Search Results (3,676)

Background: Clear aligner therapy (CAT) is widely used, yet safe per-stage rotation in periodontally compromised incisors remains uncertain. This study aims to define tooth position and support specific rotation limits by quantifying periodontal ligament (PDL) stress using finite element analysis (FEA). Methods: Four 3D FEA models (healthy; Stage I–III periodontitis) of maxillary central and lateral incisors were built in ANSYS 2024 R2. Mesial rotations of 1.25–3.0° were imposed on single teeth with a 0.5 mm PET-G aligner and attachments; the posterior segment was fixed. The PDL was modeled as nonlinear. Primary outcomes were peak PDL von Mises stress and total deformation; the mesh convergence was <5%. Results: At 3.0°, the healthy model produced 270.87 kPa (central) and 641.73 kPa (lateral). Stage I plateaued beyond ≈1.75° at ≈221.53 kPa (central) and ≈406.71 kPa (lateral). Stage II showed low central stress (86.20 kPa) but high lateral stress (2763.1 kPa) with greater deformation. Stage III yielded 825.39 kPa (central) and 1321.6 kPa (lateral). Deformation increased from <0.005 µm to ≈8.37 µm for centrals and from <0.005 µm to ≈11.139 µm for laterals with diminishing periodontal support. Conclusions: Safe rotational staging depends on periodontal support and tooth type. The recommended per stage angles are as follows: centrals ≤2.5° in healthy, 1.75° in Stage I, ≤1.0° in Stages II and III; laterals ≤1.75°, ≤1.25°, and ≤1.0°, respectively. Full article

In foundation pit engineering, precise determination of the physical–mechanical parameters of the surrounding rock is essential for reliable simulation of rock deformation and anchor cable forces. A foundation pit engineering project in Shapingba District, Chongqing, was selected as a case study. A numerical model was developed using FLAC3D, and 64 working conditions were designed via orthogonal experiments to serve as training samples. Global optimization inversion of the samples was performed using a BP neural network enhanced by particle swarm optimization. Using selected monitoring data of surrounding rock displacement and anchor cable forces, inversion was conducted to determine the physical–mechanical parameters of the foundation pit surrounding rock, and the FLAC3D model inputs were subsequently updated. Finally, simulated results were validated against field measurements. The maximum relative error of surrounding rock displacement reached 8%, with only 3% at the pit center. The largest settlement occurred in the eastern section, where the relative error was 5%. For anchor cable forces, the maximum relative error was 7.9%. This study employed a PSO-BP neural network to invert the physical–mechanical parameters of the foundation pit surrounding rock and introduced a two-stage validation using measured displacements and anchor cable forces. The approach enhances inversion accuracy and provides a practical reference for similar foundation pit engineering applications. Full article

Background: Congenital talipes equinovarus (clubfoot) affects 1–2 per 1000 newborns worldwide. The Ponseti method, based on staged manipulations and casting, is the gold standard for correction. However, the biomechanical processes underlying these corrections remain poorly understood, as infants rarely undergo imaging. Computational modeling may offer a non-invasive approach to studying correction pathways and exploring novel applications, such as customized casts. Methods: We developed a proof-of-concept framework using iterative finite element analysis (iFEA) to approximate the surface-level geometric corrections targeted in Ponseti treatment. A 3D surface model of a training clubfoot foot was scanned, meshed, and deformed stepwise under applied computational loads. The model was assumed to be homogeneous and hyperelastic, and correction was quantified using Cavus, Adductus, Varus, Equinus, and Derotation angles. We also introduced a secondary adult leg 3D surface model to assess whether model simplification influences correction outcomes, by comparing a homogeneous soft tissue model with a non-homogeneous model incorporating bone structure. Results: In the training model, iFEA generated progressive deformations consistent with Ponseti correction, with mean angular deviations of ±3.2°. In the adult leg model, homogeneous and non-homogeneous versions produced comparable correction geometries, differing by <2° in outcomes. The homogeneous model required less computation, supporting its use for feasibility testing. Applied loads were computational drivers, not physiological forces. Conclusions: This feasibility study shows that iFEA can reproduce surface-level geometric changes consistent with Ponseti correction, independent of model homogeneity. While not replicating clinical biomechanics, this framework lays the groundwork for future work that incorporates clinician-applied forces, pediatric tissue properties, and patient-specific geometries, with potential applications in customized 3D-printed casts. Full article

Foundation deformation prediction on expansive soils involves complex soil-structure interactions and environmental variability. This study develops foundation-specific hybrid modeling approaches for temporal deformation prediction using 974 days of monitoring data from four foundations on medium-expansive soil. Four hybrid architectures were evaluated—Residual-Clustering Hybrid, Elastic Net Fusion, Residual Correction, and Enhanced Robust Huber—optimized through Ridge regression-based feature selection and validated against seven baseline methods. Systematic feature engineering with optimal selection identified foundation-specific complexity requirements. Statistical validation employed bootstrap resampling, temporal cross-validation, and Bonferroni correction for multiple comparisons. Results demonstrated foundation-specific effectiveness with distinct hybrid model performance: Residual-Clustering Hybrid achieved optimal performance for Foundation F1 (R² = 0.945), Elastic Net Fusion performed best for Foundation F2 (R² = 0.947), Residual Correction excelled for Foundation F3 (R² = 0.963), and Enhanced Robust Huber showed strongest results for Foundation F4 (R² = 0.881). Statistical significance was achieved in 35.7% of comparisons with effect sizes of Cohen’s d = 0.259–1.805. Time series forecasting achieved R² = 0.881–0.963 with uncertainty intervals of ±0.654–0.977 mm. Feature analysis revealed temporal variables as primary predictors, while domain-specific features provided complementary contributions. The early warning system achieved F1-scores of 0.900–0.982 using statistically derived thresholds. Foundation deformation processes exhibit strong autoregressive characteristics, providing enhanced prediction accuracy and quantified uncertainty bounds for operational infrastructure monitoring. Full article

Persistent scatterer (PS) pixel selection is crucial in the PS-InSAR technique, ensuring the quality and quantity of PS pixels for accurate deformation measurements. However, traditional methods like the amplitude dispersion index (ADI)-based method struggle to balance the quality and quantity of PS pixels. To adequately select high-quality PS pixels, and thus improve the deformation measurement performance of PS-InSAR, the multi-temporal feature extraction network (MFN) is constructed in this paper. The MFN combines the 3D U-Net and the convolutional long short-term memory (CLSTM) to achieve time-series analysis. Compared with traditional methods, the proposed MFN can fully extract the spatiotemporal characteristics of complex SAR images to improve PS pixel selection performance. The MFN was trained with datasets constructed by reliable PS pixels estimated by the ADI-based method with a low threshold using ∼350 time-series Sentinel-1A SAR images, which contain man-made objects, farmland, parkland, wood, desert, and waterbody areas. To test the validity of the MFN, a deformation measurement experiment was designed for Tongzhou District, Beijing, China with 38 SAR images obtained by Sentinel-1A. Moreover, the similar time-series interferometric pixel (STIP) index was introduced to evaluate the phase stability of selected PS pixels. The experimental results indicate a significant improvement in both the quality and quantity of selected PS pixels, as well as a higher deformation measurement accuracy, compared to the traditional ADI-based method. Full article

Conventional projection systems typically require a fixed spatial configuration relative to the projection surface, with strict control over distance and angle. In contrast, UAV-mounted projectors overcome these constraints, enabling dynamic, large-scale projections onto non-planar and complex environments. However, such flexible scenarios introduce a key challenge: severe geometric distortions caused by intricate surface geometry and continuous camera–projector motion. To address this, we propose a novel image registration method based on global dense matching, which estimates the real-time optical flow field between the input projection image and the target surface. The estimated flow is used to pre-warp the image, ensuring that the projected content appears geometrically consistent across arbitrary, deformable surfaces. The core idea of our method lies in reformulating the geometric distortion correction task as a global feature matching problem, effectively reducing 3D spatial deformation into a 2D dense correspondence learning process. To support learning and evaluation, we construct a hybrid dataset that covers a wide range of projection scenarios, including diverse lighting conditions, object geometries, and projection contents. Extensive simulation and real-world experiments show that our method achieves superior accuracy and robustness in correcting geometric distortions in dynamic UAV projection, significantly enhancing visual fidelity in complex environments. This approach provides a practical solution for real-time, high-quality projection in UAV-based augmented reality, outdoor display, and aerial information delivery systems. Full article

This paper provides an overview of various size-dependent theories based on modified/consistent couple stress and strain gradient theories (CSTs and SGTs), highlighting the development of two-dimensional (2D) refined and advanced shear deformation theories (SDTs) and three-dimensional (3D) pure analytical and semi-analytical numerical methods, including their applications, for analyzing the static and dynamic behaviors of microscale plates and shells made from advanced materials such as fiber-reinforced composites, functionally graded (FG) materials, and carbon nanotube/graphene platelet-reinforced composite materials. The strong and weak formulations of the 3D consistent CST, along with their corresponding boundary conditions for FG microplates, are derived and presented for illustration. A comparison study is provided to show the differences in the results of a simply supported FG microplate’s central deflection, stress, and lowest natural frequency obtained using various 2D size-dependent SDTs and 3D analytical and numerical methods based on the consistent CST. A parametric study is conducted to examine how primary factors, such as the effects of dilatational and deviatoric strain gradients and couple stress, impact the static bending and free vibration behaviors of a simply supported FG microplate using a size-dependent local Petrov–Galerkin meshless method based on the consistent SGT. Influences such as the inhomogeneity index and length-to-thickness ratio are considered. It is shown that the significance of the impact of various material length-scale parameters on the central deflection and its lowest natural frequency (in the flexural mode) of the FG microplate is ranked, from greatest to least, as follows: the couple stress effect, the deviatoric strain gradient effect, and finally the dilatational strain gradient effect. Additionally, when the microplate’s thickness is less than 10⁻⁷ m, the couple stress effect on its static and dynamic behaviors becomes saturated. Conversely, the impact of the dilatational and deviatoric strain gradients consistently influences the microplate’s static and dynamic behaviors. Full article

Polylactic acid (PLA) is an eco-friendly polymer known for its biodegradability and biocompatibility, yet its properties are sensitive to recycling and sterilization. These processes may cause chain scission and structural irregularities, leading to reduced strength, brittleness, or unpredictable deformation. In this study, PLA and recycled PLA (Re-PLA) specimens were produced by FDM 3D printing with different infill rates (25%, 50%, 75%), layer thicknesses (0.15, 0.20, 0.25 mm), and printing orientations (0°, 45°, 90°). Steam sterilization at 121 °C and 1 bar for 15 min simulated biomedical conditions. Mechanical, surface, degradation, and biocompatibility properties were examined using three-point bending, roughness measurements, SEM, and cell viability tests. Results showed that infill rate was the main parameter affecting flexural strength and surface quality, while orientation increased roughness. Sterilization and recycling made deformation less predictable, particularly in St-Re-PLA. SEM revealed stronger bonding at higher infill, but more brittle fractures in PLA and Re-PLA, while sterilized specimens showed ductile features. No visible degradation occurred at any infill level. Regression analysis confirmed that second-order polynomial models effectively predicted flexural strength, with layer thickness being most influential. These findings provide critical insights into optimizing PLA and Re-PLA processing for biomedical applications, particularly in the production of sterilizable and recyclable implantable devices. Full article

The surrounding rocks of roadways are typically subjected to cyclic loading–unloading stress states in underground engineering. In addition, cyclic loads are discontinuous under real working conditions, usually while loading rock mass in a cycle–intermission–cycle manner. Based on the XTDIC 3D (XTOP Three-dimensional Digital Image Correlation) full-field strain measurement system and AE (Acoustic Emission) system, the work performed uniaxial cyclic loading–unloading tests with constant-pressure durations of 0, 0.5, 2, and 6 h. The purpose was to investigate the damage degradation mechanism of sandstone under multi-stage equal-amplitude intermittent cyclic loading and unloading. The results are as follows. (1) As the constant-pressure duration increased, the uniaxial compressive strength of sandstone samples decreased, along with a decline in elastic modulus and a deterioration in stiffness and deformation recovery capacity. (2) The evolution of deformation localization zones became more intense in sandstone samples during cyclic loading and unloading with the increased constant-pressure duration. The maximum principal strain field became more active at failure. Sandstone samples exhibited shear failure accompanied by spalling failure and an increased failure degree. (3) As the constant-pressure duration increased, the damage variable of sandstone samples increased, indicating that the constant-pressure stage promoted the damage degradation of sandstone samples. The above results reveal the damage degradation mechanism of sandstone under multi-stage equal-amplitude intermittent cyclic loading and unloading, which is of significant importance for maintaining the safety of underground engineering. Full article

This study presents an exact analytical investigation into the static response of helical single-walled carbon nanotube (SWCNT) beams based on Eringen’s differential nonlocal elasticity theory, which captures nanoscale effects arising from interatomic interactions. A key contribution of this work is the derivation of the governing equations for helical SWCNT beams, based on the nonlocal Euler–Bernoulli theory, followed by their exact analytical solution using the initial value method. To the best of the authors’ knowledge, this represents the first closed-form formulation for such complex nanostructures using this theoretical framework of nonlocal elasticity theory. The analysis considers both cantilevered and clamped–clamped boundary conditions, under various concentrated force and moment loadings applied at the ends and midpoint of the helical beam. Displacements and rotational components are expressed in the Frenet frame, enabling direction-specific evaluation of the deformation behaviour. Parametric studies are conducted to investigate the influence of geometric parameters—such as the winding angle ($\alpha$) and aspect ratio ($R/d$) and the nonlocal parameter ($R/\gamma$). Results show that nonlocal elasticity theory consistently predicts higher displacements and rotations than the classical local theory, revealing its importance for accurate modelling of nanoscale structures. The proposed analytical framework serves as a benchmark reference for the modelling and design of nanoscale helical structures such as nano-springs, actuators, and flexible nanodevices. Full article

The high hardness and toughness of AISI 4130 alloy present significant challenges during machining, including excessive cutting forces, rapid tool wear, and poor surface finish control. To address these issues, this study combines numerical simulation with turning experiments to systematically investigate the effects of tool geometry and cutting parameters on cutting force, temperature, and surface roughness. Through Deform-3D finite element modeling, one-factor, and orthogonal simulation tests, it was found that the optimal tool geometric combination (λs = 2°, κ_r = 99°, γ₀ = 5°) reduces the cutting forces by 21.86% as compared to the baseline parameters. Experimental validation showed that the agreement between simulated and measured cutting forces was 86.73%–87.8%, with simulated values being 10%–13.27% higher due to idealized boundary conditions. Surface morphological analysis by Bruker Contour Elite K shows that the surface roughness of the workpiece decreases with an increasing cutting speed and increases with an increasing feed rate and depth of cut. The above studies provide a certain research basis for optimizing the tool angle and improving the cutting efficiency. Full article

A novel rolling scheme incorporating an inclined oval-caliber configuration is proposed to enhance plastic deformation mechanisms in the traditional oval–round rolling sequence. Finite Element Method (FEM) simulations were performed using DEFORM-3D to evaluate and optimize this new scheme across multiple objectives: maximizing average effective strain, minimizing strain non-uniformity (captured via the standard deviation of effective strain), and minimizing rolling force. Numerical modeling was conducted for calibration angles of γ = 0°, 25°, 35°, and 45°, from which Pareto-optimal solutions were identified based on classical non-dominance criteria. Pairwise 2D projections of the Pareto front enabled visualization of trade-offs and revealed γ = 35° as the Pareto knee-point, representing the most balanced compromise among high deformation intensity, increased uniformity, and reduced energy consumption. This optimal angle was further corroborated through a normalized weighted sum of the objective functions. The findings provide a validated reference for designing prototype deforming tools and support future experimental validation. Full article

Endodontic rotary file geometries are often obtained using computed tomography (CT) scans, which produce 3D models comprising point clouds and triangulated surfaces. Despite being widely used, this approach has significant limitations; scanned geometries may deviate from the theoretical design due to physical deformation during manipulation, inaccuracies due to the scanner resolution, and the non-parametric nature of the resulting mesh, preventing design modification or parameter extraction. This study proposes a methodology to overcome these limitations by recognizing and reconstructing the scanned geometry. This process involves correcting deformation caused by flexion, applying filtering techniques to minimize scan-induced noise, and identifying key geometric parameters. This enables the generation of a manipulable and accurate CAD model which not only preserves the original design intention but also allows for parametric modifications and advanced finite element analysis. The proposed method bridges the gap between real geometry acquisition and design-based simulation, providing a powerful tool for endodontic instrument evaluation and optimization. Full article

This study introduces a novel numerical approach to analyze the axisymmetric bending behavior of functionally graded (FG) graphene platelet (GPL)-reinforced annular sandwich nanoplates featuring a porous core. The nanostructures are exposed to coupled magnetic and hygrothermal environments. The porosity distribution and GPL weight fraction are modeled as nonlinear functions through the thickness, capturing realistic gradation effects. The governing equations are derived using the virtual displacement principle, taking into account the Lorentz force and the interaction with an elastic foundation. To address the size-dependent behavior and thickness-stretching effects, the model employs the nonlocal strain gradient theory (NSGT) integrated with a modified version of Shimpi’s quasi-3D higher-order shear deformation theory (Q3HSDT). The differential quadrature method (DQM) is applied to obtain numerical solutions for the displacement and stress fields. A detailed parametric study is conducted to investigate the influence of various physical and geometric parameters, including the nonlocal parameter, strain gradient length scale, magnetic field strength, thermal effects, foundation stiffness, core thickness, and radius-to-thickness ratio. The findings support the development of smart, lightweight, and thermally adaptive nano-electromechanical systems (NEMS) and provide valuable insights into the mechanical performance of FG-GPL sandwich nanoplates. These findings have potential applications in transducers, nanosensors, and stealth technologies designed for ultrasound and radar detection. Full article

The Central Yunnan Water Diversion Project (CYWDP) is currently under construction and represents China’s most extensive and geologically challenging water transfer infrastructure, facing significant geohazard risks induced by intensive engineering activities, posing severe threats to its entire lifecycle safety. Therefore, monitoring and spatiotemporal evolution analysis of surface deformation along the CYWDP is critically important. This study presents the first integrated analysis of geometric distortions and multi-dimensional spatiotemporal deformation characteristics along the CYWDP, utilizing both ascending and descending orbit data from Sentinel-1. First, by integrating the Layover-Shadow Mask (LSM) model and R-Index method, we identified geometric distortion types in SAR imagery and evaluated their suitability for deformation monitoring. Subsequently, SBAS-InSAR technology was employed to derive line-of-sight (LOS) deformation information from 124 images (ascending) and 90 images (descending) acquisitions (2022–2024), enabling the identification of significant deformation zones and analyzing their spatial distribution characteristics. Finally, two-dimensional (2D) deformation fields were obtained through the joint inversion of ascending and descending orbit data in typical deformation zones. The results reveal that geometric distortions in Sentinel-1 imagery along the CYWDP are dominated by foreshortening effects, accounting for 35.3% of the study area in the ascending-orbit data and 37.9% in the descending-orbit data. A total of 10 significant deformation-prone areas were detected, and the most pronounced subsidence, amounting to −164 mm/y, was observed in the northern Jinning District (Luoci-Qujiang section), showing expansion trends toward water conveyance infrastructure. This study reveals surface deformation’s multi-dimensional spatiotemporal evolution patterns along the CYWDP. The findings support geohazard mitigation and provide a methodological reference for safety monitoring of major water conservancy projects in complex geological environments. Full article