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Analytical correction of vertical shortening based on measured data in a RC high-rise building

  • Song, Eun-seok (Department of Architectural Engineering, KwangWoon University) ;
  • Kim, Jae-yo (Department of Architectural Engineering, KwangWoon University)
  • Received : 2020.08.27
  • Accepted : 2020.11.06
  • Published : 2020.12.25
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Abstract

In this study, a process is proposed to calculate analytical correction values for the vertical shortening of all columns on all floors in a high-rise building that minimizes the error between the structural analysis predictions and values measured during construction. The weight ratio and the most probable value were accordingly considered based on the properties of the shortening value analyzed at several points in each construction stage and the distance between these measured points and unmeasured points at which the shortening was predicted. The effective range and shortening value normalization were considered using the column grouping concept. These tools were applied to calculate the error ratio between the predicted and measured values on a floor where a measured point exists, and then determine the estimated error ratio and estimated error value for the unmeasured point using this error ratio. At points on a floor where no measured point exists, the estimated error ratio and the estimated error value were calculated by applying the most probable value considering the weight ratio for the nearest floor where measured points exist. In this manner, the error values and estimated error values can be determined at all points in a structure. Then, the analytical correction value, defined as this error or estimated error value, was applied by adding it to the predicted value. Finally, the adequacy of the proposed correction method was verified against measurements by applying the analytical corrections to all unmeasured points based on the points where the measurement exists.

Keywords

Acknowledgement

The research described in this paper was financially supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) funded by the Ministry of Land, Infrastructure and Transport (No. 20AUDP-B147683-06).

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