The 155th R-CCS Cafe－part I
Date and Time: Fri. Dec. 7, 2018, 13:00 - 14:00
Place: Lecture Hall (6th floor) at R-CCS
Title: Applying HPC to mitigate disaster damage by developing and integrating advanced computational science
Speaker: Satoru Oishi (Team Lader, Computational Disaster Mitigation and Reduction Research Team)
Presentation Language: English
Presentation Material: English
Computational Disaster Mitigation and Reduction Research Team is aimed at developing advanced large-scale numerical simulation of natural disasters such as earthquake, tsunami, flood and inundation, for Kobe City and other urban areas in Hyogo Prefecture. Oishi team integrates geo hazards, water hazards and related hazards. Demand for natural disaster simulations became increasing because disasters frequently take place. Therefore, we are developing appropriate sets of computer programs which meet the demand of calculations. Computational Disaster Mitigation and Reduction Research Team is dealing with the following three kinds of research topics. Urban model development: Research for urban hazards requires urban models which represent structure and shape of cities in numerical form. However, it takes very long time to develop urban models consisting of buildings, foundations and infrastructures like bridges, ports and roads. Therefore, it is indispensable to invent methods which automatically construct urban models from exiting data that is basically ill-structured. Oishi team developed Data Processing Platform (DPP) for such purpose. By using DPP, construction of a national-wide urban model and 3D model construction from engineering drawings are achieved. Recently, Oishi team has a couple of big collaborative researches with Hanshin Expressway Co. Ltd. and National Institute for Land and Infrastructure Management (MLIT). Three dimensional bridge model for programming code will be generated automatically from paper-based engineering drawings or 2D CAD so that Oishi team can simulate the seismic response of the entire network with high fidelity models. Since paper-based engineering drawings include errors and lack of information, it is hopeless to perform a robust model construction by merely extracting information from engineering drawings. To tackle with this problem, Oishi team have developed a template-based methodology. Developing particle methods for landslide simulation using FDPS: Conventional mesh-based numerical methods, such as finite element method (FEM) and finite difference method (FDM) have difficulty to simulate the large deformations, the evolution and break-down of the traction-free-surfaces during a landslide process. On the other hand, meshfree methods, such as smoothed particle hydrodynamics (SPH), and moving particle semi-implicit method (MPS), are regarded as promising candidates for landslide simulations. Using a framework of developing parallel particle simulation code (FDPS), we try to develop a large-scale simulation code for landslide simulation. Since FDPS provides those common routines needed for parallelizing a general particle method, we can focus on the numerical schemes and the mechanisms of landslides. In this talk, we present an improvement of a mathematical reformulation of MPS (iMRMPS). This iMRMPS shows no deterioration of accuracy and convergence for randomly distributed particles, outperforming most conventional particles methods. Water related disaster: Frequency of water disaster has increased. Not only water itself but also sediment cause damage to residents and their assets. Understanding possible hazards is necessary for a measure of precaution and making less damage. Therefore, Oishi team started to deal with water and sediment related disasters by making numerical simulation model for river basins in Kobe city and Hyogo prefecture. Estimation of a damage of sediment-related disaster accompanied with flood, inundation, and sediment supply due to landslides is important to establish a prevention plan. Oishi team has developed a 2D Distributed Rainfall and Sediment Runoff/Inundation Simulator (DRSRIS) with coupling the 2D rainfall runoff model, inundation flow model , and sediment transport model on the staggered grid which performs on the supercomputer.