• Structural Monitoring and Maintenance
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• 제7권4호
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• pp.319-344
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• 2020

Inverse analysis of non-linear reinforced concrete bridge pier using recursive Gaussian filtering for in-situ condition assessment is the main theme of this work. For this purpose, minimum variance unbiased estimation using unscented sigma points is adopted here. The uniqueness of this inverse analysis lies in its approach for strain based updating of engineering demand parameters, where appropriate bound and constrained conditions are introduced to ensure numerical stability and convergence. In this analysis, seismic input is also identified, which is an added advantage for the structures having no dedicated sensors for earthquake measurement. First, the proposed strategy is tested with a simulated example whose hysteretic properties are obtained from the slow-cyclic test of a frame to investigate its efficiency and accuracy. Finally, the experimental test data of a full-scale bridge pier is used to study its in-situ condition in terms of Park & Ang damage index. Overall the study shows the ability of the augmented minimum variance unbiased estimation based recursive time-marching algorithm for non-linear system identification with the aim to estimate the engineering damage parameters that are the fundamental information necessary for any future decision making for retrofitting/rehabilitation.

• 한국전통조경학회지
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• 제28권3호
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• pp.105-113
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• 2010

본 연구는 전통공간에 대한 보존계획에 있어서, 대상물의 가치평가를 위하여 수행되는 훼손상태조사에 대한 연구이다. 특히, 전통공간에 위치해 있는 전통 건조물의 보존에 대한 관심과 흥미를 체계화하고 있는 전문가 집단에서 가치평가의 주된 요소로써 대상물의 훼손상태는 어떠한 과정과 방법에 의해서 분석될 수 있는가? 에 대한 과정과 방법론에 관한 실험적인 연구이다. 이를 위하여 본 연구에서는 문화재 '진단학(Diagnostic)'에 대한 이해를 바탕으로 수표교에 대한 물리적 특성과 대상지 환경여건에 대한 이해를 바탕으로 수행하였다. 한편, 본 연구는 그 특성상 수표교의 훼손상태를 기록하기 위하여 작성되는 훼손상태 분포도는 사진측량 기법을 적용한 실측도면을 활용하였고, 대상물의 훼손상태를 조사하기 위한 '평가지침'은 이탈리아 정부의 건축문화재 관리지침이라 할 수 있는 'Raccomandazioni Normal'을 기준으로 하였다. 이러한 연구접근은 국외 건축문화재의 훼손상태 조사에 사용되는 표준지침의 국내 문화재로의 적용 가능성에 대한 실험적인 차원에서 이루어졌음을 밝혀둔다. 그 결과, 수표교의 각 부분별 훼손상태는 침전물에 의한 훼손과 부식 등이 주를 이루고 있었으며, 부식을 비롯한 9가지의 훼손유형의 경우에는 그 구성성분의 물리 화학적 특성과 분포상태를 고려할 때, 수표교의 안전성과 관련하여 위협적인 요소로는 작용하지 않는 것으로 판단하였다. 반면에, 경관 향상을 위하여 상판마루와 멍에석, 그리고 교각부분에서 관찰되는 'Thermoclastism(열전화)' 현상의 경우, 교각을 중심으로 넓게 분포하고 있음을 감안할 때, 훼손부위의 제거와 함께 표면강화 작업의 조속한 처리가 요구될 것으로 판단하였다.

• Smart Structures and Systems
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• 제20권5호
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• pp.549-562
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• 2017

The US railroad network carries 40% of the nation's total freight. Railroad bridges are the most critical part of the network infrastructure and, therefore, must be properly maintained for the operational safety. Railroad managers inspect bridges by measuring displacements under train crossing events to assess their structural condition and prioritize bridge management and safety decisions accordingly. The displacement of a railroad bridge under train crossings is one parameter of interest to railroad bridge owners, as it quantifies a bridge's ability to perform safely and addresses its serviceability. Railroad bridges with poor track conditions will have amplified displacements under heavy loads due to impacts between the wheels and rail joints. Under these circumstances, vehicle-track-bridge interactions could cause excessive bridge displacements, and hence, unsafe train crossings. If displacements during train crossings could be measured objectively, owners could repair or replace less safe bridges first. However, data on bridge displacements is difficult to collect in the field as a fixed point of reference is required for measurement. Accelerations can be used to estimate dynamic displacements, but to date, the pseudo-static displacements cannot be measured using reference-free sensors. This study proposes a method to estimate total transverse displacements of a railroad bridge under live train loads using acceleration and tilt data at the top of the exterior pile bent of a standard timber trestle, where train derailment due to excessive lateral movement is the main concern. Researchers used real bridge transverse displacement data under train traffic from varying bridge serviceability levels. This study explores the design of a new bridge deck-pier experimental model that simulates the vibrations of railroad bridges under traffic using a shake table for the input of train crossing data collected from the field into a laboratory model of a standard timber railroad pile bent. Reference-free sensors measured both the inclination angle and accelerations of the pile cap. Various readings are used to estimate the total displacements of the bridge using data filtering. The estimated displacements are then compared to the true responses of the model measured with displacement sensors. An average peak error of 10% and a root mean square error average of 5% resulted, concluding that this method can cost-effectively measure the total displacement of railroad bridges without a fixed reference.