Search Results (303)

Predicting the evolution of microstructure and field quantities under varying processing and loading conditions is a central challenge in computational materials science and metal additive manufacturing (AM). While deep learning (DL) methods offer ultra-fast prediction capabilities post-training, existing models often struggle with poor spatial and temporal extrapolation, high parameter burdens, and an inability to effectively integrate diverse conditioning parameters alongside high-dimensional input fields. To address these bottlenecks, we propose a novel conditional generative adversarial network (CPGAN), which is designed to seamlessly ingest both initial fields and governing condition parameters. The CPGAN framework offers three distinct advantages: (1) it accurately maps the combined effects of initial states and process conditions onto evolved fields; (2) it demonstrates robust extrapolation capabilities across diverse spatial and temporal scales, including the unique ability to natively generate high-resolution rectangular domains; and (3) it achieves superior predictive accuracy and training stability compared to standard convolutional baselines by effectively suppressing spurious artifacts. We validate CPGAN’s performance against rigorous physics-based ground truths across three representative engineering applications: porosity evolution in selective laser sintering (SLS), spatial distribution of 2D von Mises stress fields in solid structures, and the spatiotemporal evolution of grain growth. The results confirm that CPGAN is a highly adaptable and efficient surrogate model, capable of simulating continuous structural and morphological evolutions even when driven by highly non-uniform spatial or temporal kinetics. Full article

Dense granular materials under low confining stress and low shear velocity—conditions relevant to low-pressure powder handling, near-surface transport, and the upper layers of stored bulk solids—remain insufficiently characterized at the microstructural level. We perform three-dimensional discrete element method (DEM) simulations of annular shear of monodisperse glass spheres at σ = 1 kPa and v = 0.01 m/s, corresponding to an inertial number I ≈ 1.06 × 10⁻³ at the quasi-static limit of the dense flow regime. The steady-state friction coefficient stabilizes at μ_ss ≈ 0.78, consistent with the quasi-static limit of the μ(I) framework. The solid volume fraction decreases monotonically from φ ≈ 0.50 at the base to φ ≈ 0.35 near the top, while the tangential velocity decays exponentially with depth (decay length δ_s ≈ 10 mm). Particle trajectory tracking reveals a sharp kinematic transition near z ≈ 5–6 mm separating a quasi-rigid basal layer (z ≲ 5 mm) from an upper shear-active zone (z ≳ 6 mm). The contact force distribution follows an exponential decay P($f$/$⟨f⟩$) ∝ exp(−β·$f$/$⟨f⟩$) with β ≈ 0.45, with strong force chains selectively concentrated in the upper zone. Together, these four microstructural descriptors co-locate within a single transition band, providing quantitative benchmarks for material characterization and constitutive modelling at the lower boundary of dense flow. Full article

This study presents an intelligent framework for the analysis of multidimensional geomechanical states in underground mining systems based on numerical simulation and machine learning methods. A three-dimensional geomechanical model of the Zholymbet deposit was developed in the RS3 environment using the generalized Hoek–Brown failure criterion. Numerical simulations were performed for representative mining scenarios characterized by complex excavation interaction and stress redistribution. The modelling results were transformed into a multidimensional geomechanical dataset containing stress, deformation, displacement, and yielding parameters. Principal component analysis (PCA) was applied to investigate the internal structure of the geomechanical state space and identify dominant patterns controlling the rock mass behavior. Clustering analysis revealed several geomechanical regimes corresponding to stable, transitional, and instability-prone conditions. Isolation Forest anomaly detection demonstrated that atypical geomechanical states are not randomly distributed but spatially localized near excavation systems and mining horizons. The obtained results indicate that hazardous geomechanical conditions are governed by complex interactions between stress concentration, deformation intensity, yielding processes, and excavation geometry. The proposed approach provides a basis for intelligent interpretation of large-scale numerical modelling results and may support geomechanical risk assessment in underground mining operations. Full article

Slamming-induced whipping has been recognized as a key contributor to fatigue damage of large ships operating under severe sea states. However, accurate prediction of whipping responses remains challenging because of complex nonlinear fluid–structure interactions. This study aims to investigate the characteristics of slamming-induced whipping and quantitatively analyze its influence on the fatigue damage of an ultra-large container ship. A three-dimensional fully nonlinear time-domain hydroelastic method, in which the boundary element model is coupled with a Timoshenko beam model, is employed to predict the slamming-induced whipping responses. Segmented model tests in long-crested irregular waves are conducted to provide wave loads of hull girders under severe sea states. The total and wave-frequency vertical bending moments are separated by the fast Fourier transform, and their statistical characteristics are evaluated through probability distributions. Fatigue damage is assessed on the basis of the rainflow counting method and the Palmgren–Miner cumulative damage rule. The contribution of high-frequency whipping responses to fatigue damage is quantitatively evaluated using a fatigue damage factor. It is demonstrated that slamming-induced whipping can significantly amplify fatigue damage by increasing stress amplitudes and cycle counts, particularly under high forward speeds and severe sea conditions. The findings provide a reliable reference for the fatigue design and safety assessment of ultra-large container ships. Full article

Soft magnetic composites (SMCs) are attracting increasing attention for electromagnetic applications owing to their three-dimensional shape flexibility and reduced eddy current loss. In this study, the 2-Pressing 1-Annealing (2P1A) process was applied to Fe–5.0 wt.%Si SMC toroidal cores to investigate the effects of pressing temperature and 1st pressing level on densification behavior, interparticle insulation structure, and frequency-dependent electromagnetic response. DEFORM-3D FEM simulations compared relative density distribution, hydrostatic stress, effective strain, and reaction load under single-press and 2P1A conditions. The 1st pressing stage was conducted at 350 °C with 30%, 50%, and 70% pressing levels, followed by final densification at 550 °C. Increasing compaction temperature reduced reaction load and hydrostatic stress range, while the 1st pressing level affected the final density distribution and stress state after 2nd pressing. TEM-EDS confirmed continuous interparticle insulation layers, and thickness measurements were used to compare local boundary structures. Among the 2P1A conditions, the 50% → 100% condition showed the smallest upper/lower relative density difference and the narrowest insulation-layer thickness range, indicating the most balanced condition in terms of densification uniformity and interparticle boundary structure. Compared with the 550 °C single-press condition, the 2P1A compacts showed higher permeability retention and Q-factor values in the 5–20 kHz range. These results indicate that the 1st pressing level influences staged densification behavior, interparticle boundary structure, and frequency-dependent electromagnetic response in Fe–5.0 wt.%Si SMC cores. Full article

Crack opening and reinforcement stress are two complementary indicators of the service state of reinforced concrete hydraulic structures, yet they are often predicted separately. This study develops a data-driven multi-task temporal fusion framework for joint 48 h ahead prediction of dam crack responses and rebar stress using multi-source monitoring data. The measured data comprise five crack-monitoring series, five rebar stress series, local temperature channels, reservoir water level, antecedent rainfall, and an auxiliary environmental signal over approximately four years. Target responses are aligned only at common measured timestamps; no synthetic target observations are introduced. A simplified engineering layout and plan-based crack–rebar distances are further used to examine whether an explicit spatial prior can strengthen the shared temporal representation without introducing synthetic target values. A residual multi-task temporal fusion network (MTTF-Net) is proposed with a shared Transformer encoder, attention pooling, task-specific decoders, and a response-continuity regularization term. The model is compared with persistence, Ridge regression, random forest, Extra Trees, XGBoost, and GRU baselines under a chronological train/validation/test split. For the independent test period, Ridge regression obtains the lowest overall RMSE (2.2968), whereas MTTF-Net provides the lowest crack RMSE (0.0141), the lowest overall MAE (1.0035), and the second-best overall RMSE (2.3813). Distance-informed ablation, denoted as MTTF-Net-S, remains close to MTTF-Net in macro-averaged $R^2$ but is not superior in the overall test metrics, indicating that the available horizontal distances are valuable engineering metadata but cannot replace richer three-dimensional structural connectivity. These results indicate that the monitoring data contain a strong linear autoregressive component, while multi-task temporal fusion improves nonlinear crack response prediction and remains competitive for stress forecasting. The source code is prepared as a public implementation package, whereas the measured monitoring dataset is subject to data owner restrictions. Full article

Optimizing the structural stability of foundations is challenging in modern geotechnical engineering. This study investigated the mechanism of geocell-reinforced foundations through discrete element modeling based on transparent soil model tests. A three-dimensional particle flow code (PFC^3D) model was developed to investigate the micromechanical soil–geocell interactions in both unreinforced and geocell-reinforced foundations under strip loading. Particle displacement, contact force distribution, and structural deformation within the foundation system were analyzed to quantify the performance of geocell reinforcement. The results show that geocell inclusion enhances structural performance by 2.1 times compared to an unreinforced foundation, increasing the bearing capacity from 60.6 to 126.8 kPa at a defined bearing capacity criterion. The geocell walls act as rigid physical boundaries that microscopically intercept the lateral migration and horizontal extrusion of soil particles. The kinematic trajectories of soil particles beneath the loading plate are forced into a downward realignment, decreasing the displacement vector rotation angle from 42° in the unreinforced soil to 27° in the reinforced soil and effectively mitigating the heave of adjacent surfaces. Furthermore, the quasi-rigid three-dimensional network completely interrupts the continuous steep contact force chains inherent in unreinforced foundations. Concentrated vertical stresses are converted into horizontal components through interfacial friction and mechanical interlocking, resulting in the lateral redistribution of the applied load by a distance of approximately 0.06 m. The geocell–soil composite considered as a flexible raft foundation extends load dispersion and reduces average subsoil pressure. A coupled tension and compression stress state in the horizontal plane is developed within the geocell structure. Forces are channeled along rigid paths by elevated bending moments and stress concentrations at the cell junctions. These findings provide micromechanical insights into the performance of geocell-reinforced-foundation systems. Full article

Mountain ecosystems are sensitive response units and critical ecological barriers to global climate change. Located in the mid-latitude climate transition zone, these ecosystems feature high ecological sensitivity and complex driving mechanisms, creating an urgent need to conduct long-sequence, high-precision dynamic assessments in order to support ecological conservation and climate adaptation decision-making. However, three key research gaps remain in the field: first, traditional assessments are dominated by static observation, lacking the capacity for long-sequence dynamic analysis and future projection; second, the coupled interaction mechanism among multiple ecological factors remains unclear, with insufficient quantitative and physical mechanism characterization; third, existing ecological zoning has not been validated for robustness, rendering it incapable of addressing climate disturbances and extreme scenarios. In order to study the regional atmospheric ecosystem, this study takes Shangluo in the eastern Qinling Mountains as the study area and constructs an integrated assessment framework integrating multi-dimensional diagnosis, simulation and projection, dynamic zoning and robustness validation based on long-sequence multi-factor data covering the years 1965–2024. The study aims to reveal the long-sequence evolution patterns and four-dimensional coupling mechanism of the Qinling Mountains atmospheric ecosystem, developing a reproducible and transferable dynamic assessment model. The results show that the study area exhibits the characteristic of elevation-dependent warming, and the correlation coefficients between elevation and air temperature, and between vegetation coverage and air quality reach −0.89 and −0.76, respectively.; ecological quality presents a spatial pattern of being high in the southwest and low in the northeast, with a coefficient of variation across the whole study area lower than 0.03. The results of 1000 Monte Carlo random disturbance validation runs show that even under intensified climate stress, the zoning pattern still maintains extremely strong disturbance resistance. This study reveals the steady-state multi-factor interaction mechanism in mountainous regions, addressing the defects of traditional static assessments that ignore ecosystem evolution and lag effects. The dynamic projection model constructed in this study can be transferred to similar mid-latitude mountainous regions worldwide, providing theoretical and technical support for regional ecological governance. Full article

Slabbing failure of roadway-side backfill bodies critically threatens gob-side entry retaining stability. This study establishes an elastic thin-plate model with edge cracks, employing an innovative load transformation to reduce the three-dimensional in situ stress state to the combined action of roof–floor uniform load and equivalent axial bending moment. Based on fracture mechanics and elastic-plastic theory, the stress intensity factor $K_1$ and crack initiation load q are derived in closed form. Results show that q is positively correlated with plate thickness t and bending moment M and negatively with crack length a in the dominant range. Applying the nonlinear Hoek–Brown criterion, the failure zone width ${\mathrm{r}}_{\mathrm{p}}$ at the crack tip is shown to exhibit an approximately exponential relationship with $K_1$ for unbolted backfill. Introduction of tensioned bolts via a stress concentration factor $\mathsf{\eta }$ transforms the failure zone growth from exponential to asymptotic saturation, quantitatively confirming the crack-arresting effect. A sensitivity analysis identifies plate thickness as the dominant parameter. The model bridges the gap between initial slabbing and progressive V-shaped notch formation. Full article

Background: Pediatric maxillary deficiency often leads to upper airway constriction and chronic sinonasal inflammation. While conventional expansion focuses on dental width, the Right Angle Maxillary Protraction Appliance (RAMPA) system targets three-dimensional skeletal remodeling. This study investigates the mechanotherapeutic impact of RAMPA on the nasal microenvironment, specifically focusing on bone remodeling triggers and mucus rheology. Methods: Pre- and post-treatment CBCT data from 20 pediatric patients were analyzed. Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) were employed to evaluate mechanical strain patterns and aerodynamic changes. We specifically identified the “BMP-2 TRIGGER ZONE” where tensile stress induces osteogenic signaling. Mucus clearance efficiency was modeled using the Carreau–Yasuda rheological framework. Results: RAMPA treatment resulted in a 61.2% mean increase in sinonasal volume (p < 0.0001), significantly outperforming natural growth baselines. FEA revealed that anterosuperior force vectors concentrated tensile stress on circummaxillary sutures, reaching thresholds for BMP-2 upregulation. CFD simulations demonstrated a significant reduction in wall shear stress (WSS) and improved airflow distribution, facilitating the transition of mucus from a high-viscosity state to a fluid state via shear-thinning effects. Conclusions: Our findings suggest that RAMPA-induced remodeling acts as a mechanotherapeutic modulator. As a proof-of-concept study, by triggering molecular signaling for bone formation and restoring sinonasal homeostasis through improved aerodynamics, this intervention may provide a comprehensive solution for chronic sinonasal inflammation beyond simple mechanical expansion. Full article

This research presents a robust multivariate statistical framework for the non-destructive prediction of geomechanical state parameters in quartz-rich coastal sands through acoustic emission (AE) monitoring. Granular media under symmetrical compressive stress function as complex natural systems, where microscopic energy dissipation—arising from particle rearrangement and grain microcracking—radiates as transient elastic waves. To decode these stochastic processes, 24 confined uniaxial compression tests were conducted across diverse soil typologies and moisture contents (0–12%). A high-dimensional data matrix was constructed, integrating 13 geotechnical variables with 48 acoustic descriptors formulated through three distinct temporal aggregations: stage-specific, history average and weighted history average. The statistical results identify the logarithmic effective vertical stress (${\log }_{10}\left({{\mathsf{\sigma }}^{\prime }}_{\mathrm{v}}\right)$) and the cumulative axial strain ($\mathsf{\epsilon }$) as the most significant geomechanical drivers, exhibiting Pearson correlation coefficients $\left|p\right|$ ≥ 0.85 with acoustic activity. In the acoustic domain, the analysis reveals that Signal Strength (${\mathrm{S}}_{\mathrm{s}}$) and cumulative energy ($\mathrm{E}$) flux are the most reliable predictors for volumetric deformation, while the amplitude ($\mathrm{A}$), b-value ($\mathrm{b}$), and average frequency ($\mathrm{F}$) emerge as critical indicators for identifying the transition between spatial rearrangement and the onset of grain fragmentation. Furthermore, the inclusion of dimensionless parameters, particularly earliness ($\mathrm{e}\mathrm{a}\mathrm{r}\mathrm{l}$), enhances model stability by standardising waveform symmetry across varying stress regimes. High-order polynomial regression models (up to the third degree) were derived, demonstrating that the statistical complexity of acoustic signatures allows for the high-fidelity inference of the soil matrix’s initial and state parameters. This methodology establishes a unified mathematical architecture for the in situ characterisation of granular skeletons, balancing computational efficiency with predictive power in intricate geological domains. Full article

Reinforced concrete (RC) buildings are the most common structural system in urbanising regions. In many cases, architectural constraints and uneven distribution of structural elements often create eccentricity between the centre of mass (CM) and the centre of rigidity (CR). This eccentricity may induce torsional effects during earthquakes that can significantly influence structural response and increase seismic vulnerability. This study investigates the impact of in-plan irregularity on the seismic performance of RC buildings using nonlinear numerical analyses. Three-dimensional models of four- and six-storey RC buildings with moment resisting frames were developed in OpenSees, where different levels of irregularity were introduced by artificially shifting the lumped mass to generate controlled eccentricities without modifying the structural configuration. Seismic performance was evaluated using nonlinear incremental dynamic analysis (IDA) based on forty ground motion records under bidirectional excitation. The results indicate that increasing CM–CR eccentricity amplifies inter-storey drift demands and elevates the probability of damage due to intensified torsional stresses. The adverse effect is most pronounced when eccentricity aligns with the direction of lower stiffness, whereas eccentricity in the stiffer direction has a limited impact on severe damage states, particularly for taller buildings. These findings provide valuable insights for risk-informed assessment, retrofitting, and prioritisation of existing plan-irregular RC buildings. Full article

Due to the asymmetry of pass profiles, F-section steel is prone to defects such as overfilling, underfilling, and twisting during production, which significantly deteriorates the dimensional accuracy, mechanical properties, and surface quality of products. To mitigate the occurrence of such defects, this study established a thermo-mechanical coupled three-dimensional finite element model for the finishing rolling process of F-section steel using ABAQUS 2022 incorporating the actual operating conditions of the steel plant’s production line. By analyzing the stress–strain fields of each pass, it was found that the maximum deformation of the rolled piece is concentrated at the junctions of the inner leg with the flange, the inner leg with the web, and the outer leg with the web. Additionally, underfilling was observed at the legs and flanges of the pass in each rolling sequence. Based on these findings, an in-depth analysis was conducted on the effects of friction coefficient, tension configuration, rolling temperature, and web reduction on pass filling degree. Conditions of low friction, small reduction, and high temperature facilitate the smooth filling of metal in the leg cavity; in contrast, conditions of high friction, large reduction, and low temperature promote the filling of surface metal and an increase in spread. Maintaining a low-tension state is a common favorable condition for improving the pass filling degree of both the legs and the surface. When the friction coefficient is 0.2, tension is 0, rolling temperature is 1040 °C, and web reduction is 4 mm, the pass filling degrees of the inner and outer legs reach their maximum values of 99.88% and 99.16%, respectively. When the friction coefficient is 0.4, tension is 0, rolling temperature is 1010 °C, and web reduction is 4 mm, the pass filling degrees of the upper and lower surfaces are maximized, reaching 98.95% and 98.22%, respectively. These findings provide data support and theoretical guidance for addressing defects encountered in F-section steel production. Full article

This research utilizes Laser Doppler Vibrometer (LDV) technology to measure pavement deflection velocity under heavy moving loads at the Virginia DOT Accelerated Pavement Testing (VDOT APT) facility. While LDVs are typically integrated into Traffic Speed Deflectometers (TSDs) for measuring deflection velocities, this research employs a standalone, tripod-mounted LDV to capture highly repeatable data under controlled Heavy Vehicle Simulator (HVS) loading. A three-dimensional viscoelastic finite element (3D-FE) model was developed in Abaqus (version 2016) and calibrated using the LDV-measured deflection velocities and site-specific material properties. The model incorporates asphalt viscoelasticity, three-dimensional nonlinear contact stresses, and continuous loading conditions. Results demonstrate very good agreement between the calibrated 3D-FE model and observed responses, with calculated percentage differences of 0.6% and 3.4% for the maximum and minimum deflection velocity peaks, respectively. These findings, along with a 10% ratio between the standard deviation of the error and the measured signal, validate the model’s accuracy and the effectiveness of LDV instrumentation. This stand-alone application of a TSD-type LDV at an APT facility, to directly measure pavement deflection velocity under a moving load to calibrate a 3D-FE model, represents a key innovative aspect and addresses an identified gap in the literature on LDV-based pavement evaluation techniques. It should be noted that the proposed framework is calibrated for a single pavement structure under controlled loading and environmental conditions, and is applicable to the initial, undamaged state of the pavement. Further validation across different material configurations, environmental gradients, and damage stages is required to generalize the approach. Full article

This study scientifically assessed the safety of the Ming Dynasty official-style timber structure of Taiyuan Chongshan Temple’s Great Mercy Hall, a nationally protected cultural relic. An integrated framework was adopted, including form restoration via 3D laser scanning and manual surveying, damage detection using impedance meters, stress wave tomography and one-dimensional stress wave testing, mechanical analysis with a differentiated material finite element model, and short-term on-site monitoring at risk points. Results showed that the 303.3 mm construction ruler length was restored, with the column grid tilting northwestward; the main structure was hardwood pine, and critical columns had severe localized damage (24% internal damage rate, 13% cross-sectional damage ratio) with 42% residual strength in some members; and the structure remained elastically safe, with material degradation causing 6.3–13.3% linear displacement amplification. Two weak links (eave purlin deflection: 33–37 mm; double-eave golden column axial force concentration: 86.9–88.5 kN) and dougong’s outward inclination due to eccentric compression were identified. Short-term monitoring indicated temperature-driven elastic responses and an 8 mm cumulative residual displacement in the northern single-step beam, and a three-level early warning threshold system was proposed. This study clarified the hall’s state as “overall stable with localized weaknesses”, providing a methodological reference for the preventive protection of similar ancient timber structures. Full article