Finite Element Simulation Model Research Articles

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.

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

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

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.

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

High-temperature flexural mechanical properties of SiC/SiC composites

To assess the flexural behavior of SiC/SiC composites in high-temperature atmospheric environments, three critical influencing factors were identified: selection of fixtures, loading and supporting roller dimensions, and span-to-thickness ratio. Subsequently, through experimental methods and finite element model simulations, the impact of these factors was investigated. The study identified the most suitable fixture materials and configuration dimensions for SiC/SiC materials. It was found that as the span-to-thickness ratio increases, the flexural strength of the material continues to rise, reaching a turning point at 543 MPa, after which it decreases. The maximum interlaminar shear stress consistently decreases with an increasing span-to-thickness ratio. Combined with the failure mode analysis of the samples, it was observed that for a span-to-thickness ratio equal to or greater than 16, the sample failure modes are all valid. Additionally, regarding the observed non-linearity in the stress-strain curve when testing with a larger span-to-thickness ratio, it is recommended to apply a large deflection correction to the flexural stress.

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.

Numerical simulation of the effect of projectile shape and size on the high-velocity impact of carbon fiber reinforced composite laminates

To investigate the impact response and damage mechanism of CFRP composite materials for high-speed trains under high-speed impact from foreign objects of different shapes and sizes, high-speed impact experiments and simulations were conducted on CFRP composite laminate at a velocity of 163 m/s. A finite element simulation model was established in Abaqus/Explicit. This model adopts the 3D-Hashin failure criterion considering strain rate effects to simulate the failure of fibers and matrix. Bonded elements with zero thickness were inserted along the fiber direction in the laminate to replicate the damage phenomena of fiber bundle debonding and pull-out. The effectiveness of the finite element model was validated by high-speed photography of the impact process and ultrasonic C-scan damage images recorded during the experiments. Based on this simulation model, the influence of projectiles of different shapes and sizes on the impact response of CFRP composite materials was studied. Projectiles of different shapes exhibit their own characteristics in terms of the time of peak force occurrence, manifestation, and characteristics of laminar damage. The peak force of the cylindrical projectile is 245.01% greater than that of the spherical one, while the conical projectile is 52.26% smaller than the spherical one. When the projectile size increases from 10 mm to 20 mm, the peak force of the spherical projectile, conical projectile, and cylindrical projectile increases by 79.67%, 120.12%, and 283.13% respectively. The total area of delamination in laminated plates is positively correlated with the size of the impacting body.

A biomechanical analysis of novel endovascular implants for aortic valve replacement and ascending aortic repair

Advances in medical technology have enabled minimally invasive treatment of type A aortic dissection with accompanying aortic regurgitation. Implants include endovascular stent grafts (ESG) and heart valve substitute (HVS) modules. Traditional implants can be divided into two types based on the assembly relationship between ESG and HVS: separated z-shaped implants (SZ) and separated diamond-shaped implants (SD). This study proposes a novel linked diamond-shaped implant (LD). To evaluate the safety and effectiveness of this new implant, finite element simulation models were created to assess the risks of endoleak, migration, and vascular wall rupture under annulus displacement load. After the SZ, SD, and LD implants were grafted in virtual release method, all the implants can cover tear-entry located in the ascending aorta, but space distance (δ) which exposed to blood was 14.5, 13.1, and 7.4 mm, respectively; the maximum areas of contact gap was 76.5, 51.5 and 6.3 mm2; the maximum migration distance (ΔL1) were 1.27, 1.06, and 0.1 mm; the maximum stress on ascending aorta was 0.19, 0.24, and 0.51 MPa, which were lower than failure stress (0.9 MPa). This study showed that both SZ and SD implants had minimal effects on the ascending aorta; however, higher risks were associated with implant migration and proximal endoleak. In contrast, the LD implant can simplify the surgical procedure, has a lower risk of endoleak and migration, and limited stress stimulation of the aorta. This study validated the feasibility and effectiveness of this novel implant using the finite element method, indicating its potential as a secure and reliable treatment option.

Simulation model of tumor-treating fields

Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm 3. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.

An imbalance multi-faults data transfer learning diagnosis method based on finite element simulation optimization model of rolling bearing

In practical engineering applications, rotating machinery is often in a healthy state, with more healthy samples and fewer multi-faults samples, which leads to be misdiagnosed. A finite element simulation model (FEM) is proposed to expand imbalanced multi-faults sample data. However, there is a significant difference in vibration response between the FEM simulation data and the measured data collected on the rotating machinery. Therefore, a method based on vibration response eigenvalue model correction has been adopted, aiming to narrow the gap between the simulation data and the measured data. In order to solve the problem of low accuracy of sample imbalance fault diagnosis under different working conditions, a transfer learning (TL) fault diagnosis method based on finite element simulation optimization model of rolling bearings to supplement imbalanced multi-fault data is proposed. Firstly, the FEM of healthy bearings is established, and the optimal radial clearance of bearings is obtained by modifying the vibration response eigenvalue model. Then, corresponding simulated fault vibration responses were obtained by setting composite faults on the optimal model. Finally, supplementing the unbalanced fault data with simulation data to create a mixed balanced dataset as samples, the TL model is trained to accomplish intelligent fault diagnosis for multi-faults. The experimental results show that using mixed data as training samples to train neural network models can improve the accuracy of transfer learning fault diagnosis by over 10%. Expanding fault samples by modifying the bearing clearance of the FEM is an effective method to address sample imbalance.

Structural Optimization of 60T Electric Mining Vehicle Frame: Finite Element Simulation Model and Analysis

Based on the research under the ore loading condition of the electric mine vehicle, this paper measures the physical frame of the 60T electric mine vehicle by means of rangefinder, ruler and drawings, and uses the software CATIA to complete the three-dimensional model of the frame and carriage of the electric mine vehicle, combined with the characteristics of ANSYS workbench software. The structure of the model is simplified. By comprehensively applying relevant knowledge of automobile dynamics, the frame load under full load condition is calculated, and the electric mine vehicle frame is applied by using ANSYS workbench software to simulate and optimize the three conditions of stationary, high-speed driving and turning before the mine car, and the position where the stress concentration and deformation of the frame structure are greatest. By increasing the thickness of the support plate and increasing its stress area, the overall weight was increased by 90.35kg, accounting for 0.9% of the total weight, and the weight increase was very small. Mechanical analysis was carried out on the three working conditions of the optimized frame of the mine car, and the stress was reduced by 25%, 24.1% and 39.2% respectively, effectively eliminating the stress concentration. The actual use of the vehicle can extend the service life of the frame, while improving the economy and stability of the vehicle.

Design, thermal-mechanical coupling analysis, and optimization of polymeric matrix composite sandwiches with a lattice core exposed to a high temperature

This study presents the design of a sandwich structure tailored for post-heat transfer applications subjected to out-of-plane compression. A three-dimensional finite element simulation model was developed to analyze the temperature distribution within the sandwich structure and investigate the effects of high-temperature exposure on its mechanical behaviors. The structure was subjected to a temperature of 300 °C for 400 s, and the temperature distribution at the upper connection point between the top face sheet and the struts of the core was determined. Subsequently, upon returning the sandwich to ambient temperature, a comprehensive calculation of its mechanical properties was conducted and then enhanced by applying different optimization techniques. The results demonstrate that filling the core with Saffil alumina fibers in the presence of a 1.5 mm a thermal barrier coating of Superwool 607 helps increase the mechanical properties of the sandwich structure by around 55%.

Seismic evaluation of steel beam-column connection equipped by circular slit dampers

AbstractThis study evaluates metallic yield dampers, specifically slit steel dampers, for protecting steel beam-to-column connections during seismic events. Finite element model simulations were conducted for the damper and its connection. Analysis of circular parameters, like the radius slot, showed that appropriately sized slit dampers exhibit advantageous seismic behavior. Moment-rotation, hysteresis curves, and plastic stresses comparisons indicate efficient energy absorption. The maximum moment was 25% lower than conventional samples. The slit steel damper model with a ductility factor of 3.5 allows significant plastic deformation before potential failure. Results emphasize the slit damper's potential for optimal performance in steel frames, suggesting its use for efficient energy absorption.

Investigation on Mechanical Properties of MAR-M247 Superalloy for Turbine Blades by Experiment and Simulation

This study aimed to investigate the metallographic structure and the impact of the heat treatment process on the MAR-M247 superalloy, a high-temperature nickel-based superalloy commonly used in turbine blades. The heat treatment process can potentially influence the mechanical properties of the MAR-M247 superalloy at different temperatures. A strength simulation analysis of gas turbine blades should include the variations in the mechanical properties of the material. The effect of heat treatment on grain size was investigated by metallographic experiments, and numerical calculations of material mechanical properties were conducted. The mechanical property parameters necessary for finite element analysis of turbine blades were determined. Finally, a finite element simulation model of the blade was established based on these mechanical property parameters, and strength analysis was performed. The simulation results provided the stress distribution and the strength of the turbine blade.