Search Results (2,434)

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 establishes a comprehensive structural isomorphism between Conway’s Game of Life and the entrepreneurial process, analysing the latter as a complex adaptive system governed by non-linear dynamics rather than linear predictability. Through a rigorous qualitative approach based on a systematic literature review and abductive inference, the research identifies and correlates four fundamental dimensions: uncertainty, adaptability, growth, and sustainability. Transcending traditional metaphorical comparisons, this paper introduces a novel mathematical model that modifies Conway’s deterministic logic by incorporating an «Agency» variable (A). This critical addition quantifies how an entrepreneur’s internal capabilities can counterbalance environmental pressures (neighbourhood density) to determine survival thresholds, effectively transforming the simulation into a «Game of Life with Agency» where participants actively influence their viability potential (Ψ). The analysis explicitly correlates specific algorithmic configurations with real-world business phenomena: high-entropy initial states («The Soup») mirror early-stage market uncertainty where outcomes are probabilistic; «gliders» represent the necessity of strategic pivoting and continuous displacement for survival; and «oscillators» symbolise dynamic sustainability through rhythmic equilibrium rather than static permanence. Furthermore, the study validates the «Gosper Glider Gun» pattern as a model for scalable, generative growth. By bridging abstract systems theory with managerial practice, the research positions these simulations as «mental laboratories» for decision-making. The findings theoretically validate iterative methodologies like the Lean Startup and conclude that successful entrepreneurship operates on the «Edge of Chaos», providing a rigorous framework for navigating high stochastic uncertainty. Full article

Assessing the stress–strain state around interacting mining excavations using the finite element method (FEM) is computationally expensive for parametric studies. This study evaluates tabular machine-learning surrogate models for the rapid prediction of full stress–strain fields in fractured rock masses treated as an equivalent continuum. A dataset of 1000 parametric FEM simulations using the elastoplastic generalized Hoek–Brown constitutive model was generated to train Random Forest, LightGBM, CatBoost, and Multilayer Perceptron (MLP) models based on geometric features. The results show that the best models achieve R² scores of 0.96–0.97 for stress components and 0.99 for total displacements. LightGBM and CatBoost provide the optimal balance between accuracy and computational cost, offering speed-ups of 15 to 70 times compared to FEM. While Random Forest yields slightly higher accuracy, it is resource-intensive. Conversely, MLP is the fastest but less accurate. These findings demonstrate that data-driven surrogates can effectively replace repeated FEM simulations, enabling efficient parametric analysis and intelligent design optimization for mine workings. Full article

Pedestrian trajectory prediction plays a vital role in autonomous driving and intelligent surveillance systems. Graph neural networks (GNNs) have shown remarkable effectiveness in this task by explicitly modeling social interactions among pedestrians. However, existing methods suffer from two key limitations. First, they face difficulty in balancing the reduction in redundant connections with the preservation of critical interaction relationships in spatial graph construction. Second, higher-order graph convolution methods lack adaptability to varying crowd densities. To address these limitations, we propose a pedestrian trajectory prediction method based on Delaunay triangulation and density-adaptive higher-order graph convolution. First, we leverage Delaunay triangulation to construct a sparse, geometrically principled adjacency structure for spatial interaction graphs, which effectively eliminates redundant connections while preserving essential proximity relationships. Second, we design a density-adaptive order selection mechanism that dynamically adjusts the graph convolution order according to pedestrian density. Experiments on the ETH/UCY datasets show that our method achieves 5.6% and 9.4% reductions in average displacement error (ADE) and final displacement error (FDE), respectively, compared with the recent graph convolution-based method DSTIGCN, demonstrating the effectiveness of the proposed approach. Full article

This work presents a combined numerical and experimental investigation into the laser machining of aluminum alloy Al 1050 H14 using a high-power Continuous Wave (CW) fiber laser. Advanced three-dimensional, coupled thermal–structural Finite Element Method (FEM) simulations are developed to model key laser–material interaction processes, including laser-induced plastic deformation, laser etching, and engraving. Cases for both static single-shot and dynamic linear scanning laser beams are investigated. The developed numerical models incorporate a Gaussian heat source and the Johnson–Cook constitutive model to capture elastoplastic, damage, and thermal effects. The simulation results, which provide detailed insights into temperature gradients, displacement fields, and stress–strain evolution, are rigorously validated against experimental data. The experiments are conducted on an integrated setup comprising a 2 kW TRUMPF CW fiber laser hosted on a 3-axis CNC milling machine, with diagnostics including thermal imaging, thermocouples, white-light interferometry, and strain gauges. The strong agreement between simulations and measurements confirms the predictive capability of the developed FEM framework. Overall, this research establishes a reliable computational approach for optimizing laser parameters, such as power, dwell time, and scanning speed, to achieve precise control in metal surface treatment and modification applications. Full article

Background: Lingual orthodontic systems have recently advanced with the introduction of fully customized CAD/CAM-based designs featuring self-ligating (SL) mechanisms. This study aimed to evaluate the three-dimensional accuracy of a customized SL lingual system in reproducing digitally planned tooth positions. Methods: A total of 280 teeth were analyzed following treatment with a fully customized self-ligating lingual system (Harmony^®, Aso International Inc., Tokyo, Japan). Digital models obtained before treatment (T0), from the setup (TS), and after treatment (T1) were superimposed using a best fit algorithm in GOM Inspect. Tooth movements were quantified across seven biomechanically relevant parameters including tip, torque, rotation, buccolingual, mesiodistal, vertical, and overall displacement. Predicted and achieved movements were compared using paired t tests and Bland–Altman analysis. Results: The fully customized SL lingual appliance achieved an overall dentition accuracy of 92.1%. Mean accuracy for linear tooth movements was 94.5% ± 2.1% in the maxilla and 93.8% ± 2.5% in the mandible. For angular movements, mean accuracy was 90.8% ± 3.4% in the maxilla and 89.3% ± 3.9% in the mandible. The highest precision was observed in anterior teeth for mesiodistal (96.2%) and buccolingual (95.8%) movements, whereas the lowest accuracy occurred in rotational movements of the posterior segments (87.1%). No statistically significant differences were found between predicted and achieved movements for most parameters (p > 0.05). Conclusions: The fully customized SL lingual orthodontic system demonstrated high accuracy in reproducing digitally planned tooth movements, particularly in the anterior segments. Although accuracy was slightly lower in the posterior regions, the overall outcomes remained mechanically and clinically acceptable across all evaluated dimensions. Full article

Shale oil is primarily hosted within nanopores, where its flow behavior exhibits significant deviations from classical Darcy flow. The combined influences of nanoscale confinement and interfacial interactions represent key scientific challenges that hinder efficient shale oil recovery. The results show that under 25 °C and 1 MPa, the displacement distances of shale oil within 12 s in 100, 200, and 300 nm channels were 2.88, 5.67, and 11.01 mm, respectively. As pore size decreases, flow capacity drops sharply, and the displacement–time relationship evolves from quasi-linear to strongly nonlinear, indicating pronounced nanoscale non-Darcy behavior. By incorporating an equivalent resistance coefficient into the plate-channel flow model, the experimental data were accurately fitted, enabling quantitative evaluation of the additional flow resistance induced by nanoconfinement and interfacial adsorption. The equivalent resistance coefficient increases markedly with decreasing pore size but decreases progressively with increasing temperature and driving pressure. Increasing temperature and pressure partially mitigates nanoconfinement effects. In 200 nm channels, the equivalent resistance coefficient decreases from 1.87 to 1.20 as temperature rises from 25 to 80 °C, while in 100 nm channels it decreases from 2.43 to 1.65 as driving pressure increases from 1 to 6 MPa. Nevertheless, even under high-temperature and high-pressure conditions, shale-oil flow does not fully recover to ideal Darcy behavior. This work establishes a nanofluidic-based prediction and evaluation framework for shale oil flow, offering theoretical guidance and experimental reference for unconventional reservoir development and the optimization of enhanced oil recovery strategies. Full article

Background: Mechanical loading is a fundamental regulator of bone remodelling; however, the mechanotransduction mechanisms governing alveolar bone adaptation under tensile-dominant orthodontic loading remain insufficiently defined. In particular, the molecular pathways associated with tension-driven cortical modelling in the periodontal ligament (PDL)–bone complex have not been systematically interpreted in the context of advanced biomechanical simulations. Methods: A nonlinear finite element model of the alveolar bone–PDL–tooth complex was developed using patient-specific CBCT data. Three loading configurations were analysed: (i) conventional orthodontic loading, (ii) loading combined with corticotomy alone, and (iii) a translation-dominant configuration generated by the Bone Protection System (BPS). Pressure distribution, displacement vectors, and stress polarity within the PDL and cortical plate were quantified across different bone density conditions. The mechanical outputs were subsequently interpreted in relation to established mechanotransductive molecular pathways involved in osteogenesis and angiogenesis. Results: Conventional loading generated compression-dominant stress fields within the marginal PDL, frequently exceeding physiological thresholds and producing moment-driven root displacement. Corticotomy alone reduced local stiffness but did not substantially alter stress polarity. The BPS configuration redirected loads toward a tensile-favourable mechanical environment characterised by reduced peak compressive pressures and parallel (translation-dominant) displacement vectors. The predicted tensile stress distribution is compatible with activation profiles of key mechanosensitive pathways, including integrin–FAK signalling, Wnt/β-catenin–mediated osteogenic differentiation and HIF-1α/VEGF-driven angiogenic coupling, suggesting a microenvironment that may be more conducive to cortical apposition than to resorption. Conclusions: This study presents a computational–molecular framework linking finite element–derived tensile stress patterns with osteogenic and angiogenic signalling pathways relevant to alveolar bone remodelling. The findings suggestthat controlled redirection of orthodontic loading toward tensile domains may shift the mechanical environment of the PDL–bone complex toward conditions associated with osteogenic than resorptive responses providing a mechanistic basis for tension-induced cortical modelling. This mechanobiological paradigm advances the understanding of load-guided alveolar bone adaptation at both the tissue and molecular levels. Full article

Uncertainty quantification in science and engineering has become increasingly important due to advances in computational mechanics and numerical simulation techniques. In this work, the relationship between uncertainty in soil material parameters and the variability of failure loads and displacements of a shallow foundation is investigated. A Drucker–Prager constitutive law is implemented within a stochastic finite element framework. The random material variables considered are the critical state line slope c, the unload–reload path slope $\kappa$, and the hydraulic permeability k defined by Darcy’s law. The novelty of this work lies in the integrated stochastic u–p finite element framework. The framework combines Drucker–Prager plasticity with spatially varying material properties, and Latin Hypercube Sampling. This approach enables probabilistic prediction of failure loads, displacements, stresses, strains, and limit-state initiation points at reduced computational cost compared to conventional Monte Carlo simulations. Statistical post-processing of the output parameters is performed using the Kolmogorov–Smirnov test. The results indicate that, for the investigated configurations, the distributions of failure loads and displacements can be adequately approximated by Gaussian distributions, despite the presence of material nonlinearity. Furthermore, the influence of soil depth and load eccentricity on the limit-state response is quantified within the proposed probabilistic framework. Full article

As a future abundant and environmentally friendly clean energy source, the decomposition process of natural gas hydrates is significantly regulated by reservoir structural characteristics. Improper extraction can easily trigger geological hazards, yet current research on the coupling mechanism between wellbore microstructure and decomposition remains incomplete. To elucidate the regulatory role of reservoir structural characteristics, this study employed a self-developed physical simulation system to conduct triaxial creep experiments. It compared the mechanical response and decomposition dynamics of sediments under layered and homogeneous hydrate distribution patterns, while simultaneously monitoring gas production and formation displacement parameters. Results indicate that layered distribution significantly influences overall sediment creep behavior and failure patterns: low-saturation sublayers dominate the creep softening–hardening mechanism, while strain evolution at different timescales and long-term bearing capacity are controlled by low- and high-saturation sublayers, respectively. Creep cohesion and internal friction angle exhibit distinct differences between the two distribution patterns, with the influence mechanisms of relevant mechanical indicators closely related to the roles of sublayers with varying saturations. The study also uncovers the intrinsic link between gas production and stratigraphic subsidence during hydrate decomposition, clarifying the core mechanism by which reservoir structures influence decomposition stability through regulating mechanical responses. The methodologies and conclusions of this research provide scientific support for predicting the long-term stability of natural gas hydrate reservoirs and enabling safe, efficient extraction, while laying the groundwork for the systematic development of comprehensive hydrate technologies. Full article

The use of geological models for mine production scheduling, planning, and design is a common aspect of current digital mine construction. Establishing a mapping relationship from digital geological resources to mining process simulation and then to risk early warning, enabling real-time interaction between digital models and physical mines, is an essential component of mining digital twins and an important direction for future development. This study is based on a non-ferrous metal mine and involves the development of data interaction functionality between 3Dmine (enterprise edition) and 3DEC7.0 software. This enables data mapping between geological models and numerical models, as well as real-time 3D visualization of risk points in the geological model. The main research findings are as follows: (1) Based on UAV photogrammetry and geological exploration data, a refined 3D geological model incorporating the surface, subsidence zones, goaf groups, and roadway systems was constructed using 3Dmine. The mine numerical model was then generated through 3Dmine-3DEC coupling technology. (2) A 3DEC-3Dmine data interaction interface based on Python was developed. Intelligent extraction and format conversion of mechanical parameters, such as stress and displacement, were achieved through secondary development, and a multi-software collaboration platform was built using an SQL database. A three-dimensional visual characterization script for risk points was developed. (3) Based on the strength–stress ratio and the nearest distance attribute assignment method, the three-dimensional visualization of blocks with different risk levels in 3Dmine is realized. (4) When the adjacent mine rooms are excavated in turn, the range of grade II risk area will be obviously expanded and a more serious grade III risk area will appear. The research findings offer a direction for the future development of mining digital twin technology, as well as technical support and theoretical guidance for analyzing and predicting safety risks during the mining process. Full article

While carbon fiber strength is typically characterized through single-fiber tensile tests, these isolated measurements do not account for the local mechanical constraints present within a composite architecture. This study employs a synergistic computational micromechanics approach combining finite element analysis (FEA) and analytical modeling to investigate how the surrounding matrix influences the Stress Intensity Factor (SIF) and the apparent ultimate strength of embedded fibers. By calculating the J-integral, we demonstrate that the matrix provides a significant shielding effect, constraining crack opening displacements and substantially reducing the SIF. This mechanism results in a marked increase in in situ fiber tensile strength relative to dry fibers. Incorporating this matrix-adjusted Weibull distribution into a longitudinal failure model significantly improves the prediction of fiber-break density accumulation, showing closer correlation with experimental benchmarks than traditional models. Full article

The flexible positioning platform is a critical structural component in the ultra-high acceleration macro–micro motion platform, enabling precise positioning across multiple scales. However, under high-frequency start–stop cycles and prolonged multi-condition operation, it is prone to fatigue damage induced by random vibrations, which poses a threat to system reliability. This study proposes a method for evaluating and optimizing the platform’s performance under random vibration based on power spectral density (PSD) analysis. In accordance with the IEC 60068-2-64 standard, representative load spectra from Tables A.8 and A.6 were selected as excitation inputs. Frequency-domain analyses of stress, strain, and displacement were conducted using ANSYS Workbench 2022R1 in conjunction with the nCode platform, incorporating the Gaussian three-sigma probability interval. The results reveal that stress and deformation are highly concentrated in the hinge region, indicating a structural vulnerability. Fatigue life predictions were carried out using the Dirlik method and Miner’s linear damage rule under various PSD loading conditions. The findings demonstrate that hinge stiffness is a key factor influencing vibration resistance and service life. This research provides theoretical support for the design optimization of flexible structures operating in complex random vibration environments. Full article

Sealing tunnel portals is widely recognized as a pivotal strategy for mitigating fire hazards in tunnel safety management. Nevertheless, the interplay between fire source locations—both longitudinally and transversely—and its impact on flame behavior and ceiling temperature profiles within enclosed structures has not been fully elucidated. Utilizing a 1:15 reduced-scale rectangular tunnel model, this research investigates how varying the fire source position affects the maximum ceiling temperature under enclosed scenarios. Dimensionless parameters, including the longitudinal dimensionless distance D and transverse dimensionless distance Z′, were derived through dimensional analysis. Observations indicate that as the fire approaches the enclosed end, the flame initially leans toward the boundary, peaking in inclination at D = 0.73, and subsequently exhibits a “wall-attached combustion” pattern due to wall confinement. While lateral displacement of the fire source pushes the high-temperature zone toward the corresponding side wall, the longitudinal temperature rise follows a non-monotonic pattern: declining continuously in in Region I (0 ≤ D ≤ 0.73) and rebounding in Region II (0.73 < D < 1). Based on these findings, a dimensionless prediction model incorporating heat release rate (HRR), transverse offset, and longitudinal fire location was developed. Furthermore, a thermal accumulation factor was introduced to refine the predictive model in Region II. The results offer theoretical insights to support fire protection design and risk assessment in enclosed tunnels. Full article

Deep foundation excavation in water-rich sand strata presents complex deformation characteristics driven by fluid–solid interaction, which distinguishes it from excavations in cohesive soft clay. This study investigates the spatiotemporal evolution and deformation mechanisms of retaining structures through a comparative analysis of field monitoring data and 3D numerical simulation, based on a subway station project in Xi’an. While the numerical simulation predicted a continuous “bulging” deformation mode, field monitoring revealed a distinct transition from a “bulging” profile to a “step-like” deformation pattern as the excavation deepened. Quantitatively, while the simulation captured the spatial trend, the measured maximum surface settlement (7.8 mm) exceeded the simulated value (1.2 mm), highlighting the dominant role of seepage consolidation. Detailed analysis indicates that this discrepancy—and the unique step-like evolution—is primarily driven by two mechanisms: the rapid stress relaxation of cohesionless sand during the time lag of support installation, and the superimposed seepage forces induced by continuous dewatering, which are often simplified in standard elastoplastic models. The study further identifies that the vertical displacement of the pile top is governed by the combined effects of basal heave and the “kick-out” deformation at the pile toe. These findings demonstrate that in high-permeability water-rich sand, deformation control depends critically on minimizing the unsupported exposure time of the excavation face. This research provides a theoretical basis for optimizing the spatiotemporal sequencing of excavation in similar geological conditions. Full article