Tailored Extended Finite-Element Model for Predicting Crack Propagation and Fracture Properties within Idealized and Digital Cementitious Material Samples

2012 ◽  
Vol 138 (1) ◽  
pp. 89-100 ◽  
Author(s):  
Kenny Ng ◽  
Qingli Dai
Keyword(s):  
Finite Element ◽  
Crack Propagation ◽  
Finite Element Model ◽  
Element Model ◽  
Cementitious Material ◽  
Extended Finite Element ◽  
Fracture Properties

A research on fatigue crack growth monitoring based on multi-sensor and data fusion

2019 ◽  
pp. 147592171986572
Author(s):  
Chang Qi ◽  
Yang Weixi ◽  
Liu Jun ◽  
Gao Heming ◽  
Meng Yao
Keyword(s):  
Finite Element ◽  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Data Fusion ◽  
Crack Propagation ◽  
Finite Element Model ◽  
Crack Length ◽  
Crack Growth ◽  
Lamb Wave ◽  
Element Model

Fatigue crack propagation is one of the main problems in structural health monitoring. For the safety and operability of the metal structure, it is necessary to monitor the fatigue crack growth process of the structure in real time. In order to more accurately monitor the expansion of fatigue cracks, two kinds of sensors are used in this article: strain gauges and piezoelectric transducers. A model-based inverse finite element model algorithm is proposed to perform pattern recognition of fatigue crack length, and the fatigue crack monitoring experiment is carried out to verify the algorithm. The strain spectra of the specimen under cyclic load in the simulation and experimental crack propagation are obtained, respectively. The active lamb wave technique is also used to monitor the crack propagation. The relationship between the crack length and the lamb wave characteristic parameter is established. In order to improve the recognition accuracy of the crack propagation mode, the random forest and inverse finite element model algorithms are used to identify the crack length, and the Dempster–Shafer evidence theory is used as data fusion to integrate the conclusion of the two algorithms to make a more accountable and correct judge of the crack length. An experiment has been conducted to demonstrate the effectiveness of the method.

An extended finite element model for CO2sequestration

2013 ◽  
Vol 23 (8) ◽  
pp. 1421-1448 ◽  
Author(s):  
Mojtaba Talebian ◽  
Rafid Al-Khoury ◽  
Lambertus J. Sluys
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Extended Finite Element

scholarly journals An extended finite-element model coupled with level set method for analysis of growth of corrosion pits in metallic structures

2014 ◽  
Vol 470 (2168) ◽  
pp. 20140001 ◽  
Author(s):  
A. S. Vagbharathi ◽  
S. Gopalakrishnan
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Level Set Method ◽  
Level Set ◽  
Concentration Field ◽  
Element Model ◽  
Jump Discontinuity ◽  
Governing Equations ◽  
Extended Finite Element ◽  
Pitting Potential

Mass balance between metal and electrolytic solution, separated by a moving interface, in stable pit growth results in a set of governing equations which are solved for concentration field and interface position (pit boundary evolution). The interface experiences a jump discontinuity in metal concentration. The extended finite-element model (XFEM) handles this jump discontinuity by using discontinuous-derivative enrichment formulation, eliminating the requirement of using front conforming mesh and re-meshing after each time step as in the conventional finite-element method. However, prior interface location is required so as to solve the governing equations for concentration field for which a numerical technique, the level set method, is used for tracking the interface explicitly and updating it over time. The level set method is chosen as it is independent of shape and location of the interface. Thus, a combined XFEM and level set method is developed in this paper. Numerical analysis for pitting corrosion of stainless steel 304 is presented. The above proposed model is validated by comparing the numerical results with experimental results, exact solutions and some other approximate solutions. An empirical model for pitting potential is also derived based on the finite-element results. Studies show that pitting profile depends on factors such as ion concentration, solution pH and temperature to a large extent. Studying the individual and combined effects of these factors on pitting potential is worth knowing, as pitting potential directly influences corrosion rate.

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