Highly Parallel Surface Crack Simulation

2011 ◽  
Author(s):  
Shuji Hao ◽  
Mingqu Zhou ◽  
Zhongke Wu ◽  
Pengfei Xu ◽  
Hongming Zhang
Keyword(s):  
Surface Crack ◽  
Parallel Surface

The Reciprocal Effect Among a Quarter-Circle Corner Crack and a Non-Aligned Surface Crack of Comparable Size in an Infinitely Large Plate Under Uniaxial Tension

2018 ◽  
Author(s):  
M. Perl ◽  
C. Levy ◽  
Q. Ma
Keyword(s):  
Surface Crack ◽  
Mutual Influence ◽  
Mutual Effect ◽  
Multiple Cracks ◽  
Relative Depth ◽  
Reciprocal Effect ◽  
Corner Crack ◽  
Parallel Cracks ◽  
Parallel Surface ◽  
Comparable Size

The reciprocal effect between a quarter-circle corner crack and a non-aligned surface crack of comparable size is addressed in the present study. The significance of understanding the reciprocal effect between the non-aligned parallel cracks is to assist in the evaluation of non-aligned multiple cracks as required in various fitness-for-service codes. For non-aligned parallel cracks, on-site inspection needs to decide whether the cracks should be treated as coalesced or separate multiple cracks. In the existing literature, criteria and standards for the adjustment of multiple non-aligned cracks are very source dependent, and those criteria and standards are often derived from on-site service experience without rigorous and systematic verification. Based on this observation, the authors previously reported on the effect of an embedded parallel crack on an edge crack in 2-D scenarios and, more recently, in 3-D scenarios of a circular corner crack influenced by a parallel surface crack. It may be just as important to evaluate the mutual effect of a quarter-circle corner crack on a non-aligned surface crack as reflected in their stress intensity factors (SIFs). In the present study, the quarter-circle corner crack and the non-aligned surface crack are assumed to be of the same length a2 = a1 = 15mm. While keeping throughout the entire analysis the geometry of the quarter-circle corner crack unchanged, the relative depth of the semi-elliptical surface crack is varied so that b1/a1 = 0.2–1.0. For each particular case a pair of horizontal (H) and vertical (S) separation distances between the two cracks is chosen (H/a2 = 0.4–2 and S/a2 = −0.5–2) and the SIFs along the 3D crack fronts are extracted for both the corner and the surface crack. The reciprocal effect on the SIFs for both cracks are discussed. It is found that the mutual influence between the corner crack and the surface crack are equally important, and each may dominate the decision making based on present criteria and standards in Fitness-for-Service.

scholarly journals CNN-Based Road-Surface Crack Detection Model That Responds to Brightness Changes

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1402
Author(s):  
Taehee Lee ◽  
Yeohwan Yoon ◽  
Chanjun Chun ◽  
Seungki Ryu
Keyword(s):  
Surface Crack ◽  
Autonomous Vehicles ◽  
Crack Detection ◽  
Model Performance ◽  
Semantic Segmentation ◽  
Road Surface ◽  
Image Brightness ◽  
The Road ◽  
Detection Model ◽  
Artificial Intelligence Models

Poor road-surface conditions pose a significant safety risk to vehicle operation, especially in the case of autonomous vehicles. Hence, maintenance of road surfaces will become even more important in the future. With the development of deep learning-based computer image processing technology, artificial intelligence models that evaluate road conditions are being actively researched. However, as the lighting conditions of the road surface vary depending on the weather, the model performance may degrade for an image whose brightness falls outside the range of the learned image, even for the same road. In this study, a semantic segmentation model with an autoencoder structure was developed for detecting road surface along with a CNN-based image preprocessing model. This setup ensures better road-surface crack detection by adjusting the image brightness before it is input into the road-crack detection model. When the preprocessing model was applied, the road-crack segmentation model exhibited consistent performance even under varying brightness values.

A simplified framework for prediction of sensor network coverage in real-time structural health monitoring of plate-like structures

2021 ◽  
pp. 147592172110332
Author(s):  
Mehrdad Ghyabi ◽  
Hamidreza Nemati ◽  
Ehsan Dehghan-Niri
Keyword(s):  
Finite Element ◽  
Sensor Network ◽  
Health Monitoring ◽  
Surface Crack ◽  
Piezoelectric Sensor ◽  
Network Coverage ◽  
Coverage Area ◽  
Fem Simulations ◽  
Network Geometry ◽  
Critical Defect

In this article, the coverage area prediction of piezoelectric sensor network for detecting a specific type of under-surface crack in plate-like structures is addressed. In particular, this article proposes a simplified framework to estimate the coverage of any given sensor network arrangement when a critical defect is known. Based on numerical results from finite element methods (FEM), a simplified framework to estimate coverage area of any given network arrangement is developed. Using such a simplified framework, one can avoid time-consuming procedure of evaluating numerous FEM models in estimating sensor network coverage. Back-scatter fields of partial cracks are estimated using a proposed function, whose parameters are estimated from the results of a limited number of FEM simulations. The proposed function efficiently predicts the back-scattered field of any combination of transmitters and receivers for a given crack geometry. Superposition is used to estimate the coverage area of an arbitrary piezoelectric (e.g., PZT) sensor network. It is shown that the coverage area of a sensor network depends on both sensor network geometry and defect properties (e.g., crack inclination) and it is not necessarily a linear function of the number of sensors. Furthermore, it is shown that the network arrangement has an important effect on the geometry of the coverage area. Experimental results of a network of 14 PZTs in two clusters confirm the accuracy of the method.

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