Accuracy Of Finite Element Analysis Research Articles

A novel machine learning framework for impact force prediction of foam-filled multi-layer lattice composite structures

Numerical simulations can provide valuable insights for the optimization of design and operational management; however, they are often impractical and computationally intensive. Machine learning methods are appealing to these problems due to their sufficient efficiency and accuracy. In this study, a novel framework for predicting the impact responses of foam-filled multi-layer lattice composite structures (FMLCSs) was proposed by combining the accurate finite element (FE) analyses, surrogate models, fast Fourier transform (FFT) method, and inverse FFT (IFFT) method. Firstly, reliable FM models were established to simulate the crashworthiness of the five FMLCSs under impact loading, including an analysis of energy transformation. Subsequently, surrogate models, namely radial basis function (RBF), polynomial response surface (PRS), Kriging (KRG), and back propagation neural network (BPNN), combined with methods of FFT and IFFT, were employed to predict the impact force-time series of the FMLCSs. More than 1000 frequency points were employed for each type of FMLCS, and all the R-square (R2) values of the established surrogate models exceeded 0.95, indicating that the proposed framework accurately predicted the impact duration and impact responses in the frequency domain. In addition, parameter sensitivity analysis revealed that a high peak impact force was accompanied by a short impact duration. Moreover, increasing the lattice-web height resulted in a significant increase in the impact duration.

Study on the fatigue performance and Residual Stress of subsurface fluid flow of 2519a aluminum alloy based on water jet peening

In this study, the influence mechanism of water jet (WJ) strengthening on the surface integrity and fatigue properties of 2519 aluminum alloy was investigated by using finite element software Abaqus 2023 and fatigue analysis software Fe-safe. The effects of jet velocity and transverse velocity on the development of surface roughness and residual stress in different strengthening stages were studied, and the fatigue properties of WJ strengthened samples were analyzed by Fe-safe fatigue software. Finally, the fatigue life and fracture morphology of WJ strengthened specimens were analyzed by fatigue test, and the accuracy of finite element analysis was verified. Results indicate that surface roughness post-WJ enhancement displays a “W” shaped distribution, positively correlated with jet velocity. Conversely, increased roughness negatively correlates with higher traverse speeds, with optimal values recorded between 400 and 600 mm/min at WJ-290 mm/s, ranging from 1.10322 to 1.41167 μm. Additionally, the study reveals that maximum residual compressive stress during the WJ-Ip phase correlates positively with jet velocity, peaking at 302 MPa for WJ-290 mm/s. The research also notes that while higher jet velocities enhance residual compressive stress, they simultaneously elevate surface roughness, potentially introducing damage and increasing the variability of stress magnitudes. The study underscores the necessity of meticulously calibrating WJ parameters to enhance surface quality effectively while minimizing adverse effects. This balance is critical to optimizing the treatment process and achieving desired material properties.

A strain field reconstruction method based on digital twin considering real-time loading deviations from intended test

For the static loading test, digital twin (DT) constructed by multi-type data fusion can combine the advantages of these data, which has potential application in test monitoring. Affected by assembly and manufacturing defects of test system, the loading deviations are difficult to avoid and quantify, and it has an important effect on the strain state of structures. However, the current DT is built by data fusion of strain gauges data and strain field of finite element analysis (FEA) only, and how to build DT considering real-time loading deviations by fusing multi-type sensor data remains a challenging task. Therefore, a strain field reconstruction method based on DT considering the real-time loading deviations (DT-SFRM-LD) is proposed to improve the accuracy of DT. In the test, the loading deviations calculated by displacement sensors data are used as FEA database input to obtain FEA strain field considering real-time loading deviations. The FEA strain field is combined with strain gauges data to construct DT in real time, which combines all the multi-type data advantages of displacement gauges, FEA strain field and strain gauges. A cylindrical shell test is performed to validate the high accuracy of DT-SFRM-LD. Results indicate that the AvgErr (5.0%) and MaxErr (13.6%) of DT-SFRM-LD are 4.3% and 10.0% lower than those of conventional DT method, and the AvgErr of DT-SFRM-LD is less affected by the eccentricity distance. In general, under different test conditions, the accuracy of DT-SFRM-LD is always higher than that of conventional DT method, indicating that considering the real-time loading deviations by displacement gauges is helpful to provide accurate FEA strain field distribution and to improve the accuracy of DT-SFRM-LD.

A novel post‐forming method for fully cured thermosetting composite parts: Prediction and investigation

AbstractThe objective of this work is to devise a post‐forming technique capable of accurately and significantly altering the shape of fully cured thermosetting composite parts. To accomplish this goal, the viscoelastic behavior and resulting deformation of fully cured parts at elevated temperatures were predicted and examined using viscoelastic mechanics, finite element analysis (FEA), surrogate modeling, and the particle swarm optimization (PSO) method. Firstly, the mechanism of fully cured parts' shape adjustment based on viscoelastic mechanics was introduced, and a method was established for the inverse identification of the stress relaxation ratio in the different directions of material. Secondly, an FEA model for predicting post‐forming was developed based on the standard linear‐solid viscoelastic model. A dataset was then compiled using parameterized FEA to train a rapid prediction model for post‐forming. The influence of various forming and structural parameters on the post‐forming process was examined. The results indicate that layup has the most significant impact, followed by displacement and temperature. The radial basis function was selected to construct the precise surrogate model after comparing it with the Kriging model and the Response Surface Methodology (RSM) model. Ultimately, to achieve the desired shape after post‐forming, the PSO method can be employed to determine the ideal combination of forming parameters.Highlights The post‐forming method could adjust the shape of fully cured composites. The mechanism of post‐forming is based on viscoelastic behavior. An accurate FEA based on the standard linear‐solid model was established. The radial basis function was developed for quick and precise prediction. The particle swarm optimization could obtain the ideal forming parameters.

Comparison of analytical and numerical methods for estimating notch strains**

AbstractIn fatigue assessments, local strains and stresses can be easily evaluated using accurate finite element analysis in a case of an individual fatigue‐critical notch or structural detail. In practical design and analysis of global models, the consideration of local notch effects using suitable estimation rules in the combination with linear elastic analysis is reasonable. Various notch rules exist but the current knowledge lacks understanding how applicable different notch rules are for estimating notch strains from elastic stresses. This work studies the Neuber′s rules for sharp and mild notches, Glinka′s equivalent strain energy density method, the correction of Neuber′s rule proposed by Sonsino for mild notches, as well as the Seeger‐Beste method. The application of different estimation rules for notch strains, applied to the elastic‐perfectly plastic steel material and to Ramberg‐Osgood material model for the aluminum material, including work hardening effect, was studied in this work by comparing the estimations with the corresponding experimental data and finite element analysis results. The Neuber′s rule for mild notches and Sonsino′s averaging method gave best correlations with the experimental data and numerical (finite element analysis) results and can be thus recommended for such analyses in compatible cases studied in this work.

Multi-source monitoring data filtering assisted deformation analysis model updating of ultra-high rockfill dam

The deformation monitoring of ultra-high rockfill dams is now characterized by the applications of various monitoring instruments and the comparably dense measurement point deployment. The deformation analysis of rockfill dam can be greatly improved based on the multi-source monitoring data using the model updating technique. However, the model updating of rockfill dam faces challenges such as imbalanced spatial distribution of data, uneven data quality, and information redundancy, which leads to low performance and limits its application. Thus, this study proposes an innovative scheme for deformation analysis model updating, involving multi-source monitoring data filtering and model parameter identification. This scheme reduces the information redundancy, and ensures the finite element analysis (FEA) model of rockfill dam better reflects the actual deformation. The application in the 295 m Lianghekou rockfill dam demonstrates its notably enhancement of FEA accuracy, further improving the safety assessment.

The Importance of Boundary Conditions and Failure Criterion in Finite Element Analysis Accuracy—A Comparative Assessment of Periodontal Ligament Biomechanical Behavior

The Importance of Boundary Conditions and Failure Criterion in Finite Element Analysis Accuracy—A Comparative Assessment of Periodontal Ligament Biomechanical Behavior

Evaluating the Accuracy of Finite Element Analysis in Predicting Mechanical Properties of Additively Manufactured Parts

This study examines the Markforged simulation software's efficacy in predicting properties of Markforged 3D-printed parts. Material extrusion (MEX) is widely used across industries for its ability to create intricate shapes with diverse internal patterns. To evaluate mechanical properties, especially due to varying infill patterns, the Markforged simulation tool is employed. Tensile test specimens based on ASTM D-638 were 3D printed using a Markforged Mark Two printer and "Onyx" material, varying layer thickness, infill pattern, and density. Deformation is simulated under a 500 N tensile load and compares to physical tests on a tensile machine, considering different pulling speeds. Results show minimal variation between simulations of solid infill patterns and experiments, regardless of speed. However, porous infill patterns exhibited notable differences. Tensile testing also revealed the impact of pulling speed on deflection for "Onyx" specimens under a 500 N load.

Multi-objective design of 3D phononic crystal waveguide by design space trimming

Ultrasonic flowmeters face unique challenges since, in addition to withstanding high fluid pressures, they have to avoid crosstalk, which is the interaction of the signals traveling through the fluid and the solid pipe. To avoid the crosstalk, which leads to poor accuracy or complete loss of the required signal, we develop a mounting mechanism based on phononic crystals (PnCs), which are artificial periodic materials possessing band gaps (BGs) due to Bragg scattering. These PnC structures should also possess high mechanical strength to sustain the fluid pressure. Designing PnCs for such applications is challenging as the BG width and the resistance to mechanical loading are conflicting objectives. To circumvent this, we propose a step-by-step design procedure to optimize both mechanical strength and wave attenuation performance of a single-phase 3D PnC waveguide using parametric sweeping and sensitivity analysis. We use finite element analysis (FEA) to characterize the behavior of the periodic unit cell and the waveguide. Since accurate dynamic FEA at high frequencies is computationally demanding, we develop surrogate models at different levels of the design process. We also consider additive manufacturing aspects in the design procedure, which we validate by 3D-printing the final design and measuring the parameters via computer tomography.

Hybrid Transcranial Magnetic Stimulation and Deep Brain Stimulation in the Presence of an Implantable Pulse Generator

Transcranial Magnetic Stimulation (TMS) has been shown to improve speech impairment in Parkinson’s Disease (PD) patients. Most PD patients undergo Deep Brain Stimulation (DBS) implantation to improve their motor function prior to the development of speech impairment. Therefore the potential for TMS treatment must take into account the DBS probes’ high conductivity, potentially causing excess stimulation. Prior research regarding this phenomenon is highly conflicting and needs investigation. This study reports electromagnetic interference using a highly accurate finite element analysis approach to determine the electric field distribution in patients with DBS probes undergoing TMS therapy. Additionally, we tested various coil orientations and coil models to fully examine the extent that TMS affects DBS. We considered accurate DBS geometry by creating high-resolution models of Medtronic 3389 DBS, including an Implantable Pulse Generator (IPG) and multiple loops at the exit point of the cranium, which previous studies lack. By studying the induced current in the DBS leads, we determined that the combination of TMS and DBS varies in safety relative to its coil orientation and coil type. Specifically, the quadruple butterfly coil (QBC) targeted at the lateral motor cortex did not induce unsafe levels of currents in the DBS leads even at 100% of the maximum stimulator output.

Controllable deformation design for 4D-printed active composite structure: Optimization, simulation, and experimental verification

Through integrating active composites and 4D printing techniques, active composites can achieve the pre-designed complex deformations. However, the tremendous design space of multiple materials brings the challenges of finding the optimum material distributions accurately, and the consistencies between simulated optimum results and actual experimental structures. Therefore, the controllable deformation design framework is proposed to guide the inverse design of 4D-printed active composite structure. The material properties of polylactic acid (PLA) and thermoplastic polyurethane (TPU) are tested and integrated into forward deformation analysis to improve the prediction accuracy of finite element analysis (FEA). An optimization integration framework with genetic algorithm is developed to optimize the material distribution and external displacement simultaneously to achieve the target deformation. Several voxelized beams and flower structures are used as engineering cases. The simulated and experimental deformation shapes and recovery shapes for the optimum structures are consistent with the target deformations. The mean squared errors (MSEs) of experimental shape and simulation shape are 0.62 mm and 0.27 mm for flower structures. These results show that the proposed methodology can obtain target deformation in simulation and experimental tests simultaneously, which can be applied into the flexible deformation design of complex active composite structures in the future.

Maximum volume ellipsoid vessels under cyclic pressure and mass constraints: LEFM-based design criteria

The paper deals with an optimization problem related to axisymmetric membrane shells made of homogeneous, linear and isotropic materials and subject to a cyclic internal pressure. The optimization problem considers the possible crack growth in the shell as a structural constraint, which is accounted for by the well-known Paris law, and hence obeys the Linear Elastic Fracture Mechanics (LEFM) principles. The design variables are the meridian shape and the thickness distribution along the axis of the shell. After recalling the general background on the mechanics of thin-walled shells, the optimization problem is stated, formulated and solved in closed form by means of Pontryagin’s Principle, showing two LEFM-based design criteria capable to help the designer in selecting the desired elastic performance through which the shell undergoes. It is shown that the derived optimal solutions are ellipsoids with variable thicknesses, whose distributions depend on the mass constraint and the applied pressure. Nevertheless, the optimal shapes guarantee the uniformity of either the meridian or the hoop stress, and such uniformity has been verified within a numerical example by an accurate finite element analysis.

SRL-assisted AFM: Generating planar unstructured quadrilateral meshes with supervised and reinforcement learning-assisted advancing front method

High-quality mesh generation is the foundation of accurate finite element analysis. Due to the vast interior vertices search space and complex initial boundaries, mesh generation for complicated domains requires substantial manual processing and has long been considered the most challenging and time-consuming bottleneck of the entire modeling and analysis process. In this paper, we present a novel computational framework named “SRL-assisted AFM” for meshing planar geometries by combining the advancing front method with neural networks that select reference vertices and update the front boundary using “policy networks”. These deep neural networks are trained using a unique pipeline that combines supervised learning with reinforcement learning to iteratively improve mesh quality. First, we generate different initial boundaries by randomly sampling points in a square domain and connecting them sequentially. These boundaries are used for obtaining input meshes and extracting training datasets in the supervised learning module. We then iteratively improve the reinforcement learning model performance with reward functions designed for special requirements, such as improving the mesh quality and controlling the number and distribution of extraordinary points. Our proposed supervised learning neural networks achieve an accuracy higher than 98% on predicting commercial software. The final reinforcement learning neural networks automatically generate high-quality quadrilateral meshes for complex planar domains with sharp features and boundary layers.

Practical Investigation on the Strengthening of the Built-Up Steel Main Girder of a Metro Station with Carbon-Fiber-Reinforced Polymer on the Inside Part of the Tensioned Flange

This study investigates the effectiveness of a carbon-fiber-reinforced polymer (CFRP) in enhancing the load-carrying capacity of a steel main girder in a metro station. The objective is to evaluate the applicability of CFRPs in sustaining increases in applied loads and assessing their effectiveness on curved surfaces. Finite element analysis (FEA) identified the most stressed areas of the girder under design loads. Based on the FEA results, a targeted strengthening procedure using CFRP sheets was proposed. Various arrangements of CFRP sheets were tested, including different orientations and thicknesses up to 60% of the girder’s flange thickness. To validate the FEA accuracy, two small-scale specimen beams were prepared and tested in the laboratory. One beam was strengthened with CFRP sheets on the tension part of the inner flange side, similar to the suggested strengthening method for the girder. The FEA results show that the CFRP increases stresses by an average of 8% to 10% for the steel main girder, with strengthening effects up to 19% at the center of the CFRP strengthening positions, differing from a regular straight flange shape. Significantly reducing stresses required a total CFRP layer thickness of at least 50% of the flange’s total thickness. Applying a CFRP on the inner face of the girder preserves its usability without the need for openings in finishes or the metal deck surface. The findings highlight CFRP’s potential to enhance load-carrying capacity on curved surfaces and sustain increased applied loads, offering a promising solution for strengthening infrastructure and similar applications.

Biomechanical Analysis of Mandibular Bone-Implant Construct With Three Implant Screw Design: A Finite Element Study

Abstract Temporomandibular joint replacement (TMJR) is a surgical procedure that relies heavily on the biomechanical properties of the implant-bone interface for success. In this study, we investigated the effects of three commonly used implant screw thread designs (buttress, square, and triangle) on the biomechanical performance of the mandibular bone-implant construct, with the aim of improving osseointegration. Using finite element analysis, we simulated the mechanical behavior of the prosthesis and mandible and examined the biomechanics of the temporomandibular joint. We considered five coefficients of friction ranging from 0.1 to 0.5 in our analyses. Our hypothesis was that changing the screw thread shape while keeping the pitch, height, and depth constant could enhance the biomechanical environment at the peri-implant bone. Our results indicate that the square thread design produced the highest stress concentration, while the triangle thread design exhibited the most favorable distribution of stress around the implant. Furthermore, increasing the coefficient of friction led to an increase in stress concentration in the implant and surrounding bone. Our findings offer valuable insights into the biomechanical performance of different screw thread designs in the mandibular bone-implant construct. They highlight the significance of considering screw thread shape and coefficient of friction in TMJR implant design. Future studies should incorporate the viscoelastic properties of bone to improve the accuracy of finite element analysis. This research contributes to the optimization of TMJR implants and ultimately enhances patient outcomes.

Does rotation increase the acoustic field of view? Comparative models based on CT data of a live dolphin versus a dead dolphin

Rotational behaviour has been observed when dolphins track or detect targets, however, its role in echolocation is unknown. We used computed tomography data of one live and one recently deceased bottlenose dolphin, together with measurements of the acoustic properties of head tissues, to perform acoustic property reconstruction. The anatomical configuration and acoustic properties of the main forehead structures between the live and deceased dolphins were compared. Finite element analysis (FEA) was applied to simulate the generation and propagation of echolocation clicks, to compute their waveforms and spectra in both near- and far-fields, and to derive echolocation beam patterns. Modelling results from both the live and deceased dolphins were in good agreement with click recordings from other, live, echolocating individuals. FEA was also used to estimate the acoustic scene experienced by a dolphin rotating 180° about its longitudinal axis to detect fish in the far-field at elevation angles of −20° to 20°. The results suggest that the rotational behaviour provides a wider insonification area and a wider receiving area. Thus, it may provide compensation for the dolphin’s relatively narrow biosonar beam, asymmetries in sound reception, and constraints on the pointing direction that are limited by head movement. The results also have implications for examining the accuracy of FEA in acoustic simulations using recently deceased specimens.

Design and Analysis of Multifidelity Finite Element Simulations

Abstract The numerical accuracy of finite element analysis (FEA) depends on the number of finite elements used in the discretization of the space, which can be varied using the mesh size. The larger the number of elements, the more accurate the results are. However, the computational cost increases with the number of elements. In current practice, the experimenter chooses a mesh size that is expected to produce a reasonably accurate result, and for which the computer simulation can be completed in a reasonable amount of time. Improvements to this approach have been proposed using multifidelity modeling by choosing two or three mesh sizes. However, mesh size is a continuous parameter, and therefore, multifidelity simulations can be performed easily by choosing a different value for the mesh size for each of the simulations. In this article, we develop a method to optimally find the mesh sizes for each simulation and satisfy the same time constraints as a single or a double mesh size experiment. A range of different mesh sizes used in the proposed method allows one to fit multifidelity models more reliably and predict the outcome when meshes approach infinitesimally small, which is impossible to achieve in actual simulations. We illustrate our approach using an analytical function and a cantilever beam finite element analysis experiment.

Multiparameter Estimation of IPMSMs Using Core Loss Current Calculations in dq-Axis Equivalent Circuit Model

Accurate parameter estimation is critical for high-performance modeling and control of interior permanent magnet synchronous machines (IPMSMs). Core loss effects affect the accuracy of the parameter estimation, especially in high loading conditions with saturated cores. Existing research on parameter estimation considering core loss effects generally focuses on the core loss equivalent resistance estimation; however, they require either accurate core loss experimental data or finite element analysis (FEA) model. The core loss equivalent resistance is dependent on the loading conditions, harmonics, frequency, and temperature, which increases the difficulty of accurately estimating the resistance. This article firstly proposes a direct core loss equivalent current estimation method for multiparameter estimation purposes without estimating the core loss equivalent resistance. Based on the estimated core loss equivalent currents, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis inductances equivalent currents are calculated to perform the multiparameter estimation. The proposed approach can improve the precision of the parameter estimation and the computation efficiency by calculating the core loss equivalent resistance currents without having the core loss data. The effectiveness of the proposed multiparameter estimation method is evaluated by comparing the calculated and measured torques of a laboratory 4.5 kW IPMSM in various operating conditions. The improved accuracy of the proposed method is verified by comparing it with two existing online parameter estimation methods and FEA-based offline parameter estimation results.

Study on a Novel Hybrid Thermal Network of Homopolar Inductor Machine

The thermal analysis is necessary for the design and safe operation of the homopolar inductor machine (HIM) applied in the flywheel energy storage system (FESS). However, due to its unique three-dimensional (3-D) structure, the thermal analysis of HIM relies on the 3-D finite element analysis (FEA) or computational fluid dynamics (CFD), which is time-consuming and computationally inefficient. To facilitate the thermal analysis and design of HIM, a fast and accurate analytical model is essential. In this article, the novel 2-D and 3-D hybrid thermal networks combined with a coupled iterative analysis method are proposed to predict the temperature of HIM. First, the structure, operation principle, and material properties of HIM are illustrated. Second, the heat sources of HIM, including iron loss, rotor eddy current loss, rotor air friction loss, copper loss, and bearing loss, are fully analyzed and investigated. Third, the proposed hybrid thermal model (HTM) and coupled iterative analysis method are demonstrated and applied to predict its temperature. The proposed thermal model and analysis methods are explained in detail. The influences of different speeds and operation conditions on the temperature rise of HIM are analyzed based on the proposed thermal model and FEA. Finally, the temperature of an HIM prototype is tested, which proves the accuracy of FEA and the proposed method. The proposed HTM can quickly and accurately predict the temperature of HIM, which provides a new idea for the temperature prediction of this kind of machine.

3D FE analysis for buckling behavior of longitudinal reinforcement embedded in LRS FRP-confined concrete under axial compression

Large rupture strain (LRS) FRPs have great potential to be used for seismic retrofit of RC columns because of its high rupture strain (i.e., > 5%) that provides better confinement effects. However, in FRP-confined RC columns, the longitudinal reinforcements may buckle before the LRS FRP rupture, especially in the case of large stirrup spacing. This study aims to present a 3D finite element (FE) model for simulating the buckling effect of longitudinal reinforcements in LRS FRP-confined RC columns. A modified concrete damaged plasticity model (CDPM) is proposed to consider the deformation and mechanical characteristics of LRS FRP-confined concrete. Removal of failed concrete elements is considered to facilitate the buckling of longitudinal reinforcements in LRS FRP-confined RC columns. The FE analysis accuracy was verified by comparisons with test results. The factors affecting the buckling of longitudinal reinforcements were discussed through an extensive parametric study. Empirical formulas for the stress and strain values at which the longitudinal reinforcement starts to soften were developed. An empirical formula for the ultimate axial strain of LRS FRP-confined RC columns determined by longitudinal reinforcement buckling was also obtained by regression analysis.