• 한국전산구조공학회논문집
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• 제27권6호
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• pp.581-588
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• 2014

최근에 널리 사용되고 있는 PSC 교량은 콘크리트의 처짐과 균열 등의 취약점을 긴장재와 강봉을 사용하여 보완하고 성능을 향상시킨 구조물이다. 따라서 PSC 교량에서 긴장재에 작용하는 하중을 적절하게 산정하는 것은 구조물의 안전하고 효율적인 유지, 보수를 위하여 중요하다. 이 논문은 텐던에 작용하는 하중과 앵커헤드 변형과의 관계를 확인하기 위하여 멀티 텐던 앵커헤드의 변형률에 대한 수치해석을 수행하고 분석한 것이다. 정확한 해석을 위하여 재료의 물성, 접촉 문제의 비선형성 등을 모두 고려하였으며 해석은 범용 유한요소 프로그램인 Abaqus를 사용하여 수행되었다. 수치해석 결과로부터 텐던에 작용하는 하중을 추정하는 데에는 hoop 방향 변형률이 가장 유용하며, 마찰 계수, 경계조건, 그리고 배치 등에 따라 영향을 받는 것을 확인하였다.

• Smart Structures and Systems
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• 제16권3호
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• pp.415-433
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• 2015

Tendon failures in bonded post-tensioned bridges over the last two decades have motivated ongoing investigations on various aspects of unbonded tendons and their monitoring methods. Recent research shows that change of strain distribution in anchor heads can be useful in detecting wire breakage in unbonded construction. Based on this strain variation, this paper develops a damage detection model that enables an automated tendon monitoring system to identify and locate wire breaks. The first part of this paper presents an experimental program conducted to study the strain variation in anchor heads by generating wire breaks using a mechanical device. The program comprised three sets of tests with fully populated 19-strand anchor head and evaluated the levels of strain variation with number of wire breaks in different strands. The sensitivity of strain variation with wire breaks in circumferential and radial directions of anchor head in addition to the axial direction (parallel to the strand) were investigated and the measured axial strains were found to be the most sensitive. The second part of the paper focuses on formulating the wire breakage detection framework. A finite element model of the anchorage assembly was created to demonstrate the algorithm as well as to investigate the asymmetric strain distribution observed in experimental results. In addition, as almost inevitably encountered during tendon stressing, the effects of differential wedge seating on the proposed model have been analyzed. A sensitivity analysis has been performed at the end to assess the robustness of the model with random measurement errors.