1. Earthquake damage simulator for railways with self-correcting function

Rapid recovery of railway operations following an earthquake depends on being able to quickly obtain data about damage that has occurred. Until now, damage was estimated on the basis of seismic intensity observed through trackside seismographs and seismic damage nomographs, using the natural period and the yield acceleration of structures as parameters. This meant that obtaining more detailed damage estimation using local ground and structural characteristics, was difficult. This abstract introduces an earthquake damage simulator with a self-correcting function (Fig. 1). Simulation begins automatically when an Earthquake Early Warning is received. The simulator processes the information available at that moment (epicenter, seismic observation records, etc.) and predicts trackside seismic waveforms in real time. The simulator can estimate damage through detailed dynamic analyses of the behavior of structures, electric poles and railway vehicles using the seismic waveforms.

Using the simulator, damage can be estimated within several minutes to several tens of minutes taking into account the difference of in characteristics of deep soil structures, the surface ground and vibration characteristics of each railway structure. An algorithm automatically updates the parameters in the simulator used for estimating damage by adding information, such as boring survey data and structural design sheets, and observed ground motion. As a result, damage estimation can automatically improve with as damage and earthquake data is collected and accumulated.

Generally, increasing simulation accuracy requires longer calculation time. This simulator however, manages to combine high precision and immediacy thanks to the self-correction function and ranking of structures in order of priority for inspection, thereby allowing operations to resume more quickly following an earthquake.

This research was financially supported by the Ministry of Land, Infrastructure, Transport and Tourism.