Finite Element Method Model Research Articles

Comparative Analysis of Non-Rigid Registration Techniques for Liver Surface Registration.

Non-rigid surface-based soft tissue registration is crucial for surgical navigation systems, but its adoption still faces several challenges due to the large number of degrees of freedom and the continuously varying and complex surface structures present in the intra-operative data. By employing non-rigid registration, surgeons can integrate the pre-operative images into the intra-operative guidance environment, providing real-time visualization of the patient's complex pre- and intra-operative anatomy in a common coordinate system to improve navigation accuracy. However, many of the existing registration methods, including those for liver applications, are inaccessible to the broader community. To address this limitation, we present a comparative analysis of several open-source, non-rigid surface-based liver registration algorithms, with the overall goal of contrasting their strength and weaknesses and identifying an optimal solution. We compared the robustness of three optimization-based and one data-driven nonrigid registration algorithms in response to a reduced visibility ratio (reduced partial views of the surface) and to an increasing deformation level (mean displacement), reported as the root mean square error (RMSE) between the pre-and intra-operative liver surface meshed following registration. Our results indicate that the Gaussian Mixture Model - Finite Element Model (GMM-FEM) method consistently yields a lower post-registration error than the other three tested methods in the presence of both reduced visibility ratio and increased intra-operative surface displacement, therefore offering a potentially promising solution for pre- to intra-operative nonrigid liver surface registration.

Thermal expansion behavior and analysis of Al/AlN interpenetrating phase composites with different preform porosity

In this work, the coefficient of thermal expansion (CTE) of Al/AlN interpenetrating phase composites (IPCs) has been measured based on the length change from room temperature (RT) to 200 °C. 3D representative volume elements (RVEs) are created to model the microstructures of Al/AlN IPCs and the finite element models generated from RVEs are used to study thermal expansion behavior. CTE was predicted utilizing the finite element method (FEM) and thermo-elastic models of Kerner, Turner and Schapery, after which the results were compared with the experimental values. According to experimental results, a notable reduction in the CTE of IPCs is observed as preform porosity decreases. This shows that an AlN preform can effectively enhance dimensional stability. A comparative analysis of extant literature indicates that IPCs may attain a lower CTE compared to particle-reinforced composites. Experimental data align closely with analytical models. The FE simulation results demonstrate better consistency with experimental data only under conditions of high preform porosity, since residual thermal stresses and plastic deformation were not considered.

Comparative Study of Numerical Methods for Predicting Crack Propagation in Reinforced Concrete Hollow Core Slabs

Hollow core slabs are commonly used in prefabricated building construction and are calculated and constructed using gravity loads. The dead loads of the structure are reduced by using this slab system. Different criteria, such as the initiation and propagation of cracks in the hollow core slab, are used to analyze these slabs. Fracture mechanics is the basis for studying crack propagation. The present study was conducted to analyze the propagation of cracks in hollow core slabs under common loading conditions using the finite element method and numerical modeling to analyze cracks in reinforced concrete members. This research is theoretically conducted using finite element software. This research takes into account the potential varieties of cracks in concrete slabs. Slabs should consider all three types of cracks, which are shear, flexural, and flexural-shear cracks obtained from the reference test. Two Contour integral and XFEM methods are used to analyze cracks in Abaqus software. To validate and control the modeling process, the laboratory results of the research of Ibrahim N. Najma, Raid A. Daudb, and Adel A. Al-Azzawi. December 2, 2019, has been used. The outcomes of this study showed that the probability of the formation of a flexural-shear crack in the slab is higher than in other crack forms.

Influence of modelling hypotheses on strength assessment of CFRP stepped repairs

Composite stepped repairs can achieve high strength recovery without the addition of bolts or fasteners to the structure. They are therefore a major issue in the field of aerospace composite structure damage repair. However, there is no standardized method to design this type of repairs. Many analytical, semi-analytical and finite element models were proposed throughout the years to predict the strength of stepped repairs, using various hypotheses and simplifications. The aim of this paper is to investigate the influence of modelling hypotheses on stress distribution and strength prediction of composite stepped repairs. Five simplified stepped joint models using macro-element (ME) modelling and finite element method (FE) are compared to a full 3D FE model of a stepped repaired panel. The influence of step length and adhesive fracture toughness was investigated to determine the field of validity of each model. Among FE models, it was shown that modelling the equivalent joint under 2D generalized plain strain gives a very close strength prediction to the 3D stepped repair model while saving computation time. Simplified macro-element models under bar or beam hypotheses are fairly close to the results of FE modelling, but the deviation between those and FE is sensitive to step length and adhesive fracture toughness.

Multi-scale simulation of Mo–Ag laminated metal matrix composites with Mo–Ag diffusion layer and parallel gap resistance welding in solar cells

Thus far, Mo/Ag laminated metal matrix composites (LMMCs) have been widely used as interconnectors in solar cells. In order to enhance the connection strength between Mo–Ag LMMCs and solar cells, a multi-scale simulation technique (MSM) was utilised to simulate the parallel gap resistance welding (PGRW) process. This method involved molecular dynamics (MD) simulation and the finite element method (FEM). The structure of the Mo–Ag diffusion layer was examined by high-resolution transmission electron microscopy (HRTEM), which revealed a thickness of around 5 nm. It exhibited a wedge-shaped configuration that augmented the bonding between Mo and Ag. The characteristics of the Mo–Ag diffusion layer were computed using molecular dynamics (MD), which has a substantial influence on the properties of the interconnectors. The FEM model was provided with these characteristics, and a total of nine sets of orthogonal simulation experiments were devised. The findings indicate that when a voltage of 0.5 V is applied, the distance between the electrodes is 0.15 mm, and the pressure on the electrodes is 8.89 N, the temperature at the interface of the workpiece can reach 940 °C. Furthermore, the internal stress (90 MPa) remains below the material's yield strength (430 MPa). In addition, based on the specifications of nine sets of orthogonal trials, the interconnectors were welded to the solar cells, and further 45° tensile tests were performed on the resulting joints. According to the simulation, the connection strength can achieve a maximum value of 558 gf (5.47 N) using the optimal parameters. Meanwhile, the findings from electron backscatter diffraction (EBSD) revealed that the primary process involved in the connection mechanism of PGRW is the mutual diffusion and recrystallization that occur due to electrode pressure and resistance heat.

Application of Response Surface-Corrected Finite Element Model and Bayesian Neural Networks to Predict the Dynamic Response of Forth Road Bridges under Strong Winds.

With the rapid development of big data, the Internet of Things (IoT), and other technological advancements, digital twin (DT) technology is increasingly being applied to the field of bridge structural health monitoring. Achieving the precise implementation of DT relies significantly on a dual-drive approach, combining the influence of both physical model-driven and data-driven methodologies. In this paper, two methods are proposed to predict the displacement and dynamic response of structures under strong winds, namely, a Bayesian Neural Network (BNN) model based on Bayesian inference and a finite element model (FEM) method modified based on genetic algorithms (GAs) and multi-objective optimization (MOO) using response surface methodology (RSM). The characteristics of these approaches in predicting the dynamic response of large-span bridges are explored, and a comparative analysis is conducted to evaluate their differences in computational accuracy, efficiency, model complexity, interpretability, and comprehensiveness. The characteristics of the two methods were evaluated using data collected on the Forth Road Bridge (FRB) as an example under unusual weather conditions with strong wind action. This work proposes a dual-driven approach, integrating machine learning and FEM with GNSS and Earth Observation for Structural Health Monitoring (GeoSHM), to bridge the gap in the limited application of dual-driven methods primarily applied for small- and medium-sized bridges to large-span bridge structures. The research results show that the BNN model achieved higher R2 values for predicting the Y and Z displacements (0.9073 and 0.7969, respectively) compared to the FEM model (0.6167 and 0.6283). The BNN model exhibited significantly faster computation, taking only 20 s, while the FEM model required 5 h. However, the physical model provided higher interpretability and the ability to predict the dynamic response of the entire structure. These findings help to promote the further integration of these two approaches to obtain an accurate and comprehensive dual-driven approach for predicting the structural dynamic response of large-span bridge structures affected by strong wind loading.

Behavior of Concrete-Filled Steel Tube Columns with Multiple Chambers and Round-Ended Cross-Sections under Axial Loading

Concrete-filled round-ended steel tubes (CFRTs) are a unique type of composite stub columns, which have the advantage of aesthetics and a well-distributed major–minor axis. Thus, the structure has been widely employed as piers and columns in bridges. To improve the mechanical performance of CFRTs with a large length–width ratio and to enhance the restraint effect of steel tubes on concrete, this study investigates the compressive property of multi-chamber, concrete-filled, round-ended steel tubular (M-CFRT) stub columns using a combination of experimental and numerical analyses. A detailed compression test on eight specimens is conducted to examine the compressive property of M-CFRT stub columns. The study focuses on understanding the influence of some key parameters on ultimate bearing capacity, failure stage, damage modes, and ductility. Additionally, the accuracy of the finite element modeling method in simulating the ultimate bearing capacity of the structure is verified. Finally, the calculating formula for the ultimate bearing capacity of M-CFRT stub columns is proposed on the basis of the experimental and numerical findings. Results of the formula calculation are consistent with the experimental data. These research findings serve as a valuable reference for designing similar structures in engineering practice.

A Finite Element Method for Determining the Mechanical Properties of Electrospun Nanofibrous Mats.

This study focuses on the mechanical properties of electrospun nanofibrous mats, highlighting the importance of the characteristics of single nanofibers in determining the overall mechanical behavior of the mats. Recognizing the significant impacts of the diameter and structural properties of the nanofibers, this research introduces a novel methodology for deriving the effects of the mechanical properties of single nanofibers on the aggregate mechanical performance of electrospun oriented nanofiber mats. For this purpose, a finite element method (FEM) model is developed to simulate the elastoplastic response of the mats, incorporating the influence of structural parameters on mechanical properties. The validation of the FEM model against experimental data from electrospun polyacrylonitrile (PAN) nanofibers with different orientations demonstrates its effectiveness in capturing the elastic-plastic tensile behaviors of the material and confirms its accuracy in terms of reflecting the complex mechanical interactions within the nanofibrous mats. Through a detailed analysis of how nanofiber diameter, orientation of fibers, length-to-width ratio, and porosity affect the mechanical properties of the mats, this research provides valuable insights for the engineering of nanofibrous materials to meet specific mechanical requirements. These findings improve our understanding of nanofibrous mat structures, allowing for better performance in diverse applications as well as highlighting the critical importance of identifying the properties of single nanofibers and their associated impacts on material design.

Multimode Rayleigh wave dispersion spectrum inversion using Wasserstein distance coupled with Bayesian optimization

We develop a new automatic framework for the nondestructive multichannel analysis of surface waves that combines multimode dispersion spectrum matching and a finite-element method (FEM)-based inversion to enhance the accuracy of subsurface profiling in site investigation activities. This framework eliminates the need for manual identification of the Rayleigh wave energy component and multimode assignment, reducing dependence on operator experience and judgment. The dispersion spectrum is generated through an FEM model that simulates 2D seismic wave propagation, taking into account the actual acquisition layout and lateral variations in the subsurface. We introduce the Wasserstein distance (WD) for evaluating the difference between the observed and simulated spectra and incorporate Bayesian optimization for efficiently inverting S-wave velocity profiles. The effectiveness of our framework is demonstrated through synthetic data examples, and the superiority of the WD-based objective function is illustrated by comparing it with the conventional mean square error-based objective function. Subsequently, we conduct a field test on a reclaimed landfill to validate our framework. This test confirms the ability of the framework to retrieve multimode Rayleigh waves and demonstrates its effectiveness in providing high-resolution S-wave profiles of the shallow subsurface.

The effect of deformation rate on the process of hot extrusion with dispensing of round hollow semi-finished products

Background. Stamping of round hollow semi-finished products by hot reverse extrusion is one of the initial operations in the manufacture of hollow products for special purposes. The force and shape change of the metal during hot plastic forming is significantly affected by the deformation rate or the speed of movement of the deforming tool. For special-purpose products, certain mechanical properties are required in the wall height and bottom part. The wall height properties are ensured at subsequent stretching transitions with thinning of the semi-finished product obtained by hot extrusion, which involves working out the metal structure by plastic deformation to achieve the required properties. Therefore, it is an urgent task to study the effect of the deformation rate on the force and shape change of the metal during hot reverse extrusion of hollow semi-finished products.Goal. To determine the influence of the deformation rate on the parameters of hot reverse extrusion with the dispensing of hollow semi-finished products from round and square billets by means of finite element method (FEM) modeling and to compare the results of theoretical researches.Methodology of implementation. Theoretical researches of extrusion power modes, specific forces, and the stress-strain state of metal were carried out by modeling using the FEM in the DEFORM software environment.Results. The FEM was used to model the process of hot reverse extrusion with dispensing of round hollow semi-finished products from mild steel with protrusions at the end of the bottom part on the side of the cavity and on the outer surface. The deformation rate was in the range of 20 to 80 mm/sec. Round and square cross-sectional blanks were used. The dependence of the extrusion force on the punch displacement was determined. The distribution of specific forces on the deforming tool was determined. The stress-strain state and temperature distribution in the deformed metal at the end of extrusion were determined. The development of the metal structure by hot plastic deformation was evaluated and the results obtained were comparedConclusions. The effect of the deformation rate on the parameters of hot reverse extrusion with dispensing of round hollow semi-finished products was determined

Comparative Analysis and Evaluation of Seismic Response in Structures: Perspectives from Non-Linear Dynamic Analysis to Pushover Analysis

This study presents a detailed comparative analysis of different methods for evaluating seismic response in structures, focusing on maximum displacements and collapse assessment. The results obtained through modal spectral analysis, non-linear dynamic analysis, and the incremental pushover analysis applied to a specific structure are compared. It has been found that the choice of time step and the consideration of ductility are critical for obtaining accurate predictions. The results of the non-linear dynamic analysis of the building’s response indicate that an earthquake equivalent to the one that affected the city of Lorca (southeast Iberian Peninsula) in 2011 would have a devastating impact on the studied structure, highlighting the importance of the finite element method modelling in predicting the formation of plastic hinges and assessing structural safety. These findings highlight the importance of utilising multiple analysis approaches and detailed modelling to fully understand the seismic behaviour of structures and ensure adequate resistance and stability to extreme events.

Study of the demagnetization behavior of no-insulation persistent-current mode HTS coils under external AC fields by 3D FEM simulation

The no-insulation (NI) winding technique is promising for applications in the persistent-current mode (PCM) operation of high-temperature superconducting (HTS) coils. To produce an NI PCM coil, it is essential to understand its demagnetization behavior (i.e. decay of persistent DC current) under an external AC field, which occurs in maglev trains, electric machines and other dynamic magnet systems. For this purpose, a 3D finite-element method (FEM) model, capturing the full electromagnetic properties of NI HTS coils is established. This work studied three kinds of AC fields, observing the impact of turn-to-turn contact resistivity on demagnetization rates, which is attributed to current distribution modulations. Under a transverse AC field, the lower contact resistivity attracts more transport current to flow in the radial pathway to bypass the ‘dynamic resistance’ generated in the superconductor, leading to slower demagnetization. Under an axial AC field, the demagnetization rate exhibits a non-monotonic relation with the contact resistivity: (1) the initial decrease in contact resistivity leads to a concentration of induced AC current on the outer turns, which accelerates the demagnetization; (2) the further decrease in contact resistivity makes the current smartly redistribute to avoid flowing through the loss-concentrated outer turns, thus slowing down the demagnetization. Under a rotating DC field, a hybrid of transverse and axial fields, the impact of contact resistivity on the demagnetization rate exhibits combined characteristics of the transverse and axial components. Additionally, quantitative prediction of the demagnetization rate of NI PCM coil under external AC field is instructive for practical designs and operations, which is tested by this 3D FEM model, and a comparison with experimental results is conducted.

Assessment of Factors Affecting Pavement Rutting in Pakistan Using Finite Element Method and Machine Learning Models

Assessment of Factors Affecting Pavement Rutting in Pakistan Using Finite Element Method and Machine Learning Models

Coupled thermal-mechanical analysis of power electronic modules with finite element method and parametric model order reduction

This work presents a new approach for performing a parametric study and examining nonlinear material behaviours of a coupled thermal-mechanical model of a Power Electronics Module (PEM) by integrating the Finite Element Method (ANSYS-FEM) with Parametric Model Order Reduction (pMOR). The considered coupling method solves the thermal and structural models concurrently compared to the widely practised sequential coupling method. Instead of constant parameter values, which are generally regarded for pMOR studies, the temperature-dependent material properties of the wire material have been parametrised in the work using the pMOR method. A generalised 2D model has been regarded here for thermal-mechanical analysis with the pMOR approach, parametrising temperature-dependent coefficient of thermal expansion (CTE) and Young’s modulus (E) of the wire material to explore their impact on wire bonds. The matrix interpolation method has been applied here for the pMOR study, and PRIMA, a Krylov subspace-based model order reduction (MOR) technique, has been exercised for local model order reductions. A new efficient process of matrix interpolation, based on the Lagrange interpolation technique, has been developed to implement matrix interpolation in the parametric reduced order model (pROM). The local reduced order models (ROMs) have a degree of freedom (DOF) of just 8, compared to the full-order models’ (FOMs) of 50,602. The pROM provides an excellent solution and reduces computational time by 84% for the presented case.

Structural behavior of historical Obruk Inn under different earthquakes

Masonry structures is one of the most preferred structure types throughout history. The advantageous of these structures can be categorized as longevity, affordability and easy access to materials. Due to a lack of information and constructive errors, masonry structures suffer major damage under effect of earthquakes. While the vertical load carrying capacity of a masonry structure is excellent, its performance under horizontal loads is very poor. The brittle behavior of masonry structures, in particular, causes the structure to suffer significant damage or collapse completely during an earthquake. Türkiye is situated over a major earthquake zone. Throughout history, there has been numerous major earthquakes. These earthquakes have demolished the masonry structures resulted in significant life and economic losses. Therefore, in recent days, the examination of the seismic resilience performance of masonry structures as well as the required strengthening have become a pivotal issue. Thus, the aim of this study is to analyze the seismic performance of historical Obruk Inn subjected to different earthquake effects via finite elements method (FEM). To do this, the plans obtained from on-site inspections for historical Obruk Inn to create structural FEM model and its performance was evaluated under the influence of various earthquake excitations. As a result of the analyses, it was determined that the historical Obruk Inn structure should have immediate be strengthened against a possible earthquake.

Mechanical Testing of Selective-Laser-Sintered Polyamide PA2200 Details: Analysis of Tensile Properties via Finite Element Method and Machine Learning Approaches.

This study delves into the mechanical characteristics of polyamide PA2200 components crafted using selective laser sintering (SLS) technology. Our primary objective is to analyze the tensile behavior of the components printed at various orientations, showing its response to diverse loading conditions. Finite element method (FEM) modeling was employed to analyze the tensile behavior of these details. The time determined for breaking the detail is 9 s. In addition we forecast key properties, such as tensile behavior and strength, using machine learning (ML) techniques, and the best models are for predicting relative elongation are KNeighborsRegressor and SVR.

Development of an adaptive two-phalanx grip model for robotic manipulators

The purpose of this work is to study the problem of uniform grip at the points of contact of a round or spherical object (fruits and vegetables) with the grip. The research methodology uses pressure sensors mounted on the “fingers” of the handle. At a certain force value in the contact zone, the “fingers” of the handle stop. The grip must create equal forces at the points of contact of all “fingers” for an even grip. To explore these issues, phalangeal graspers adapting to the fetal surface are analyzed here. The flat model shows the general patterns of the relationship between the forces of the “fingers” of the grip and the round object to be grasped. The flat model shows the general patterns of the relationship between the forces of the “fingers” of the grip and the round object to be grasped. We examined the 3D model of this gripper and calculated the parameters of the 3D model. Conclusions and practical consequences are the values of stresses and elastic displacements at the points of the contact lines of the teeth of the 3D models of the gripper and the object being grabbed. The distribution of forces on a flat diagram and the values of von Mises stresses in the 3D model demonstrate a certain similarity in the uniformity of distribution of these parameters. Color scales with the values of the corresponding parameters are also presented; the calculation was carried out using the finite element modeling method in inventor.

Integrated CFD-FEM approach for external gear pump vibroacoustic field prediction

In this work, a three-dimensional fluid-structural and vibro-acoustics coupled model of a gear pump is presented. Gear pumps represent the majority of the positive displacement machines used for flow generation in fluid power systems. Typically, the dynamics of gear pumps are dependent on the characteristics of the fluid dynamics inside the pump, which translates into vibrations to the housing. These vibrations then propagate to the surrounding medium and emit sound. The purpose of this study is to propose a three-dimensional fully integrated computational model to simulate the complete gear pump behaviour from the fluid dynamics to the structural vibrations, up to the vibroacoustic response. In this hybrid configuration, a transient CFD (Computational Fluid Dynamics) model is first developed to simulate the 3D flow field with a deforming and re-meshing approach to take into account the variation of the volume between the gears. Second, the internal pressure field calculated at each time step is then used as a loading into a structural FEM (Finite Element Method) model of the gear pump to compute the actual stresses and deformations of the housing. Third, the results of the structural response are used as excitation in a vibroacoustic sub-model to simulate the radiated noise using a high-order FEM technique. The comparison between the numerical and experimental flow curves validates the CFD model. The sound power calculations from the vibroacoustic model show good comparison with the sound intensity measurements around the pump casing, confirming the validity of the proposed coupled model. The described CFD-FEM approach proves to be a powerful gear pump design tool: it provides a reliable estimate of gear pump working parameters such as fluid power and vibroacoustic characteristics, starting from the CAD (Computer-Aided Design) geometry of the components. Furthermore, being one of the first multi-domain simulation models of a gear pump, this work can be useful to researchers as a starting point to correlate the noise emitted with the internal flow in full 3D conditions.

Three-Dimensional Finite Element Modeling of Spray-Applied Pipe Liners Repaired Corrugated Metal Pipes Buried Under Shallow Cover

Corrugated metal pipes (CMPs) corrode over time. To maintain structural performance, deteriorated CMPS must be replaced or rehabilitated. Spray-applied pipe liners (SAPLs) are one of the quickest ways to rehabilitate deteriorated CMPs among other ways. Only a few lab tests and finite element studies from the past have been done on this new method. The calibration of a three-dimensional (3D) full-scale finite element method model using test results obtained at the Center for Underground Infrastructure Research and Education laboratory at the University of Texas at Arlington is covered in this paper. The tests were carried out on circular invert cut CMPs that had been rehabilitated with polymeric SAPLs. To repair the invert-cut CMPs, three different thicknesses were used: 0.25, 0.5, and 1-in. The removal of an 18-in. invert from the intact CMP represented the deterioration of the CMP. A full 3D corrugated model was developed to represent the test setup in the FE model using ABAQUS. To perform the calibration process, the load–displacement curves, earth pressure distribution, and strain around the liner were compared to the test results. The comparison of these parameters showed the capability of the model for verification. The verified FE model was used to generate the load–displacement graphs for other thicknesses and elastic modulus of the liner. In addition, the role of the embedment depth is also considered in the analyses in which the maximum deformation of the rehabilitated pipe has decreased by 58.9% with increasing the burial depth of the pipe from 0.4D (D = external pipe diameter) to 1.0D.

Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data

Abstract Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.