Presentation Title

Image Processing on Flow Visualization of Fire

Faculty Mentor

Marko Princevac

Start Date

17-11-2018 9:45 AM

End Date

17-11-2018 10:00 AM

Location

C304

Session

Oral 2

Type of Presentation

Oral Talk

Subject Area

engineering_computer_science

Abstract

Flow visualization is a major tool that can be used when trying to understand how wildfires behave and spread. Flow visualization allows for important qualitative information on the flow of the fire to be obtained which often quantitative measurements cannot provide. In this project, we used an optical method called Background Oriented Schlieren Photography (BOS) to visually see and understand the convective flow around flames, like the ones in wildfires.The flames induce a convective, buoyancy-driven, flow due to the temperature gradient between the flame and its surroundings. These temperature gradients result in density fluctuations. Based on the Gladstone-Dale Principal, the relation between the refractive index of the fluid and its density is what allows the Background Oriented Schlieren (BOS) system to visualize the fire’s convective flow. After experimentation, Image processing is applied to the BOS recordings of the flames to enhance the frames. Then after running image processing codes, optical flow algorithms are used on BOS recording to see the layers of the density gradient around the flame. This visual density gradients allows for the direction and speed of a flames from one frame to the next to be obtained.

Summary of research results to be presented

This project had two portions the seventy-three experimental trials, from which I helped with twenty-three, that were conducted at a USDA forest service facility off campus and the image processing using python. The experimental setup was supposed to recreate a South Carolina environment and ecosystem during November. The data that was collected will help the department of defense have more knowledge before they conduct their control burns in the forest of South Carolina. We used the BOS technique to help visualize the diffusive flow of wildfires. To enhance the qualitative results of the BOS we performed image and fluid base processing on the video recording to isolate the fire and show how the gradient density would look like around it. I then obtained fluid mechanical properties from the preprocessed image by appling a dense optical flow algorithm called the Gunnar Farneback algorithm.

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Nov 17th, 9:45 AM Nov 17th, 10:00 AM

Image Processing on Flow Visualization of Fire

C304

Flow visualization is a major tool that can be used when trying to understand how wildfires behave and spread. Flow visualization allows for important qualitative information on the flow of the fire to be obtained which often quantitative measurements cannot provide. In this project, we used an optical method called Background Oriented Schlieren Photography (BOS) to visually see and understand the convective flow around flames, like the ones in wildfires.The flames induce a convective, buoyancy-driven, flow due to the temperature gradient between the flame and its surroundings. These temperature gradients result in density fluctuations. Based on the Gladstone-Dale Principal, the relation between the refractive index of the fluid and its density is what allows the Background Oriented Schlieren (BOS) system to visualize the fire’s convective flow. After experimentation, Image processing is applied to the BOS recordings of the flames to enhance the frames. Then after running image processing codes, optical flow algorithms are used on BOS recording to see the layers of the density gradient around the flame. This visual density gradients allows for the direction and speed of a flames from one frame to the next to be obtained.