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Mechanical engineer Michael Gollner and his graduate student, Sriram Bharath Hariharan, of the University of California, Berkeley, recently visited NASA’s John H. Glenn Research Center in Cleveland, Ohio. There, they dropped burning objects into a deep pit and studied how fire vortices form in microgravity conditions. The Glenn Center houses a Zero Gravity Research Facility, which includes an experimental drop tower that simulates the experience of being in space.
“You get five seconds of microgravity,” Gollner said. The researchers lit a small paraffin wick to generate swirls of fire and dropped it, studying the flame all the way down.
Experiments like this, presented at the American Physical Society’s 73rd Annual Meeting of Fluid Dynamics, can help fire scientists answer two types of questions. First, they illuminate the ways that fire can burn in zero gravity and can even inform protective measures for astronauts. “If something is burning, it could be a very dangerous situation in space,” Gollner said. Second, it can help researchers better understand the role of gravity in the growth and spread of destructive fires.
The fire burned differently without gravity, Gollner said. The flame was shorter and wider. “We have seen a real slowdown in combustion,” Gollner said. “We haven’t seen the same dramatic eddies we have with ordinary gravity.”
Other researchers, including a team from Los Alamos National Laboratory in New Mexico, have introduced new developments to a computational fluid dynamics model that can incorporate fuels with varying moisture content. Many existing environmental models average the humidity of all fuels in an area, but that approach fails to capture variations found in nature, said chemical engineer Alexander Josephson, a postdoctoral researcher who studies prediction. of the fires in Los Alamos. As a result, these models could provide inaccurate predictions of fire behavior, he said.
“If you’re walking in the forest, you see the wood here and the grass there, and there are many variations,” Josephson said. Dry grasses, wet mosses, and hanging limbs don’t have the same water content and burn in different ways. A fire could evaporate moisture from wet moss, for example, while at the same time consuming drier limbs. ‘We wanted to explore how these fuels interact during the passage of fire.
Los Alamos scientists worked to improve their model called FIRETEC (developed by Rod Linn), collaborating with researchers from the University of Alberta in Canada and the Canadian Forest Service. Their new developments take into account changes in moisture content and other characteristics of simulated fuel types. Canadian Forest Service researcher Ginny Marshall recently began comparing her simulations with real-world data from boreal forests in northern Canada.
During a reaction flow session, Matthew Bonanni, a graduate student in engineer Matthias Ihme’s lab at Stanford University in California, described a new fire propagation model based on a machine learning platform. Predicting where and when fires will burn is a complex process, says Ihme, driven by a complex mix of environmental influences.
The goal of Ihme’s group was to build a tool that was both accurate and fast, capable of being used for risk assessment, early warning systems and the design of mitigation strategies. They built their model on a specialized computer platform called TensorFlow, which was designed by Google researchers to run machine learning applications. As the model trains on more physical data, Ihme said, its simulations of heat build-up and fire propagation dynamics get better and faster.
Ihme said he is thrilled to see what advanced computational tools make for fire prediction. “It was a very empirical area of research, based on physical observations, and our community works on more fundamental problems,” he said. But adding machine learning to the toolbox, he said, shows how algorithms can improve the fidelity of experiments. “This is a really exciting journey,” he said.
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