• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2000년도 봄 학술발표회 논문집
• /
• pp.133-140
• /
• 2000

Drilling and blasting method for excavating rock mass is generally used in underground construction; but this technique has some shortcomings. For instance, rock mass damage is inevitable during drilling and blasting, and blast-induced vibration frequently causes some problems. Until now, field measurement method is used to predict the overbreak and vibration; but it has many limitations. Therefore, numerical analysis method is needed to overcome such limitations, and to estimate and predict damage and vibration due to tunnel blasting in the design stage. In this study, damage zone of rock mass due to stoping and contour blasting is compared based on standard tunnel blasting pattern, and the propriety of the standard tunnel blasting pattern is estimated. Then, blasting pattern is optimized so that the damage zone due to sloping blasting with reduced charge is consistent with that due to contour blasting.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
• /
• pp.321-329
• /
• 2002

Artificial neural network has been used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training patterns for neural network teaming process and ambiguity in the relationship of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damages of the railway bridge using dynamic response. The comparison between the mode shape and the natural frequency of structure as training pattern is investigated for approriate selection of the training pattern in the damage detection of railway bridge using the PNN.

• 한국소음진동공학회논문집
• /
• 제25권11호
• /
• pp.739-746
• /
• 2015

Several damage counting methods can be applied for the fatigue issues of a ground vehicle system using strain data and acceleration data is partially used for a high cyclic loading case. For a vibration test, acceleration data is, however, more useful than strain one owing to the good nature of signal-to-random ratio at acceleration response. The test severity can be judged by the fatigue damage and the pseudo-damage from the acceleration response stated in ISO-16750-3 is one of sound solutions for the vibration test. The comparison of fatigue damages, derived from both acceleration and strain, are analyzed in this study to determine the best choice of fatigue damage over multi-spectral input pattern. Uniaxial excitation test was conducted for a notched simple specimen and response data, both acceleration and strain, are used for the comparison of fatigue damages.

• Smart Structures and Systems
• /
• 제14권3호
• /
• pp.307-325
• /
• 2014

A newly developed method based on energy is presented to study the damage pattern of FRP material. Basalt fiber reinforced polymer (BFRP) is employed to monitor the damage under fatigue loading. In this study, acoustic emission technique (AE) combined with scanning electronic microscope (SEM) technique is employed to monitor the damage evolution of the BFRP specimen in an approximate continuous scanning way. The AE signals are analyzed based on the wavelet transform, and the analyses are confirmed by SEM images. Several damage patterns of BFRP material, such as matrix cracking, delamination, fiber fracture and their combinations, are identified through the experiment. According to the results, the cumulative energy (obtained from wavelet coefficients) of various damage patterns are closely related to the damage evolution of the BFRP specimens during the entire fatigue tests. It has been found that the proposed technique can effectively distinguish different damage patterns of FRP materials and describe the fatigue damage evolution.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2013년도 춘계학술대회 논문집
• /
• pp.179-180
• /
• 2013

• Structural Engineering and Mechanics
• /
• 제60권5호
• /
• pp.829-849
• /
• 2016

In this paper, experimental as well as numerical analysis of Glass Fiber Reinforced Polymer (GFRP) laminated composite has been presented under ballistic impact with varying projectile nose shapes (conical, ogival and spherical) and incidence velocities. The experimental impact tests on GFRP composite plate reinforced with woven glass fiber ($0^{\circ}/90^{\circ}$)s are performed by using pneumatic gun. A three dimensional finite element model is developed in AUTODYN hydro code to validate the experimental results and to study the ballistic perforation characteristic of the target with different parametric variations. The influence of projectile nose shapes, plate thickness and incidence velocity on the variation of residual velocity, ballistic limit, contact force-time histories, energy absorption, damage pattern and damage area in the composite target have been studied. The material characterization of GFRP composite is carried out as required for the progressive damage analysis of composite. The numerical results from the present FE model in terms of residual velocity, absorbed energy, damage pattern and damage area are having close agreement with the results from the experimental impact tests.

• 한국BIM학회 논문집
• /
• 제9권1호
• /
• pp.42-51
• /
• 2019

Maintenance of aging structures has attracted societal attention. Maintenance of the aging structure can be efficiently performed with a digital twin. In order to maintain the structure based on the digital twin, it is required to accurately detect the damage of the structure. Meanwhile, deep learning-based damage detection approaches have shown good performance for detecting damage of structures. However, in order to develop such deep learning-based damage detection approaches, it is necessary to use a large number of data before and after damage, but there is a problem that the amount of data before and after the damage is unbalanced in reality. In order to solve this problem, this study proposed a method based on Generative adversarial network, one of Generative Model, for generating acceleration data usually used for damage detection approaches. As results, it is confirmed that the acceleration data generated by the GAN has a very similar pattern to the acceleration generated by the simulation with structural analysis software. These results show that not only the pattern of the macroscopic data but also the frequency domain of the acceleration data can be reproduced. Therefore, these findings show that the GAN model can analyze complex acceleration data on its own, and it is thought that this data can help training of the deep learning-based damage detection approaches.

• Structural Monitoring and Maintenance
• /
• 제5권2호
• /
• pp.231-242
• /
• 2018

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

• Structural Monitoring and Maintenance
• /
• 제5권2호
• /
• pp.243-260
• /
• 2018

Detection of damages in fibre reinforced plastic (FRP) composite structures is important from the safety and serviceability point of view. Usually, damage is realized as a local reduction of stiffness and if dynamic responses of the structure are sensitive enough to such changes in stiffness, then a well posed inverse problem can provide an efficient solution to the damage detection problem. Usually, such inverse problems are solved within the framework of pattern recognition. Support Vector Machine (SVM) Algorithm is one such methodology, which minimizes the weighted differences between the experimentally observed dynamic responses and those computed using the finite element model- by optimizing appropriately chosen parameters, such as stiffness. A damage detection strategy is hereby proposed using SVM which perform stepwise by first locating and then determining the severity of the damage. The SVM algorithm uses simulations of only a limited number of damage scenarios and trains the algorithm in such a way so as to detect damages at unknown locations by recognizing the pattern of changes in dynamic responses. A rectangular fiber reinforced plastic composite plate has been investigated both numerically and experimentally to observe the efficiency of the SVM algorithm for damage detection. Experimentally determined modal responses, such as natural frequencies and mode shapes are used as observable parameters. The results are encouraging since a high percentage of damage cases have been successfully determined using the proposed algorithm.

• Structural Engineering and Mechanics
• /
• 제36권4호
• /
• pp.481-497
• /
• 2010

The shaking table tests were conducted on two small-scale models (Model 1 and Model 2) to examine the earthquake-induced damage of a concrete gravity dam, which has been planned for the construction with the recommendation of the peak ground acceleration of the maximum credible earthquake of 0.42 g. This study deals with the numerical simulation of shaking table tests for two smallscale dam models. The plastic damage constitutive model is used to simulate the crack/damage behavior of the bentonite-concrete mixture material. The numerical results of the maximum failure acceleration and the crack/damage propagation are compared with experimental results. Numerical results of Model 1 showed similar crack/damage propagation pattern with experimental results, while for Model 2 the similar pattern was obtained by considering the modulus of elasticity of the first and second natural frequencies. The crack/damage initiated at the changing point in the downstream side and then propagated toward the upstream side. Crack/damage accumulation occurred in the neck area at acceleration amplitudes of around 0.55 g~0.60 g and 0.65 g~0.675 g for Model 1 and Model 2, respectively.