Modeling and Simulation of Hot Mudflow Movement Prediction Using Cellular Automata

Abstract

Prediction model is needed for reducing mudflow disaster impact. We assume that mudflow has similar characteristic with fluid dynamic model. Therefore we adopt dynamical model of fluid to build hot mudflow movement model. The general parameters of this model are landscape data, mud volume per-day, and obstacle such as dikes and buildings. In this research we use approximation model using cellular automata to create a novel model for mudflow movement that is simple and powerful model to simulate dynamical model of fluid flow. The important properties in our model as Cellular Automata model are neighbor definition and rules. We use 8 neighbor cells and moment with Gaussian function. Cellular Automata rules are built with landscape data and obstacle data. The simulation result is visualization of mudflow movement as fluid movement that depends on dynamical model characteristics