A 3-dimensional large-scale Fluid-Structure Interaction (FSI) framework is developed for the simulation of strength of the coastal structures to withstand tsunami. One-way coupling is used in this framework. Moving Particle Simulation (MPS) is adopted for fluid computations involving free surface flow and Finite Element Method (FEM) is adopted for structural computations. To achieve high parallel efficiency and reduce development costs, the open parallel source named ADVENTURE_Solid is used as the structural analysis solver and LexADV_EMPS is used as fluid analysis solver. Since our proposed framework combines two different numerical methods: FEM and MPS, and distribution of physical values in their methods are differently expressed; therefore interpolation related to fluid forces on fluid-structure interface is required. Accuracy of the interpolation directly affects reliability of result obtained by the FSI simulation. In this study we propose three interpolation methods and quantitatively evaluate their accuracies by solving a benchmark test case. In addition, using an interpolation method that achieves highest accuracy among the three methods, we perform a large-scale parallel FSI simulation of a nuclear power station subjected to a tsunami wave to demonstrate applicability of our proposed framework.

In order to diminish the network congestion rate and enhance the network performance of ICN (Information-Centric Networking) architecture, especially in the IoT (Internet of Things) era, this research proposes an adaptive congestion control mechanism for the IoT sensor network. Particularly, the proposed system can response the content requests from the consumers by caching an appropriate number of content chunks at the ICN router according to the content popularity and priority levels. We also utilize both content popularity and priority-based ranking delay time for the data transmission from sensors to the data server. The evaluation results show that the proposed architecture with the dynamic control/adaptive mechanism can provide higher network performance efficiency for the future Internet by achieving higher throughput with lower request (Interest) packet drop rate and higher cache hit rate as we increase the number of IoT sensors, then solving the network congestion issue in ICN.