Development of numerical simulation method for prediction of surface earthquake fault behavior

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This research is aimed at developing a new numerical analysis method for prediction of fault behavior, based on model experiments which are to clarify the mechanism of rupture processes of faulting. New experiment techniques using CT scanner and 3D photoelasticity are developed ; the 3D photoelasticity uses new devices and data analysis method. It is shown in the model experiments that the governing mechanism of faulting is the bifurcation that leads to highly variable fault behaviors. Based on this observation, a new analysis method, called non-linear stochastic finite element method (NL-SSFEM) has been developed. This method analyzes the stochastic behavior of unconsolidated soil layers and find the most unstable bifurcated solution that corresponds to the actual faulting.The NL-SSFEM is tuned in applying geo-materials. The validity of the method is verified by reproducing several model experiments carried out by other researchers. For two-dimensional problem of normal or reverse faulting and for three-dimensional problem of lateral sliding, the NL-SSFEM is able to give fairly good evaluation of several parameters of fault configuration and loading. It should be emphasized the variability of these parameters is also well evaluated and that the NL-SSFEM is able to compute the probability of failure. Actual faulting is next studied. The targets are the Nojima Fault (coupled reverse and lateral faulting) and the Shirlongpong Fault (reverse faulting). Constructing a computer model for actual unconsolidated layers, the NL-SSFEM simulates the faulting, and the configuration of simulated faults is compared with observed ones. Good agreement supports the usefulness of the NL-SSFEM as a tool for predicting the fault behavior. The NL-SSFEM provides information about the faulting probability, as the amount of base movement that leads to the surface faulting. Although not verified, the values of the probability seems reasonable from the past data of faulting.