The full text of this article
Stochastic failure analysis of the gusset plates in the Mississippi River Bridge
by Mojtaba Mahmoodian; Amir Alani; Kong Fah Tee
International Journal of Forensic Engineering (IJFE), Vol. 1, No. 2, 2012
Abstract: The I-35W Mississippi River Bridge over Minneapolis, Minnesota, collapsed suddenly on August 1, 2007. Previous studies showed that the demand-to-capacity ratio for one of the gusset plates had become extremely high after about 40 years of service of the bridge and therefore, the failure of the gusset plate caused the failure of the whole bridge. A forensic assessment using stochastic reliability analysis is carried out in this research to check whether the collapse of the bridge could have been predicted at the design stage. For this purpose, the probabilities of failure for different types of stresses in the gusset plate are estimated. To consider the uncertainties involved in dead load and live load increments with time, the gamma process concept is employed to model stress increments. It is shown that the probability of failure in the year 2007 was higher than the recommended value. Therefore, it can be concluded that if the results of this study had been available at the design stage, the lack of reliability in 2007 could have been predicted and the collapse of the bridge and its disastrous consequences could have been prevented. It is also concluded that stochastic reliability analysis can be used as a rational tool for failure analysis and reliability assessment of bridges to prevent the risk of collapse.
Online publication date: Sun, 18-Nov-2012
is only available to individual subscribers or to users at subscribing institutions.
Go to Inderscience Online Journals to access the Full Text of this article.
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Forensic Engineering (IJFE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable).
See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org