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Estimation of the magnitudes of future earthquakes produced by faults is critical in seismic hazard assessment, especially for faults that are short in extent compared with the thickness of the seismogenic layers of the upper crust. A new seismogenic fault model for earthquake size estimation was constructed by combining (a) new assessments of the precise location and distribution of active faults from aerial photograph analysis and (b) estimations of subsurface structures from geological, gravity, and seismicity datasets. The integrated results of (1) tectonic landforms determined from aerial photographs, (2) geologic data showing the distribution of geologic faults, (3) Bouguer gravity anomaly data over wavelengths of 4–200 km, and (4) seismicity data were superimposed on geographic information system (GIS) data around the nuclear power plants in Japan. The results indicate the possible occurrence of large earthquakes, because the lengths of the subsurface earthquake faults were estimated to be longer than the length of the surface faults if subsurface structures were included.

Seismotectonic zonation for seismic hazard assessment of background faults and earthquakes by the Headquarters for Earthquake Research Promotion (HERP [1]) is based on the results of the seismotectonic boundaries of Kakimi et al. [2]. However, several unsolved problems, such as map scale, remain in this approach for better prediction of the magnitude and frequency of blind earthquakes. The aim of this study was to construct a new quantitative and objective seismotectonic province map for the main islands of Japan (Honshu) for rational earthquake size estimation of blind faults and earthquakes. The resolution of the map was set as the second-order map grid of ca. 10 by 10 km of the Geographic Survey of Japan. Then, the parameters of (1) observed seismicity, (2) distribution of active faults converted to earthquake moment release rate, (3) width of the seismogenic layer, and (4) Bouguer gravity anomaly were assigned independently to each grid for principal component analysis. The first principal component of the principal analysis in this study represents the degree of tectonic activity for both the northeastern and southwestern Honshu islands. The resulting principal component scores were then applied to a cluster analysis to conduct quantitative classifications, and the result provided three and nine seismotectonic provinces in the northeastern and southwestern Honshu islands, respectively.

Multiple regressions are developed using world earthquake data and active fault data, and the regressions are then evaluated with Akaike’s Information Criterion (IEEE Trans Autom Control, 19(6):716–723). The AIC method enables selection of the regression formula with the best fit while taking into consideration the number of parameters. By using parameters relevant to earthquakes and active faults in the regression analyses, we develop a new empirical equation for magnitude estimation as .

The aim of this study is to demonstrate the tsunami potential caused by high-angle branching faults with relatively low net slip compared to that of the 2011 off the Pacific coast of Tohoku (Tohoku-oki) earthquake of Mw9.0, located in the upper part of the mega-thrust along the Japan Trench where the Tohoku-oki earthquake ruptured, as deduced from the distribution of active faults illustrated by a bathymetric geomorphological study and seismic profile records (Nakata et al. Active faults along Japan Trench and source faults of large earthquakes. . 19 Dec 2012). The results show that the expected tsunami from high-angle branching faults becomes about one and a half times as high as the case of low-angle thrust faults. This demonstrates the importance of the distribution of high-angle branching faults on the continental slope and their subsurface structure in tsunami hazard assessment.

Topographic anaglyph images were viewed with red-cyan glasses enabled to recognize topographic relief features easily. Anaglyphs produced from digital elevation model (DEM) data are a very effective technique to identify tectonic geomorphology. The aim of this paper was to introduce an extensive area of topographic anaglyph images produced from the 5-m-mesh and 10-m-mesh inland DEM of Geospatial Information Authority of Japan, as well as the 1-s-mesh DEM on the seafloor. In this paper, we present two examples which show that the extensive area of anaglyph produced from combined detailed DEM is advantageous for identifying broad tectonic geomorphology near a coastal area, as well as in urban areas, to view “naked” topography exaggerated vertically. For instance, the NW-SE trending active flexure scarp on the Musashino surface to the north of Tokyo Metropolis has been identified by means of interpretation of these images. The tectonic deformation on the shallow seafloor near Kisakata has also been identified, where the emergence of the lagoon associated with the Kisakata earthquake (M7.0) of 1804 was recorded in the historical documents. When anaglyphs from detailed DEM are extensive and have emphasized vertical exaggeration, they are valuable for recognizing long-wave (one kilometer to several hundred meter scaled) deformations.

To aim at the advancement of strong motion predictions, we develop empirical relations between stress drops on strong motion generation areas (SMGAs) and depths of SMGAs based on previous broadband source models estimated by the empirical Green’s function method. A total of 25 source models for 13 crustal earthquakes of Mw from 5.7 to 6.9 in Japan are used in this study. It is found that stress drops on SMGAs for reverse faults are larger than those for strike-slip faults on average. The average stress drops are 21.2 MPa, 13.3 MPa, and 18.0 MPa for reverse, strike-slip, and all types of faults, respectively. In the derived empirical relation for all types of faults, the stress drops increase by about 1 MPa every 1 km in depth. This depth dependency is similar to the relation between stress drops on asperities and the depths of asperities derived by Asano and Iwata (Pure Appl Geophys, 168:105–116, 2011), and the absolute value is 4 MPa larger than that by Asano and Iwata (Pure Appl Geophys, 168:105–116, 2011). The depth dependency of stress drops for reverse faults is stronger than that for strike-slip faults. The total area of SMGAs is about 0.8 times of the total area of asperities by Somerville et al. (Seismol Res Lett, 70:59–80, 1999). The result can be interpreted by frequency-dependent source radiations, since asperities are estimated from longer-period (>2 s) strong motions than SMGAs, which are mainly estimated from strong motions in the period range from 0.1 to 5 s.

We compiled the stress drops on the asperities in inland earthquakes caused by strike-slip faults. Then, we applied the log-normal distribution to the data and obtained the medium of 10.7 MPa and the logarithmic standard deviation of 0.45. Also, we compiled the stress drops on the asperities in inland earthquakes caused by reverse faults and obtained the medium of 17.1 MPa and the logarithmic standard deviation of 0.39.

By using the obtained log-normal distributions, we examined a procedure for assigning the heterogeneous dynamic stress drops to each asperity. We adopted 12.2 MPa, which had been estimated by Dan et al. (J Struct Constr Eng (Trans Archit Inst Japan), 76:(670):2041–2050, 2011) for long strike-slip faults, as the medium, and 18.7 MPa, which had been estimated by Dan et al. (J Struct Constr Eng (Trans Archit Inst Japan), 80(707):47–57, 2015) for long reverse faults.

Moreover, we truncated the log-normal distributions of the dynamic stress drops on the asperities at the value of 3.4 MPa for strike-slip faults and of 2.4 MPa for reverse faults because they should be larger than the dynamic stress drop averaged over the entire fault.

Finally, we proposed a procedure for evaluating fault parameters taking into account of the heterogeneous dynamic stress drops on the asperities and calculated strong ground motions. The results had wider variations of the peak ground accelerations and velocities than those with uniform dynamic stress drops on the asperities, while the averages were almost the same.

In our previous studies (Ohori and Hisada, Zisin 2(59):133–146, 2006, Bull Seismol Soc Am 101:2872–2886, 2011), we simulated the strong-motion records of the mainshock (5.4) of the 2001 Hyogo-ken Hokubu earthquake, Japan, on the basis of the empirical Green’s tensor spatial derivative (EGTD) estimated from data of 11 aftershocks (3.5–4.7). The agreement between the observed and calculated waveforms at the closest station in source distance was satisfactory over a long duration, and the amplitude was well reproduced. But considering the lowest corner frequency of about 1.0 Hz for the mainshock, we targeted 0.2–1.0 Hz band-pass-filtered velocity waveforms. In the present study, we tried to simulate the broadband strong motions beyond the corner frequencies for the same events as in our previous studies mentioned above. To correct the discrepancies among the corner frequencies of events, we assumed the scaling law based on the ω model (Aki, J Geophys Res 72:1217–1231, 1967) and compensated the spectral amplitude decay beyond the corner frequency. After estimating the EGTD from 11 aftershock events using 0.2–10 Hz band-pass-filtered waveforms, we simulated the strong-motion records for the mainshock and aftershocks. In simulation of each event, the EGTD elements were multiplied by the moment tensor elements followed by summation and corrected in the spectral amplitude, taking the corner frequency of each event into account. As example results, the simulated waveforms at the closest epicentral distance was compared with the observed ones. The agreement between the calculated and observed waveforms was acceptable for most of events.

In this study, hazard evaluation methodologies were developed for the decay heat removal of a typical sodium-cooled fast reactor in Japan against snow, tornado, wind, volcanic eruption, and forest fire. In addition, probabilistic risk assessment and margin assessment methodologies against snow were developed as well. Snow hazard curves were developed based on the Gumbel and Weibull distributions using historical records of the annual maximum values of snow depth and daily snowfall depth. Wind hazard curves were also evaluated using the maximum wind speed and instantaneous speed. The tornado hazard was evaluated by an excess probability for the wind speed based on the Weibull distribution multiplied by an annual probability of the tornado strike at a target plant. The volcanic eruption hazard was evaluated using geological data and tephra diffusion simulation which indicated tephra layer thickness and tephra diameter. The forest fire hazard was evaluated based on numerical simulation which contributed to creating a response surface of frontal fire intensity and Monte Carlo simulation for excess probability calculation. After developing an event tree and failure probabilities, the snow PRA showed the order of 10/year of core damage frequency. Event sequence assessment methodology was also developed based on plant dynamics analysis coupled with continuous Markov chain Monte Carlo method in order to apply to the event sequence against snow. Furthermore, this study developed the snow margin assessment methodology that the margin was regarded as the snowfall duration to the decay heat removal failure which was defined as when the snow removal speed was smaller than the snowfall speed.

All of the nuclear power stations of TEPCO had experienced huge external events. One of which is the Niigata-ken Chuetsu-Oki earthquake in 2007 at Kashiwazaki-Kariwa Nuclear Power Station (NPS), and the other is the Great East Japan Earthquake in 2011 at Fukushima Daiichi NPS and Fukushima Daini NPS. Especially, the Fukushima Daiichi Units 1–3 experienced severe accident, since prolonged station blackout (SBO) and loss of ultimate heat sink (LUHS) were induced by the huge tsunami which was generated by the Great East Japan Earthquake. The most important lesson learned was that the defense-in-depth for external event was insufficient. Therefore, we are implementing many safety enhancement measures for tsunami in our Kashiwazaki-Kariwa Nuclear Power Station. Thus, in order to confirm the effectiveness of these safety enhancement measures, TEPCO performed tsunami PRA studies. The studies were conducted in accordance with “The Standard of Tsunami Probabilistic Risk Assessment (PRA) for nuclear power plants” [1] established by the Atomic Energy Society of Japan. TEPCO conducted two state (the state before the implementation of accident management (AM) measures and the state at the present) evaluations to confirm the effectiveness of the safety enhancement measures. In this evaluation, TEPCO were able to confirm the effectiveness of safety enhancement measures carried out towards plant vulnerabilities that were found before these measures were implemented.