ABSTRACT
The text in this paper is for visual purpose only. No rights can be taken from this.
Although bridges are designed for 75 years according to the AASHTO LRFD Bridge Design Specifications (2014), the observed service life is shorter due to the deterioration of various elements over the years. The major reasons of the deterioration can be attributed to two causes: 1) rapid increase of the live load (weight and frequency) and 2) the gradual loss in the load carrying capacity. Therefore, in order to accurately evaluate the performance of various types of bridges and implement appropriate maintenance and repair schemes, it is important to predict the long-term live load for the bridge structure.
In this study, the research is aimed at developing a probabilistic approach to predict the long-term live load for bridge structures. Daily maximum vehicle weight data is extracted from weight data is extracted from Weigh-in-Motion (WIM) data collected from more than 80 sites in New Jersey. K-S test is used to select the most appropriate distribution for the daily maximum vehicle weight data. A prediction model is developed for long-term live load based on the selected distribution. Moreover, the predicted live load is compared with the actual live load that observed at 10 and 20 years intervals based on the last 20 years of WIM data collected from various sites in New Jersey. Probability Plots for Daily Maximum Bias Ratio for Span Length of 100 ft with Different Distributions, site 195 (1993). https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781315207681/cd556cd4-4dcf-4efe-8e29-56fc67b8bfbd/content/fig139_1.tif"/> Bias Factors Calculated using Prediction Method I with Normal Distribution.
Span Length (ft.)
Bias Factor
1 Day
1 Year
5 Years
10 Years
50 Years
75 Years
60
1.69
1.90
1.95
1.97
2.02
2.03
80
1.56
1.75
1.79
1.81
1.85
1.86
100
1.48
1.64
1.68
1.70
1.73
1.74
120
1.43
1.59
1.63
1.64
1.68
1.68
140
1.38
1.54
1.57
1.59
1.62
1.63
160
1.26
1.40
1.44
1.45
1.48
1.49
180
1.13
1.26
1.29
1.30
1.33
1.34
200
0.96
1.08
1.11
1.12
1.15
1.15
