• Title/Summary/Keyword: 평균 정규 로드각

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Punching Fracture Simulations of Circular Unstiffened Steel Plates using Three-dimensional Fracture Surface (3차원 파단 변형률 평면을 이용한 비보강 원판의 펀칭 파단 시뮬레이션)

  • Park, Sung-Ju;Lee, Kangsu;Choung, Joonmo
    • Journal of Ocean Engineering and Technology
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    • v.30 no.6
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    • pp.474-483
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    • 2016
  • Accidental events such as collisions, groundings, and hydrocarbon explosions in marine structures can cause catastrophic damage. Thus, it is extremely important to predict the extent of such damage, which determines the total amount of oil spills and the residual hull girder strength. Punching fracture tests were conducted by Choung (2009b), where various sizes of indenters and circular unstiffened steel plates with different thicknesses were used to quasi-statically realize damage extents. A three-dimensional fracture strain surface was developed based on a reference (Choung et al., 2015b), where the average stress triaxiality and average normalized Lode angle were used as the parameters governing the fracture of ductile steels. In this study, new numerical analyses were performed using very fine axisymmetric elements in combination with an Abaqus user-subroutine to implement the three-dimensional fracture strain surface. Conventional numerical analyses were also conducted for the tests to identify the best fit fracture strain values by changing the fracture strains. Based on the phenomenon of the average normalized Lode angle starting out positive and then becoming slightly negative, it was inferred that the shear stress primarily dominates in determining the fractures locations, with a partial contribution from the compressive stress. It should be stated that the three-dimensional fracture surface effectively predicted at least the shear stress-dominant fracture behavior of a mild steel.

Ductile Fracture Predictions of High Strength Steel (EH36) using Linear and Non-Linear Damage Evolution Models (선형 및 비선형 손상 발전 모델을 이용한 고장력강(EH36)의 연성 파단 예측)

  • Park, Sung-Ju;Park, Byoungjae;Choung, Joonmo
    • Journal of Ocean Engineering and Technology
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    • v.31 no.4
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    • pp.288-298
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    • 2017
  • A study of the damage evolution laws for ductile materials was carried out to predict the ductile fracture behavior of a marine structural steel (EH36). We conducted proportional and non-proportional stress tests in the experiments. The existing 3-D fracture strain surface was newly calibrated using two fracture parameters: the average stress triaxiality and average normalized load angle taken from the proportional tests. Linear and non-linear damage evolution models were taken into account in this study. A damage exponent of 3.0 for the non-linear damage model was determined based on a simple optimization technique, for which proportional and non-proportional stress tests were simultaneously used. We verified the validity of the three fracture models: the newly calibrated fracture strain model, linear damage evolution model, and non-linear damage evolution model for the tensile tests of the asymmetric notch specimens. Because the stress evolution pattern for the verification tests remained at mode I in terms of the linear elastic fracture mechanics, the three models did not show significant differences in their fracture initiation predictions.

Analysis of Behavior Patterns from Human and Web Crawler Events Log on ScienceON (ScienceON 웹 로그에 대한 인간 및 웹 크롤러 행위 패턴 분석)

  • Poositaporn, Athiruj;Jung, Hanmin;Park, Jung Hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.6-8
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    • 2022
  • Web log analysis is one of the essential procedures for service improvement. ScienceON is a representative information service that provides various S&T literature and information, and we analyze its logs for continuous improvement. This study aims to analyze ScienceON web logs recorded in May 2020 and May 2021, dividing them into humans and web crawlers and performing an in-depth analysis. First, only web logs corresponding to S (search), V (detail view), and D (download) types are extracted and normalized to 658,407 and 8,727,042 records for each period. Second, using the Python 'user_agents' library, the logs are classified into humans and web crawlers, and third, the session size was set to 60 seconds, and each session is analyzed. We found that web crawlers, unlike humans, show relatively long for the average behavior pattern per session, and the behavior patterns are mainly for V patterns. As the future, the service will be improved to quickly detect and respond to web crawlers and respond to the behavioral patterns of human users.

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