• Title/Summary/Keyword: compatible stochastic field

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Non-statistical Stochastic Finite Element Method Employing Higher Order Stochastic Field Function (고차의 추계장 함수와 이를 이용한 비통계학적 추계론적 유한요소해석)

  • Noh, Hyuk-Chun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.2A
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    • pp.383-390
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    • 2006
  • In this paper, a stochastic field that is compatible with Monte Carlo simulation is suggested for an expansion-based stochastic analysis scheme of weighted integral method. Through investigation on the way of affection of stochastic field function on the displacement vector in the series expansion scheme, it is noticed that the stochastic field adopted in the weighted integral method is not compatible with that appears in the Monte Carlo simulation. As generally recognized in the field of stochastic mechanics, the response variability is not a linear function of the coefficient of variation of stochastic field but a nonlinear function with increasing variability as the intensity of uncertainty is increased. Employing the stochastic field suggested in this study, the response variability evaluated by means of the weighted integral scheme is reproduced with high precision even for uncertain fields with moderately large coefficient of variation. Besides, despite the fact that only the first-order expansion is employed, an outstanding agreement between the results of expansion-based weighted integral method and Monte Carlo simulation is achieved.

Optimal sensor placements for system identification of concrete arch dams

  • Altunisik, Ahmet Can;Sevim, Baris;Sunca, Fezayil;Okur, Fatih Yesevi
    • Advances in concrete construction
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    • v.11 no.5
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    • pp.397-407
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    • 2021
  • This paper investigates the optimal sensor placements and capabilities of this procedure for dynamic characteristics identification of arch dams. For this purpose, a prototype arch dam is constructed in laboratory conditions. Berke arch dam located on the Ceyhan River in city of Osmaniye is one of the highest arch dam constructed in Turkey is selected for field verification. The ambient vibration tests are conducted using initial candidate sensor locations at the beginning of the study. Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification methods are used to extract experimental dynamic characteristics. Then, measurements are repeated according to optimal sensor locations of the dams. These locations are specified using the Effective Independence Method. To determine the optimal sensor locations, the target mode shape matrices which are obtained from ambient vibration tests of the selected dam with a large number of accelerometers are used. The dynamic characteristics obtained from each ambient vibrations tests are compared with each other. It is concluded that the dynamic characteristics obtained from initial measurements and those obtained from a limited number of sensors are compatible with each other. This situation indicates that optimal sensor placements determined by the Effective Independence Method are useful for dynamic characteristics identification of arch dams.