Research Results Expected

There are four achievement points of this project (A to D).

① Data on inundation calculation for torrential rain, storm surge, and tsunami that take the variability of climate change and crustal movement into consideration
Based on the occurrence probability distribution for attributes of typhoons that struck the Japanese archipelago and surrounding areas, we performed calculations with Monte Carlo simulation. Using this typhoon model, we calculated tens of thousands of typhoons, and implemented prediction for storm surge inundation. Similarly, for earthquakes, we obtained the scaling rule for earthquakes, ran tens of thousands of cases for which the parameters necessary for the probability tsunami model are estimated based on moment magnitude, and calculated inundation. At this time, calculations have been performed for protective structures according to the level of damage.
② Experimental data and existing disaster data to evaluate vulnerability in protective structures, evacuation routes, buildings, etc.
We installed a device to generate water flow with quick-opening date and a backflow generator (combined, we refer to these devices as “coastal disaster re-creation tanks” hereafter) that allow scaling of tests on human behavior during disasters and of the vulnerability of protective structures, etc., from the actual size to approximately 1/20. Test results from these tanks are stored in the coastal disaster prevention platform. Many formats of disaster mechanism that cannot be handled with existing experimental data and disaster data, as well as fragility, were examined, and such data were accumulated. Furthermore, by combining these data with a coastal disaster prevention VR system that is an addition to the coastal disaster re-creation tanks, we measured human behavior during disasters, and a database was built.
③ Evacuation behavior data during water disaster and questionnaire data
From a large-scale questionnaire, data of residents in regard to evacuation behavior during a water disaster, as well as evacuation behavior data, were collected, quantified, and patterned, to prepare a model.
④ Law and legal precedence on disasters
In past trials on disasters, it was assumed that a certain percentage of people would be affected by a disaster. Therefore, the kinds of lawsuits and results were gathered and put into database, and a system was designed as a regulation.
⑤ Population prediction and associated activity prediction data for the area at risk of inundation
Considering population, we improved the disaster prediction method. In the past method, predictions of disasters including population were not examined; therefore, we prepared a model on this subject. In addition, we prepared prediction data from simulation of activities in the areas at risk of inundation.
We prepared a database of information gathered with the above perspectives (1 to 5), and built a platform that can be browsed, updated, and corrected.

    When the big data of the developed coastal disaster prevention platform, precipitation data, tsunami observation data, etc. were used, including the evacuation start time and locations, there were multiple solutions for evacuation routes. To select the optimal solution, we developed a smart evacuation guiding system.
Specifically, it is a system that uses data obtained from the coastal disaster prevention platform to prepare a risk map of evacuation routes, add the behavioral patterns of humans, and show when, where, and which route to take to evacuate based on actual observation data. Depending on the situation, the system may be offline; thus, measures against such situations were also examined. These systems will be able to show the safer route in addition to likely evacuation locations of families and friends by incorporating the situations of other people.

   At present, the height of a breakwater is meant to withstand a 100-year disaster. Its main objective is to reduce damage to the areas at risk of inundation, provide time for evacuation, and protect sustainable town buildings and human lives. Some residents feel that planners decide the height on their own, making it difficult to reach consensus around decision making. Therefore, we developed a system that can present multiple alternatives for urban design by using the coastal disaster prevention platform data and computers.
Specifically, we built a system that is able to generate disaster-resistant urban designs with computers that include the rate of damage to structures in response to the inundation rate by the storm surge and tsunami, the disaster rate based on evacuation simulation, the height of the breakwater based on regulations, limit to roads and evacuation shelters, and population prediction (generative design system). This system presents multiple urban designs, with which government and residents can reach a consensus.

    By incorporating information (data) from across the world into the coastal disaster prevention platform, smart evacuation guiding system and a generative design system for urban design can be applied to coastal cities around the world. Through such international development, smart technology for disaster prevention and mitigation for infrastructure can be widely distributed.