Infrastructure maintenance is becoming increasingly important in Japan. Especially in Hokkaido.
For example, about 40% the conventional construction method road tunnels have been
constructed over the past 40~50 years. And also, road bridges built during the growing s economy
period account for about 40% of the total in 1955 to 1973. Therefore, many road bridges and
conventional construction method tunnels will come to its rehabilitation stage, and almost bridges
and tunnel linings must be maintenance or repair. Moreover, Hokkaido is northern part of Japan,
which is cold and showy region. The risk of frost damage is high. There have been cases in which
the bridge and road tunnel lining has deformed as a result of freezing in winter. Damage
distinguishing factor in the winter is a significant impact on the degradation process of the road
bridge and tunnel. So, we focused on the inspection data of road bridge and tunnel in Hokkaido.
In this paper consist of three parts.
1) Identification methods based upon actual inspection data in order to carry out strategic
maintenance for tunnel structures. The resistance of deteriorating road bridge and tunnel
lining structures is non-stationary stochastic processes, and reliability problems of such
structures are essentially different of time-independent reliability problems.
2) The damage distinguishing factor of road bridge and tunnel lining show log-normal
distribution, which excellent fit with various data on the durations of disabilities, irrespective
of their severity. Persisting long tails suggest the fractal nature of disability distributions.
3) And finally, numerical examples are worked out to demonstrate the usefulness of this
estimation method for Infrastructure maintenance Management System. And long tails of
distributions for road bridge and tunnel linings are analyzed.