Physics-Based Simulation of Spatiotemporal Patterns of Earthquakes in the Corinth Gulf, Greece, Fault System

ABSTRACT A physics-based earthquake simulation algorithm for modeling the long-term spatiotemporal process of strong (M ≥ 6.0) earthquakes in Corinth Gulf area, Greece, is employed and its performance is explored. The underlying physical model includes the rate- and state-dependent frictional formulation, along with the slow tectonic loading and coseismic static stress transfer. The study area constitutes a rapidly extending rift about 100 km long, where the deformation is taken up by eight major fault segments aligned along its southern coastline, and which is associated with several strong (M ≥ 6.0) earthquakes in the last three centuries, since when the historical earthquake catalog is complete. The recurrence time of these earthquakes and their spatial relation are studied, and the simulator results reveal spatiotemporal properties of the regional seismicity such as pseudoperiodicity as well as multisegment ruptures of strong earthquakes. As the simulator algorithm allows the display of the stress pattern on all the single elements of the fault, we are focusing on the time evolution of the stress level before, during, and after these earthquakes occur. In this respect, the spatiotemporal variation of the stress and its heterogeneity appear to be correlated with the process of preparation of strong earthquakes in a quantitative way.

Source Parameter Sensitivity of Earthquake Simulations assisted by Machine Learning

<p>After large magnitude earthquakes have been recorded, a crucial task for hazard assessment is to quickly estimate Ground Shaking (GS) intensities at the affected region. Urgent physics-based earthquake simulations using High-Performance Computing (HPC) facilities may allow fast GS intensity analyses but are very sensitive to source parameter values. When using fast estimates of source parameters such as magnitude, location, fault dimensions, and/or Centroid Moment Tensor (CMT), simulations are prone to errors in their computed GS. Although the approaches to estimate earthquake location and magnitude are consolidated, depth location estimates are largely uncertain. Moreover, automatic CMT solutions are not always provided by seismological agencies, or such solutions are available at later times after waveform inversions allow the determination of moment tensor components. The uncertainty on these parameters, especially a few minutes after the earthquake has been registered, strongly affects GS maps resulting from simulations.</p><p>In this work, we present a workflow prototype to produce an uncertainty quantification method as a function of the source parameters. The core of this workflow is based on Machine Learning (ML) techniques. As a study case, we consider a domain of 110x80 km centered in 63.9ºN-20.6ºW in Southern Iceland, where the 17 best-mapped faults have hosted the historical events of the largest magnitude. We generate synthetic GS intensity maps using the AWP-ODC finite-difference code for earthquake simulation and a one-dimensional velocity model, with 40 recording surface stations. By varying a few source parameters (e.g. event magnitude, CMT, and hypocenter location), we finally model tens of thousands of hypothetical earthquakes. Our ML analog will then be able to relate GS intensity maps to source parameters, thus simplifying sensitivity studies.</p><p>Additionally, the results of this workflow prototype will allow us to obtain ML-based intensity maps a few seconds after an earthquake occurs exploiting the predictive power of ML techniques. We will evaluate the accuracy of these maps as standalone complements to GMPEs and simulations.</p>

Evaluation of Structure Performance under Seismic Load with Non-Liner Time History on High-Rise Building Affected by Kendeng Fault Earthquake Simulation

Indonesia is a country located in the convergence of small plates and large plates. Furthermore, this causes Indonesia to be high potentially to earthquake hazards. The newest geological research published by Geophysical Research Letter (2016) shows the existence of Fault Kendeng, a fault stretches along 300 km from South Semarang, Central Java, to East Java with a movement of 0,05 millimeter per year [1]. As a result of its research, an evaluation using a non-linear time history analysis for structural buildings is necessary. The objective of this study is to evaluate structural buildings using a non-linear time history analysis. This study applies DSHA (Deterministic Seismic Hazard Analysis) method to obtain acceleration time history on bedrocks. Since the record of ground movement in Indonesia is limited, the attenuation function equation used to scale and match other country’s time acceleration history data. SSA (Site-Specific Analysis) is used to propagate earthquake acceleration from bedrocks to the surface. The earthquake acceleration on the surface generates as the earthquake load on the buildings. The results of Kendeng fault earthquake simulation using non-linear time history analysis shows that column members capacity is more robust than beam members capacity which the beam collapse mechanism occurs initially. From the maximum total drift ratio result, when the Kendeng fault earthquake occurs, the building structure performance level is at collapse prevention level Based on ATC-40 [2]. This research result shows that 96,7% of plastic hinge has not yielded. However, some elements are already damaged. Since most damage members are column, then it may require column strengthening to enhance maximum performance level at life safety condition category.