With regard to horizontal components in seismic design of nuclear facilities in Japan when input ground motions are generated based on response spectrum, simulated ground motions composed of two mutually orthogonal components are generated for one target response spectrum. In such a case, the characteristics of the two ground motions are distinguished by the randomness of the phase angle given by the uniformly distributed random numbers and/or the difference in the phase characteristics of the two different components of the observation records. On the other hand, US Nuclear Regulatory Commission standards state that, when performing seismic response analysis for nuclear facilities using the method of simultaneous input of three earthquake ground motion components, the three components should be shown to be statistically independent of each other, and an absolute value for correlation coefficient as proposed by Chen (1975) is introduced as a criterion. In this paper, focusing on the correlation coefficient by Chen (1975), we found the correlation coefficients between two orthogonal components in records of observed strong motions in Japan after 2000, and performed statistical analyses of these correlation coefficients, then analyzed the impact of various earthquake-related parameters upon them. In addition, we actually generated simulated ground motions via a common practice based on the response spectrum and analyzed their correlation coefficients.
To assist the advancement of tsunami risk assessment methods for nuclear power plants, requirements for the generation of artificial tsunami waveforms crucial for close linkage between the probabilistic tsunami hazard analysis and tsunami fragility analysis were first listed. Then, basic studies were conducted to model the phase and amplitude spectra of waveforms observed during the 2011 Tohoku earthquake tsunami. Consequently, the average values of the group delay times and amplitude spectrum for each period band were confirmed to be effective for each modeling. Finally, based on these requirements and results of the basic studies, a technique for generating artificial tsunami waveforms using a statistical method was proposed.
To acquire new knowledge through earthquake ground motion evaluation from a new perspective, the authors attempted to create a site-specific earthquake ground motion evaluation model by machine learning using earthquake ground motion records obtained in the past as training data. The epicentral direction and response duration time of the earthquake ground motion, which had not been addressed by conventional attenuation relations, were also examined. Overall, the observed values were evaluated and modeled well, within twice to half the observed values. The average ratio of the evaluated value to the observed value was approximately 1, and the common logarithmic standard deviation was slightly greater than 0.2 for the amplitude of ground motion and slightly greater than 0.1 for the response duration time. The impact of the epicentral direction on the response duration time was large, and in some cases, it was almost equal to or greater than the impact of each parameter in the conventional prediction equations.