Finite Element Analysis Software Research Articles

Detailed Design of Special-Shaped Steel Structures Based on DfMA: The BIM-FEM Model Conversion Method

(1) This paper, based on the characteristics of complex steel structures as well as difficult points in the process of their detailed design, introduces the product design concept of DfMA (Design for Manufacturing and Assembly) from the manufacturing industry and studies the detailed design method of BIM-FEM model conversion. The BIM software Revit (2020) is used as the basis for the BIM detailed design of the project, which achieves the purpose of rapid modeling and provides a detailed design model basis for finite element analysis. (2) Utilizing the Revit API and C# for secondary development as the technical means, this approach involves converting the geometric entity model described by CSG-Brep into an APDL stream. This creates an interface with the finite element analysis software ANSYS (12.0) to implement the detailed design of BIM-FEM model conversion, optimizing the algorithm for converting complex analysis models that require high precision for special-shaped steel structures. (3) This research addresses issues such as the disconnection between the design, manufacturing, and construction of special-shaped steel structures, providing support for design decisions. Moreover, it enhances the detailed design method by improving the standardization of special-shaped components under the condition of design diversity. (4) These studies provide sustainability for engineering design, manufacturing, and construction projects, enabling the maximization of benefits and product lifecycle management (PLM) through these projects. (5) Finally, a case study analysis was conducted on the Wuhan City New Generation Weather Radar Construction Project, designed by the Central South Architectural Design Institute (CSADI), to verify the detailed design of BIM-FEM model conversion. This proved the scientific validity, practicality, and necessity of this research.

Structural Analysis of an Off-Road Vehicle Suspension System Using CATIA and ANSYS

This project delves into the structural analysis of an off-road vehicle suspension system, employing cutting-edge software tools such as CATIA and ANSYS. Off-road vehicles necessitate robust suspension systems capable of withstanding harsh terrain conditions while ensuring vehicle stability, manoeuvrability, and passenger comfort. The study focuses on evaluating the structural integrity, performance, and behaviour of the suspension system under diverse load conditions and terrain scenarios. This project focuses on conducting a comprehensive structural analysis of an off-road vehicle suspension system using advanced engineering software tools, specifically CATIA and ANSYS. CATIA is a powerful computer-aided design (CAD) software known for its capabilities in creating detailed 3D models, while ANSYS is a leading finite element analysis (FEA) software used for simulating structural behaviour and analyzing mechanical systems. Keywords: suspension system, CATIA v5, ANSYS, iterations, FEA.

Numerical and theoretical investigation of crack propagation in the windshield in collision with a dummy headform

Studies show that the impact of the pedestrian head and windshield is a significant contributing factor to casualties in traffic accidents. Accordingly, investigating the mechanical response of the windshield and its failure mechanism is of significant importance in enhancing the safety of pedestrians in car accidents. This study conducted the pedestrian protection head impact test to determine the fracture mode of the windshield, acquire the acceleration curve of the headform impactor, and accurately obtain the peak acceleration and Head Injury Criterion (HIC). Subsequently, to quickly predict HIC and facilitate structural selection in designing automobiles, a theoretical analysis model for predicting peak acceleration was established and validated against the test results. To analyze the damage mechanism in detail, finite element analysis software LS-DYNA was employed to simulate the crack propagation in the windshield based on the peridynamics theory. Through a comparison between the numerical simulation and experimental results, the accuracy of the bond-based peridynamics model was verified, accurately revealing its failure mode and mechanical response to impact. Meanwhile, the peak acceleration and HIC were effectively predicted, which provided an effective approach for vehicle safety evaluation and design.

Design of an Axial-Type Magnetic Gear with Auxiliary Flux-Enhancing Structure

In this paper, a new axial-type magnetic gear with an auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AMGs, it has a higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of the proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterparts in RMGs, the AFS-AMG achieves a small size. Then, the geometrical parameters of the AFS-AMG are optimized to obtain better electromagnetic performance, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume.

Joint stress of a hinged platform composed of eight boxes

The box-type hinged platform has important applications in ocean engineering. In this paper, a multi-module assembled box-type platform is described. The mid-section load of the platform is numerically simulated based on the three-dimensional velocity potential theory and the indirect time-domain method through the hydrodynamic module AQWA in ANSYS. The stress of the hinged joints of platforms was performed using finite element analysis software in ANSYS software. The results show that: (1) In irregular waves, the shear force and bending moment in the middle section of the platform increases with the increase of the significant wave height; (2) Under the same towing scheme, the stress of the hinged joints between box platforms shows an increasing trend with the increase of wave level. Under the same wave working condition, the stress at the uniaxial nut of the hinged joints is relatively high, which is prone to fracture.

In-plane behaviour of masonry infill walls with openings strengthened using textile reinforced mortar

A numerical study was carried out to simulate the in-plane behaviour of a 1:2.5 scaled one-storey one-bay masonry-infilled reinforced concrete (RC) frame retrofitted with textile-reinforced mortar (TRM). The study used ABAQUS finite element analysis (FEA) software and a three-dimensional (3-D) finite element method. Using a ductile design and details, the TRM-reinforced structure encountered in-plane displacement-control cyclic loads during the test. This study assesses how accurately a representative numerical model can replicate the results of an experimental test. Parametric research was conducted following the numerical model's calibration. To develop a suitable numerical model, suitable constitutive models based on the concrete damage plasticity (CDP) approach were used to characterize the nonlinear response of TRM, masonry infill, and concrete. The experimental findings, which aggrandize the response simulation, served as the basis for calibrating the models. Using a finite element framework and the simplified micro model technique, the masonry structure is simulated at the infill component level. The numerical model demonstrated accurately the ability to simulate the in-plane behaviour of the modified RC frame with infill walls, including its initial stiffness, deterioration, deformation-resisting ability, and failure patterns. Furthermore, a parametric study was conducted to determine the significance of the full-bond scenario between the RC frame infilled with masonry and the TRM considering: (1) the location of the strengthening material on the specimen and (2) the number of layers of the strengthening material. All retrofitted wall specimens showed a considerable improvement in in-plane performance; some features of the wall's behaviour were found to be strongly influenced by the parameters under examination. It can be observed that the specimen with two layers of TRM on both sides of the infill wall exhibit the maximum lateral load carrying capacity and maximum deflection resisting characteristics while the other retrofitted specimens controlled the deflection to some extent and significantly enhancing the load carrying capacities of the masonry system.

Finite Element Analysis Study of Buried Crack Defects in B-Sleeve Fillet Welds

Finite Element Analysis Study of Buried Crack Defects in B-Sleeve Fillet Welds

Fracture behaviour of thin-walled cold-formed steel at elevated temperatures

Cold-formed steel (CFS) is being increasingly used in structural applications due to its high strength-to-weight ratio, ease of construction and versatility. The performance of CFS structures in fire has received signification recent attention, but the fracture behaviour of thin-walled CFS at elevated temperatures, which is fundamental to the fire response of the key components, like connections has yet to be extensively studied; this is therefore the subject of the present paper. First, using experimental data on cold-formed grade S280GD+Z275 steel at elevated temperatures from the literature, damaged true stress-strain curves considering the post-necking behaviour are determined. Then, a fracture prediction approach, implemented in the finite element analysis software Abaqus and considering ductile damage and a damage evolution law is calibrated and validated against the experimental data. Finally, the applicability of the proposed approach to different types of CFS material, including high-strength CFS, is assessed. The results show that the proposed model can accurately predict the fracture behaviour of CFS at elevated temperatures.

Multi-Objective Optimization of a Multi-Cavity, Significant Wall Thickness Difference Extrusion Profile Mold Design for New Energy Vehicles.

With the rapid development of the new energy vehicle market, the demand for extruded profiles for battery trays, mainly characterized by significant wall thickness differences in multiple chambers, is increasing, posing new challenges to production and quality control. This study examines the multi-objective optimization problem in the design process of aluminum profile dies with multi-cavity profiles and significant wall thickness differences. Using QFORM-extrusion professional aluminum extrusion finite element analysis software and the response surface analysis method, the standard deviation of the velocity (SDV), standard deviation of the pressure (SDP), and thick wall hydrostatic pressure (TWHP) on the profile section at the die exit are optimized. By analyzing the functional relationship between the key die structure parameters (the height of the baffle plates, the length of the bearing, and the height of the false mandrel) and the optimization objective, the optimal combination scheme of die structure parameters was obtained using the NSGA2 (non-dominated sorting genetic algorithm-2) multi-objective genetic optimization algorithm. The results show that, compared with the initial design scheme, the standard deviation of profile section velocity was reduced by 5.33%, the standard deviation of pressure was reduced by 11.16%, and the thick wall hydrostatic pressure was increased by 26.47%. The die designed and manufactured using this scheme successfully completed the hot extrusion production task, and the profile quality met the predetermined requirements, thus verifying the effectiveness of this study in optimizing the design of a multi-cavity aluminum profile die with significant differences in wall thickness for complex structures.

[Design and support performance evaluation of medical multi-position auxiliary support exoskeleton mechanism].

Aiming at the status of muscle and joint damage caused on surgeons keeping surgical posture for a long time, this paper designs a medical multi-position auxiliary support exoskeleton with multi-joint mechanism by analyzing the surgical postures and conducting conformational studies on different joints respectively. Then by establishing a human-machine static model, this study obtains the joint torque and joint force before and after the human body wears the exoskeleton, and calibrates the strength of the exoskeleton with finite element analysis software. The results show that the maximum stress of the exoskeleton is less than the material strength requirements, the overall deformation is small, and the structural strength of the exoskeleton meets the use requirements. Finally, in this study, subjects were selected to participate in the plantar pressure test and biomechanical simulation with the man-machine static model, and the results were analyzed in terms of plantar pressure, joint torque and joint force, muscle force and overall muscle metabolism to assess the exoskeleton support performance. The results show that the exoskeleton has better support for the whole body and can reduce the musculoskeletal burden. The exoskeleton mechanism in this study better matches the actual working needs of surgeons and provides a new paradigm for the design of medical support exoskeleton mechanism.

Design and validation of a piezoelectric diaphragm micropump for drug delivery

There is a common eye ailment called Dry Eye Disease (DED) that causes symptoms of discomfort, visual disturbance, and tear film instability, which cause damage to the ocular surface. For treatment of this illness, the application of artificial tear fluid is usually prescribed. This work presents the design process of a piezoelectric micropump to become part of an automatic pumping system for delivering artificial tear fluid to people suffering from DED. Low polarizing voltage, portability, and achieving a variable output flow rate in the range of 1 µl/min, which is the necessary range needed by a person suffering from DED, are the focus of this design. Standard microfabrication techniques widely used in the CMOS industry and for MEMS development will be used for manufacturing the proposed micropump. For this reason, the materials and manufacturing processes involved must be CMOS-compliant. For the piezoelectric actuator, zinc oxide (ZnO) was selected due to its compatibility with CMOS technology and because it is readily available in thin film form through a sputtering process. Other materials involved in the device are silicon and aluminum. The design was validated through finite element analysis software, COMSOL Multiphysics®. The maximum flow rate obtained by a single micropump device was 2.51µl/min operating at 20V peak with a frequency of 900Hz. Also, the flow rate is controllable through variations in frequency, thus making it suitable for the application previously described.

Comparison of finite element analysis results with strain gauge measurements of a front axle housing

Abstract. The strength of the front axle of tractors used on rough terrain is crucial in countries in which agriculture is widespread. Rough agricultural fields, rugged village roads, and ground irregularities cause unexpected reaction forces on the axles. Thus, it is important to analyze the front axle of a tractor with respect to stress, which eventually leads to cracks and premature failure. In this study, ANSYS 13.0 finite element analysis (FEA) software (ANSYS, 2010) was used to predict the strength of a design under loading conditions. ANSYS 13.0 allows products to be tested in a virtual environment and helps to prevent problems that may arise later and accordingly improve them. This study aims to investigate the stresses that occur on the housing of the front axle of a tractor. The reaction forces acting on the front axle housing can cause cracks near the middle of the housing. The study applies a static load of 30 000 N to both hubs at the end of the front axle housing and uses the FEA method to predict and evaluate the maximum stress areas on the housing. Strain gauges are bonded to these locations to measure the real-life stresses on the axle housing in these areas. The results of the FEA and strain gauge measurements were compared, and a correlation was found with 98 % accuracy.

Numerical Simulation of Dynamic Response of Atmospheric Storage Tanks Under Coupling Effect of External Two-source Blast

In the event of a material leak in an atmospheric steel tank farm, it is likely to cause a fire and explosion, leading to an escalation of secondary accidents. According to the historical domino accident data to analyze the accident characteristics, the explosion phenomenon is common in atmospheric pressure steel storage tank accidents, and the coupling phenomenon is obvious. However, there is a dearth of research on multiple explosions in steel storage tank farms. This paper investigates the dynamic response of an atmospheric pressure storage tank under the coupling effect of simultaneous detonation of two explosive wave sources. With the help of finite element analysis software to establish a simplified model of the tank under the action of two sources of blast wave coupling, to explore the propagation law of the blast wave scenario and the dynamic response process of the tank. The deformation damage of the tanks by the angular size of the blast load is revealed, and the structural energy changes are analyzed. The study of the dynamic response of steel tanks under the dual-source explosion scenario can provide a theoretical reference basis for quantitative damage in realistic scenarios.

Numerical assessment of using FRP rebars as an alternative passive reinforcement in RC beams

AbstractRecent sustainable building strategies make the right decisions to be environmentally friendly and reduce carbon emissions. In some reinforced concrete (RC) elements, fiber-reinforced polymer (FRP) bars have been proposed as an alternative to conventional steel bars. The demand for using noncorrosive and/or nonmetallic reinforcing bars in various reinforced concrete projects has increased. Although these concrete elements are lightweight, have a long lifespan, and need little maintenance, their non-ductile nature and bond with the surrounding concrete create significant challenges. Several experimental investigations have been conducted to evaluate the behavior of RC elements, even with their high cost. This study aims to assess numerically the viability of using FRP bars instead of traditional steel ones in simply supported reinforced concrete beams (RCBs) as longitudinal reinforcement (passive reinforcement). Utilizing the three-dimensional (3D) nonlinear finite element analysis (FEA) software (ABAQUS), a total of eighteen models were carried out to validate the results available in reference case studies with FRP bars. The verification of the numerical results has been verified by comparing them with the reference experimental data. Next, in order to assess the rigidity of such RCBs with FRP bars, parametric research was carried out. The numerical results proved that RCBs with FRP bars have a positive impact on enhancing load-carrying capacities. But on the other hand, the strain energy of such RCBs with CFRP bars is reduced to about 75% of the strain energy of RCBs with steel bars, which leads to low beam ductility.

Development of a Fiber Bragg Grating accelerometer based on a tandem single-notched hinge structure

A Fiber Bragg Grating low-frequency accelerometer with a single-notched hinge in series is proposed to improve the hinge structure’s sensitivity and the cross-sensitivity of the accelerometer of low-frequency seismic waves. The sensitivity and the cross-sensitivity of the accelerometer are improved by connecting the single-notched hinge structure in series and experimentally verified. Based on the theoretical analysis, the resonance frequency and sensitivity formula of the accelerometer are derived. At the same time, the accelerometer is simulated by finite element analysis software to simulate and analyze the characteristics of the accelerometer in terms of resonance frequency, strain distribution, and amplitude-frequency response. The structural parameters of the accelerometer are optimized by numerical analysis software, and the effects of the structural parameters on the sensitivity and resonance frequency of the accelerometer are analyzed. The experimental results show that the resonance frequency of the accelerometer is 110 Hz, the flat region is 0.6–50 Hz, the linearity is as high as 98.9%, the sensitivity is 1040.41 pm/g, and the cross-sensitivity of the accelerometer in the flat interval is 4.94%. This indicates that the accelerometer shows good linearity and cross-sensitivity in the flat interval, which well meets the needs of seismic wave signal monitoring in low-frequency oil and gas exploration.

Deep-learning approach based on multi-data fusion for damage recognition of marine platforms under complex loads

This paper presents an innovative deep-learning network underpinned by advanced data-fusion techniques developed explicitly for detecting structural damage in marine platforms. This study commences with a rigorous validation of the proposed methodology employing detailed experimental procedures and subsequently applies this method to identify damage under specific random load conditions utilizing state-of-the-art finite element analysis software. This entails the meticulous construction of an extensive database mirroring the real-life conditions encountered by a deep-water jacket platform in the South China Sea. By conducting thorough simulations based on the characteristic environmental loads of this marine area, the study succeeds in closely replicating real-world conditions. The developed damage-identification model, which is specifically adapted to the distinctive requirements of non-Gaussian white-noise loads, exhibits notable accuracy. The experimental outcomes derived from the application of the proposed deep-learning algorithm for data fusion indicate an impressive accuracy rate of 92.01%. In simulated scenarios involving complexly loaded jacket platforms, the model attains an accuracy of 88.25%, highlighting the robustness of the method and its wide applicability in the field of marine structural health monitoring.

Multi-axis CNC finishing and surface roughness prediction of TC11 titanium alloy open integral micro impeller

The titanium alloy open integral micro impeller has a strong material strength and high removal rate in the field of multi-axis CNC machining. The flow channel is tiny and the blades are thin and highly twisted. It is difficult to control the surface accuracy and prone to overcutting and undercutting. The NX2212 software post-processing module plans two distinct blade finishing process routes and verifies them using virtual machine tool simulation, taking into account the technical challenges of micro impeller machining. Following verification, the tool path machining code is imported into MATLAB for data fitting. The workpiece surface working condition is determined based on the simulation findings, the blade surface roughness value is calculated, and a physical simulation model of blade finishing is created in the finite element analysis software. The outcomes demonstrate how well the “segmented and sub-regional cutting” processing method may raise blade accuracy. The leading and trailing edges of the blade both had surface roughness increases of 4.86% and 4.19%. The surface morphology of the micro impeller is measured using a white light interferometer, and it is CNC machined using two distinct process methods. The findings demonstrate that there is a significant difference between the value calculated by the finite element analysis software and the surface roughness value measured experimentally which together make up less than 5%. An investigation of the impact of cutting parameters on the surface roughness of micro-structure components is carried out using a three factor, three-level BBD experiment that is founded on the second-order response surface method. The findings indicate that the feed per tooth influences surface roughness more significantly than cutting depth and cutting speed for a reasonable range of cutting parameters; Surface roughness will rise with lower or higher cutting speeds; Raising the feed per tooth and the cutting speed simultaneously may reduce surface roughness; Surface roughness can be accurately predicted and controlled using the second-order response surface method.

Design and fabrication of a novel all-quartz resonant pressure sensor with continuously variable section of DETF

This paper reports a novel piezoelectric quartz crystal pressure sensor with a double-ended tuning fork (DETF) resonator. The key design is the resonator beams with a continuously variable section shape. Different from the traditional DETF with straight beams or the one with variable sections with steps, this design can improve sensitivity effectively. Theoretical analysis indicates that the sensitivity will increase with a decrease in beam width. Resonant pressure sensors with three different DETFs are designed and analyzed by finite element analysis software. Simulation results show that the sensitivity of this design is 162.27 Hz/MPa. This sensor has a typical structure, which includes three parts: the diaphragm, DETF resonator, and back-cavity structure. Quartz MEMS processes have been used in fabrication. The three parts are bonded together by vacuum glass frit sealing process. Test results of this sensor show that the natural frequency is 44.709 kHz with a quality factor of 12 717. The sensitivity is 155.6 Hz/MPa in the pressure range of 0–20 MPa. The results indicate that this novel design has advantages in sensitivity and fabrication processes. It will be a benefit for a high-performance and low-cost pressure measurement.

Procedure in developing a longitudinal-torsional vibration-assisted micro-milling system

Micromachining is an advanced microfabrication technique for micro-sized or micro-accuracy products through subtractive manufacturing such as micro-milling. Vibration-assisted machining (VAM) is a method in which small amplitude vibrations are applied to the tool or workpiece to enhance the fabrication process. Milling results could be improved by adding longitudinal and torsional vibration to the tool using piezoelectric components vibrating at the ultrasonic frequency with an amplitude of less than 1 μm is used. A slip ring is required to transmit electric power from a static structure to a rotating frame. After the power has been transmitted to the system, an ultrasonic horn, called an acoustic horn or sonotrode, amplifies the vibrations at the tool’s tip. Since the excitation vibration is only longitudinal, the magnification of the vibration at the tooltip is also only longitudinal. Grooves are added to the side of the ultrasonic horn to produce torsional vibrations. This vibration is then simulated through finite element analysis software, explicitly using explicit dynamics. A 3D simulation is run for a quarter cycle of micro-milling through a Ti-6Al-4V material. It could be concluded that the LTVAM application may improve machining quality, such as temperature reduction of up to 9%, cutting force reduction of up to 35%, and surface roughness improvement of up to 27%.

Harnessing artificial neural networks for inverse design and analysis of MEMS-based Fabry–Pérot filters

MEMS-based Fabry–Pérot (MEMS-FP) filters have become increasingly important in optical applications such as frequency selection spectroscopy and spectral analysis. Prior to the manufacturing of MEMS-FP devices, conducting a thorough theoretical analysis of their properties is crucial. Currently, Finite Element Analysis (FEA) is the primary method for investigating the theoretical performance of MEMS-FP during the design process. However, the complexity of modeling and prolonged simulation times associated with FEA software pose significant challenges, impeding the development timeline for MEMS-FP devices. To address these challenges, we proposed a machine learning-based method to computer-aided design of the MEMS-FP devices. Our approach involves using an Artificial Neural Network (ANN) to predict their physical properties and an inverse design method, utilizing optimization algorithms such as PSO, NSGA-II, and SA, to derive the optimal design scheme for MEMS-FP devices. Our method accelerates the prediction of physical properties of MEMS-FP devices and enables the design automation of optimal schemes in just minutes within a limited design space. This approach not only reduces the research time and complexity associated with MEMS-FP devices but also shortens their development cycle. Furthermore, one specific MEMS-FP device is fabricated and tested for proof-of-concept of our proposed method.