Search Results (3,014)

Shield tunnels in operation are often affected by complex geological conditions, environmental factors, and structural aging, leading to cumulative damage in the segments and, consequently, increased deformation that compromises structural safety. To investigate the deformation behavior of tunnel linings under random damage conditions, this study integrates finite element numerical simulation with deep learning techniques to analyze and predict the deformation of shield tunnel segments. First, a refined three-dimensional finite element model was established, and a random damage modeling method was developed to simulate the deformation evolution of tunnel segments under different damage ratios. Additionally, a statistical analysis was conducted to assess the uncertainty in deformation caused by random damage. Furthermore, this study introduces a convolutional neural network (CNN) surrogate model to enable the rapid prediction of shield tunnel deformation under random damage conditions. The results indicate that as the damage ratio increases, both the mean deformation and its variability progressively rise, leading to increased deformation instability, demonstrating the cumulative effect of damage on segment deformation. Moreover, the 1D-CNN surrogate model was trained using finite element computation results, and predictions on the test dataset showed excellent agreement with FEM calculations. The surrogate model achieved a correlation coefficient (R²) exceeding 0.95 and an RMSE below 0.016 mm, confirming its ability to accurately predict the deformation of tunnel segments across different damage conditions. To the best of our knowledge, the finite-element–deep-learning hybrid approach proposed in this study provides a valuable theoretical foundation for predicting the deformation of in-service shield tunnels and assessing structural safety, offering scientific guidance for tunnel safety evaluation and damage repair strategies. Full article

This paper presents a simple thermoelectrical temporal surface method for numerically studying the appearance of a dry band on a polluted insulator. The proposed method combines an empirical expression of the pollution layer surface conductivity, expressed as a function of the temperature and equivalent salt deposit density (ESDD), and a surface approach for modeling the pollution layer, using thermoelectrical temporal simulations based on the finite element method (FEM). Using different material substrates, pollution layer thicknesses, and ESDD levels, the reliability and limitations of the simple thermoelectrical numerical model have been studied. The numerical results obtained demonstrated that the proposed thermoelectrical model can dynamically simulate the dry band appearance in accordance with the experimental results in terms of the temporal evolution of the temperature and the pollution layer resistance, as well as the evolution of the voltage drop and E-field along the dry band formation zone. The results also demonstrate the influence of the material substrate and the pollution layer thickness, which directly influence the thermal aspect of the dry band formation. The simple thermoelectrical numerical surface model was used to study the dry band appearance on a uniformly polluted 69 kV insulator. The results obtained enabled a dynamic simulation of the appearance of the first dry band, which appeared in the middle of the insulator, and to deeply investigate the evolution of the surface temperature, electric potential, and E-field distributions along the insulator. The proposed simple thermoelectrical model combined with the empirical model is able to simulate the influence of a non-uniform pollution layer. Hence, the proposed model provides a simple numerical tool for studying the evolution of the potential and E-field distributions along uniformly and non-uniformly polluted insulation equipment to identify the probability of a region of high dry band appearance relative to the insulator material and geometry. This can aid in the development of new types of mitigation methods to improve the performance of all types of insulators under polluted conditions. Full article

The wear of hip prostheses represents a significant challenge for the longevity and functionality of joint implants. Recent studies have explored surface texturing of prostheses as a strategy to enhance tribological performance. This study aims to evaluate the impact of textured ceramic surfaces with dimples on wear and friction reduction in ceramic-on-ceramic (CoC) prostheses. Materials and Methods: Three-dimensional models of ceramic surfaces with and without dimples were created. Contact pressure was analyzed and wear volume was estimated using Archard’s law. Simulations were conducted using finite element methods (FEM) under various loading conditions. Results: Numerical simulations demonstrated that the wear rate for the dimpled femoral head was 0.2369 mm³/year, compared to 0.286 mm³/year for the smooth counterpart, highlighting a wear reduction of 17.2%. Conclusions: The integration of textured surfaces with dimples in ceramic prostheses can substantially improve their functionality and durability, representing a promising approach to addressing the issues associated with hip prosthesis wear. Full article

This study investigates the optimization of thickness distribution in simply supported and cantilever plates to maximize gaps between adjacent natural frequencies. The research employs a genetic algorithm (GA) as the primary optimization tool, with the finite element method (FEM) integrated for structural dynamics analysis. The optimization process focuses on tailoring the plate thickness (stiffness) while maintaining fixed overall dimensions. The study considers square and rectangular plates with two boundary conditions: simply supported and cantilever. The optimization targets gaps between the first three natural frequencies. The GA-based optimizer demonstrates effectiveness in increasing the relative separation between neighboring natural frequencies, as defined by the fitness function. Compared to the reference individuals, the optimized individuals achieve objective function values from 0.25 to 2.5 times higher. The GA optimization tool is also compared with an alternative optimization tool achieving up to 35% better results. This research contributes to the field of structural dynamics by demonstrating the potential of genetic algorithms in optimizing plate designs for enhanced vibrational characteristics. Such optimization is particularly relevant in civil engineering, where plate elements are widely used, and where controlling dynamic properties can improve serviceability and reduce the risk of resonance under operational or environmental loads. The findings have implications for various engineering applications where controlling dynamic properties of plate structures is crucial. Full article

This paper presents an experimental and numerical investigation of the axial compression behavior of perforated cold-formed steel upright profiles commonly used in pallet racking systems. The primary objective is to examine how slenderness influences the failure modes and load-bearing capacity of these structural elements. Three column lengths, representative of typical vertical spacing in industrial rack systems, were tested under pin-ended boundary conditions. All specimens were fabricated from 2 mm thick S355 steel sheets, incorporating web perforations and a central longitudinal stiffener. Experimental results highlighted three distinct failure mechanisms dependent on slenderness: local buckling for short columns (SS-340), combined distortional–flexural buckling for medium-length columns (MS-990), and global flexural buckling for slender columns (TS-1990). Finite Element Method (FEM) models developed using ANSYS Workbench 2021 R1 software accurately replicated the observed deformation patterns, stress concentrations, and load–displacement curves, with numerical results differing by less than 5% from experimental peak loads. Analytical evaluations performed using the Effective Width Method (EWM) and Direct Strength Method (DSM), following EN 1993-1-3 and AISI S100 specifications, indicated that EWM tends to underestimate the ultimate strength by up to 15%, whereas DSM provided results within 2–7% of experimental values, especially when the entire net cross-sectional area was considered fully effective. The originality of the study is the comprehensive evaluation of full-scale, perforated, stiffened cold-formed steel uprights, supported by robust experimental validation and detailed comparative analyses between FEM, EWM, and DSM methodologies. Findings demonstrate that DSM can be reliably applied to perforated sections with moderate slenderness and adequate web stiffening, without requiring further local reduction in the net cross-sectional area. Full article

Buffer stops have always been installed on blind tracks to mitigate the hazards associated with overruns due to insufficient or wrong braking. Conventional buffer stops fixed to the rails may absorb only limited energy while Energy-Absorbing Buffers Stops (EABS) dissipate higher energy hydraulically and/or by friction from sliding blocks clamped to the rail head. The assessment of EABS performances in terms of maximum stopping distance and maximum allowed deceleration is usually performed by using the common kinematic rules of motion and considering the overrunning train as a single mass hitting the buffer stop. This paper studies the dynamic characteristics of the collision of entire trains with a friction EABS applying a Longitudinal Train Dynamics (LTD) approach. Several realistic scenarios using the UIC approved TrainDy software were simulated considering various train compositions, with different types of vehicles (locomotives, freight wagons and passenger coaches) and different kinds of buffers. The results show that high dynamic loads are exerted on the vehicles within the train, while the average deceleration and the stopping distance are not greatly influenced when compared with a simpler Finite Element Method (FEM) approach that does not consider the train composition. The progressive application of the EABS braking force increases the stopping distance but can reduce the peak deceleration of about 50%. The results may be used to tune the design parameters of friction EABS according to the currently available specifications and standards for rolling stock structural assessment considering that no international standards for EABS exist currently. Full article

Dual-mode sensors are currently facing difficulties in achieving independent sensing of parameters as well as low sensitivity. In this paper, we propose a dual-mode sensor using the finite element method (FEM) based on a coupled silver–PDMS–gold (SPG) cavity. We coupled a square ring resonant cavity with a double-ring resonant cavity structure, thus identifying a unique resonant cavity structure. The square ring resonator is made of silver and a double-ring resonant cavity filled with PDMS. Our proposed SPG cavity can independently achieve temperature and refractive index sensing. The SPG cavity enables us to obtain the highest biosensing sensitivity of about 1030 nm/RIU and the highest temperature sensitivity of about 216 pm/K. In addition, SPG cavities have excellent tolerances for geometric parameters. Our results provide new methodologies for metasurface design for dual-mode sensing. Full article

This study presents a preliminary analysis of an innovative system that combines indoor air conditioning with water recovery and storage. The device integrates Peltier cells with a horizontal Earth-to-Air Heat Exchanger (EAHX), exploiting the ground stable temperature to enhance cooling and promote condensation. Warm, humid air is pre-cooled via the geothermal pipe, then split by a fan into two streams: one passes over the cold side of the Peltier cells for cooling and dehumidification, while the other flows over the hot side and heats up. The two airstreams are then mixed in a water storage tank, which also serves as a thermal mixing chamber to regulate the final air temperature. The analysis investigates the influence of soil thermal conditions on condensation within the horizontal pipe and the resulting cooling effect in indoor spaces. A hybrid simulation approach was adopted, coupling a 3D model implemented in COMSOL Multiphysics^® with a 1D analytical model. Boundary conditions and meteorological data were based on the Typical Meteorological Year (TMY) for Palermo. Two scenarios were considered. In Case A, during the hours when air conditioning is not operating (between 11 p.m. and 9 a.m.), air is circulated in the exchanger to pre-cool the ground and the air leaving the exchanger is rejected into the environment. In Case B, the no air is not circulated in the heat exchanger during non-conditioning periods. Results from the June–August period show that the EAHXs reduced the average outdoor air temperature from 27.81 °C to 25.45 °C, with relative humidity rising from 58.2% to 66.66%, while maintaining nearly constant specific humidity. The system exchanged average powers of 102 W (Case A) and 96 W (Case B), corresponding to energy removals of 225 kWh and 212 kWh, respectively. Case A, which included nighttime soil pre-cooling, showed a 6% increase in efficiency. Condensation water production values range from around 0.005 g/s with one Peltier cell to almost 0.5 g/s with seven Peltier cells. As the number of Peltier cells increases, the cooling effect becomes more pronounced, reducing the output temperature considerably. This solution is scalable and well-suited for implementation in developing countries, where it can be efficiently powered by stand-alone photovoltaic systems. Full article

A novel mechanism for seamless morphing trailing edge flaps is presented in this paper. This bio-inspired morphing concept is derived from an elephant’s trunk and is called the Elephant Trunk Mechanism (ETM). The structural flexibility of an elephant’s trunk and its ability to perform various types of deformations make it a promising choice in morphing technology for increasing the performance of continuous and smooth downward bending deformation at a trailing edge. This mechanism consists of a number of tooth-like elements attached to a solid wing box; the contractions of these tooth-like elements by external actuation forces change the trailing edge shape in the downwards direction. The main actuation forces are applied through wire ropes passing through tooth-like elements to generate the desired contractions on the flexible teeth. A static structural analysis using the Finite Element Method (FEM) is performed to examine this novel morphing concept and ensure its structural feasibility and stability. Topology optimization is also performed to find the optimum configuration with the objective of reducing the structural weight. The optimized mechanism is then attached to the flap section of a UAS-S45 wing. Finally, a skin analysis is performed to find its optimum skin material, which corresponds to the requirements of the morphing flap. The results of structural analysis and topology optimization reveal the reliability and stability of the proposed mechanism for application in the Seamless Morphing Trailing Edge (SMTE) flap. The optimization results led to significant improvements in the structural parameters, in addition to the desired weight reduction. The ETM maximum vertical displacement increased by 8.6%, while the von Mises stress decreased by 10.43%. Furthermore, the factor of safety improved from 1.3 to 1.5, thus indicating a safer design. The mass of the structure was reduced by 35.5%, achieving the primary goal of topology optimization. Full article

Bulk Acoustic Wave (BAW) resonators are essential components in modern RF communication systems due to their high selectivity and quality factor. However, spurious resonances caused by Lamb wave mode propagation along the in-plane directions degrade the filter performance. Traditional Finite Element Method (FEM) simulations provide accurate modeling but are computationally expensive, especially for arbitrarily shaped resonators and solidly mounted resonators (SMRs), whose stack of materials is composed of many thin layers of different materials. To address this, we extend a previously published model (named the Quasi-3D model), which employs the Transmission Line Matrix (TLM) method, enabling efficient simulations of complex geometries with more precise meshing. The new approach allows us to simulate different geometries, and we will show several apodized geometries with the aim of minimizing the lateral modes. In addition, the proposed approach significantly reduces the computational cost while maintaining high accuracy, as validated by FEM comparisons and experimental measurements. Full article

This study proposes a new method of symmetrical stirring using an anchor paddle to improve the heating uniformity of liquids. To simulate the complex physical process of microwave heating a fluid while stirring it, the finite element method (FEM) and the arbitrary Lagrangian–Eulerian (ALE) method were utilised to model the interactions between electromagnetics, heat transfer, and fluid flow. The temperature coefficient of variation (COV) of the water when subjected to microwave heating and the symmetrical stirring paddle decreased by an 11.2–81.5% compared to that achieved by the traditional rotating turntable method, and it further decreased as the stirring frequency increased. This implies that the stirring method performed more favourably than the rotation method in improving the uniformity of the microwave heating. The distributions of the three physical fields indicated that symmetrical stirring enhanced the axial fluid flow and heat transfer, reducing the large intrinsic temperature difference along the vertical direction. Furthermore, the computation results were validated experimentally, showing that the proposed method is sufficiently accurate for evaluating the uniformity of microwave heating. Full article

Measuring the soil’s deformation and strength during loading is essential when evaluating saturated, undisturbed soft clays with the triaxial test apparatus. A photogrammetry method has been developed to measure total and localized volume changes on saturated, undisturbed soft clays during triaxial testing. In this study, an application of the photogrammetry method is presented by performing a series of triaxial tests with different confining pressures on saturated undisturbed soft clays. Three-dimensional numerical simulations of soft clay deformation are conducted using finite element analysis (FEM) software. The research paper showed that the photogrammetry method delivers a more accurate representation of the soil sample’s deformation, as conventional tests and simulations tend to overestimate the deviator stress values relative to photogrammetry slightly. The simulation from FEM results show a strong relationship with the localized deformation data obtained through photogrammetry. This photogrammetry method provides valuable theoretical insights and practical uses in engineering applications. Full article

Magnetic separation is an important method in the processing process, and its essence is the targeted dispersion of the mineral processing slurry pulp in the magnetic field space. The slurry is a complex multiphase fluid system with continuous phase carrying a large number of discrete phase particles, in which the magnetic particles agglomerate, migrate, and disperse under the dominance of magnetic force. In this process, there is nonlinear and unstable dynamic coupling between the continuous phase (liquid) and the discrete phase (solid particles) and between the discrete phases. In this paper, a dynamic cyclic multi-dipole magnetic moment algorithm with a higher calculation accuracy is innovatively proposed to calculate the magnetic interaction force between particles. Moreover, the P-E magnetization model suitable for a two-dimensional uniform magnetic field is further improved and optimized to make it applicable to a three-dimensional gradient magnetic field. Finally, based on the coupling of the Finite Element Method (FEM), Computational Fluid Dynamics (CFDs), and Discrete Element Method (DEM), a dynamic coupling model capable of accurately simulating the magnetic separation process is developed. This model can be used to study the separation behavior of particles under a multiphase flow and multi-force field and to explore the motion behavior of magnetic particles. Full article

The condition monitoring of gearboxes is crucial to ensuring the reliability and efficiency of modern industrial machinery. The accurate estimation of Time-Varying Mesh Stiffness (TVMS) is a key aspect of modeling gear meshing behavior and generating vibration signals used for fault diagnosis. In this study, TVMS is calculated by using the Refined Finite Element Method (R-FEM), which captures detailed gear-body compliance and distributed load effects. The dynamic model of a two-stage gearbox is then used to generate vibration responses under both healthy and faulty conditions. A comprehensive parametric sensitivity analysis is conducted on critical gear modeling parameters, including tooth profile deviations, mesh convergence in contact zones, assembly tolerance-induced interaxial variations, load-dependent stiffness variations, and hub-radius effects. Experimental validation using a gearbox test bench confirms that the proposed methodology accurately reproduces fault-specific harmonic components. These results indicate that the hybrid FEM–dynamic modeling approach effectively balances accuracy and computational efficiency, thereby providing a robust framework for advanced fault detection and maintenance strategies in gear systems. Full article

In this study, Artificial Neural Networks (ANN) were employed to develop a Digital Twin (DT) of the Rotary Friction Welding (RFW) process. The neural network models were trained to predict the peak temperature generated during the welding process of dissimilar Ti Grade 2/AA 5005 joints over a temperature range of 20–640 °C. This prediction was based on a parametric numerical model of the RFW process constructed using the Finite Element Method (FEM) within the ADINA System software. Numerical simulations enabled a detailed analysis of the temperature distribution within the weldment. Accurate temperature predictions are essential for assessing the mechanical properties and microstructural integrity of the welded materials. Artificial Intelligence (AI) models, trained on historical data and real-time inputs, dynamically adjust critical process parameters—such as rotational speed, axial force, and friction time—to maintain optimal weld quality. A key advantage of employing AI-augmented DT systems in the RFW process is the ability to conduct real-time (less than 0.1 s) optimization and adaptive control. By integrating a Genetic Algorithm (GA) with the DT algorithm of the RFW process, the authors developed an effective tool for analyzing parameters such as axial force and rotational speed, in order to determine the optimal welding conditions, which translates into improved joint quality, minimized defects, and maximized process efficiency. Full article