Researchers develop tools to predict the dispersal of chemical plumes, pollutants | 8/21/2018 | Staff
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On April 4, 2017, the town of Khan Sheikhoun in northwest Syria experienced one of the worst chemical attacks in recent history. A plume of sarin gas spread more than 10 kilometers (about six miles), carried by buoyant turbulence, killing more than 80 people and injuring hundreds.

Horrified by the attack, but also inspired to do something useful, Kiran Bhaganagar, professor of mechanical engineering at The University of Texas at San Antonio, and her team from Laboratory of Turbulence Sensing and Intelligence Systems, used computer models to replicate the dispersal of the chemical gas. Results were published in Natural Hazards in May 2017. The accuracy of her simulations showed the ability to capture real world conditions despite a scarcity of information.

Attack - Questions - Direction - Bhaganagar - Evacuations

"If there is a sudden a chemical attack, questions that are important are: 'how far does it go' and 'what direction does it go,'" Bhaganagar said. "This is critical for evacuations."

Bhaganagar's research is supported by the U.S. Department of Army Edgewood Chemical and Biological Center (ECBC), who hope to adopt her models to assist in the case of an attack on American soil.

Chemicals - Agents - Sarin - Gas - Exhaust

Chemicals, whether toxic agents like sarin gas or exhaust from vehicles, travel differently from other particulates in the atmosphere. Like wildfires, which can move incredibly fast, chemicals create their own micro-conditions, depending on the density of the material and how it mixes with the atmosphere. This phenomenon is known as buoyant turbulence and it leads to notable differences in how chemicals travel during the day or at night, and during different seasons.

"In the nighttime and early morning, even when you have calm winds, the gradients are very sharp, which means chemicals travel faster," Bhaganagar explained.

Turbulence - Model - Predict - Range - Scales

Even ordinary turbulence is difficult to mathematically model and predict. It functions on a range of scales, each interacting with the others, and disperses energy...
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