Cagdas Kafali (cxk50@po.cwru.edu)

and

Arthur A. Huckelbridge Jr., Assoc. Professor (aah4@po.cwru.edu)

The Department of Civil Engineering

Case School of Engineering

Case Western Reserve University

10900 Euclid Avenue

Cleveland, OH 44106-7201

An aging inventory of steel bridges has made the estimation of remaining fatigue lifetime an increasingly critical parameter in the management of that inventory. Strictly analytical means of evaluating remaining fatigue life are available, but they are dependent upon the validity of the stress prediction technology utilized, which, at best, will be approximate in nature.

Field strain observation offers the potential of greatly improving fatigue lifetime assessment. Rainflow data processing technology allows the on-line compilation of s stress histogram, which is directly applicable in the fatigue damage assessment and lifetime prediction of critical structural members. The technology is currently available and developed to the point where routine field application is increasingly feasible by non-research personnel. Uncertainties associated with the analytical modeling of the structural system can be largely eliminated, and the reliability of the management of the bridge inventory, from the aspect of fatigue lifetime, can be increased substantially.

The objective of this research is to implement a fatigue lifetime assessment system, which could be turned over to, and readily utilized by any non-research bridge personnel. AASHTO fatigue evaluation criteria (S-N curve approach) is used to develop an algorithm which predicts the remaining life of the structural system.