Finite Element Predictions Research Articles

Automated bone property analysis using corrected in vivo dental cone-beam CT data of human wrists

Fracture liaison services are essential to mitigate underdiagnosis and undertreatment of osteoporosis-related fractures. However, it often suffers from limited access to dual-energy X-ray absorptiometry (DXA) or high-resolution peripheral quantitative CT equipment. This in vivo study of 21 patients aims to evaluate the feasibility of dental cone beam CT (dCBCT) to analyse bone properties of human wrists, comparing with DXA and finite element (FE) analysis. dCBCT grey-scale values were transformed to HU using a phantom containing materials with known HU values. Strong correlations were found between bone mineral content (BMC) from dCBCT and DXA (r = 0.78 to 0.84, p < 0.001), as well as between BMC from dCBCT FE-predicted stiffness (r = 0.91) and maximum force (r = 0.93), p < 0.001. BMC values from dCBCT were higher than DXA measurements (2.34 g vs. 1.5 g, p < 0.001). Cortical thickness strongly correlated to bone mineral density (BMD) from dCBCT (r = 0.83, p < 0.001). No statistically significant correlations were found between trabecular bone microstructure and FE predictions. The results indicate the feasibility to analyse osteoporosis related bone properties of human wrists from corrected dCBCT data. The dCBCT values of BMD and BMC were strongly correlated with DXA.

Machine Learning–Finite Element Mesh Optimization-Based Modeling and Prediction of Excavation-Induced Shield Tunnel Ground Settlement

Ground settlement prediction for shield construction is highly important and challenging. This study introduces a machine learning algorithm combined with finite element numerical simulation, i.e., machine learning–finite element mesh optimization. For surface subsidence prediction, 16 combination models of ANN, KNN, RF and SVR were optimized by PSO, GA, BT and BO, involving raw data preprocessing, principal component analysis, hyperparameter selection and prediction accuracy evaluation. A subway shield tunneling project was analyzed, in which the meshes of finite element numerical models were discretized into different sizes from 1.0[Formula: see text]m to 2.0[Formula: see text]m. In total, 360 sets of data points were extracted from the simulation results, including stress, strain, shield jacking force, internal friction angle, cohesion force, and settlement, of which 252 data points were used as the input parameters of machine learning model. Analysis of average error rate of finite element–machine learning coupling models showed that the finite element model had the highest accuracy of settlement prediction when the mesh size of the finite element model was 1.4[Formula: see text]m, and the GA-SVR model had the highest accuracy and generalization ability in ground settlement prediction. This study highlights the uniqueness of machine learning–finite element mesh optimization model in application.

Data-driven homogenisation of viscoelastic porous elastomers: Feedforward versus knowledge-based neural networks

A computational framework is established to implement time-dependent data-driven surrogate constitutive models for the homogenised mechanical response of porous elastomers at large strains. The aim is to enhance the computational efficiency of multiscale analyses through the use of these surrogate models. To achieve this, explicit finite element (FE) simulations are conducted to predict the homogenised response of a cubic unit cell of a porous elastomer, using two different viscoelastic descriptions of the parent material, subject to pseudo-random, multiaxial, non-proportional histories of macroscopic strains. The histories of homogenised variables extracted from each set of FE predictions form a training dataset, which is used to train two different surrogate models, both relying on artificial neural networks (NNs). The first model predicts the increment in macroscopic stress over a simulation step, as a function of the macroscopic stress and strain at the beginning of the step, of the prescribed macroscopic strain increment, and of the corresponding time increment. The second model uses the same inputs and outputs but tests a knowledge-based modelling approach: it relies on the aid of an additional nonlinear elastic constitutive model, which is time- and path-independent and known a priori. This model represents an existing base of knowledge which is augmented and corrected by a NN after training on viscoelastic data. The data-driven surrogate model, therefore, learns the viscoelastic behaviour of the unit cell starting from knowledge of its elastic response. The two surrogate models are found to have comparable and very high accuracies, capturing the response of the homogenised unit cell to complex loading histories. Hyperparameter optimisation shows that the second, knowledge-based model requires a simpler NN and therefore incurs a smaller computational cost.

Inclusion of Muscle Forces Affects Finite Element Prediction of Compression Screw Pullout but Not Fatigue Failure in a Custom Pelvic Implant

Custom implants used for pelvic reconstruction in pelvic sarcoma surgery face a high complication rate due to mechanical failures of fixation screws. Consequently, patient-specific finite element (FE) models have been employed to analyze custom pelvic implant durability. However, muscle forces have often been omitted from FE studies of the post-operative pelvis with a custom implant, despite the lack of evidence that this omission has minimal impact on predicted bone, implant, and fixation screw stress distributions. This study investigated the influence of muscle forces on FE predictions of fixation screw pullout and fatigue failure in a custom pelvic implant. Specifically, FE analyses were conducted using a patient-specific FE model loaded with seven sets of personalized muscle and hip joint contact force loading conditions estimated using a personalized neuromusculoskeletal (NMS) model. Predictions of fixation screw pullout and fatigue failure—quantified by simulated screw axial forces and von Mises stresses, respectively—were compared between analyses with and without personalized muscle forces. The study found that muscle forces had a considerable influence on predicted screw pullout but not fatigue failure. However, it remains unclear whether including or excluding muscle forces would yield more conservative predictions of screw failures. Furthermore, while the effect of muscle forces on predicted screw failures was location-dependent for cortical screws, no clear location dependency was observed for cancellous screws. These findings support the combined use of patient-specific FE and NMS models, including loading from muscle forces, when predicting screw pullout but not fatigue failure in custom pelvic implants.

Cylindrical Composite Structural Design for Underwater Compressed Air Energy Storage

Abstract The utilization of renewable energy sources is pivotal for future energy sustainability. However, the effective utilization of this energy in marine environments necessitates the implementation of energy storage systems to compensate for energy losses induced by intermittent power usage. Underwater compressed air energy storage (UWCAES) is a cost-effective and emission-free method for storing energy underwater. This technology has proven to be effective and viable, and it offers significant benefits in terms of energy efficiency and sustainability. In this paper, a cylindrical composite structure UWCAES tank is designed. At first, the materials and shapes of the different forms of air containers were evaluated, and the relationship between container diameter, length, and number of air containers was analyzed on the basis of the range of energy storage densities for different kinds of systems. Subsequently, the materials to be applied in the tanks were investigated and selected according to the actual working conditions of the system. Eventually, finite element models (FEMs) and prediction formula were developed, and the influence of changes in the thicknesses of the steel reinforcement was discussed. The results demonstrated that the storage tank possesses adequate environmental resistance and load-bearing capacity, which can provide a reference for its practical engineering implementation.

On the role of the retained porosity on the shock response of additively manufactured high-performance steel: Experiments, constitutive model and finite-element predictions

Experiments have shown that for quasi-static and moderate strain-rates (of the order of 102–103/s) the mechanical response of additively manufactured (AM) and traditionally processed high-strength steels is similar whereas the impact behavior is markedly different. In this paper, we reveal that the main reason for this difference is the retained porosity in the AM material. Fully-implicit finite element calculations are presented in which we simulate both the launching of the impact plate and the impact between the two plates. The constitutive model used is the elastic/plastic model for porous ductile materials with matrix displaying tension-compression asymmetry and Johnson-Cook hardening law that accounts for both strain-rate effects and plastic history. It is shown that even a very small initial porosity changes the wave front, decreases the Hugoniot while increasing the shock rise time, when compared to a void free material. Furthermore, quantitative comparisons between simulation results and plate impact data for both the AM and the wrought AF9628 steel are provided. The good agreement show that the model captures the impact response and illustrates the model capabilities to provide information on field variables that cannot be directly measured.Additive manufacturing (AM) of metals is rapidly advancing as a robust method for production of geometrically complex parts. To enhance understanding of material performance and open up additional application opportunities, dynamic characterization of newly printed alloys is required to validate their effectiveness. In this paper, we present results from plate impact testing of AF9628 steel, a newly developed high-strength low alloy martensitic steel for structural applications which require resistance to high-rate deformation. We put into evidence differences in the shock structure between the AM and the traditionally processed material. To gain understanding, we conduct fully-implicit finite element (FE) calculations in which we model both the launching of the impact plate and the impact between the two plates, respectively. An elastic/plastic damage model that accounts for the effects of the tension-compression asymmetry in plastic deformation and its influence on porosity evolution is used. The FE results reveal that even a very small amount of initial porosity leads to an increase in the shock rise time, explaining the observed trends. Furthermore, quantitative comparisons between simulation results and plate impact data for both the AM and the wrought AF9628 are provided. The good agreement show that the model captures the impact response and illustrates the model capabilities to provide information on field variables that cannot be directly measured.

Prediction of the Contact Behavior of Stepseals: Experimental and Numerical Investigations

The contact behavior of a stepseal affects its reliability and remaining life. In this study, experimental and numerical analyses were performed to investigate the contact behavior of a typical stepseal. Its dimensions and material properties were also tested. The Mooney–Rivlin hyperelastic model was used to fit the stress–strain data of the rubber. A static contact pressure of 105.1 MPa was obtained using the Fujifilm pressure measurement film. A finite element model of a stepseal with reasonable element sizes was established. A comparison between the experimental results and finite element (FE) predictions shows that the finite element method underpredicts the maximum static contact pressure and contact length. For the maximum contact pressure, the test results were approximately 30.4% higher than those of the FE predictions.

An Investigation of Thermomechanical Behavior in Laser Hot Wire Directed Energy Deposition of NAB: Finite Element Analysis and Experimental Validation

Laser Hot Wire (LHW) Directed Energy Deposition (DED) Additive Manufacturing (AM) processes are capable of manufacturing parts with a high deposition rate. There is a growing research interest in replacing large cast Nickel Aluminum Bronze (NAB) components using LHW DED processes for maritime applications. Understanding thermomechanical behavior during LHW DED of NAB is a critical step towards the production of high-quality NAB parts with desired performance and properties. In this paper, finite element simulations are first used to predict the thermomechanical time histories during LHW DED of NAB test coupons with an increasing geometric complexity, including single-layer and multilayer depositions. Simulation results are experimentally validated through in situ measurements of temperatures at multiple locations in the substrate as well as displacement at the free end of the substrate during and immediately following the deposition process. The results in this paper demonstrate that the finite element predictions have good agreement with the experimental measurements of both temperature and distortion history. The maximum prediction error for temperature is 5% for single-layer samples and 6% for multilayer samples, while the distortion prediction error is about 12% for single-layer samples and less than 4% for multilayer samples. In addition, this study shows the effectiveness of including a stress relaxation temperature at 500 °C during FE modeling to allow for better prediction of the low cross-layer accumulation of distortion in multilayer deposition of NAB.

A multi-level-variable correlated mechanistic model system for irradiation-induced multi-scale volume growths of U-10Mo/Zr dispersion nuclear fuels

Irradiation-induced volumetric deformations in dispersion nuclear fuels arouse a critical concern in nuclear fuel design. Utilizing the concepts from mesomechanics and homogenization, a multi-level-variable correlated mechanistic model system called the Dispersion Fuel Swelling Analysis Model System (DFSAMS) is developed for the irradiation-induced multi-scale volume growths of U-10Mo/Zr dispersion nuclear fuels. These models could directly correlate the macroscopic irradiation-induced volume growth strain with the dynamically varying multi-level information, including the obtained particle volume fractions, the current porosities of recrystallized zones of fuel grains, the macroscale porosities of fuel particles, the average numbers of fission gas atoms within fuel bubbles, the average bubble pressures and the macroscale pressures of fuel particles related to the macroscale hydrostatic pressures of dispersion fuels. The obtained theoretical results align favorably with finite element predictions and a diverse range of experimental data, demonstrating the effectiveness of the newly developed model system. It is indicated that: (1) the irradiation creep performance of the Zr matrix becomes the predominant factor influencing the macroscale volume growth deformations of U-10Mo/Zr dispersion fuels, due to the differed resistance to volumetric deformations of U-10Mo particles; (2) the as-fabricated bubbles of fuel particles will gradually decrease in size under the macroscale hydrostatic pressures due to the irradiation creep deformations occurring in the surrounding solid skeleton, contributing negatively to the macroscale volumetric expansion of U-10Mo/Zr dispersion fuels, especially in cases with higher initial porosity. The important theoretical models are supplied here for efficient numerical simulation of the irradiation-induced thermal-mechanical coupling behaviors in U-10Mo/Zr dispersion fuel elements.

Flow behaviors of various metals under tensile load

Abstract The influence of flow behaviors on the results of finite element (FE) analyses of metal-forming processes is dominant, even though it varies with strain hardening and softening phenomena. However, obtaining a flow curve with sufficient accuracy is not easy, particularly at large strains. Among various well-known methods of obtaining flow curves, tensile testing-based method is effective to obtain flow curves at large strains at room temperature. It is believed that the strain hardening behavior at large strains during the tensile test was not fully known. In this study, the flow curves, previously obtained using the combined tensile test and finite element method (FEM) approach, are classified as four categories, including monotonic strain hardening function, double-curvature strain hardening function, strain hardening-perfectly-plastic function, and perfectly-plastic-strain softening function. The tensile test characteristics of each type are investigated using its FE predictions, revealing that the specific type of a material can be identified by the tensile test.

3D strain heterogeneity and fracture studied by X-ray tomography and crystal plasticity in an aluminium alloy

Strong correlations between measured strain fields and crystal plasticity finite element (CP-FE) predictions based on the real microstructure are found for a plane strain tensile specimen made of 6016 T4 aluminium alloy. This is achieved using multimodal X-ray lab tomography giving access to both the initial grain structure and the strain evolution. The real microstructure of the central region of interest (ROI) of the undeformed specimen is obtained non destructively using lab-based diffraction contrast tomography (DCT) and meshing. An in situ tensile test, using absorption contrast tomography (ACT) is then performed for twelve loading increments up to fracture. Taking advantage of the plane strain condition, the evolution of the internal strain field is measured by two-dimensional digital image correlation (DIC) in the material bulk using the natural speckle provided by intermetallic particles. Early strain heterogeneities in the form of slanted bands, that are spatially stable over time, are revealed and the fracture path – determined from the post mortem scan – is found to coincide with the bands exhibiting maximum strain. CP-FE simulations are performed on the meshed microstructure of the specimen acquired by DCT and are compared with image correlation measurements. The measured strain fields are well described by 3D CP-FE predictions, whilst it is shown that neither a macroscopic anisotropic plasticity model nor a CP-FE simulation with random grain orientations could reproduce the measurements.

Strain measurement of CFRP-Steel bonded joints using distributed optical fibre sensors

ABSTRACT Externally bonded carbon fibre reinforced polymer (CFRP) is widely employed for strengthening steel structures. The CFRP-steel bond behaviour is typically conducted using the single-lap joint (SLJ) and double-lap joint (DLJ) shear tests. This study utilizes advanced distributed optical fibre sensors (DOFS) to measure strains in CFRP-steel SLJs and DLJs, with a specific focus on examining the bending effect. An experimental investigation was conducted to verify the appropriate adhesive and fibre coating materials, achieving synergistic deformation between optical fibre sensors and adherends. The strain results reveal that PI-coated fibres bonded with epoxy resin enhance deformation compatibility. The CFRP strain distributions within the joints are accurately measured by DOFS, enabling the calculation of bending strain to assess joint bending effects. The observed strain aligns well with the finite element (FE) predictions. A more significant bending effect is observed in SLJs compared to DLJs, predominantly concentrated at the loaded end. It can be inferred that the SLJs are subjected to mixed-mode I/II loading in shear tests, and the DLJs appears to be mainly influenced by mode II loading. Additionally, the verified FE model demonstrates that the shear strain across the thickness of the adhesive layer exhibits significant variation at the bond ends.

An improved flexural design procedure of steel plate I‐girders considering elastic lateral torsional buckling at elevated temperatures

AbstractIn the present study, an improved design method is proposed for the flexural design of steel plate I‐girders at elevated temperatures. The proposed method accounts for two important phenomena accompanying the temperature increase in steel I‐girders: (1) alteration of the failure mode and (2) degradation of the material properties. The main strategy of the proposed procedure is to find the ambient‐temperature‐equivalent design parameters of steel I‐girders at elevated temperatures. The basic design relationships are adopted from the flexural design provisions of AISC 360‐16 and then modified to accommodate the elevated temperatures and instability conditions of I‐girders. To evaluate the accuracy and efficiency of the proposed method, a comprehensive finite element study is conducted using ABAQUS. To this aim, 54 numerical models of steel plate I‐girders with different cross‐section slenderness parameters were investigated. All the simulated I‐girders were prone to fail in elastic lateral‐torsional buckling mode at both ambient temperature and elevated temperatures. To corroborate the numerical modeling and analysis process at ambient and elevated temperatures, the results were verified against the available experimental data. Based on the results, the maximum absolute deviation of the ultimate flexural strength obtained from the proposed method from the finite element predictions was 9%.

Dynamic Behavior of Ribbed Viscoelastic CNT‐PDMS Thin‐Films for Multifunctional Applications

AbstractTailored ribbing structures are obtained by large‐scale rolling in polymer PDMS thin‐films by adding carbon nanotubes (CNT) inclusions, which significantly improved the mechanical behavior of systems subjected to dynamic compressive strain rates. A nonlinear explicit dynamic three‐dimensional finite‐element (FE) scheme is used to understand and predict the thermomechanical response of the manufactured ribbed thin‐film structures subjected to dynamic in‐plane compressive loading. Representative volume element (RVE) FE models of the ribbed thin‐films are subjected to strain rates as high as 104 s−1 in both the transverse and parallel ribbing directions. Latin Hypercube Sampling of the microstructural parameters, as informed from experimental observations, provide the microstructurally based RVEs. An interior‐point optimization routine is also employed on a regression model trained from the FE predictions that can be used to design ribbed materials for multifunctional applications. The model verifies that damage can be mitigated in CNT‐PDMS systems subjected to dynamic compressive loading conditions by controlling the ribbing microstructural characteristics, such as the film thickness and the ribbing amplitude and wavelength. This approach provides a framework for designing materials that can be utilized for applications that require high strain rate damage tolerance, drag reduction, antifouling, and superhydrophobicity.

Prediction of elastic properties of woven polymer composites using micromechanical models and measured microstructural parameters

Prediction of elastic properties of plain weave composites using two well-known micromechanical models is addressed, along with a dedicated finite element model of the unit cell which includes details of the woven architecture. Predictions of micromechanical models are carried out using geometric input parameters statistically measured from micrographies of the unit cell of the plain weave composite and compared to finite element predictions and to measured elastic properties of an E-glass/vinyl ester plain weave composite. The micromechanical models predict that the width and thickness of the yarn in the fill and warp directions greatly influence the elastic properties and anisotropy of the plain weave composite. Good agreement between all approaches and the measured values is observed for the in-plane elastic properties, as long as the input geometric parameters of the unit cell required for the models are measured with statistical rigor. However, transverse shear moduli are not accurately predicted by the examined micromechanical models, only by the finite element method. Reasons for such discrepancies are discussed and supported by modeling findings and digital image correlation full field strain maps.

Mesoscopic finite-element prediction method for impact-energy absorption mechanism of multiphase STF/Kevlar composite fabric

Shear-thickening fluids (STFs) effectively enhance the impact-energy absorption of Kevlar fabrics and offer an extensive range of applications for human-safety protection. To precisely depict the impact-energy absorption mechanism and stress transfer behavior of multiphase STF/Kevlar composite fabrics under high strain rates, this study introduces a yarn-interface-friction constitutive model that accounts for the strain rate-thickening effect of STFs. The model is incorporated into a mesoscale numerical simulation to enhance computational accuracy. Theoretical models (impact-pit morphology, yarn-strain, and fabric-strain energy models) are employed to evaluate the off-plane displacement, strain distribution, and impact-energy absorption during impact imprint tests. The established simulation model shows high similarity (0.99) to the impact imprint profile curve and reveals that the strain energy and interfacial friction energy of the composite fabrics contribute primarily to energy dissipation during the impact process. Furthermore, in all specimens, C-STF/Kevlar (CNTs reinforced STF/Kevlar) exhibits reduced off-plane displacement, increased primary-yarn stress, and a higher capacity for impact kinetic-energy absorption. The proposed interface-friction constitutive model can accurately predict the deformation and energy absorption levels of the composite fabrics at various strain rates, thereby offering effective simulation guidance for the preliminary design of composite fabrics.

Compressive behavior of fiber-reinforced concrete strengthened with CFRP strips after exposure to temperature environments

Abstract Reinforced concrete constructions are extremely vulnerable to fire damage over their lifespan. Despite its non-flammability, concrete is nonetheless affected by fire exposure, which impacts its stress–strain characteristics and durability. Therefore, developing strengthening methods is an economical option compared to the costs of demolishing and rebuilding constructions. This article aims to experimentally and numerically examine the strengthening of fiber-reinforced concrete cylinders by using carbon fiber-reinforced polymer (CFRP) strips after exposure to 600°C. Four different concrete mixtures have been investigated. A total of 48 cylinders were subjected to axial compression testing. The testing program primarily focused on three variables: (i) exposure temperature (600°C); (ii) the effect of using various types of fibers (steel fiber, polypropylene, and hybrid fibers); and (iii) CFRP strengthening. Finite element (FE) models were created using the ABAQUS program to conduct numerical analysis of concrete cylinders in exposure to heating scenarios and strengthen them with CFRP strips. The results show that when subjected to a temperature of 600°C, the compressive strength decreased significantly, ranging from 23.7 to 53.3%. The presence of fibers significantly impacted compressive strength, regardless of the fiber type, leading to an enhanced ratio of up to 34.7% in comparison to the control cylinders (i.e., unheated and unstrengthened cylinders). The suggested strengthening procedures using CFRP strips effectively repaired the heat-damaged cylinders, surpassing the initial compressive strength of unheated cylinders. The FE prediction shows satisfactory, consistent results in comparison to experimental data.

Impact of Impeller Speed Adjustment Interval on Hemolysis Performance of an Intravascular Micro-Axial Blood Pump.

In recent years, intravascular micro-axial blood pumps have been increasingly used in the treatment of patients with cardiogenic shock. The flow rate of such blood pumps requires adjustment based on the patient's physiological condition. Compared to a stable flow state with fixed rotation speed, adjusting the speed of blood pump impeller to alter flow rate may lead to additional hemolysis. This study aimed at elucidating the relationship between adjusting interval of a blood pump's impeller speed and the hemolysis index. By comparing simulation results with P-Q characteristic curves of the blood pump measured by experiments, the accuracy of the blood pump flow field simulation model was confirmed. In this study, a drainage tube was employed as the device analogous to an intravascular micro-axial blood pump for achieving similar shear stress levels and residence times. The hemolysis finite element prediction method based on a power-law model was validated through hemolysis testing of porcine blood flow through the drainage tube. The validated models were subsequently utilized to investigate the impact of impeller speed adjusting intervals on hemolysis in the blood pump. Compared to steady flow, the results demonstrate that the hemolysis index increased to 6.3% when changing the blood pump flow rate from 2 L/min to 2.5 L/min by adjusting the impeller speed within 0.072 s. An adjustment time of impeller speed longer than 0.072 s can avoid extra hemolysis when adjusting the intravascular micro-axial blood pump flow rate from 2 L/min to 2.5 L/min.

Understanding the machined material’s behaviour in electro-discharge machining (EDM) using a multi-phase smoothed particle hydrodynamics (SPH) modelling

Electro-discharge machining (EDM) has been extensively employed for machining hard alloys, and its simulations have been widely conducted using finite element analysis (FEA). However, the majority of mesh-based models depended on forecasting the crater profile only based on the temperature gradient, without offering detailed data regarding the machined material properties. It is crucial to understand the behaviour of the machined material in order to accurately assess the flushing efficiency, analyse the wear on the electrode, and examine the interaction between the debris generated during machining and the remaining workpiece. This is done to ensure that no recast material is left behind after the EDM process. For the first time, a meshless smoothed particle hydrodynamics multi-phase model was implemented to gain practical insights and comprehensively understand a very intricate phenomenon that occurs within a very short time. Additionally, this approach is utilised to investigate the characteristics of the materials being machined. We utilised our SPH model to simulate both the capacitance- and transistor-based EDM of Ti–6Al–4V and AISI304 steel. Our simulation considered the temperature-dependent thermal properties and latent heats of the materials. The accuracy of our model was confirmed by comparing its results with experimental, analytical, and finite element analysis (FEA) results. The machined material was observed during its removal from the surface, and the dimensions of the resulting crater, as well as its aspect ratio and the rate at which the material was removed, were predicted with an error ranging from 2 to 22%. This error is far lower than that of the typical finite element (FE) prediction. This model lays the groundwork for a more complex model that will more accurately represent EDM and other similar manufacturing processes.

Ejector pin-related high-cycle fatigue fracture of the critical die corner during automatic multistage cold forging of an automotive wheel nut

An experimental and numerical study on the ejector pin's mechanics during automatic multistage cold forging (AMSCF) of an automobile wheel nut is conducted. The traditional, decoupled die structural analysis method (DDSM) of analyzing die structures as one of the post-processing functions is criticized, which uses the tractions exerting on the die parts predicted from the forging simulation under the rigid die assumption. To cope with the matter of the DDSM, a multibody treatment scheme (MBTS) is proposed to simulate the AMSCF process, emphasizing the ejector pin's mechanics, using an implicit elastoplastic finite element method. The experiments qualitatively validate the finite element predictions. It is shown that the asymmetric sheared material in AMSCF greatly influences the ejector pin's mechanics, which is characterized by its lateral and longitudinal displacements because of its structural flexibility. It is emphasized that the detailed understanding of the ejector pin's mechanics may not only give a helpful connection towards smart manufacturing because of its mechanical flexibility and sensitivity to the excitations and responses, but it also reveals the reason for the die's high-cycle fatigue (HCF) fracture of the critical die corner (CDC) near at the end of the ejector pin.