Search Results (2,770)

Biosensors are rapidly emerging as a pivotal technology with far-reaching implications in fields such as medical diagnostics, environmental analysis and pharmaceutical research. Among the various biosensing platforms, Graphene Field-Effect Transistor (GFET) biosensors have attracted considerable interest due to their exceptional sensitivity, potential for cost-efficient fabrication, and compatibility with scalable manufacturing processes. This work computationally addresses sensing mechanisms and design strategies associated with GFET-based biosensors, with a focus on the influence of electrolyte gating on device performance, tackling the role of graphene’s quantum capacitance and testing the electrical detection of β2-microglobulin as a case study. Molecular dynamics is used to rationalize the details of the physisorption of a single biomolecule onto the graphene surface, while finite element method simulations are employed to evaluate device sensitivity and figure of merit. Results reveal that incorporating quantum capacitance into the model leads to a Sensitivity-over-FWHM_min figure of merit exceeding 100 L/g being achievable for a β2-microglobulin concentration of 0.001 g/L. These computational outcomes highlight the relevance of quantum-electrostatic effects in GFET biosensor performance and suggest potential routes towards the optimization of graphene-based electronic biodetector engineering. Full article

The cold V-bending of Grade 4 titanium bone plates at room temperature is a critical forming operation that must be optimized to control strain localization and springback and to reduce the risk of surface cracking. This study proposes a combined experimental, numerical, and artificial intelligence-based approach for the analysis and optimization of this process. Tensile tests were first performed to characterize the mechanical behavior of the material and to calibrate the constitutive law used in the finite element model. The numerical model was then validated through comparison with experimental V-die bending results. A design of experiments was subsequently applied to investigate the effects of sheet thickness, die shoulder distance, punch radius, and punch displacement on two key responses: equivalent plastic strain (PEEQ) and spring back. The results show that sheet thickness and die shoulder distance are the most influential parameters. In addition, artificial neural network models were developed to predict process responses, and Bayesian regularization showed the best overall predictive performance among the tested ANN training algorithms, namely Levenberg–Marquardt, Bayesian regularization, and scaled conjugate gradient. The proposed framework provides a basis for optimizing the forming of titanium orthopedic implants. Full article

This article presents a systematic analysis of the application of advanced mathematical and computational approaches in dental bioengineering, with a focus on biomaterials processing and machining-related technologies. The aim is to critically synthesize current knowledge on the use of numerical simulations, statistical modeling, and algorithm-based methods in the analysis and optimization of technological processes in dentistry. The review was conducted following the PRISMA framework to ensure a transparent and reproducible selection of relevant studies addressing the intersection of dental applications, manufacturing processes, and computational modeling. The results reveal that the current research does not constitute a unified modeling framework, but rather a heterogeneous set of approaches targeting specific aspects of biomaterial processing. The analyzed studies demonstrate the application of finite element analysis, empirical statistical models, and geometry-based computational methods, particularly in processes such as drilling and grinding of ceramic dental materials. These approaches enable detailed analysis of mechanical and thermal loading conditions, as well as partial optimization of process parameters. However, their applicability is often limited by their empirical nature, lack of integration, and insufficient linkage to real-time process control. The synthesis highlights a significant research gap in the development of integrated and multiphysics modeling frameworks capable of combining mechanical, thermal, and geometrical aspects of machining processes. Future research should focus on the implementation of digital twins, adaptive process control, and personalized modeling strategies to enhance the accuracy, efficiency, and predictability of dental biomaterial processing. Full article

The development of electric bus superstructures requires an integrated engineering approach combining structural design, numerical simulation, experimental validation and durability assessment. This need is particularly important for electric buses, where heavy roof-mounted battery systems and auxiliary components influence structural load paths, fatigue durability and rollover crashworthiness. This paper presents a measurement-supported workflow for the development of a virtual electric bus superstructure model, including finite element analysis, multibody dynamics simulations, operational load assessment, fatigue-oriented evaluation and rollover crashworthiness analysis. The finite element model is used to assess static load cases, modal properties and structural response under selected design conditions. A multibody vehicle model with nonlinear suspension characteristics is applied to simulate representative operating scenarios and to support the definition of dynamic load cases. Operational measurement data from previous work are used as a basis for realistic load characterization. Experimental torsional stiffness and modal tests are used to validate the numerical model. The main contribution of the study is the integration of these numerical, experimental and operational-data-based activities into a consistent early-stage verification process. The proposed workflow supports early identification of critical structural regions, assessment of design modifications and reduction in prototype-based design iterations. Full article

Induction heating is widely used in industrial processes such as forging, hardening, and additive manufacturing, but its accurate numerical simulation requires coupled electromagnetic and thermal finite element analyses with nonlinear, temperature-dependent material properties. This work proposes a deep learning surrogate model based on a convolu-tional neural network for TEAM Workshop Problem 36, a reference benchmark for nonlinear magneto-thermal induction heating. A database of more than 40,000 finite element solutions was generated by varying the supply current from 2 to 6 kA and the frequency from 2 to 6 kHz, while accounting for transient nonlinear effects, including the Curie transition. The network, composed of 24 layers with transposed convolutions, batch normalization, and dropout, maps current, frequency, and time to radial temperature distributions in the steel billet. For most operating conditions, the model achieves mean absolute percentage errors of about 6–7% for radial line in the middle of the billet and about 10% for radial line close to the billet end. Larger discrepancies occur during the early heating stage and near the Curie temperature. Prediction times are reduced by three to four orders of magnitude with respect to a single finite element analysis. The results indicate that the proposed surrogate enables fast temperature estimation for optimization, digital twins, and closed-loop control of induction heating systems. Full article

It is essential to exercise control over the environmental impact of deep excavation construction in soft soil areas from the perspective of deformation in order to ensure engineering safety. A three-dimensional finite element model of the foundation pit was developed, thereby creating a comparison between the results of the numerical simulation and the actual on-site monitoring data. This process served to validate the precision of the simulations. The focal point of the study pertained to the three-dimensional effects of support structure deformation and ground settlement during excavation. A comprehensive analysis of the spatial distribution and evolutionary patterns of underground diaphragm wall deformation and ground settlement behind the wall at varying excavation depths was conducted. The results demonstrated that both support structure deformation and ground settlement behind the excavated structure exhibited substantial spatial effects. In particular, larger deformations were observed near the symmetrical plane of the excavation centre. Conversely, greatly smaller deformations were observed in the corners of the excavation. The research findings aim to provide useful references for practical engineering projects. Full article

This study focused on burn-through leakage at girth welds of mechanically lined pipe (MLP) during field service. Field failure analysis, experimental tests, and numerical simulation were combined to investigate the process parameters of seal welding and multi-pass girth butt welding. Macroscopic metallography and energy dispersive spectroscopy (EDS) of failed specimens showed that excessive welding heat input (high current) caused severe expansion of the heat-affected zone (HAZ) and significant element dilution. The results indicated that the HAZ width of the solid-wire girth weld increased markedly from 1.312 mm to 2.247 mm under high-current conditions. Meanwhile, the Fe mass fraction in the root pass sharply increased to 33.66%, while key corrosion-resistant elements such as Cr and Ni were greatly reduced, which directly led to local pitting corrosion and perforation leakage. In addition, a moving heat source model was established in Abaqus 2024 to simulate the multi-pass welding process. The results showed that strong stress concentration developed at the groove root and the interface between the backing steel pipe and corrosion-resistant liner during repeated thermal cycles. The maximum von Mises stress reached 686.56 MPa during the second butt welding pass. After final cooling, the residual hoop tensile stress and axial tensile stress at the center of the inner surface reached 500–550 MPa and 480–510 MPa, respectively. By correlating microscopic compositional evolution with the macroscopic residual stress field, this study revealed the weld failure mechanism of MLP joints. The proposed finite element method can also be used as an efficient tool to predict the effects of welding speed, current, and voltage on residual stress, providing guidance for field welding procedure optimization and pipeline structural integrity assessment. Full article

This study investigates the reliability of power-terminal solder joints in intelligent power modules (IPMs) subjected to thermal cycling, random vibration, and packaging/assembly-induced deformation. Fifty IPMs were tested under temperature cycling from −55 °C to 125 °C and random vibration from 20 to 2000 Hz, and the experimental observations were combined with finite element simulations of thermal, vibration, and deformation loads. The modules survived 200 temperature cycles in the free state, whereas functional abnormalities occurred after board-level assembly and subsequent environmental loading. Simulation results showed that random vibration produced limited solder-layer stress because the first structural mode was above the excitation range, while packaging and PCB deformation markedly increased the initial stress of the power-terminal solder joints. When local deformation reached approximately 0.5 mm, the calculated solder-pad stress reached or exceeded the shear-strength risk range, consistent with the failure tendency observed in highly deformed modules. Weibull analysis further indicated a fatigue-dominated failure process with an increasing failure rate. These findings suggest that deformation control, package stiffness improvement, and assembly flatness management are critical for improving the reliability of IPM power-terminal solder joints. Full article

The automotive panoramic roof exhibits a large-size and thin-wall geometry, with a length-to-thickness ratio approaching the thousand level. This geometric feature makes its forming quality highly sensitive to forming conditions. During the glass molding process, variations in temperature evolution, loading, and cooling parameters may lead to residual stress accumulation and springback deformation, thereby affecting dimensional accuracy and final forming quality. In this study, a full-process finite element model was established and combined with an L16(4^5) orthogonal design to investigate the effects of five key process parameters—heating temperature, holding time, quenching air velocity, quenching air pressure, and quenching time—on the mean residual stress and mean springback displacement in the glass molding process (GMP). The results showed that, within the given parameter ranges, heating temperature, holding time, and quenching time had relatively pronounced effects on the mean residual stress; the mean residual stress was relatively low when the heating temperature was 680 °C, the holding time was 3 s, and the quenching time was 12 s. Heating temperature, quenching air velocity, and quenching time had relatively pronounced effects on the mean springback displacement; the mean springback displacement was relatively low when the heating temperature was 677.5 °C, the quenching air velocity was 13 m/s, and the quenching time was 10 s. Based on the orthogonal analysis, regression models for the mean residual stress and mean springback displacement were further developed, and parameter combinations were screened using the NSGA-III method. Experimental validation showed that the relative error of the mean residual stress was controlled within 15%, indicating that the established model could, to some extent, capture the relationship between process parameters and forming quality indicators, thereby providing guidance for precision forming and process optimization of large-scale thin-walled automotive panoramic roofs. Full article

To address the issues of insufficient pre-dispersion in the classification zone and inadequate powder-processing capacity in traditional turbine-type air classifiers, this paper proposes a bottom-fed vertical triple-cage classifier. Numerical simulations were performed using the finite element analysis software ANSYS FLUENT to compare and analyze the influence of the classifier chamber structure on flow patterns and classification performance. The results reveal that when the top diameter of the classification chamber is relatively large, with a top-diameter-to-rotor-diameter ratio of 1.45–1.50, the energy consumption of the rotating cage increases, and the scale of vortices within the classification zone increases significantly. Conversely, when this ratio falls within the range 1.30–1.35, wear on the chamber walls becomes markedly more severe. Among the tested configurations, the T-C-type chamber, which features a ratio of 1.40, proved to be the optimal structure, delivering a separation sharpness of 0.71 and a cut size (Dc) of 22.4 µm. This study provides a theoretical basis for the structural optimization design of such classifiers. Full article

This study introduces the design process and fabrication method of a soft pneumatic silicone-based exosuit intended to assist human elbow extension and flexion movement for rehabilitation. First of all, an integrated fabrication method is developed to replace the step-by-step casting and cloth fiber layer, using a 3D-printed PVA mold in silicone casting to ensure the airtightness of the silicone actuator, and a carbon fiber woven mesh is used as the base plate of the actuator to improve its bending performance. Then, the finite element analysis is used to optimize the geometric parameters, hardness, and the number of air chambers for the exosuit structure. The experimental evaluation confirms that the exosuit achieves a bending angle of 112 degrees without any load and 71 degrees with a load of 2 kg. Combining with the PI angular controller, the system limits the maximum absolute tracking error to 4.29 degrees. These results also suggest the proposed exosuit is a promising candidate for practical rehabilitation tasks. Full article

In underground engineering, the dynamic failure mechanisms of rock masses containing openings under impact loading are of vital importance. This study systematically investigates the effects of opening shape, size, and orientation on the dynamic behavior of red sandstone. Dynamic impact tests are first performed using a split Hopkinson pressure bar together with high-speed photography and digital image correlation for full-field strain and crack monitoring. A two-dimensional combined finite–discrete element (FDEM) model is then developed to reproduce the dynamic failure process. It is found that the opening size significantly affects the dynamic compressive strength, while the opening shape dictates crack initiation and propagation. Circular openings induce symmetric cracking, square openings cause corner-dominated cracks, and horseshoe-shaped openings produce asymmetric failure whose dominant side depends on the rotation angle. The FDEM model established in this study successfully reproduces the main crack paths and failure modes observed in experiments, which provides a powerful tool for the analysis of rock dynamic failure. Moreover, the results in this study also provide practical engineering guidance for the reinforcement and support measures for different opening shapes. Full article

Stenting is a minimally invasive treatment used in managing peripheral artery disease (PAD). However, clinical challenges persist, including in-stent thrombosis and restenosis, primarily driven by axial foreshortening or elongation and suboptimal balance between radial stiffness and flexibility inherent to conventional stent designs. This study proposes an innovative arrow-shaped geometry exhibiting zero Poisson’s ratio (ZPR) behaviour for 3D-printed self-expanding Nitinol stents. The complete stent deployment process was modelled using finite element analysis (FEA), including radial crimping and subsequent expansion to enable systematic parametric investigation while accounting for µ-3D printing constraints. Response surface methodology (RSM) rigorously evaluated mechanical performance, defining peak stress, chronic outward force (COF), radial resistive force (RRF), and foreshortening (FS) as constraint and objective functions within the optimisation framework. The optimised ZPR stent achieved favourable performance: extremely low foreshortening (|FS| ≤ 0.12%), representing outstanding axial stability compared with previously reported self-expanding stents, and a well-balanced radial response with ~50% higher radial strength than positive Poisson’s ratio (PPR) structures, while 16.67% lower than negative Poisson’s ratio (NPR) counterparts. These results highlight the ZPR stent’s capability to minimise axial deformation while maintaining adequate radial support, highlighting substantial potential for precise, stable deployment in PAD applications. Full article

This study investigates the application of advanced metal additive manufacturing (AM) and topology optimization for the development of a structurally efficient and lightweight 3U nanosatellite frame. Payload weight is a critical factor in space mission costs; therefore, a stock 3U CubeSat design was subjected to structural optimization using specialized Generative Design Software. The optimized model was fabricated using Powder Bed Fusion—Direct Metal Laser Sintering (PBF-DMLS) on an EOS M290 metal printer with AlSi10Mg aluminum alloy. While AlSi10Mg differs in ultimate tensile strength from traditional wrought aerospace alloys, it was selected to evaluate the baseline feasibility of this application. To evaluate manufacturability and preliminary performance, Finite Element Analysis (FEA), including structural and modal response analyses, was conducted. While the optimized design successfully achieved a 53% mass reduction (from 333 g to 155 g) and met the 30 Hz minimum fundamental frequency requirement, static analysis indicated a maximum simulated stress of 287 MPa. Because this exceeds the material’s nominal yield strength of 220 MPa, localized plastic deformation is predicted in the bare-frame configuration under maximum launch loads. This necessitates further design iterations and full-assembly simulations, incorporating the load-sharing effects of integrated panels prior to physical qualification. Post-processing successfully met JAXA dimensional and surface roughness requirements. Ultimately, this study serves as a foundational manufacturability baseline, demonstrating the applicability of PBF-DMLS for nanosatellites. Full article

To address safety hazards such as line damage and operational instability caused by icing on high-voltage overhead transmission lines, this study conducts numerical simulation research on wire vibration de-icing based on the ANSYS finite element platform. Using a 100 m span transmission line as the research model, 49.8 m ice-covered sections are set on both sides of the line, and the 0.4 m range in the middle is designated as the concentrated excitation force area of the vibration motor. By applying intermittent harmonic loads in the excitation stage, the process of mechanical vibration de-icing is accurately reproduced. At the same time, life and death element technology is introduced to remove ice-covered units with stress exceeding the critical failure threshold, accurately realizing the dynamic simulation of the entire process of ice-covering cracking and detachment. This study selects resonance frequency bands that are suitable for the structural characteristics of the transmission line through static analysis, modal analysis, and harmonic response analysis, and preliminarily locks in candidate excitation frequencies. Combined with transient dynamics simulation, the optimal excitation frequency for vibration de-icing of transmission lines is determined by comprehensively considering the efficiency of de-icing and the safety constraints of conductor dancing. A method for determining the optimal de-icing frequency based on multi-step finite element analysis has been developed, which can provide theoretical support and simulation reference for the structural design, frequency matching, and operational parameter optimization of mechanical vibration de-icing devices for high-voltage transmission lines and overhead cables. Full article