• Title/Summary/Keyword: 손상구성모델

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A Study on Relationship between Structural Safety and Maintenance of Derailing Prevent Guard Rail (탈선방지 가드레일의 구조안전성과 유지보수 상관성에 관한 연구)

  • Jung-Youl Choi;Hyeon-Yo Park;Jee-Seung Chung
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.593-599
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    • 2023
  • There is risk of derailment due to various factors such as vehicle-track load imbalance in curved parts, so urban railways install and operate derailing prevent guard rails. The angle-type derailing prevent guard rail is composed of various parts including the guard angle. Even if derailment does not occur, various damages occur in the components, so continuous maintenance is required. Through the damage status analysis, the components of the angle-type derailing prevent guard rail with high damage frequency were classified, and conditions for the occurrence of various damages were investigated. In addition, a numerical analysis using a precise 3D numerical model was performed to analyze the cause of the damage analytically. In order to analytically simulate the derailment situation, the static ultimate load condition was applied, and the actual drawing of the angle-type derailing prevent guard rails, rails, and wheels was used for modeling. By analyzing the results of the damage status investigation and finite element analysis, we tried to investigate the damage of the components.

통합형 점소성 구성방정식을 적용한 유한요소해석에 관한 연구

  • Kim, Jong-Beom;Lee, Hyeong-Yeon;Yoo, Bong;Kwak, Dae-Young;Lim, Yong-Taek
    • Proceedings of the Korean Nuclear Society Conference
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    • 1995.05a
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    • pp.1014-1020
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    • 1995
  • 고온구조물은 고온에서의 운전상태에 따라 복잡한 하중이력을 경험하게 됨으로써 상온에서 발생하는 손상 기구와는 달리 온도 의존성을 가질 뿐만 아니라, 상온에서 볼 수 없는 크립-피로의 상호작용에 의한 손상현상이 나타나게 된다. 따라서 고온 구조물의 건전성 평가를 위한 비탄성 해석을 신뢰성 있게 수행하기 위해서는 구조물의 비선형 거동을 비교적 정확히 예측할 수 있는 통합 구성방정식의 개발 및 적용과 온도에 따른 재료의 물성치 확보가 필수적이다. 본 연구에서는 통합 점소성 모델인 수정된 Chaboche 모델에 대해서 내연적 시간 적분법을 적용하여 ABAQUS의 UMAT으로 구현하였고, 개발된 프로그램을 이용하여 INCONEL 718을 사용한 단순 인장해석, 반복 소성 특성해석 및 크립 해석을 수행하여 프로그램의 신뢰성을 평가하였다. 또한 원공이 있는 평판에 대한 예제해석을 수행함으로써 개발된 프로그램이 고온구조물의 건전성 평가를 위한 비탄성 해석에 적절하게 적용될 수 있음을 확인하였다.

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Analysis of the effect of damage fields containing stochastic uncertainty on stiffness reduction (확률적 불확실성을 포함한 손상 장에서의 강성 저감 효과 분석)

  • Noh, Myung-Hyun;Lee, Sang-Youl;Park, Tae-Hyo
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2011.04a
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    • pp.357-361
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    • 2011
  • 본 논문에서는 확률적 불확실성을 포함한 손상 장에서 강성저감 효과를 추정하는 방법을 제안하였다. 실제 교량 구조물에 분포된 손상 장은 매우 불확실하며 손상의 위치와 형상 또한 정확히 알 수 없는 경우가 많다. 그러나 대부분의 손상 추정 문제는 균열이나 손상의 위치와 형상을 기지의 주어진 정보로 가정하고 손상을 추정한다. 제안 기법에서는 이러한 손상의 위치와 형태가 본질적으로 불확실하다는 가정 하에 이 불확실성을 수정 가우스 강성 저감 분포 함수를 도입하여 기술한다. 교량에 국부적으로 발생된 손상은 교량의 요소강성의 저감 분포로 변환되어 손상이 발생한 전체 시스템의 강성을 표현하고 이를 통해 손상이 발생한 시스템의 전체 응답을 해석할 수 있게 된다. 수정 가우스 강성 저감 분포 함수는 손상 분포의 개략적 중심을 표현하는 평균 변수와 강성 저감의 비국소적 분포 특성을 묘사하는 표준편차 변수, 손상 중심의 손상 정도를 표현하는 강성저감 변수로 구성된다. 본 논문에서는 손상 장에서 손상의 위치나 형태에 대한 확률적 불확실성을 기술하는 수정 가우스 강성 저감 분포 함수를 포함한 유한요소모델을 정식화하여 제시한다. 또한 단일 또는 복합 균열로 인해 교량 구조물에 국부적인 손상이 야기된 경우에 대한 수치 예제를 통하여 균열 등에 대한 정보가 불확실하더라도 수정 가우스 강성 저감 분포 함수를 통해 강성 저감 효과가 분석될 수 있음을 확인하였다.

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Simulation-Based Damage Estimation of Helideck Using Artificial Neural Network (인공 신경망을 사용한 시뮬레이션 기반 헬리데크 손상 추정)

  • Kim, Chanyeong;Ha, Seung-Hyun
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.33 no.6
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    • pp.359-366
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    • 2020
  • In this study, a simulation-based damage estimation method for helidecks is proposed using an artificial neural network. The structural members that share a connecting node in the helideck are regarded as a damage group, and a total of 37,400 damage scenarios are numerically generated by applying randomly assigned damage to up to three damage groups. Modal analysis is then performed for all the damage scenarios, which are selectively used as either training or validation or verification sets based on the purpose of use. An artificial neural network with three hidden layers is constructed using a PyTorch program to recognize the patterns of the modal responses of the helideck model under both damaged and undamaged states, and the network is successively trained to minimize the loss function. Finally, the estimated damage rate from the proposed artificial neural network is compared to the actual assigned damage rate using 400 verification scenarios to show that the neural network is able to estimate the location and amount of structural damage precisely.

Vibration Response Analysis of Caisson Structure-Foundation Interface using Forced Vibration (강제진동해석을 통한 케이슨 구조-지반 경계의 진동응답 분석)

  • Lee, So-Ra;Lee, So-Young;Kim, Jeong-Tae;Kim, Heon-Tae;Park, Woo-Sun;Yi, Jin-Hak
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2010.04a
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    • pp.145-148
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    • 2010
  • 항만 구조물의 건전성 평가 기술의 개발을 위한 기초 연구로서, 강제진동해석을 통하여 케이슨 구조-지반 경계부의 손상에 대한 진동응답을 분석하고자 한다. 이를 위해 세 단계의 연구를 수행하였다. 첫째, 케이슨 구조물의 진동특성 분석을 위해 시간영역기반의 AR(auto-regressive)모델을 선정하였다. 둘째, 모형 케이슨 구조물을 대상으로 진동응답 계측실험을 수행하였으며, AR-모델을 통해 진동특징을 실험적으로 분석하였다. 셋째, 대상 케이슨 시스템의 유한요소모델을 구성하고, 구조-지반 경계부의 손상에 따른 동적응답 특성의 변화를 수치적으로 분석하였다. 이를 위해 강제진동을 모사 하였으며, 구조-지반 경계부의 강성변화에 따른 케이슨 구조물의 진동응답의 변화를 분석하였다.

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Numerical Analysis of Load Carrying Capacity of RC Structures Based on Concrete Damage Model (콘크리트 손상 모델을 적용한 콘크리트 구조물 구조내력 해석)

  • Woo, Sang Kyun;Lee, Yun;Yi, Seong Tae
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.16 no.5
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    • pp.121-128
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    • 2012
  • In this paper, nonlinear analysis for reinforced concrete structure for power transmission line is performed by considering the characteristics of the failure, which are depend on loading conditions and concrete material models. On the numerical evaluation for the failure behavior, the finite element analysis is applied. For the concrete material model, microplane model based on concrete damage is introduced. However, to describe the crack bridging effect of long and short fiber of steel fiber reinforced concrete (SFRC), tensile softening model is suggested and applied for SFRC. An numerical results by finite element technique are compared with the experiment results for box culvert specimen. Comparing on the experimental and analytical results, validity and reliability of numerical analysis are investigated.

Cyclic Creep Model for the Deflection Calculation of Reinforced Concrete Flexural Members under Fatigue Loads (피로하중을 받는 철근콘크리트 휨부재의 처짐산정을 위한 반복크리프 모델)

  • 오병환;김동욱
    • Journal of the Korea Concrete Institute
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    • v.13 no.5
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    • pp.415-422
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    • 2001
  • The present paper focuses on the development of a realistic analysis model for the deformation calculation of reinforced concrete beams subjected to fatigue loadings. The proposed model considers the effect of cyclic creep, which arises from the repeated loading, to calculate the deformation of reinforced concrete beams. A comprehensive experimental program has been set up to identify the deformation accumulation of reinforced concrete beams under repeated loadings. The major test variables were the concrete compressive strength and the magnitude of fatigue loads. The model was calibrated from the present test results. The proposed model allows more realistic analysis of reinforced concrete beams under fatigue loads, especially deformation accumulation of such beams.

Development of the Big-size Statistical Volume Elements (BSVEs) Model for Fiber Reinforced Composite Based on the Mesh Cutting Technique (요소 절단법을 사용한 섬유강화 복합재료의 대규모 통계적 체적 요소 모델 개발)

  • Park, Kook Jin;Shin, SangJoon;Yun, Gunjin
    • Composites Research
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    • v.31 no.5
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    • pp.251-259
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    • 2018
  • In this paper, statistical volume element modeling method was developed for multi-scale progressive failure analysis of fiber reinforced composite materials. Big-size statistical volume elements (BSVEs) was considered to minimize the size effect in the micro-scale, by including as many fibers as possible. For that purpose, a mesh cutting method is suggested and adapted into the fiber model generator that creates finite element domain rapidly. The fiber defect model was also developed based on the experimental distribution of the fiber strength. The size effects from the local load sharing (LLS) are evaluated by increasing the fiber inclusion in the micro-scale model. Finally, continuum damage mechanics (CDM) model to the fiber direction was extracted from numerical analysis on BSVEs. And it was compared with strength prediction from typical representative volume element (RVE) model.

Design and Implementation of AR Model based Automatic Identification and Restoration Scheme for Line Scratches in Old Films (AR 모델 기반의 고전영화의 긁힘 손상의 자동 탐지 및 복원 시스템 설계와 구현)

  • Han, Ngoc-Soc;Kim, Seong-Whan
    • The KIPS Transactions:PartB
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    • v.17B no.1
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    • pp.47-54
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    • 2010
  • Old archived film shows two major defects: line scratch and blobs. In this paper, we present a design and implementation of an automatic video restoration system for line scratches observed in archived film. We use autoregressive (AR) image model because we can make stochastic and specifically autoregressive image generation process with our PAST-PRESENT model and Sampling Pattern. We designed locality maximizing scanning pattern, which can generate nearly stationary time-like series of pixels, which is a strong requirement for a stochastic series to be autoregressive. The sampled pixel series undergoes filtering and model fitting using Durbin-Levinson algorithm before interpolation process. We designed three-stage film restoration system, which includes (1) film acquisition from VHS tapes, (2) simple line scratch detection and restoration, and (3) manual blob identification and sophisticated inpainting scheme. We implemented film acquisition and simple inpainting scheme on Texas Instruments DSP board TMS320DM642 EVM, and implemented our AR inpainting scheme on PC for sophisticated restoration. We experimented our scheme with two old Korean films: "Viva Freedom" and "Robot Tae-Kwon-V", and the experimental results show that our scheme improves Bertalmio's scheme for subjective quality (MOS), objective quality (PSNR), and especially restoration ratio (RR), which reflects how much similar to the manual inpainting results.

Development of Deep Learning-Based Damage Detection Prototype for Concrete Bridge Condition Evaluation (콘크리트 교량 상태평가를 위한 딥러닝 기반 손상 탐지 프로토타입 개발)

  • Nam, Woo-Suk;Jung, Hyunjun;Park, Kyung-Han;Kim, Cheol-Min;Kim, Gyu-Seon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.1
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    • pp.107-116
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    • 2022
  • Recently, research has been actively conducted on the technology of inspection facilities through image-based analysis assessment of human-inaccessible facilities. This research was conducted to study the conditions of deep learning-based imaging data on bridges and to develop an evaluation prototype program for bridges. To develop a deep learning-based bridge damage detection prototype, the Semantic Segmentation model, which enables damage detection and quantification among deep learning models, applied Mask-RCNN and constructed learning data 5,140 (including open-data) and labeling suitable for damage types. As a result of performance modeling verification, precision and reproduction rate analysis of concrete cracks, stripping/slapping, rebar exposure and paint stripping showed that the precision was 95.2 %, and the recall was 93.8 %. A 2nd performance verification was performed on onsite data of crack concrete using damage rate of bridge members.