic microstructured surfaces offer a promising passive strategy for drag reduction in marine and aerospace applications. This study employs computational fluid dynamics (CFD) simulations to systematically investigate the drag reduction performance and mechanisms of groove-type microstructures, addressing both geometry selection and dimensional optimization. Three representative geometries (V-groove, blade-groove, and arc-groove) were compared under identical flow conditions (inflow velocity 5 m/s, Re = 7.5 × 10⁵) using the shear-stress-transport (SST k-ω) turbulence model, and the third-generation Ω criterion was employed for threshold-independent vortex identification. The results establish a clear performance hierarchy: blade-groove achieves the highest drag reduction rate of 18.2%, followed by the V-groove (16.5%) and arc-groove (14.7%). The analysis reveals that stable near-wall microvortices form dynamic vortex isolation layers that separate the high-speed flow from the groove valleys, with blade grooves generating the strongest and most fully developed vortex structures. A parametric study of blade-groove aspect ratios (h⁺/s⁺ = 0.35–1.0) further demonstrates that maintaining h⁺/s⁺ ≥ 0.75 preserves effective vortex-isolation layers, whereas reducing h⁺/s⁺ below 0.6 causes vortex collapse and performance degradation. These findings establish a comprehensive design framework combining geometry selection (blade-groove > V-groove > arc-groove) with dimensional optimization criteria, providing quantitative guidance for practical biomimetic drag-reducing surfaces. Full article

Progressive rock slope destabilization poses significant geohazard risks, necessitating advanced monitoring frameworks to detect precursory failure signals. This study presents a comprehensive time-dependent evaluation of the displacement probability (CTEDP) model, which integrates GNSS-derived spatiotemporal data with multi-parameter reliability indices to enhance landslide risk assessment. Five monitoring points on a destabilizing rock slope were analyzed from mid-November 2024 to early January 2025 using kinematic metrics (velocity, acceleration, and jerk), statistical measures (e.g., moving averages), and reliability indices (RI₀, RI₁, RI₂, and RI_combined). Point 1 exhibited the most critical behavior, with a cumulative displacement of ~60 mm, peak velocities of 34.5 mm/day, and accelerations up to 1.15 mm/day². The CTEDP for active points converged to 0.56–0.61, indicating sustained high risk. The 90th percentile displacement threshold was 58.48 mm for Point 1. Sensitivity analysis demonstrated that the GNSS-derived reliability indices dominated the RI_combined variance (r = 0.999, explaining 99.8% of variance). The first- and second-order reliability indices (RI₁, RI₂) at Point 1 exceeded the 60-index threshold, indicating a transition to Class B (“Low Risk—Trend Surveillance Required”) status, while other points showed coherent deformation of 37–45 mm. Results underscore the framework’s ability to integrate spatiotemporal displacement, kinematic precursors, and statistical variability for early-warning systems. This approach bridges gaps in landslide prediction by accounting for spatial heterogeneity and nonlinear geomechanical responses. Full article

This study investigates the effects of saline reclaimed water recharge on soil salt accumulation and water migration in Xinjiang, China, aiming to provide scientific guidance for the sustainable utilization of reclaimed water in arid regions. Indoor vertical infiltration simulation experiments were conducted using reclaimed water with varying salinity levels (0, 1, 2, 3, and 4 g L⁻¹) to evaluate their impacts on soil water–salt distribution and infiltration dynamics. Results showed that irrigation with saline reclaimed water increased soil pH and significantly enhanced both the infiltration rate and wetting front migration velocity, while causing only minor changes in the moisture content of the wetted zone. When the salinity was 2 g L⁻¹, the observed improvement effect was the most significant. Specifically, the cumulative infiltration increased by 22.73% after 180 min, and the time required for the wetting peak to reach the specified depth was shortened by 21.74%. At this salinity level, the soil’s effective water storage capacity reached 168.19 mm, with an average moisture content increase of just 6.20%. Soil salinity increased with the salinity of the irrigation water, and salts accumulated at the wetting front as water moved downward, resulting in a characteristic distribution pattern of desalination in the upper layer and salt accumulation in the lower layer. Notably, reclaimed water recharge reduced soil salinity in the 0–30 cm layer, with salinity in the 0–25 cm layer decreasing below the crop salt tolerance threshold. When the salinity of the reclaimed water was ≤2 g L⁻¹, the salt storage in the 0–30 cm layer was less than 7 kg ha⁻¹, achieving a desalination rate exceeding 60%. Reclaimed water with a salinity of 2 g L⁻¹ enhanced infiltration (wetting front depth increased by 27.78%) and desalination efficiency (>60%). These findings suggest it is well suited for urban greening and represents an optimal choice for the moderate reclamation of saline-alkali soils in arid environments. Overall, this study provide a reference for the water quality threshold and parameters of reclaimed water for urban greening, farmland irrigation, and saline land improvement. Full article

Understanding the evolution of the atmospheric boundary layer height (BLH) is essential for characterizing air–surface exchange and air pollution processes. This study investigates the consistency and applicability of three BLH retrieval methods based on multi-source remote sensing observations at Beijing Southern Suburb station during autumn–winter 2023. Using Doppler wind lidar (DWL) and microwave radiometer (MWR) data, the Haar wavelet covariance transform (HWCT), vertical velocity variance (Var), and parcel methods were applied, and 10 min averages were used to suppress short-term fluctuations. Statistical analysis shows good overall consistency among the methods, with the strongest correlation between HWCT and Var method (R = 0.62) and average systematic positive bias of 0.4–0.6 km for the parcel method. Case studies under clear-sky, cloudy, and hazy conditions reveal distinct responses: HWCT effectively captures aerosol gradients but fails under cloud contamination, the Var method reflects turbulent dynamics and requires adaptive thresholds, and the Parcel method robustly describes thermodynamic evolution. The results demonstrate that the three methods are complementary in capturing the material, dynamic, and thermodynamic characteristics of the boundary layer, providing a comprehensive framework for evaluating BLH variability and improving multi-sensor retrievals under diverse meteorological conditions. Full article

Blast-induced vibrations from newly constructed tunnels may adversely affect adjacent existing tunnel structures. To ensure the safety of the existing tunnel, it is essential to investigate its dynamic response under blast disturbances. Based on an expansion project for a highway double-arch tunnel, this study employed the dynamic finite element program LS-DYNA to analyze the vibration velocity and effective stress in the tunnel lining subjected to blast vibrations. The distribution characteristics of vibration velocity and effective stress at different locations of tunnel lining were obtained. A relationship model between the peak particle velocity (PPV) and effective stress was established. According to the maximum tensile stress theory, a safety criterion based on vibration velocity was determined. To facilitate field monitoring, a correlation between the vibration velocity at the arch waist and foot was established, leading to a proposed safety threshold for the arch foot vibration velocity. Furthermore, a statistical relationship was developed between the charge weight per hole in the upper bench cut and the vibration velocity at the arch foot to guide blasting design. Using the arch foot vibration velocity as the safety standard, the maximum permissible charge weight to ensure the structural safety of the existing tunnel was recommended. Full article