Finite Element Simulation Model Research Articles

Dynamic Response and Damage Assessment of Partially Confined Metallic Cylinders Under Transverse Blast Loading

An analysis of the dynamic response and damage assessment of partially confined metallic cylinders under transverse air-blast loading is presented in this paper. The examination of the blast shock wave load distribution and the consequences of standoff distances on the plastic deformation of cylinders was conducted with meticulous attention in the experimental testing. The charges of TNT were determined to have masses of 16.3 kg and 29.5 kg, while the distances at which they were placed from the target varied between 1.5 m and 4.25 m. Three unique deformation modes were found to exist in the unilaterally supported cylinder, all of which were directly connected to the distribution of the blast load. In order to obtain an improved understanding of the dynamic behaviors exhibited in cylinders, a finite element simulation model was utilized and subsequently validated using an examination of the experimental results. The assessment of shock wave damage was conducted by utilizing the residual deformation of the metallic cylinder as an equivalent characterization under lateral blast shock wave loading. The duration of the positive pressure zone of the shock wave was determined to be between one-fourth and ten times the vibration period of a unilaterally supported cylinder, indicating that the P-I (overpressure-impulse) criterion could be utilized for damage evaluation. The incorporation of the P-I criterion was subsequently employed to evaluate the detrimental consequences, taking into consideration the radial distribution of residual deformation identified in metal cylindrical shell constructions subjected to lateral blast shock wave loading. This research contributed to a better comprehension of the dynamic behavior of partially confined metallic cylinders subjected to lateral blast loading and highlights the significance of the P-I criterion for evaluating and mitigating the damage effects in such scenarios.

A quantitative study of the effects of physical properties and external loads on the liquefaction of saturated sand based on an intelligent numerical cyclic triaxial test system

ABSTRACT Soil liquefaction would cause significant damage to the safety of cargo transportation. The aim of this article is to conduct a quantitative study of the influence of the main physical characteristic parameters of saturated sand and external loads on its liquefaction. On the basis of the physical cyclic triaxial test (CTT), the finite element simulation model and PSO-BP neural network prediction model and importance analysis model were optimised in this study. Based on this, an innovative intelligent numerical CTT system for saturated sand was constructed. The research results indicate the influence of external load, effective internal friction Angle and plasticity index on the liquefaction of saturated sand is significant, and the average weight is 40.15%, 29.15% and 25.05%, respectively. In this paper, the relevant research provides a theoretical basis for effective control of sand liquefaction and provides new ideas and feasible solutions for subsequent research on sand liquefaction.

Prediction and design optimization of mechanical properties for rubber fertilizer hose reinforced with helically wrapped nylon

Predicting and optimizing the mechanical performance of the helically wound nylon-reinforced rubber fertilizer hose (HWNR hose) is crucial for enhancing the performance of hose pumps. This study aims to enhance the service life of HWNR hoses and the efficiency of liquid fertilizer transport. First, a finite element simulation model and a mathematical model were established to analyze the influence of fiber layer arrangement on the maximum shear strain on the coaxial surface (MSS) and the reaction force on the extrusion roller (RF). For the first time, the Crested Porcupine Optimizer algorithm was used to improve the Generalized Regression Neural Network (CPO-GRNN) method to establish a surrogate model for predicting the mechanical properties of HWNR hoses, and it was compared with Response Surface Methodology (RSM). Results showed CPO-GRNN's superiority in handling complex nonlinear problems. Finally, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was employed for optimization design. Compared to the original HWNR hose with an MSS of 0.906 and an RF of 30,376N, the optimized design reduced the MSS by 7.99% and increased the RF by 2.46%, significantly enhancing their service life and liquid fertilizer transport capacity. However, further research on fatigue damage is needed.

Heat-Dissipation Design and 3D Printing of Ternary Silver Chalcogenide-Based Thermoelectric Legs for Enhancing Power Generation Performance.

Thermoelectric devices have received significant attention because of their potential for sustainable energy recovery. In these devices, a thermal design that optimizes heat transfer and dissipation is crucial for maximizing the power output. Heat dissipation generally requires external active or passive cooling devices, which often suffer from inevitable heat loss and heavy systems. Herein, the design of heat-sink integrated thermoelectric legs is proposed to enhance heat dissipation without external cooling devices, realized by finite element model simulation and 3D printing of ternary silver chalcogenide-based thermoelectric materials. Owing to the self-induced surface charges of the synthesized AgBiSe2 (n-type) and AgSbTe2 (p-type) particles, these particle-based colloidal inks exhibited high viscoelasticity, which enables the creation of complex heat-dissipation architectures via 3D printing. Power generators made from 3D-printed heat-dissipating legs exhibit higher temperature differences and output power than traditional cuboids, offering a new strategy for enhancing thermoelectric power generation.

Piezoelectric MEMS resonator with magnetic tip mass for energy harvesting from ultra-low intensity magnetic fields

This article addresses the limitation in the implementation of the Internet of Things (IoT) due to its energy dependence on batteries. The central focus of this work is the development and characterization of a magnetoelectric (ME) energy generator for IoT, which combines a piezoelectric microelectromechanical system (MEMS) with a magnetic mass to interact with ambient magnetic fields (MFs). The device's efficiency is validated through finite element modeling (FEM) simulations and electrical characterization. Its applicability in environments with residual magnetic fields, such as near common household appliances, highlights its viability. Specific results, such as a maximum generated power of 0.55 µW, corresponding to a power density of 9.19 µW/cm³, for a magnetic field strength of 5 µT, emphasize its ability to address energy challenges and promote the sustainable autonomy of IoT.

Dispersion characteristics of arc-axis waveguides

Ultrasonic single mode excitation methods, mode separation algorithms and damage detection applications all require the calculation of the dispersion characteristics of the waveguide. However, existing dispersion calculation methods are mainly applicable to straight-axis waveguides. Therefore, in this paper, a novel semi-analytical finite element method in cylindrical coordinates (SAFEM-CC) is established and we focus on the dispersion characteristics of arc-axis waveguides. The cross-section of the waveguide can have arbitrary complex shapes, and the correctness of this method is verified by the finite element eigenfrequency method. At the same time, this paper takes the example of an arc-axis structure with a square cross-section and investigates the convergence of SAFEM-CC under different numbers of elements, element types, and element orders. This paper also establishes a finite element simulation model to study the waveform transmission law over a wide frequency range and the wave amplitude distribution law within the cross-section of arc-axis waveguides. The dispersion characteristics of arc-axis waveguides at different radii are also investigated. Finally, the correctness of the proposed method and the dispersion characteristics of arc-axis waveguides are verified by a large number of experiments. The main conclusions are as follows: the waveform transmission laws of the guided wave in arc-axis waveguides at each frequency agree with the dispersion curve; the theoretical wavestructure gives the distribution law of the amplitude within the cross-section; when the axis is arc, the displacement of the wavestructure on the inner and outer sides does not have symmetry, and the difference between the left and right sides gradually increases as the radius decreases.

9‐2: Invited Paper: Research on Strain Sensor Embeded in Foldable AMOLED Display

Strain sensors which are embeded in AMOLED are introduced and studied in this paper. High accuray strain sensing are achieved, resolution of the sensors are about 0.05%. By combing the strain sensors in the panel, mechanical behaviors can be monitored and studied in real time. The snesors are used to conduct the foldable AMOLED mechanical and reliability study. Dynamic and static strains and related mechanism are introduced and discussed. Finite element simulation models considering the mechanical properties of materials including hyperelasticity, viscoelasticity and creep are established. Finally, the strain sensors and finite element anlysis are combined to study the mechanical response of AMOLED under dynamic folding, static folding, and different temperature and humidity environments.

3D FE simulation of PISA monopile field tests at Dunkirk using SANISAND-MS

This paper presents an investigation into the suitability of the SANISAND-MS model for the three-dimensional finite-element (3D FE) simulation of cyclic monopile behaviour in sandy soils. In addition to previous work on the subject, the primary focus of this study is to further assess the model's capability to reproduce the accumulation of permanent deflection/tilt under cyclic lateral load histories. To this end, experimental data from the PISA field campaign are employed, particularly those emerged from the medium-scale cyclic tests conducted at the Dunkirk site in France. The methodology adopted herein involves calibrating the SANISAND-MS model's parameters to align with 3D FE simulation of a selected monotonic pile test reported by the PISA team using a bounding surface plasticity model partly similar to SANISAND-MS. Subsequently, the soil parameters governing SANISAND-MS’ ratcheting response are calibrated using only minimal information from published PISA field data. While representing the first attempt to simulate the reference data set using a fully ‘implicit’ 3D FE approach, this paper offers novel insights into calibrating and using advanced cyclic models for monopile analysis and design – particularly, with regard to the quantitative influence of pile installation effects and sand's microstructural evolution under drained cyclic loading.

Design and Optimization of External Rotor Consequent Pole Permanent Magnet Motor with Low Iron Loss and Low Torque Ripple

To reduce the iron loss and torque ripple of an external rotor consequent pole (ERCP) motor used in an electric vehicle air-conditioning compressor, the magnetic pole structure of the motor was improved, and an unequal piecewise consequent pole (CP) structure was designed. The performance of the motor is optimized by reducing the harmonic content in the air gap flux density and reducing the iron saturation degree of the motor. The designed CP structure can significantly reduce the iron loss and torque ripple of the motor. Based on the Taguchi method, the optimal size parameters of the unequal piecewise CP structure are determined, and the final optimization design scheme is obtained. The results of finite element simulation and high-precision iron loss model show the following: compared with the original motor, the iron loss and torque ripple of the motor with the final optimized design scheme are significantly reduced.

Research on the Improvement of Cable Ampacity in Dense Cable Trench

Due to the influence of many factors, distribution cables are often densely placed at the bottom of the cable trench. As a result, it is easy for distribution cables to become the thermal bottleneck of the whole transmission line. To address this dilemma, this paper establishes a finite element simulation model of a cable trench to analyze the hot spots of cables with different arrangements in the cable trench. Then, the model’s accuracy is verified based on real temperature rise experiments. For an arrangement with overheating risk, the ampacity improvement method of filling the cable trench with high-thermal-conductivity material was proposed, and the ampacity improvement effect under different filling ratios was assessed. Finally, combined with the analysis of economic benefit and cost, the method of determining the optimal filling ratio was used, and the impact resistance of the cables under the impact of new energy load was analyzed. The results indicate that, for the case of the optimal filling ratio, the cables in the dense cable trench showed superior impact resistance. The investigations in this paper make significant contributions to the promotion of the maximum utilization of cables.

Flexural behaviours of concrete-filled stainless-steel tubular beams under cold-region low temperatures

Applications of concrete-filled square (or circular) stainless-steel tubes keep increasing in cold-region coastal engineering structures. However, their behaviours under low-temperature bending have not been fully investigated, which brings obstacles to their engineering applications. To address this issue, this paper investigated flexural behaviours of concrete-filled square/circular stainless-steel tubular beams (CFSSSTBs/CFCSSTBs) at low temperatures through eight four-point bending tests. The main studied parameters were low temperatures (20∼−60 ℃) and cross-section type (circular or square shape). Test results showed that both CFSSSTBs and CFCSSTBs exhibited flexural failure and exhibited excellent ductility under low-temperature bending benefiting from the excellent ductility of stainless steel; bending resistances of CFSSSTBs and CFCSSTBs were improved by 5% and 22%, respectively. This study also developed finite element models (FEMs) for simulations on flexural behaviours of CFSSSTBs/CFCSSTBs at low temperatures. The FEMs considered both low-temperature material and geometric nonlinearities. Validations against eight tests proved the capacities of FEM simulations on low-temperature flexural behaviours of CFSSSTBs/CFCSSTBs. Finally, the code equations in Eurocode 4 and AISC 360 were used to predict the stiffness and ultimate bending resistances of CFSSSTBs/CFCSSTBs. Validations showed that the code equations underestimated the bending resistances of CFSSSTBs/CFCSSTBs. This study provided fundamental information on the flexural bending mechanism of CFSSSTBs/CFCSSTBs) at low temperatures.

Digital twin-based probabilistic prediction of microcrack initiation and propagation in the weld zone of orthotropic steel deck

Orthotropic steel deck (OSD) has become the primary bridge deck structure for steel bridges, but it is vulnerable to fatigue cracks in the weld zone of OSD under traffic loading. This study proposes a digital twin (DT)-based framework to give the probabilistic prediction of microcrack initiation and propagation in the weld zone of OSD. The DT-based framework couples crystal plasticity finite element model (CPFEM) simulations with fatigue tests through Dynamic Bayesian Network (DBN). The fatigue tests of the specimen (physical entity) cut from the weld zone of OSD and sliced to the centimeter scale are carried out using the standard dynamic test system together with optical microscope. The CPFEM simulations are used to develop a multiscale virtual entity to map the physical entity. The role of the DBN is to integrate the uncertainties into a hierarchical network. After completing the updating of uncertainties in the virtual entity via DBN, the microcrack propagation is predicted probabilistically by the DBN inference, and the microcrack initiation is predicted probabilistically by the inverse DBN inference. The results demonstrate the feasibility and accuracy of the DT-based framework for a full prediction of microcrack initiation and propagation in the weld zone of OSD.

Analysis and design of wireless power transfer system with anti-misalignment constant voltage output characteristics

PurposeThis study aims to solve the problem of high output voltage fluctuation and low efficiency caused by the misalignment of the magnetic coupling structure in the wireless charging system for electric vehicles. To address these issues, this paper proposes a dual LCC-S wireless power transfer (WPT) system based on the double-D double-layer quadrature (DDDQ) coil, which can realize the anti-misalignment constant voltage output of the system.Design/methodology/approachFirst, this paper establishes the equivalent circuit of a WPT system based on dual LCC-S compensation topology and analyzes its constant-voltage output characteristics and the relationship between system transmission efficiency and coupling coefficient. 1. Quadruple D (Ahmad et al., 2019) and double-D quadrature pad (DDQP) (Chen et al., 2019) coils have good anti-misalignment in the transverse and longitudinal directions, but the magnetic induction intensity in the center of the coils is weak, making it difficult for the receiving coil to effectively couple to the magnetic field energy. 2. Based on the double-D quadrature (DDQ) structure coil that can eliminate the mutual inductance between coupling coils and cross-coupling, Gong et al. (2022a) proposed a parameter optimized LCC-LC series-parallel hybrid topology circuit, which ensures that the output current fluctuation is controlled within 5% only when the system is misaligned within the 50% range along the X direction, achieving constant current output with anti-misalignment. The magnetic coupling structure’s finite element simulation model is established to analyze the change in magnetic induction intensity and the system’s anti-misalignment characteristics when the coil offsets along the x and y axes. Finally, an experimental prototype is developed to verify the constant voltage output performance and anti-misalignment performance of the system, and the proposed anti-misalignment system is compared with the systems in existing literature, highlighting the advantages of this design.FindingsThe experimental results show that the system can achieve a constant voltage output of 48V under a time-varying load, and the output voltage fluctuates within ±5% of the set value within the range of ±60 mm lateral misalignment and ±72 mm longitudinal misalignment.Originality/valueBased on the dual LCC-S WPT system, the mutual inductance between the same side coils is reduced by adding decoupling coils, and the anti-misalignment characteristics and output power of the system are improved in a certain range. It is aimed at improving the stability of the system output and transmission efficiency.

3D Printed MXene-Based Wire Strain Sensors with Enhanced Sensitivity and Anisotropy.

Stretchable strain sensors play a crucial role in intelligent wearable systems, serving as the interface between humans and environment by translating mechanical strains into electrical signals. Traditional fiber strain sensors with intrinsic uniform axial strain distribution face challenges in achieving high sensitivity and anisotropy. Moreover, existing micro/nano-structure designs often compromise stretchability and durability. To address these challenges, a novel approach of using 3D printing to fabricate MXene-based flexible sensors with tunable micro and macrostructures. Poly(tetrafluoroethylene) (PTFE) as a pore-inducing agent is added into 3D printable inksto achieve controllable microstructural modifications. In addition to microstructure tuning, 3D printing is employedfor macrostructural design modifications, guided by finite element modeling (FEM) simulations. As a result, the 3D printed sensors exhibit heightened sensitivity and anisotropy, making them suitable for tracking static and dynamic displacement changes. The proposed approach presents an efficient and economically viable solution for standardized large-scale production of advanced wire strain sensors.

A digital twin model of the axial temperature field of a DC cable for millisecond calculations

The most important features of digital twin technology for transmission and transformation equipment are symbiotic evolution and state prediction. In constructing the digital twin model for DC cables, the transient and steady-state temperature fields need to be considered comprehensively in the modeling process to consider the multi-physical field coupling, mathematical model, operational data, and environmental conditions in specific cases, which makes it difficult to satisfy the real-time requirements of the digital twin. To solve this problem, in this paper, a digital twin technology architecture for DC cables is proposed, and a neural network learning model is constructed to minimize the latency due to the complexity of the model simulation. Moreover, an efficient digital twin model that is based on the model-driven approach is developed for the fast computation of the axial temperature field of DC cables. The use of the Sequence-to-Sequence residual neural network algorithm for the reduced-order multi-physics field coupling modeling reduces the computational time and ensures as much accuracy as possible up to the finite element model simulation. The simulation results show that the use of the digital twin model reduces the simulation time from 275 s to 0.56 s, and the relative error between the accuracy of the digital twin model and the finite element model for the axial temperature field of the DC cable is 0.46 %. Finally, verification of the reasonableness and feasibility of the proposed method is carried out via an experimental platform according to the standard of CIGRE TB496. In particular, the maximum value of the DC cable temperature is verified to have a small error compared with the result of the Sequence-to-Sequence calculation under specific working conditions.

Finite element modeling simulation of oxygen evolution during charging in lithium-oxygen batteries

The quest for advanced energy storage solutions has intensified the focus on developing next-generation secondary batteries, with lithium-oxygen batteries (LOB) standing out for their superior theoretical gravimetric energy density. This study introduces a novel model-based approach to battery development, enabling the detailed analysis of charge–discharge cycles and oxygen evolution efficiency within a virtual environment. Our model distinctively simulates the oxidative decomposition of lithium peroxide (Li2O2) and differentiates between its formation through solution and surface pathways, addressing the complexities of the charging process and its multiple elementary steps. The developed model further categorizes the oxidative decomposition species into four distinct types, facilitating a comprehensive understanding of their interactions, voltage profile changes, and O2 evolution within the battery's porous cathode. This approach not only enhances the understanding of battery behavior but also aids in refining the design of component materials, thereby propelling forward the development of LOBs with improved energy density and cycle performance.

Simulation Study and Optimization Strategies for Vacuum Infusion of GFRP Hoses Based on Resin Time-Viscosity Variables.

During the infusion process of a glass-fiber-reinforced thermosetting composite hose, the viscosity of its resin matrix undergoes temporal variations. Consequently, if the impact of resin viscosity changes over time on the internal resin fluidity is not considered during the infusion process, this may result in the incomplete impregnation of the hose, characterized by the presence of numerous voids. This phenomenon adversely affects the quality of the pipe's curing and forming process. Therefore, based on the characteristic variations in resin viscosity, this paper considers the changes in fluidity caused by the resin's temporal evolution within the material. We establish a finite element simulation model to calculate and analyze the overall infusion effects of resin viscosity changes during the hose infusion process. Furthermore, based on the predicted analysis, a variable parameter infusion strategy is proposed to increase resin impregnation in the hose, thereby reducing internal void content and subsequently improving the quality of material curing and forming.

Evaluating perovskite solar panels for thermal stability and inclination performance through finite element modelling

This paper presents a foresight simulation of perovskite solar modules, focusing on their behavior under different wind velocities and the thermal effects of varying solar irradiance conditions. Despite the burgeoning interest in Perovskite solar panels (PSPs) due to their lower material costs and promising efficiencies, there exist significant research gaps, particularly in the interaction between wind flow and thermal variations, as well as the performance dynamics under distinct wind velocities. To address these gaps, Finite Element Modelling (FEM) simulations were conducted to analyze the thermal stability and wind stress resistance of PSPs, employing a structural design analogous to commercial silicon PV panels. The simulations revealed that the implementation of a cooling system effectively lowered the average temperature of the perovskite layer by a factor of 2.46, significantly reducing the risk of thermal degradation. Additionally, wind stress simulations demonstrated a direct proportionality between the vertical pressure on the panels and their inclination angles, suggesting that lower angles could minimize wind-induced damage while considering daily solar azimuth. The study’s outcomes contribute to the understanding of PSPs’ mechanical and thermal resilience, proposing an optimized design approach for enhanced durability and efficiency in real-world applications. However, the segregation of thermal and wind flow simulations suggests an area for further integrated studies to fully comprehend the simultaneous effects of environmental factors on PSP performance.

Effects of Hard-to-Measure Material Parameters on Clinching Joint Geometries Using Combined Finite Element Method and Machine Learning

<div>In this article, we investigated the effects of material parameters on the clinching joint geometry using finite element model (FEM) simulation and machine learning-based metamodels. The FEM described in this study was first developed to reproduce the shape of clinching joints between two AA5052 aluminum alloy sheets. Neural network metamodels were then used to investigate the relation between material parameters and joint geometry as predicted by FEM. By interpreting the data-driven metamodels using explainable machine learning techniques, the effects of the hard-to-measure material parameters during the clinching are studied. It is demonstrated that the friction between the two metal sheets and the flow stress of the material at high (up to 100%) plastic strain are the most influential factors on the interlock and the neck thickness of the clinching joints. However, their dependence on the material parameters is found to be opposite. First, while the friction between the two metal sheets promotes the formation of the interlock, it reduces the neck thickness and thus increases the risk of breaking in this region. Second, it is easier to form the interlock if the deformed material exhibits small flow stress at high plastic strain, but the neck thickness tends to be thinner in this case. The identified material parameters help to significantly reduce the relative error between the simulated results and the experimental results, not only in the configurations from which they are identified but also in a new configuration. This methodology shows its potential in the cases where material parameters are not available or difficult to measure.</div>

The Effect of a Ferromagnetic Steel Enclosure on Magnetic Shielding Systems: Analysis, Modeling, and Experimental Validation

The Effect of a Ferromagnetic Steel Enclosure on Magnetic Shielding Systems: Analysis, Modeling, and Experimental Validation