STUDY OF HEAT DISTRIBUTION PHENOMENON WITH A FIRE SOURCE AGAINST DISTANCE AND TIME IN EXPERIMENT AND SIMULATION

• Main Author: Arya R.B., Dhika
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/71740
• Institution: Institut Teknologi Bandung

A fire is a common phenomena in Indonesia (especially in regions with widespread forest like Borneo island and also Sumatera island) and has generated a lot of attention of all local government, national government, and international government but most especially the locals itself. The main impact of a fire is the emergence of smokes resulted from the fire happened, it has impact on both the well-being of the citizen and all of the ongoing transportation both from and to the island. The author in this final project will create a small-scale simulation to find out fire’s physical parameter and it’s behaviour on how it will affect it’s surrounding based on system-environment model in thermodynamics using a simple module that is able to detect all those physical parameter from fire including; Carbon dioxide content, Temperature, and Humidity. Although both Carbon dioxide content and Humidity is yet to be used, The author managed to acquire the data on how temperature changes over time once the fire sets out. Analysis that has been done shows that there are gradient from the change of temperature over time, which can ultimately be processed and modeled. The data that is acquired through the experiment, will then be given test to determine the validity of the data as well as to analyze the physical phenomenon using Computational Fluid Dynamics (CFD) software. The outcome of this final project is that a fire can be detected through gradient changes that occur when a fire gets closer to the sensor module, which if modeled will be in accordance with polynomial modeling based on the heat diffusion equation. This final project can then be developed into a dataset that will be able to detect fire based on gradient values that depend on the area of fire which occurs using the concept of deep learning.