scholarly journals Finite element modeling of shape memory polyurethane foams for treatment of cerebral aneurysms

2021 ◽  
Author(s):  
H. R. Jarrah ◽  
A. Zolfagharian ◽  
M. Bodaghi
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Shape Memory ◽  
Cerebral Aneurysms ◽  
Element Model ◽  
Polyurethane Foams ◽  
Patient Specific ◽  
Structural Cell ◽  
Element Modeling ◽  
Shape Memory Polyurethane

AbstractIn this paper, a thermo-mechanical analysis of shape memory polyurethane foams (SMPUFs) with aiding of a finite element model (FEM) for treating cerebral aneurysms (CAs) is introduced. Since the deformation of foam cells is extremely difficult to observe experimentally due to their small size, a structural cell-assembly model is established in this work via finite element modeling to examine all-level deformation details. Representative volume elements of random equilateral Kelvin open-cell microstructures are adopted for the cell foam. Also, a user-defined material subroutine (UMAT) is developed based on a thermo-visco-elastic constitutive model for SMPUFs, and implemented in the ABAQUS software package. The model is able to capture thermo-mechanical responses of SMPUFs for a full shape memory thermodynamic cycle. One of the latest treatments of CAs is filling the inside of aneurysms with SMPUFs. The developed FEM is conducted on patient-specific basilar aneurysms treated by SMPUFs. Three sizes of foams are selected for the filling inside of the aneurysm and then governing boundary conditions and loadings are applied to the foams. The results of the distribution of stress and displacement in the absence and presence of the foam are compared. Due to the absence of similar results in the specialized literature, this paper is likely to fill a gap in the state of the art of this problem and provide pertinent results that are instrumental in the design of SMPUFs for treating CAs.

Patient Specific Finite Element Modeling of a Human Skull

2006 ◽  
Vol 49 ◽  
pp. 227-234 ◽  
Author(s):  
Norio Inou ◽  
Michihiko Koseki ◽  
Koutarou Maki
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Finite Element Modeling ◽  
Image Data ◽  
Element Model ◽  
Biomechanical Study ◽  
Modeling Method ◽  
Patient Specific ◽  
Human Skull ◽  
Element Modeling

This paper presents automated finite element modeling method and application to a biomechanical study. The modeling method produces a finite element model based on the multi-sliced image data adaptively controlling the element size according to complexity of local bony shape. The method realizes a compact and precise finite element model with a desired total number of nodal points. This paper challenges to apply this method to a human skull because of its intricate structure. To accomplish the application of the human skull, we analyze characteristics of bony shape for a mandible and a skull. Using the analytical results, we demonstrate that the proposed modeling method successfully generates a precise finite element model of the skull with fine structures.

Determining the Rayleigh damping parameters of flexible pavements for finite element modeling

2021 ◽  
pp. 107754632110267
Author(s):  
Jiandong Huang ◽  
Xin Li ◽  
Jia Zhang ◽  
Yuantian Sun ◽  
Jiaolong Ren
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Natural Frequencies ◽  
Least Squares Method ◽  
Element Model ◽  
Beam Model ◽  
Element Modeling ◽  
Rayleigh Damping ◽  
Damping Matrix

The dynamic analysis has been successfully used to predict the pavement response based on the finite element modeling, during which the stiffness and mass matrices have been established well, whereas the method to determine the damping matrix based on Rayleigh damping is still under development. This article presents a novel method to determine the two parameters of the Rayleigh damping for dynamic modeling in pavement engineering. Based on the idealized shear beam model, a more reasonable method to calculate natural frequencies of different layers is proposed, by which the global damping matrix of the road pavement can be assembled. The least squares method is simplified and used to calculate the frequency-independent damping. The best-fit Rayleigh damping is obtained by only determining the natural frequencies of the two modal. Finite element model and in-situ field test subjected by the same falling weight deflectometer pulse loads are performed to validate the accuracy of this method. Good agreements are noted between simulation and field in-situ results demonstrating that this method can provide a more accurate approach for future finite element modeling and back-calculation.

scholarly journals Method for patient-specific finite element modeling and simulation of deep brain stimulation

2008 ◽  
Vol 47 (1) ◽  
pp. 21-28 ◽  
Author(s):  
Mattias Åström ◽  
Ludvic U. Zrinzo ◽  
Stephen Tisch ◽  
Elina Tripoliti ◽  
Marwan I. Hariz ◽  
...  
Keyword(s):  
Finite Element ◽  
Deep Brain Stimulation ◽  
Finite Element Modeling ◽  
Modeling And Simulation ◽  
Brain Stimulation ◽  
Patient Specific ◽  
Element Modeling ◽  
Deep Brain

Experimentally validated predictive finite element modeling of the V0-V100 probabilistic penetration response of a Kevlar fabric against a spherical projectile

2018 ◽  
Vol 9 (4) ◽  
pp. 504-524 ◽  
Author(s):  
Gaurav Nilakantan
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Finite Element Modeling ◽  
Element Model ◽  
Ballistic Impact ◽  
Impact Testing ◽  
Woven Fabric ◽  
Projectile Impact ◽  
Element Modeling ◽  
The Impact

This work presents the first fully validated and predictive finite element modeling framework to generate the probabilistic penetration response of an aramid woven fabric subjected to ballistic impact. This response is defined by a V0-V100 curve that describes the probability of complete fabric penetration as a function of projectile impact velocity. The exemplar case considered in this article comprises a single-layer, fully clamped, plain-weave Kevlar fabric impacted at the center by a 0.22 cal spherical steel projectile. The fabric finite element model comprises individually modeled three-dimensional warp and fill yarns and is validated against the experimental material microstructure. Sources of statistical variability including yarn strength and modulus, inter-yarn friction, and precise projectile impact location are mapped into the finite element model. A series of impact simulations at varying projectile impact velocities is executed using LS-DYNA on the fabric models, each comprising unique mappings. The impact velocities and outcomes (penetration, non-penetration) are used to generate the numerical V0-V100 curve which is then validated against the experimental V0-V100 curve obtained from ballistic impact testing and shown to be in excellent agreement. The experimental data and its statistical analysis used for model input and validation, namely, the Kevlar yarn tensile strengths and moduli, inter-yarn friction, and fabric ballistic impact testing, are also reported.

Corrugated structures reinforced by shape memory alloy sheets: Analytical modeling and finite element modeling

2018 ◽  
Vol 233 (7) ◽  
pp. 2445-2454 ◽  
Author(s):  
Maryam Koudzari ◽  
Mohammad-Reza Zakerzadeh ◽  
Mostafa Baghani
Keyword(s):  
Finite Element ◽  
Shape Memory Alloy ◽  
Shape Memory Alloys ◽  
Finite Element Modeling ◽  
Shape Memory ◽  
Smart Structure ◽  
Design Parameters ◽  
Asymmetric Mode ◽  
Element Modeling ◽  
Structure Changes

In this study, an analytical solution is presented for a trapezoidal corrugated beam, which is reinforced by shape memory alloy sheets on both sides. Formulas are presented for shape memory alloys in states of compression and tension. According to the modified Brinson model, shape memory alloys have different thermomechanical behavior in compression and tension, and also these alloys would behave differently in different temperatures. The developed formulation is based on Euler–Bernoulli theory. Deflection of the smart structure and the effect of asymmetric response in shape memory alloys are studied. Results found from the semi-analytic modeling are compared to and validated through a finite element modeling, and there is more than [Formula: see text] agreement between two solutions. With regard to the results, the neutral axis of the smart structure changes in each section. The maximum deflection ratio of asymmetric mode to symmetric one mode is 1.7. Additionally, the effect of design parameters on deflection is studied in detail.

scholarly journals Finite Element Modeling and Mechanical Behavior of Masonry-Infilled RC Frame

2016 ◽  
Vol 10 (1) ◽  
pp. 76-92
Author(s):  
Hongyu Deng ◽  
Baitao Sun
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Element Model ◽  
Simulation Method ◽  
Shear Resistance ◽  
Calculation Formula ◽  
Infill Wall ◽  
Seismic Code ◽  
Element Modeling ◽  
Contact Position

During the analysis of reinforced concrete structures, the infill wall is usually simplified as a diagonal inclined strut to facilitate finite element modeling calculations. However, the actual seismic damage and single frame-filled wall pushover experimental results show that when the earthquake shear force is huge, the top of the infill wall and the beam–column connections are usually, thus the path of the force transfer will be changed. Based on this actual failure phenomenon, a new calculation model which has different contact position between the equivalent bracing walls and the frame columns is generated. Thus, the force analysis is given based on this model, the formulae for calculating the equivalent width of bracing walls, the shear bearing capacity of the wall-filled frame, and the infill wall’s actual participation in the stiffness. A finite element simulation method by ABAQUS is used to determine an empirical formula for calculating the reasonable contact position between the equivalent bracing walls and the frame columns. The verification results show that the finite element model presented in this paper is more reasonable, and the stiffness and shear resistance of infill wall should not be neglected. The calculation formula of stiffness of infill wall presented in this paper is coincided with seismic code. But the calculation formula of shear resistance of infill wall presented in seismic code is higher than the actual value, so it is suggested that calculation formula presented in this paper should be accepted.

Development of the Finite Element Modeling Markup Language

2002 ◽  
Author(s):  
J. G. Michopoulos
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Element Model ◽  
Data Interpretation ◽  
Markup Language ◽  
Document Type ◽  
Element Modeling ◽  
Type Definition ◽  
Extensible Markup ◽  
Modeling Data

The finite element modeling Markup Language (femML) effort is addressing the problems of data interpretation and exchange for intra- and inter- application interoperability in the Finite Element Modeling domain. This is achieved through the development of an extensible markup language (XML) variant for finite element model data that will permit the storage, transmission, and processing of finite element modeling data distributed via the World Wide Web and related infrastructure technologies. The focus of this work was to utilize the XML’s power of semantic encapsulation along with the existing and continuously improving associated technology to develop a dialect for exchanging FEM data across various codes with heterogeneous input format syntactic specifications. The main aspects of a finite element definition have been used as archetypes for defining the XML element taxonomy definitions. Namely, the geometry, the material, and the loading aspects of a structural component specification are used to define the first level elements of the associated Document Type Definition (DTD). The element list has been amended with a behavior element specification that represents the solution data to be exchanged or visualized. Various tools have been developed to demonstrate associated concepts along with the ANSYS set of tools.

A Predictive Analysis of Wall Stress in Abdominal Aortic Aneurysms Using a Neural Network Model

2021 ◽  
Author(s):  
Balaji Rengarajan ◽  
Sourav Patnaik ◽  
Ender A. Finol
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Finite Element Modeling ◽  
Wall Stress ◽  
Aortic Aneurysms ◽  
Multivariate Adaptive Regression Splines ◽  
Patient Specific ◽  
Clinical Images ◽  
Element Modeling ◽  
Abdominal Aortic

Abstract In the present work, we investigated the use of geometric indices to predict patient-specific abdominal aortic aneurysm (AAA) wall stress by means of a novel neural network (NN) modeling approach. We conducted a retrospective review of existing clinical images of two patient groups: 98 asymptomatic and 50 symptomatic AAA. The images were subject to a protocol consisting of image segmentation, processing, volume meshing, finite element modeling, and geometry quantification, from which 53 geometric indices and the spatially averaged wall stress (SAWS) were calculated. We developed feed-forward NN models composed of an input layer, two dense layers, and an output layer using Keras, a deep learning library in Python. The NN models were trained, tested, and validated independently for both AAA groups using all geometric indices, as well as a reduced set of indices resulting from a variable reduction procedure. We compared the performance of the NN models with two standard machine learning algorithms (MARS: multivariate adaptive regression splines and GAM: generalized additive model) and a linear regression model (GLM: generalized linear model). The NN-based approach exhibited the highest overall mean goodness-of-fit and lowest overall relative error compared to MARS, GAM, and GLM, when using the reduced sets of indices to predict SAWS for both AAA groups. The use of NN modeling represents a promising alternative methodology for the estimation of AAA wall stress using geometric indices as surrogates, in lieu of finite element modeling.

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