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| Estimation of extreme vehicle load effect based on generalized Pareto distribution |
| FENG Haiyue1, YI Tinghua1, 2, CHEN Bin3 |
1. School of Civil Engineering, Dalian University of Technology, Dalian 116023, China;
2. State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China;
3. College of Civil Engineering and Architecture, Zhejiang University of Technology, Hangzhou 310003, China |
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Abstract In order to solve the data correlation of the vehicle load effect and make full use of the data samples, the modified method of independent storms (MMIS) is proposed. First, a triple class threshold method is proposed to obtain the threshold by primary data analysis. Then considering that the vehicle load effect of simply supported beam bridge is mainly affected by the single heavy vehicle, the MMIS is adopted to extract the independent and identically distributed (IID) data. Finally, the extreme vehicle load effect is estimated by generalized Pareto distribution. In the end, the estimation of extreme vehicle load effect is performed on the measured data of the bridge recorded by weigh-in-motion (WIM) and compared with the peak-over-threshold method and method of independent storms. The results show that within the short estimation period (T<20 years), all the three methods can better estimate the extreme load effect, while within the middle or long estimation period, the estimation of the modified method of independent storms is higher and safer.
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Received: 04 May 2014
Published: 15 August 2015
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