New Model Helps Soldiers Determine Weather Patterns

U.S. Army scientists developed a new technique that models atmospheric turbulence to help predict weather patterns and assist in planning for flights.

Small, irregular motions in the air is referred to atmospheric turbulence. For those on the ground, it might not seem that important. Plus, it’s virtually invisible, so people can’t see the chaotic velocity and pressure changes. For military and other entities, understanding these bumps in the atmosphere has far-reaching implications.

Atmospheric turbulence impacts optic and acoustic waves, which could be detrimental to soldiers relying on their sight and auditory senses. It can also impact how a laser travels during reconnaissance or how sounds emit from systems. Even unmanned aerial missions can be impacted by turbulence.

Understanding turbulence and the ability to calculate its behavior could literally be life-saving. U.S. Army researchers designed a computer model that can do just that. In essence, this tool could help soldiers predict weather patterns earlier, giving them the ability to better assess potential flying conditions.

Existing methods of analyzing this type of data struggle in calculating turbulence in the lowest layer of the atmosphere because of trees, tall buildings and other aspects of Earth’s landscape. It can be almost impossible to account for every element surrounding a target using these methods.

Led by Dr. Yansen Wang, the Army scientists sought a new method and turned their attention to the possibility of statistical mechanics as a solution. They considered the Lattice-Boltzmann method, which physicists and engineers use to predict small-scale fluid behavior.

ABLE-LBM simulation models the behavior of fine-scale turbulence flows moving over a building. (Image courtesy of CNN/U.S. Army.)

ABLE-LBM simulation models the behavior of fine-scale turbulence flows moving over a building. (Image courtesy of CNN/U.S. Army.)

“The Lattice-Boltzmann method is normally used to predict the evolution of a small volume of turbulence flows, but it has never been used for an area as large as the atmosphere,” Wang said. “When I read about it in a research paper, I thought that it could be applied to not just a small volume of turbulence but also atmospheric turbulence.”

The LBM technique looks at particles as a fluid collection instead of as a continuum. Wang and his team found this approach was a more accurate way to model atmospheric turbulence. An added benefit was that it requires a lot less computation. The result was the creation of the Atmospheric Boundary Layer Environment model, designed specifically for highly turbulent flow in complex and urban domains.

ABLE-LBM models show the behavior of west wind, left, and southwest wind, right. Even a change in wind direction results in different flow and turbulence fields between the simulations. (Image courtesy of U.S. Army.)

ABLE-LBM models show the behavior of west wind, left, and southwest wind, right. Even a change in wind direction results in different flow and turbulence fields between the simulations. (Image courtesy of U.S. Army.)

“On the battlefield, you want atmospheric turbulence data quickly, but you don’t necessarily have any supercomputers on hand,” Wang said. “However, you do have modern computer architecture with thousands of processors that make computing fast if the algorithm is appropriate. With the ABLE-LBM, you can use those modern computer architectures to compute turbulence on the battlefield without having to connect to a high performance computing center.”

This model offers a versatile approach that has the potential to be used in other sectors of the military as well as in the civilian world. Understanding boundary layer turbulence has the potential to enhance civil planning for emergency responses to both man-made and natural disasters such as fires or chemical spills.

“Many people are interested in applying this method in various fields,” Wang said. “This technique has paved a new way to model atmospheric turbulence. Our research was the first to set the path for this new direction, so we have a lot of proving to do.”

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