Estimating extreme temperature differences in steel box girder using long-term measurement data

You-liang Ding , Gao-xin Wang

Journal of Central South University ›› 2013, Vol. 20 ›› Issue (9) : 2537 -2545.

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Journal of Central South University ›› 2013, Vol. 20 ›› Issue (9) : 2537 -2545. DOI: 10.1007/s11771-013-1766-6
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Estimating extreme temperature differences in steel box girder using long-term measurement data

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Abstract

The extreme temperature differences in flat steel box girder of a cable-stayed bridge were studied. Firstly, by using the long-term measurement data collected by the structural health monitoring system installed on the Runyang Cable-stayed Bridge, the daily variations as well as seasonal ones of measured temperature differences in the box girder cross-section area were summarized. The probability distribution models of temperature differences were further established and the extreme temperature differences were estimated with a return period of 100 years. Finally, the temperature difference models in cross-section area were proposed for bridge thermal design. The results show that horizontal temperature differences in top plate and vertical temperature differences between top plate and bottom plate are considerable. All the positive and negative temperature differences can be described by the weighted sum of two Weibull distributions. The maximum positive and negative horizontal temperature differences in top plate are 10.30 °C and −13.80 °C, respectively. And the maximum positive and negative vertical temperature differences between top plate and bottom plate are 17.30 °C and −3.70 °C, respectively. For bridge thermal design, there are two vertical temperature difference models between top plate and bottom plate, and six horizontal temperature difference models in top plate.

Keywords

structural health monitoring / cable-stayed bridge / steel box girder / temperature difference / extreme value analysis

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You-liang Ding, Gao-xin Wang. Estimating extreme temperature differences in steel box girder using long-term measurement data. Journal of Central South University, 2013, 20(9): 2537-2545 DOI:10.1007/s11771-013-1766-6

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