The author here shares his vision of next-generation models for seismic soil-structure interaction (SSI) analysis. These models should combine reasonable considerations of wave effects in half-infinite soil with a correct representation of nonlinearity in the structure, and in both the so-called near field, i.e., in that part of soil near a base mat, and in the soil-structure contact surface. The far field, i.e., all of the soil except for the near field, is treated as a linear horizontally layered medium, as is currently done in the well-known program SASSI. The importance of considering nonlinear effects even in very stiff structures like NPPs was shown by the March 2011 Great East Japan Earthquake that hit northeastern Japan’s Pacific coast. Although the idea of calculating SSI wave effects in the time domain has been around for several decades ago, current NPP design practices are linear. Next-generation SSI models should enable practical time-domain analysis. The author suggests a road map – the sequence of problems to be solved to achieve a proposed level. Some of these problems have already been solved, at least in principle, but other solutions are yet to be found. The author describes the current status of his research and ideas about implementing modern computational techniques such as parallel computation.

During the last fifty years, the city of Lima has experienced an immigration process that has led to the urbanization of the Andean foothills surrounding the capital. With the aim of analyzing the dynamic response of these new populated places, a target area in a district called Independencia is chosen. Seven microtremor array measurements are carried out at different points on the flat level and along the slope in order to evaluate the variation in the depth of the bedrock. In addition, a seismometer is installed on the slope with the objective of determining if amplification due to topography exists in the area of study.

The present study examines how post-disaster local collaboration towards effective power savings was accomplished in the summer of 2012 at the household level in the Japanese cities in Yokohama and Kawasaki following a major earthquake. A framework was developed to evaluate the local communities’ capacity for stakeholder collaboration. Results of a survey were analysed statistically to determine the emergence of citizens’ voluntary information sharing, as well as the effects of a local governmental campaign and power-saving education at the workplace, on actual power-saving practices at the household level by local residents. Proactive citizens shared the relevant information and adopted effective and enduring power-saving practices. Some citizens were also responsive to the call for power saving by local government and adopted effective power-saving practices. The residential power-saving education at the workplace was shown to have resulted in more effective and rational power-saving practices being carried out at the household level.

Public fire insurance has recently appeared in China. The basis for calculating the premium is the accurate measurement of Publicliability risk in fire. The generalized linear model (GLM) is widely used for measuring this risk in practice, but the GLM often cannot be satisfied, especially in fat-tailed distribution. A nonparametric Gaussian kernel linear model used to improve the GLM is applied to measure publicliability risk in fire, yielding a favorable effect. Results show three major risk factors that were measured precisely – the nature of the industry, the scale of public places and the level of fire precaution.

Natural disasters may cause extreme damage and enormous economic loss. It is important to look for efficient and precise damage prediction models using neural networks, which are increasingly used in many applications. One challenge of developing such a damage prediction model is its limited amount of available data. We therefore chose to predict typhoon damage loss based on a general regression neural network (GRNN). The GRNN is able to converge to kernel functions of data with limited training samples available. This paper investigates a GRNN-based neural network and introduces a loss prediction index. The proposed GRNN structure gives an improved prediction performance with a normalized mean squared error of 0.0071 and a correlation of 0.9321. According to prediction results of economic loss, 30 typhoons have been grouped into five categories by hierarchical cluster analysis. Due to its simplicity and fast-converging features, this scheme is suitable for practical, simple but robust typhoon damage prediction.

The characteristics of secular changes in M₂ tidal amplitude in the East China Sea and the effect of projected sea level rise on tide amplitude were studied. Based on measurement data analysis, it was clarified that rapid sea level rise and M₂ tidal amplitude decrease had been observed at observatories that face the East China Sea around 1998. The change in M₂ tidal amplitude of the East China Sea by sea level rise was then studied in numerical experiments. And results showed that tidal amplitude increased on the west coast of the Korean Peninsula and the Taiwan Strait. A similar study was conducted for the Yatsushiro Sea and the Ariake Sea, which showed the highest M₂ tidal amplitude in Japan. As a result, it was found that M₂ tidal amplitude increased in the whole bays, which was against resonance tide theory. It was shown that mean sea level rise and M₂ tidal amplitude increase and decrease affected by sea level rise must be considered when predicting the risk of seashore disaster by global warming.

Floods in Bangladesh are often so catastrophic that they inflict substantial damage to the nation’s agriculture-based economy. To reduce this vulnerability, it is imperative to establish an effective flood early warning system across the country. There are too many urgent and complex issues about early flood warning activities in Bangladesh, however, and flood management is relatively complex, with several types of authorities currently involved in the effort. It is therefore necessary for stakeholders to create a National Road Map that offers future directions toward flood risk management. Issues prioritized by quantitative ranking in the implementation of an effective flood early warning must be identified on the National Road Map. In order to comprehensively prioritize listed interventions that are issues requiring improvement, two types of questionnaire were conducted. Next, multi-criteria analysis (MCA) and the analytic hierarchy process (AHP) strength, weakness, opportunity and threat (SWOT) were applied to survey results derived from pair-wise comparison, and both types of results were combined. Interventions with the highest priority in each cascade were identified based on quantitative importance. To ensure consistency among stakeholders, a fuzzy AHP was applied to each cascade. As a result, the most important and urgent interventions that contributed to creating a National Road Map were identified by integrated decision-making and new quantitative decision-making was shown by integrating MCA and AHP-SWOT.

Flood risk assessment should be one of the basic methods for disaster damage mitigation to identify and estimate potential damage before disasters and to provide appropriate information for countermeasures. Existing methods usually do not account for uncertainty in risk assessment results. The concept of uncertainty is especially important for developing countries where risk assessment results may often be unreliable due to inadequate and poor quality data. We focus on three questions concerning risk assessment results in this study: a) How much does lack of data in developing countries influence flood risk assessment results? b) Which data most influence the results? and c) Which data should be prioritized in data collection to improve risk assessment effectiveness? We found the largest uncertainty in the damage data among observation, model, and agricultural damage calculations. We conclude that reliable disaster damage data collection must be emphasized to obtain reliable flood risk assessment results and prevent uncertainty where possible. We propose actions to improve assessment task efficiency and investment effectiveness for developing countries.

Concerns are growing against the increasing strength of typhoons, the increasing severity of damage caused by floods and storm surges, the increased incidence of landslide damage, the increasing risk of drought, etc., attributed to the effect of global warming. As natural disaster hazard attributed to climate change intensifies drastically, the capacity to prevent disaster is weakening due to degrading infrastructure and an aging population, with a large gap beginning to appear between the two. We have not sufficiently understood such disasters brought by intensifying natural disaster hazards, and in fact may constitute a greater threat than we can imagine. Focusing on the dry dam as a flood control measure that can coexist with the environment, this study discusses new functions of the dry dam and new ways to employ it in coordination with conventional dams, proposing these measures as an effective adaptation against flood and sedimentation disasters that will continue to intensify in the future.

Two torrential downpours hit Amami-Ohshima Island in 2010 and 2011 and affected the administration of chronic dialysis treatments. The 2010 Amami Torrential Downpour in particular created communication and transportation breakdown. The communication blackout, which affected the emergency communication system of the local administrative damage control organization, hindered contact between dialysis centers and patients. The disrupted patient transfer system forced local and national government to take emergency measures and provide rescue services. The 2011 Amami South Area Torrential Downpour caused similar problems. The reallocation of patients and the adaptation of dialysis schedules appeared to solve the transportation problems. The use of a satellite phone was suggested to resolve the communication problem. New psychiatric complications were also identified. Local dialysis disaster relief should be established in advance in disaster-prone areas. Lessons learned from various disasters should translate into better preparedness.