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

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.

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6135
Author(s):  
Suria Devi Vijaya Kumar ◽  
Michael Lo Yin Kai ◽  
Thibankumar Arumugam ◽  
Saravanan Karuppanan

This paper discusses the capabilities of artificial neural networks (ANNs) when integrated with the finite element method (FEM) and utilized as prediction tools to predict the failure pressure of corroded pipelines. The use of conventional residual strength assessment methods has proven to produce predictions that are conservative, and this, in turn, costs companies by leading to premature maintenance and replacement. ANNs and FEM have proven to be strong failure pressure prediction tools, and they are being utilized to replace the time-consuming methods and conventional codes. FEM is widely used to evaluate the structural integrity of corroded pipelines, and the integration of ANNs into this process greatly reduces the time taken to obtain accurate results.


2021 ◽  
Vol 11 (3) ◽  
pp. 1220
Author(s):  
Azeem Ul Yaqin Syed ◽  
Dinesh Rokaya ◽  
Shirin Shahrbaf ◽  
Nicolas Martin

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.


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