• Journal of Power System Engineering
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• v.15 no.6
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• pp.73-80
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• 2011

The experimental investigation focuses on an influence of artificial aging time in longitudinal butt welded Al 6013-T4 aluminum alloy on the fatigue crack growth resistance. The preferred welding processes for this alloy are frequently tungsten inert gas welding (TIG) process due to its comparatively easier applicability and better weldability than other gas metal arc welding. Fatigue crack growth tests were carried out on compact tension specimens (CT) in longitudinal butt TIG welded after T82 heat treatment was varied in three artificial aging times of 6 hours, 18 hours and 24 hours. Of the three artificial aging times, 24 hours of artificial aging time are offering better resistance against the growing fatigue cracks. The superior fatigue crack growth resistance preferred spatial variation of materials within each specimen in the Paris equation based on reliability theory and fatigue crack growth rate by crack length are found to be the reasons for superior fatigue resistance of 24 hours of artificial aging time was compared to other joints. The highest of crack propagation resistance occurs in artificial aging times of 24 hours due to the increase in grain size (fine grained microstructures).

• Structural Engineering and Mechanics
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• v.26 no.1
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• pp.99-109
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• 2007

A cracked composite specimen, comprised of an epoxy and an aluminium plate, was fractured under a tensile load. In this paper, two crack configurations were investigated. The first was an artificial center crack positioned in the epoxy plate parallel to the material interface. The other was for two edge cracks in the epoxy plate, again, parallel to the interface. A tensile test was carried out by gradually increasing the applied load and it was verified that the cracks always moved suddenly in an outward direction from the interface. The d/a ratio was gradually reduced to zero, and it was confirmed that the maximum stress intensity factor value for the artificial center crack, $K_{{\theta}{\theta}}^{max}$, approached that of an artificial interface crack,$K_{{\theta}{\theta}}^{ifc\;max}$ (where: 2a is the crack length and d is the offset between the crack and interface). The same phenomenon was also verified for the edge cracks. Specifically, when the offset, d, was reduced to zero, the maximum stress intensity factor value, $K_{{\theta}{\theta}}^{max}$, approached that of an artificial interface edge crack.

• Journal of the Korea Concrete Institute
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• v.21 no.4
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• pp.409-417
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• 2009

In this study, autogenous crack healing and artificial crack healing using electrochemical electro deposition method were conducted to compare in the aspects of corrosion monitoring. Furthermore, the analysis of impressed voltage characteristics, galvanic current and linear polarization resistance comparison, and photo image processing technique were performed for quantitative comparisons of healing ratio. As a result, it was found that, in view of impressed voltage of artificial crack healing, the measured voltage was increased as time goes by. From the galvanic test results of artificial crack healing, the current vs. potential distribution value were formed widely in comparison with autogenous crack healing. In this point, it was shown that artificial crack healing has more eleatic resistance capacity than autogenous crack healing technique. Finally, it was found that artificial crack healing was 1.63 times higher than autogenous healing in view of crack healing ratio.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1922-1928
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• 1999

Rotary bending fatigue tests were carried out to investigate the influence of artificial defects on fatigue limit in annealed and austempered ductile iron. Obtained main results are as follows : (1) Artificial defect(micro hole type, dia.<0.4 mm) on specimen surface did not bring about a obvious reduction of fatigue limit in austempered ductile iron(ADI) as compared with annealed ductile iron. (2) According to the investigation of $\sqrt{area}_c$ which is the critical defect size to crack initiation at artificial defect, $\sqrt{area}_c$ of ADI is larger than that of annealed ductile iron. This shows that the situation of crack initiation at artificial defect in ADI is more difficult in comparison with annealed ductile iron. (3) One of the reasons for the low rate of crack initiation from artificial defect in ADI is that the resistance of matrix to crack initiation is higher than that of annealed ductile iron. (4) In case that the $\sqrt{area}$ of artificial defect and graphite nodule is the same, the rate of crack initiation from graphite nodule is higher than that from artificial defect. This reason is that the serious ruggedness around graphite nodule is formed by austempering treatment.

• Journal of Ocean Engineering and Technology
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• v.1 no.1
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• pp.104-110
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• 1987

Fatigue tests by axial loading (R = 0.05) were carried out to investigate fatigue crack growth characteristics of small surface cracks in 2 1/4 Cr-1 Mo steel at room temperature by using flat specimens with a small artificial pit. All the data of the fatigue crack growth rate obtained in the present test are determined as a function of the stress intensity factor range about a semi-elliptical crack, so that the application of linear fracture mechanics to the surface fatigue crack growth and to the fatigue crack growth into depth, and all the data obtained from tests were discussed in comparison with the data of Type 304 stainless steel and two type of mild steel under the same test conditions. The obtained results are as follows: 1)When the cycle ratios are same, surface fatigue crack length and its depth are almost same and fall within a narrow scatter band in spite of different stress levels. 2)Relations of the surface fatigue crack growth rate (da/dN) and fatigue crack growth rate into depth (db/dN) to its stress intensity factor range ($\Delta K_{Ia}, \Delta K_{Ib}$) can be plotted as a straight line at log-log diagram without dependence of stress level and coincide with the data of part-through crack in various steels.

• Smart Structures and Systems
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• v.25 no.4
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• pp.459-469
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• 2020

The presence of cracks in mechanical components is a very important problem that, if it is not detected on time, can lead to high economic costs and serious personal injuries. This work presents a methodology focused on identifying cracks in unbalanced rotors, which are some of the most frequent mechanical elements in industry. The proposed method is based on Artificial Neural Networks that give a solution to the presented inverse problem. They allow to estimate unknown crack parameters, specifically, the crack depth and the eccentricity angle, depending on the dynamic behavior of the rotor. The necessary data to train the developed Artificial Neural Network have been obtained from the frequency spectrum of the displacements of the well- known cracked Jeffcott rotor model, which takes into account the crack breathing mechanism during a shaft rotation. The proposed method is applicable to any rotating machine and it could contribute to establish adequate maintenance plans.

• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.369-374
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• 2005

This study proposes a technique for the recognition of crack patterns, which includes horizontal, vertical, diagonal($-45^{\circ}$), diagonal($+45^{\circ}$), and random cracks, based on image processing technique and artificial neural network. A MATLAB code was developed for the proposed image processing algorithm and artificial neural network. Features were determined using total projection technique, and the structure(no. of layers and hidden neurons) and weight of artificial neural network were determined by learning from artificial crack images. In this process, we adopted Bayesian regularization technique as a generalization method to eliminate overfitting Problem. Numerical tests were performed on thirty-eight crack images to examine validity of the algorithm. Within the limited tests in the present study, the proposed algorithm was revealed as accurately recognizing the crack patterns when compared to those classified by a human expert.

• Journal of the Korean Society for Heat Treatment
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• v.12 no.3
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• pp.215-220
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• 1999

Rotary bending fatigue tests were carried out to investigate the artificial defect sensitivity of fatigue limit in annealed and austempered ductile irons. Artificial defect(hole, diameter${\leq}0.4mm$) machined on specimen surface did not bring about an obvious reduction of fatigue limit in austempered ductile iron as compared with annealed. As a result of investigation on $\sqrt{area}$ c which is the critical artificial defect size. $\sqrt{area}$ c of austempered ductile iron is larger than that of annealed. This means that the crack initiation at artificial defect in austempered ductile iron is more difficult in comparison with annealed. In case that the $\sqrt{area}$ c of artificial defect and graphite nodule are same, the rate of crack initiation for graphite nodule is higher than that of artificial defect.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.245-246
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• 2022

Typically, the methods of crack detection on concrete structures include some problems, such as a low accuracy and expensive. To solve these problems, we proposed a neural network-based crack search method. The proposed algorithm goes through three convolutions and is classified into crack and non-crack through the softmax layer. As a result of the performance evaluation, cracks can be detected with an accuracy of 99.4 and 99.34 % at the training model and the validation model, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.168-177
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• 1999

Fatigue damage is the phenomena which is accumulated gradually with loading cycle in material. It is represented by fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$. Fracture mechanical parameters estimating large crack growth behavior can calculate quantitative amount of fatigue crack growth resistance in engineering material. But fatigue damage has influence on various load, material and environment. Therefore, In this study, we propose that artificial intelligent fatigue damage model can predicts fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$ simultaneously using fracture mechanical and nondestructive parameters.