Research On The Relationship Between The Characteristic Parameters Of The P-Wave And Ground Motion Considering Focus Mechanism

According to the survey data, almost five million earthquakes occurred on the earth every year, more than twenty of which can cause serious damage to human. In addition to earthquake disasters directly, such as the destruction of engineering structure and natural environment and seismic casualties, the earthquake also brings up the serious secondary disasters, such as fire, flood, toxic-hazardous materials leak. In the situation of unable to accurately predict earthquakes, Earthquake Early Warning (EEW) is one of the most economic and feasible method of protecting against and mitigating earthquake disasters. EEW mainly use the characters of early seismic wave to calculate the strength of the earthquake before the destructive wave arrived. If it is over standard values, the system will give warning so that we can take measures to reduce the damage. Because of the Earthquake Early Warning system’s great economic benefit, some countries have successively set up earthquake early warning system and put into use. But false alarm and leakage alarm of the warning system happen occasionally, the basic theory of earthquake early warning system needs further study. As the relationship between peak ground acceleration (PGA) and characteristic parameters and the influence of focus mechanism are insufficient, most studies focused on finding the relationship between magnitude (M) and characteristic parameters of P-wave, and making use of the attenuation relationship to estimate the strength of ground motion. So we mainly study the focus mechanism’s effect on the relationship between characteristic parameters of P-wave and PGA. This paper’s mainly research work is as follows:(1)We propose some linear regression formulations of P-wave’s two period parameters and PGA under circumstances of dividing the type of focal mechanisms or not As the focus mechanism doesn’t distinguish, the linear regression between the period τc and PGA is superior to the period τpmax during the same time window. After classifying the focal mechanism of 165 records according to the rake angle, under the reverse fault and reverse-oblique fault, the linear correlation between the period parameters and the peak acceleration parameters is obviously reduced because of their complex sliding mechanism.(2)We put forward some linear regression formulations of P-wave’s amplitude characteristic parameters and PGA when focus mechanism is classified or not. Besides of the displacement (Pd) studied yet, the acceleration parameter (Pa) is used to estimate the strength of ground motion. If focus mechanism isn’t classified, during the same time window, the Pa’s linear regression between PGA is superior to displacement Pd. After classifying the focus mechanism, the regression correlation between two amplitude characteristic parameters and PGA of normal fault is more obvious. The dispersion is lower a little.(3)Regarding the strike-slip fault’s correlations between characteristic parameters and PGA in above as an early warning algorithm, we research the warning success ratio at different characteristic parameters threshold. Both the period parameters’and the amplitude parameters’warning success ratio reduces first and increases later. The acceleration parameter’s warning success ratio is higher than other parameters on the whole.(4)We propose a method to calculate the probability distribution function of different characteristic parameters, Based on the distribution curve of characteristic parameters in the different peak ground acceleration range and different time window. It can provide a useful reference for the real warning system with different demands to calculate the threshold of characteristic parameters.