• Computers and Concrete
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• 제26권6호
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• pp.533-546
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• 2020

The prediction of spall response of reinforced concrete members like columns and slabs have been attempted by earlier researchers with analytical solutions, as well as with empirical models developed from data generated from physical or numerical experiments, with different degrees of success. In this article, compared to the empirical models, more versatile and accurate models are developed based on model-free approach of artificial neural network (ANN). Synthetic data extracted from the results of numerical experiments from literature have been utilized for the purpose of training and testing of the ANN models. For two concrete members, namely, slabs and columns, different sets of ANN models were developed, each of which proved to have definite advantages over the corresponding empirical model reported in literature. In case of slabs, for all three categories of spall, the ANN model results were superior to the empirical models as evaluated by the various performance metrics, such as correlation, root mean square error, mean absolute error, maximum overestimation and maximum underestimation. The ANN models for each category of column spall could handle three variables together: namely, depth, spacing of longitudinal and transverse reinforcement, as contrasted to the empirical models that handled one variable at a time, and at the same time yielded comparable performance. The application of the ANN models for spall prediction of concrete slabs and columns developed in this study has been discussed along with their limitations.

• Smart Structures and Systems
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• 제31권4호
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 추계학술대회 논문집
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• pp.342-347
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• 2004

The dynamic responses of a PSC bridge for automated guide-way transit system are investigated by analytical approach of bridge-vehicle interaction. In this study, the dynamic responses, concerned with a spall on the surface of bridge are emphasized. A simply supported pre-stressed concrete bridge is adopted as a numerical example. Dynamics of three-dimensional dynamic interaction system between bridges and vehicles is considered in this study. The FE method and modal analysis is used for modeling a bridge for dynamic response analysis. An AGT vehicle is idealized as a model with 11DOFs including lateral motion. It was found that the dynamic responses of bridge can be affected by a spall of surface. Especially, the vibrations are increased much more when a spall is exist.

• 화약ㆍ발파
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• 제23권3호
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• pp.19-25
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• 2005

본 연구에서는 이완식 발파공법과 건교부 제시 발파공법을 적용한 현장에서 지반진동과 소음을 측정, 분석하고 비교하였다. 건교부 방식 발파에 비해 이완식 발파공법이 다소간 진동감쇠 효과가 있었다 발파매트를 사용한 이완식 발파시험 견과가 건교부 방식 발파에 비하여 소음이 감쇠되는 것으로 나타났으며, 파쇄입도는 다소 떨어졌다.

• 한국군사과학기술학회지
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• 제5권3호
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• pp.89-97
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• 2002

In this study, the effect of $\alpha$-phase morphology on the dynamic deformation behavior at ultra high strain rate was investigated by EBW(Explosive Bridge Wire) test. All of tests and analyses were conducted on three typical microstructures of Ti-6Al-4V alloy, i.e. equiaxed, widmanstatten and bimodal microstructures. The spall strength and HEL(Hugoniot Elastic Limit) of the specimens that have the thickness of 2mm and 4mm were highest with the bimodal microstructure. These results were similar with previous study which was performed by dynamic torsion test(Kolsky torsion test).

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2013년도 추계 학술논문 발표대회
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• pp.38-39
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• 2013

In this study, in regard to fiber reinforced mortar mixing steel fiber and 4types of organic fiber, impact test was carried out. Because to predict fracture reduction performance with flexural, tensile strength when types of fiber were different as impact reduction performance of concrete is closely related with toughness such as flexural strength, tensile strength and fracture energy etc. As a result, enhancement of toughness by fiber reinforcement controls the spall of rear. On the other hand in case of steel fiber relatively turned up high toughness in appropriate load compared with organic fiber but in same mixing rate, impact reduction performance by projectile showed low performance due to few number of an individual of mixing.

• 한국구조물진단유지관리공학회 논문집
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• 제17권1호
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• pp.37-45
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• 2013

본 연구에서는 다양한 RC 슬래브의 접촉 발파 실험을 수행하여 내폭 성능을 평가하였다. RC 슬래브의 내폭 성능 향상을 위해 섬유 보강과 외부 CFRP 시트 보강을 도입하였다. 폭발하중 실험은 $2,000{\times}1,000{\times}100mm$ RC 슬래브를 제작하였고, 일반 콘크리트와 강섬유 보강 콘크리트, 하이브리드 PVA 섬유 보강 시멘트 복합체, 초고성능 콘크리트를 적용하였다. 접촉 발파로 생긴 RC 슬래브의 손상 정도를 크레틀, 스폴과 브리치의 직경과 깊이로 평가하였다. 실험 결과를 LS-DYNA 유한요소해석 프로그램과 Morishita 등의 예측식으로 검증하고 비교분석하였다. 분석 결과, LS-DYNA 프로그램을 이용하여 크레틀, 스폴, 브리치의 직경 및 깊이에 대한 개략적인 예측이 가능하며, 폭발하중 하에서 손상부의 거시적 거동을 모사함으로써 부재의 파괴 이력을 나타낼 수 있었다. 국부 손상에 대한 세가지 예측식이 소개되어 있으나 경험식으로써의 한계가 존재하며, 이에 대한 추가 연구가 필요하다고 판단된다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2009년도 춘계 학술대회 제21권1호
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• pp.475-476
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• 2009

본 연구는 W/B 28%의 고강도 콘크리트를 대상으로 PET섬유의 직경 및 혼입률을 변화시켜 콘크리트 기초특성 및 폭렬방지 특성을 검토한 것이다. 유동성 및 압축강도는 0.05vol.%이하 범위의 혼입률에서 유사한 경향을 나타내었다. 내화시험후 폭렬방지 특성으로는 40${\mu}m$의 경우는 0.05vol.%에서 폭렬이 방지되었고, 20${\mu}m$의 경우 0.03vol.%에서도 폭렬이 방지되는 것으로 나타났다.

• 대한기계학회논문집
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• 제18권7호
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• pp.1759-1772
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• 1994

In this study, we re-examined the Tate's modified Bernoulli equation to study penetration phenomena for long rod projectile into single or multi-layered finite thickness plates. We used the force equlibrium equation at mushroomed nose/target interface instead of conventional pressure equation at the stagnation point. In our penetration model, we considered the velocity dependent $R_t$ value for semi-infinite target and considered only the back face effect for finite target. To compensate for $R_t$ value according to target's thickness and back face effect, we used the spherical cavity expansion theory for semi-infinite plate and used the cylindrical cavity expansion theory for finite plate. Also we developed the experimental technique using make screen to measure the penetration duration time at each layered plate. In 3-layered laminated RHA/mild steel/ A1 7039 plate, we observed that spall had occured around the back face of A1 7039 plate by the stress wave interaction. Through the comparison between theoretical and experimental data including Lambert's results, we conform that our study has good confidences.

• 한국전산구조공학회논문집
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• 제30권2호
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• pp.169-177
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• 2017

본 논문에서는 기어 전달오차의 EEMD 적용을 통한 기어 이빨의 박리결함과 균열결함의 분류법을 소개한다. 두 가지 결함을 적용한 기어의 유한요소모델을 바탕으로 전달오차를 획득하고 전달오차에서 나타나는 두 가지 결함의 특징과 정상상태의 전달오차와의 차이를 나타내는 RTE에서 나타나는 두 가지 결함의 특징을 확인했으며 유한요소해석 결과를 이용한 시뮬레이션 신호를 구성하여 신호처리를 통한 RTE 획득과정을 구성하였다. 시뮬레이션 신호로부터 얻은 RTE의 EEMD 적용을 통하여 박리과 균열의 신호가 각기 다른 IMF에서 비중이 크다는 것을 확인하였고, 이를 실험을 통해 검증하고자 하였다. 한 쌍의 기어와 서보모터, 파우더브레이크 그리고 기어의 회전량을 측정하기 위한 엔코더로 구성되어있는 테스트베드를 꾸려 전달오차를 획득하였다. 두 개의 기어를 이용하여 정상, 박리, 균열 세가지 상황에 대한 전달오차를 획득하여 시뮬레이션과 같은 과정을 거쳐 결함이 신호로 구분되는 것을 확인했다. 이를 정량화 하기위해 파고율을 각 IMF에 적용하였고 첫 번째 IMF와 세 번째 IMF의 파고율을 특징 신호로 선정하였다. 실험을 통해 확보된 데이터를 이용하여 Bayes decision 이론을 이용하여 분류 방법을 제시하였다.