Use Of Finite Elements Research Articles

Using optimization approach to design dental implant in three types of bone quality - A finite element analysis

Background/PurposeThe use of finite element (FE) analysis in implant biomechanics offers many advantages over other approaches in simulating the complexity of clinical situations. The aim of this study was to perform an optimization analysis of dental implants with different thread designs in three types of bone quality. Materials and methodsThe three-dimensional FE model of a mandibular bone block with a screw-shaped dental implant and superstructure was simulated. In the optimization analysis, the design variables included the thread pitch and the thread depth of the implant. The objective was to minimize the displacement of the implant to the target value. Three FE models with different bone qualities (D2: better bone quality; D3: ordinary bone quality; D4: poor bone quality) were created. ResultsThe FE results showed that the displacement of the implant and the stress of the cortical bone increased, while the Young's modulus of the cancellous bone decreased. In the D2 bone, changing the thread pitch and thread depth had little effect on cortical stress and implant displacement. However, in D3 and D4 bone, increasing thread depth reduced cortical stress by 40 % and implant displacement by at least 9 %. ConclusionAdjusted thread depth for D3 and D4 bone would reduce crestal bone stress and increase implant stability, but only a little alteration on crestal bone stress and implant stability for D2 bone.

Influence of the thickness of TiAlSiN on the thermal properties as input parameter for FEM-simulation

Hard coatings deposited by physical vapor deposition are state of the art for wear and oxidation protection of cutting tools. The cutting performance depends on coating material and process as well as cutting edge microgeometries. Both have an influence on the thermomechanical tool loads resulting in tool wear. Therefore, a process adapted design for the consideration of the entire system is necessary. One approach to substitute costly machining investigations and save material resources is the use of finite element (FE)-based chip formation simulations. However, in order to perform these simulations, information about chemical, thermal and physical coating behavior in the temperature range relevant for machining is necessary. In the present study, nanocomposite TiAlSiN coatings with varying coating thicknesses were deposited on cemented carbide tools. The effect of coating thickness on coating morphology, chemical composition, thermal conductivity as well as indentation hardness at ϑ = 20 °C, ϑ = 200 °C, ϑ = 400 °C and ϑ = 600 °C was analyzed. Therefore, three coating variants with a coating thickness of ds = 2 μm, ds = 4 μm and ds = 6 μm were deposited. Additionally, the distribution of the heat, generated during turning 42CrMo4 + A, was simulated for the coated cutting tool. A columnar morphology with constant chemical composition was determined for the variants. While the arithmetic mean value of the coating roughness increased with increasing coating thickness, there was no influence of coating thickness on thermal diffusivity and high temperature coating hardness measurable. Nevertheless, an influence of the tool temperature can be observed in the application behavior in turning tests as well as in the simulation, possibly caused by a change in the contact conditions due to increasing cutting edge microgeometry by increasing coating thickness. Regarding the tested TiAlSiN hard coatings no significant influence of the coating thickness on properties such as thermal diffusivity and indentation hardness were observed. This leads to the assumption, that even when the coating thickness is changed no significant changes in the FEM simulation are needed, which makes modelling easier.

Fiber-reinforced friction materials: Experimental, statistical and computational universal analysis

In this paper, the experimental, statistical and computational universal analysis methods applicable to most fiber-reinforced friction materials (FMs) are presented for four natural wollastonite fibers (WFs) with different length-to-diameter (L/D) ratios. Machine learning (ML) methods for friction coefficient prediction of friction materials are compared and screened. Numerical statistics and calculations are used in conjunction with the use of finite element (FE) models to determine the performance metrics and friction wear mechanisms of FMs. The experimental and computational results show that the artificial neural network (ANN) model performs the best in COF prediction with an accuracy of 0.961. The friction fluctuation, friction stability and integrated friction performance of the WF-containing samples are better than those of the blank samples. For the first time, the FE model was used to explain the swirling phenomenon on the wear surface of FMs. This study provides new ways and ideas for the design, experimentation, data processing and application of friction composites.

Geometric determinants of the mechanical behavior of image-based finite element models of the intervertebral disc.

The intervertebral disc is an important structure for load transfer through the spine. Its injury and degeneration have been linked to pain and spinal fractures. Disc injury and spine fractures are associated with high stresses; however, these stresses cannot be measured, necessitating the use of finite element (FE) models. These models should include the disc's complex structure, as changes in disc geometry have been linked to altered mechanical behavior. However, image-based models using disc-specific structures have yet to be established. This study describes a multiphasic FE modeling approach for noninvasive estimates of subject-specific intervertebral disc mechanical behavior based on medical imaging. The models (n = 22) were used to study the influence of disc geometry on the predicted global mechanical response (moments and forces), internal local disc stresses, and tractions at the interface between the disc and the bone. Disc geometry was found to have a strong influence on the predicted moments and forces on the disc (R2 = 0.69-0.93), while assumptions regarding the side curvature (bulge) of the disc had only a minor effect. Strong variability in the predicted internal disc stresses and tractions was observed between the models (mean absolute differences of 5.1%-27.7%). Disc height had a systematic influence on the internal disc stresses and tractions at the disc-to-bone interface. The influence of disc geometry on mechanics highlights the importance of disc-specific modeling to estimate disc injury risk, loading on the adjacent vertebral bodies, and the mechanical environment present in disc tissues.

Seismic response prediction using a hybrid unsupervised and supervised machine learning in case of 3D RC frame buildings

The seismic vulnerability assessment represents an important step in monitoring the buildings’ capacity and checking their performance during and after earthquake events. The Nonlinear Time History Analysis (NL-THA) is considered the most reliable method that is used to calculate the exact structural behavior of any building. However, this sophisticated method is known for its complexity, the use of Finite Element (FE) software, and computational time consuming, especially in the case of tall buildings. For that reason, An Artificial Neural network (ANN) is used to develop a new model able to predict the essential Engineering Demand Parameters (EDPs), i.e., the Maximum Base Shear (MBS), the Maximum Inter-story Drift (MIDR) and the Maximum Roof Drift Ratio (RDR). Unsupervised algorithms such as the Principal Component Analysis PCA and the Autoencoder are coupled with the ANN to reduce the dimensionality, improve the dataset quality, and reduce the irrelevant features. More than 192,000 buildings are analyzed using the NL-THA and eighty artificial ground motions (GMs) to generate the dataset. The buildings’ characteristics are generated randomly from the selection range. The results showed that the Autoencoder-ANN model represents the highest performance compared to the PCA-ANN and ANN models. The Autoencoder-ANN model could quickly and accurately predict the seismic responses of unseen ground motions using only the building’s characteristics and the GM parameters without using any FE software.

Probabilistic Bayesian Approach for Delamination Localization in GFRP Composites Using Nonlinear Guided Waves

Abstract Nondestructive evaluation (NDE) techniques that use nonlinear wave–damage interactions have gained significant attention recently due to their improved sensitivity in detecting incipient damage. This study presents the use of finite element (FE) simulation with the experimental investigation to quantify the effects of guided waves’ propagation through multiple delaminations in unidirectional glass fiber-reinforced polymer (GFRP) composites. Further, it utilizes the outcomes of nonlinear interactions between guided waves and delaminations to locate the latter. This is achieved through probabilistic Bayesian updating with a structural reliability approach. Guided waves interacting with delaminations induce nonlinear acoustic signatures that can be quantified by the nonlinearity index (NLI). The study found that the NLI changes with the interrogation frequency, as confirmed by numerical and experimental observations. By using the numerical outcomes obtained from the nonlinear responses, a Bayesian model-based approach with subset simulation is proposed and subsequently used to locate multiple delaminations. The results indicate that both the log-likelihood and log-evidence are key factors in determining the localization phenomenon. The proposed method successfully localizes multiple delaminations and evaluates their number, interlaminar position, width, and type.

Offshore Wind Turbine Monopile Foundation Systems in Multilayered Soil Strata under Aerodynamic and Hydrodynamic Loads: State-of-the-Art Review

Due to the large demand to produce clean and renewable energy, offshore wind farms are extensively being used to help with economic development. Offshore Wind Turbine (OWT) structures are usually supported by various types of foundations and its selection depends on several factors such as water depth, economic costs, construction methodologies, seabed bathymetry, soil characteristics, and load characteristics. The present State-of-the-Art review focuses on OWT-monopile foundation systems embedded in multi-layered soil strata subjected to aerodynamic and hydrodynamic loading conditions. The purpose of this study is to carry out a comprehensive review on the performance of OWT-monopile foundation structures to support the design and drafting choices and thereby provide an understanding to reduce the costs. Two specific subject areas are addressed in this paper: (1) Factors affecting the performance of OWT-Monopile Foundation Systems; and (2) Experimental modeling and numerical analyses of OWT-Monopile Foundation Systems. The immediate challenge to the design of OWTs is to analyze the dynamic response of the foundation structure when exposed to both aerodynamic and hydrodynamic loads acting simultaneously. The limitations of the existing guidelines point to the need for improved design methods to obtain an economical design of OWT-monopile foundations. The use of Finite Element (FE) models is effective in studying the functioning of OWT-monopile structures. The present study suggests the development of further numerical models and modifications to the existing ones to properly assess soil-monopile interactions. This study also suggests further investigations on the design and analysis of OWT-monopile foundations considering the effect of (i) aerodynamic and hydrodynamic loading conditions with soil-monopile interactions, and (ii) multi-layered seabed characteristics.

Multi-axial elastic–viscoplastic curves of unidirectional carbon nanotube-polymer nanocomposites considering interphase and interface debonding using finite element modeling

This paper aims to predict the elastic-viscoplastic curves of unidirectional carbon nanotube (CNT)-reinforced polymer nanocomposites under the multi-axial tensions, including bi-axial transverse-transverse, bi-axial longitudinal-transverse and tri-axial longitudinal-transverse-transverse loadings by the use of finite element (FE) modeling. The role of the interphase between the CNT and polymer matrix as well as the debonding at the CNT/interphase interface in the stress-strain curves of nanocomposites is investigated. The polymer matrix and interphase region are characterized as elastic-viscoplastic materials, while the CNT behaves as the elastic material. The present results in uni-axial loading are compared to the available numerical outcomes for indicating the accuracy of the FE modeling. The simulation of multi-axial load conditions is based on the three-dimensional representative volume element (RVE) of the unidirectional CNT-polymer nanocomposite. The effect of interface strength on the elastic-viscoplastic stress-strain curves is examined under bi-axial and tri-axial loadings.

Use of Finite Elements in the Training of a Neural Network for the Modeling of a Soft Robot.

Soft bioinspired manipulators have a theoretically infinite number of degrees of freedom, providing considerable advantages. However, their control is very complex, making it challenging to model the elastic elements that define their structure. Finite elements (FEA) can provide a model with sufficient accuracy but are inadequate for real-time use. In this context, Machine Learning (ML) is postulated as an option, both for robot modeling and for its control, but it requires a very high number of experiments to train the model. A linked combination of both options (FEA and ML) can be an approach to the solution. This work presents the implementation of a real robot made up of three flexible modules and actuated with SMA (shape memory alloy) springs, the development of its model through finite elements, its use to adjust a neural network, and the results obtained.

Computing committors via Mahalanobis diffusion maps with enhanced sampling data.

The study of phenomena such as protein folding and conformational changes in molecules is a central theme in chemical physics. Molecular dynamics (MD) simulation is the primary tool for the study of transition processes in biomolecules, but it is hampered by a huge timescale gap between the processes of interest and atomic vibrations that dictate the time step size. Therefore, it is imperative to combine MD simulations with other techniques in order to quantify the transition processes taking place on large timescales. In this work, the diffusion map with Mahalanobis kernel, a meshless approach for approximating the Backward Kolmogorov Operator (BKO) in collective variables, is upgraded to incorporate standard enhanced sampling techniques, such as metadynamics. The resulting algorithm, which we call the target measure Mahalanobis diffusion map (tm-mmap), is suitable for a moderate number of collective variables in which one can approximate the diffusion tensor and free energy. Imposing appropriate boundary conditions allows use of the approximated BKO to solve for the committor function and utilization of transition path theory to find the reactive current delineating the transition channels and the transition rate. The proposed algorithm, tm-mmap, is tested on the two-dimensional Moro-Cardin two-well system with position-dependent diffusion coefficient and on alanine dipeptide in two collective variables where the committor, the reactive current, and the transition rate are compared to those computed by the finite element method (FEM). Finally, tm-mmap is applied to alanine dipeptide in four collective variables where the use of finite elements is infeasible.

The use of finite elements modeling to analyze phase shifting transformer in steady-state service conditions

PurposeThe aim of this paper is to find a fast-acting numerical model of the phase shifter.Design/methodology/approachThe 3D FE model of the investigated unit is presented and compared with the results of the measurements. Due to its size, it is not suitable for transient analyses. The simplified 2D finite elements approach is discussed afterwards, with the identity of the magnetic energy stored in both models as the criterion of similarity between 2D and 3D models.FindingsThe introduction of scaling factors for the magnetic permeability values in particular volumes of the two-transformer set of the phase shifter enabled acceptable accuracy in calculations of the basic exploitation parameters of the phase shifter.Research limitations/implicationsThe developed methodology allows the analysis of the exploitation conditions of two separated transformers connected in a power grid inside the single finite elements model.Originality/valueAlthough the numerical models of power transformers are extensively discussed in the literature, the usage of the equivalent fast 2D model for the representation of two cooperating transformers at load conditions was not published yet.

Lower Bound Finite Element Limit Analysis of Geo-Structures with Non-Associated Flow Rule

The use of finite elements and limit analysis in the stability analysis of geo-structures is not uncommon nowadays, with the assumption of associated flow rule and rigid perfectly plastic constitutive soil model. Nevertheless, the simplified assumption may lead to misevaluation of the objective function for the nonlinear optimisation solution, thus giving rise to uncertainty in the design of geo-structures. In this study, the influence of non-associated flow rule on the stability evaluations for obliquely- and eccentrically-loaded shallow foundations, as well as for retaining structures with cohesionless granular backfill, is examined using lower bound finite elements and second-order cone programming (SOCP). A wide range of dilation angles (ψ) is considered for the study (e.g., from zero to a maximum of soil internal friction angle φ), and it is generally observed that failing to consider the non-associated flow rule in the soil constitutive model would yield non-conservative designs of geo-structures. These inaccurate predictions and subsequent unreliable stability analysis are more pronounced in cases of large soil internal friction angles. The findings in this study would be of great importance for practical design applications.

Analytical model for the panel zone resistance in welded steel beam-to-column joints

This article addresses the problem of prediction of the plastic shear resistance of the panel zone (PZ) in welded steel beam-to-column joints under monotonic loading. As a first step, an extensive review of existing analytical models is proposed. The capabilities of the latter are then assessed through comparisons against available experimental data. These comparisons reveal that none of them is able to accurately capture all the complex phenomena governing the plastic shear resistance of the PZ. Therefore, a new analytical model has been developed based on the extensive use of finite element (FE) analysis. This approach includes the development and validation of a FE model within the Abaqus© environment and the use of the so-validated model in order to perform a parametric study on (non-)axially loaded (un-)stiffened exterior and interior joints. This parametric study helped to gain a better understanding of the actual stress distributions within the PZ. Based on these observations, a new analytical model is proposed and validated against the numerical results. This model proves to work well and to outperform existing analytical models by providing a more coherent estimation of the plastic shear resistance of the PZ.

Ductile fracture modeling of metallic materials: a short review

Since the end of the last century a lot of research on ductile damaging and fracture process has been carried out. The interest and the attention on the topic are due to several aspects. The margin to reduce the costs of production or maintenance can be still improved by a better knowledge of the ductile failure, leading to the necessity to overcome traditional approaches. New materials or technologies introduced in the industrial market require new strategies and approaches to model the metal behavior. In particular, the increase of the computational power together with the use of finite elements (FE), extended finite elements (X-FE), discrete elements (DE) methods need the formulation of constitutive models capable of describing accurately the physical phenomenon of the damaging process. Therefore, the recent development of novel constitutive models and damage criteria. This work offers an overview on the current state of the art in non-linear deformation and damaging process reviewing the main constitutive models and their numerical applications.

Designing drones by combining finite element and atomistic simulations: a didactic approach

A didactic multiscale approach for drone modeling is proposed. Specifically, we investigate the drone structure at both macroscopic and microscopic scales, by making use of finite element and atomistic simulations, respectively. The structural analysis is performed with the aim to equip the drone with specific sensors and measuring instruments capable to detect the existence of volcanic ash, SO 2 , CO 2 and other pollutants in the atmosphere after a volcanic eruption. We show that, by modeling the tubular structure of the drone with a sandwich constituted by a a polystyrene core, carbon fiber skins and epoxy matrix, a weight saving of 7 grams for each drone arm can be obtained, in comparison to the standard commercial drones, although a slight worsening of the mechanical performances is observed. In addition, the molecular structure of the polystyrene chains has been investigated by using atomistic Molecular Dynamics simulations, providing further information on the local structure of the polymer chains. Additional improvements of the weight saving could be obtained by means of the the topological optimization techniques on the body of the drone and on the supports for landing.

Damage Detection at a Reinforced Concrete Specimen with Coda Wave Interferometry.

Reinforced concrete is a widely used construction material in the building industry. With the increasing age of structures and higher loads there is an immense demand for structural health monitoring of built infrastructure. Coda wave interferometry is a possible candidate for damage detection in concrete whose applicability is demonstrated in this study. The technology is based on a correlation evaluation of two ultrasonic signals. In this study, two ways of processing the correlation data for damage detection are compared. The coda wave measurement data are obtained from a four-point bending test at a reinforced concrete specimen that is also instrumented with fibre optic strain measurements. The used ultrasonic signals have a central frequency of 60 kHz which is a significant difference to previous studies. The experiment shows that the coda wave interferometry has a high sensitivity for developing cracks and by solving an inverse problem even multiple cracks can be distinguished. A further specialty of this study is the use of finite elements for solving a diffusion problem which is needed to state the previously mentioned inverse problem for damage localization.

Analytical model for the prediction of the plastic shear resistance of the panel zone in welded joints

AbstractThis article addresses the problem of prediction of the plastic shear resistance of the panel zone (PZ) in welded steel beam‐to‐column joints under monotonic loading. Existing analytical models are first critically reviewed through comparisons with available experimental data. These comparisons reveal that none of them is able to accurately capture all the complex phenomena governing the plastic shear resistance of the PZ. Therefore, a new analytical model is developed based on the extensive use of finite element (FE) analysis. This approach includes the development and validation of a FE model within the Abaqus environment and the use of the so‐validated model in order to perform a parametric study on (non‐)axially loaded (un‐)stiffened interior and exterior joint configurations. This parametric study helps to gain a better understanding of the actual distributions of stresses within the PZ. Based on these observations, a new analytical model is proposed and validated against the numerical results. This model proves to work well and to outperform existing analytical models by providing a more coherent estimation of the plastic shear resistance of the PZ.

Further developments on boundary-field equation methods for nonlinear transmission problems

This paper is concerned with new insights on the application of the boundary-field equation approach, which refers basically to the combined use of finite element and boundary integral equation methods, to numerically solve nonlinear exterior transmission problems in 2D and 3D. As a model, we consider a nonlinear second-order elliptic equation in divergence form holding in an annular domain coupled with the Laplace equation in the corresponding unbounded exterior region, together with transmission conditions on the interface and a suitable radiation condition at infinity. We first extend the classical Johnson & Nédélec coupling procedure, which makes use of only one boundary integral equation, to our nonlinear model without assuming any restrictive smoothness requirement on the boundary but only Lipschitz-continuity. Next, we extend the applicability of a recently introduced modification of the Costabel & Han coupling method, which employs the two boundary integral equations arising from the Green representation formula, to our nonlinear model as well. This new boundary-field equation method is based on the introduction of both Cauchy data on the boundary as independent unknowns. Primal and dual-mixed variational formulations are analyzed for each extension described above, and suitable hypotheses on the nonlinear coefficient of the elliptic equation allow to establish well-posedness of the corresponding continuous and discrete schemes by using monotone operator and nonlinear Babuška-Brezzi theories. Finally, a priori error estimates are established.

Analytical Model of Two-Directional Cracking Shear-Friction Membrane for Finite Element Analysis of Reinforced Concrete.

There are a multitude of existing material models for the finite element analysis of cracked reinforced concrete that provide reduced shear stiffness but do not limit shear strength. In addition, typical models are not based on the actual physical behavior of shear transfer across cracks by shear friction recognized in the ACI 318 Building Code. A shear-friction model was recently proposed that was able to capture the recognized cracked concrete behavior by limiting shear strength as a yielding function in the reinforcement across the crack. However, the proposed model was formulated only for the specific case of one-directional cracking parallel to the applied shear force. This study proposed and generalized an orthogonal-cracking shear-friction model for finite element use. This was necessary for handling the analysis of complex structures and nonproportional loading cases present in real design and testing situations. This generalized model was formulated as a total strain-based model using the approximation that crack strains are equal to total strains, using the proportional load vector, constant vertical load, and modified Newton–Raphson method to improve the model’s overall accuracy.

Nonparametric Density Estimation Over Complicated Domains

AbstractWe propose a nonparametric method for density estimation over (possibly complicated) spatial domains. The method combines a likelihood approach with a regularization based on a differential operator. We demonstrate the good inferential properties of the method. Moreover, we develop an estimation procedure based on advanced numerical techniques, and in particular making use of finite elements. This ensures high computational efficiency and enables great flexibility. The proposed method efficiently deals with data scattered over regions having complicated shapes, featuring complex boundaries, sharp concavities or holes. Moreover, it captures very well complicated signals having multiple modes with different directions and intensities of anisotropy. We show the comparative advantages of the proposed approach over state of the art methods, in simulation studies and in an application to the study of criminality in the city of Portland, Oregon.