scholarly journals Effects of different ceramic and composite materials on stress distribution in inlay and onlay cavities: 3-D finite element analysis

2009 ◽  
Vol 28 (6) ◽  
pp. 661-670 ◽  
Author(s):  
Kivanç YAMANEL ◽  
Alper ÇAGLAR ◽  
Kamran GÜLSAHI ◽  
Utku Ahmet ÖZDEN
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Composite Materials ◽  
Stress Distribution ◽  
Element Analysis

scholarly journals Three-Dimensional Finite Element Analysis of Stress Distribution in a Tooth Restored with Full Coverage Machined Polymer Crown

2021 ◽  
Vol 11 (3) ◽  
pp. 1220
Author(s):  
Azeem Ul Yaqin Syed ◽  
Dinesh Rokaya ◽  
Shirin Shahrbaf ◽  
Nicolas Martin
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Stress Distribution ◽  
Three Dimensional ◽  
Intraoral Scanner ◽  
Element Analysis ◽  
Dental Ceramic ◽  
Dimensional Finite Element ◽  
Three Dimensional Finite Element ◽  
Ceramic Crown

The effect of a restored machined hybrid dental ceramic crown–tooth complex is not well understood. This study was conducted to determine the effect of the stress state of the machined hybrid dental ceramic crown using three-dimensional finite element analysis. Human premolars were prepared to receive full coverage crowns and restored with machined hybrid dental ceramic crowns using the resin cement. Then, the teeth were digitized using micro-computed tomography and the teeth were scanned with an optical intraoral scanner using an intraoral scanner. Three-dimensional digital models were generated using an interactive image processing software for the restored tooth complex. The generated models were imported into a finite element analysis software with all degrees of freedom concentrated on the outer surface of the root of the crown–tooth complex. To simulate average occlusal load subjected on a premolar a total load of 300 N was applied, 150 N at a buccal incline of the palatal cusp, and palatal incline of the buccal cusp. The von Mises stresses were calculated for the crown–tooth complex under simulated load application was determined. Three-dimensional finite element analysis showed that the stress distribution was more in the dentine and least in the cement. For the cement layer, the stresses were more concentrated on the buccal cusp tip. In dentine, stress was more on the cusp tips and coronal 1/3 of the root surface. The conventional crown preparation is a suitable option for machined polymer crowns with less stress distribution within the crown–tooth complex and can be a good aesthetic replacement in the posterior region. Enamic crowns are a good viable option in the posterior region.

scholarly journals A Machine Learning Approach as a Surrogate for a Finite Element Analysis: Status of Research and Application to One Dimensional Systems

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1654
Author(s):  
Poojitha Vurtur Badarinath ◽  
Maria Chierichetti ◽  
Fatemeh Davoudi Kakhki
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Finite Element Analysis ◽  
Finite Element ◽  
Artificial Neural Networks ◽  
Stress Distribution ◽  
Maintenance Scheduling ◽  
Element Analysis ◽  
One Dimensional ◽  
Artificial Neural

Current maintenance intervals of mechanical systems are scheduled a priori based on the life of the system, resulting in expensive maintenance scheduling, and often undermining the safety of passengers. Going forward, the actual usage of a vehicle will be used to predict stresses in its structure, and therefore, to define a specific maintenance scheduling. Machine learning (ML) algorithms can be used to map a reduced set of data coming from real-time measurements of a structure into a detailed/high-fidelity finite element analysis (FEA) model of the same system. As a result, the FEA-based ML approach will directly estimate the stress distribution over the entire system during operations, thus improving the ability to define ad-hoc, safe, and efficient maintenance procedures. The paper initially presents a review of the current state-of-the-art of ML methods applied to finite elements. A surrogate finite element approach based on ML algorithms is also proposed to estimate the time-varying response of a one-dimensional beam. Several ML regression models, such as decision trees and artificial neural networks, have been developed, and their performance is compared for direct estimation of the stress distribution over a beam structure. The surrogate finite element models based on ML algorithms are able to estimate the response of the beam accurately, with artificial neural networks providing more accurate results.

scholarly journals Folding photopolymerized origami sheets by post-curing

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Xiaodong He ◽  
Christopher-Denny Matte ◽  
Tsz-Ho Kwok
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Stress Distribution ◽  
Maximum Principal Stress ◽  
Second Step ◽  
Post Processing ◽  
Element Analysis ◽  
Digital Light Processing ◽  
Processing Step ◽  
Lower Maximum

AbstractThe paper presents a novel manufacturing approach to fabricate origami based on 3D printing utilizing digital light processing. Specifically, we propose to leave part of the model uncured during the printing step, and then cure it in the post-processing step to set the shape in a folded configuration. While the cured regions in the first step try to regain their unfolded shape, the regions cured in the second step attempt to keep their folded shape. As a result, the final shape is obtained when both regions’ stresses reach equilibrium. Finite element analysis is performed in ANSYS to obtain the stress distribution on common hinge designs, demonstrating that the square-hinge has a lower maximum principal stress than elliptical and triangle hinges. Based on the square-hinge and rectangular cavity, two variables—the hinge width and the cavity height—are selected as principal variables to construct an empirical model with the final folding angle. In the end, experimental verification shows that the developed method is valid and reliable to realize the proposed deformation and 3D development of 2D hinges.

Finite Element Analysis and Investigation of Double-Row Piles Supporting Structure

2013 ◽  
Vol 838-841 ◽  
pp. 779-785
Author(s):  
Liang Gu
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Stress Distribution ◽  
Maximum Shear Stress ◽  
Horizontal Displacement ◽  
Deep Foundation ◽  
Foundation Pit ◽  
Double Row ◽  
Element Analysis ◽  
Supporting Structure

The double-row piles supporting structure is a new type of supporting and protecting for deep foundation excavation. It is widely used to in design of deep foundation pit. Now how to simply and effectively design the structure of double-row piles is in a research and discuss stage. Using the Midas GTS finite element method, the displacement and stress distribution of double-row piles in the different stages of excavation are obtained, and the horizontal displacement and stress distribution of double-row piles in the different stages of excavation are calculated. The results of Midas GTS finite element analysis as follows: (1) after the excavation of foundation pit, the horizontal displacement of pile-top is maximum. The horizontal displacement decreases gradually with depth increases. And the displacement of front row piles is larger than that of back row piles; (2) the maximum shear stress is at the distance 5m to the foundation basement. The higher bending moment at the pile-top and the distance 10m to the foundation basement are consistent with the actual monitoring date. (3) the results of finite element analysis is close to the Richard software and actual monitoring data. It is show that using the finite element analysis to analyze the double-row piles supporting structure with is veritable and credible.

Finite Element Analysis of Thermal Stress Distribution in Planar SOFC

2019 ◽  
Vol 7 (1) ◽  
pp. 1977-1986 ◽  
Author(s):  
Chih-Kuang Lin ◽  
Tsung-Ting Chen ◽  
An-Shin Chen ◽  
Yau-Pin Chyou ◽  
Lieh-Kwang Chiang
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Thermal Stress ◽  
Stress Distribution ◽  
Element Analysis ◽  
Thermal Stress Distribution
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