Nav: Home

Army scientists create new technique for modeling turbulence in the atmosphere

August 07, 2018

Army researchers have designed a computer model that more effectively calculates the behavior of atmospheric turbulence in complex environments, including cities, forests, deserts and mountainous regions.

This new technology could allow Soldiers to predict weather patterns sooner using the computers at hand and more effectively assess flight conditions for aerial vehicles on the battlefield.

Turbulence may be invisible to the naked eye, it is always present around us in the air in the form of chaotic changes in velocity and pressure.

Traditional computational fluid dynamics methods of analyzing atmospheric turbulence treat the fluid as a continuum, solving the nonlinear Navier-Stokes differential equations that are involved.

However, calculating the turbulence in the planetary boundary layer, the lowest layer of the atmosphere, can be difficult due to how the presence of trees, tall buildings and other aspects of the landscape directly influences its behavior.

TCFD methods must account for all effects of the neighboring points surrounding the target, which creates an immense computational load that is very difficult to implement efficiently on modern parallel architectures, such as Graphics Processing Unit accelerators.

As a result, these methods often face challenges when confronted with more intricate environments due to limitations in treating complex surface boundaries.

In an attempt to search for an alternative approach, a team of U.S. Army Research Laboratory scientists led by Dr. Yansen Wang turned to the field of statistical mechanics for ideas.

What they found was the Lattice-Boltzmann method, a technique used by physicists and engineers to predict fluid behavior on a very small scale.

"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."

Unlike TCFD methods, the LBM treats the fluid like a collection of particles instead of a continuum and has been widely used in fluid simulation to accurately portray fluid dynamics.

Wang and his team determined that this new approach could accurately model atmospheric turbulence while requiring much less computation than if they had solved for the NS differential equations.

This fundamental change essentially allowed them to disregard a huge chunk of the neighboring points on the grid model, cutting the number of neighboring behaviors to account for and significantly lessening the computational load.

As a result of their investigation, the researchers used the newly developed multi-relaxation-time Lattice-Boltzmann method to create an advanced Atmospheric Boundary Layer Environment model, which specifically treated highly turbulent flow in complex and urban domains.

This marks the first time that an advanced MRT-LBM model has been used to model the atmosphere.

The newly developed ABLE-LBM model paves the way for a highly-versatile approach to atmospheric boundary layer flow prediction.

In addition to providing faster operating speed and simpler complex boundary implementation, this approach is intrinsically parallel and thus compatible with modern parallel architectures, making it a potentially viable modeling method on tactical compute platforms for the U.S. military.

"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."

The development of the ABLE-LBM model has significant ramifications on many other aspects of Army operations besides weather forecast.

Atmospheric turbulence can significantly affect the behavior of optic and acoustic waves, which directly impact what Soldiers can see and hear.

It can act as an important factor in reconnaissance and change the path that a laser travels or how sounds are emitted from a system.

Small unmanned aerial systems are also at the mercy of turbulence vortices, which can occur when a gust of wind hits a building.

Knowing how the turbulence will behave can help sUAS avoid collisions and even take advantage of existing updrafts to fly without their propellers to save energy.

Potential applications can also be found outside the military in civilian life.

Better knowledge of boundary layer turbulence can assist in civil planning in both preparation and emergency response when dealing with chemical spills, industrial fires and other man-made or natural disasters.

"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."
Details of this breakthrough are described in the paper, "Simulation of stratified flows over a ridge using a lattice-Boltzmann model" by Yansen Wang, Benjamin T. MacCall, Christopher M. Hocut, Xiping Zeng and Harindra J. S. Fernando in the journal Environmental Fluid Mechanics (available online at

The results and methodology of ABLE-LBM were presented at the American Meteorological Society Mountain Meteorology Conference June 29 in Santa Fe, New Mexico.

The U.S. Army Research Laboratory is part of the U.S. Army Research, Development and Engineering Command, which has the mission to ensure decisive overmatch for unified land operations to empower the Army, the joint warfighter and our nation. RDECOM is a major subordinate command of the U.S. Army Materiel Command.

U.S. Army Research Laboratory

Related Behavior Articles:

Religious devotion as predictor of behavior
'Religious Devotion and Extrinsic Religiosity Affect In-group Altruism and Out-group Hostility Oppositely in Rural Jamaica,' suggests that a sincere belief in God -- religious devotion -- is unrelated to feelings of prejudice.
Brain stimulation influences honest behavior
Researchers at the University of Zurich have identified the brain mechanism that governs decisions between honesty and self-interest.
Brain pattern flexibility and behavior
The scientists analyzed an extensive data set of brain region connectivity from the NIH-funded Human Connectome Project (HCP) which is mapping neural connections in the brain and makes its data publicly available.
Butterflies: Agonistic display or courtship behavior?
A study shows that contests of butterflies occur only as erroneous courtships between sexually active males that are unable to distinguish the sex of the other butterflies.
Sedentary behavior associated with diabetic retinopathy
In a study published online by JAMA Ophthalmology, Paul D.
Curiosity has the power to change behavior for the better
Curiosity could be an effective tool to entice people into making smarter and sometimes healthier decisions, according to research presented at the annual convention of the American Psychological Association.
Campgrounds alter jay behavior
Anyone who's gone camping has seen birds foraging for picnic crumbs, and according to new research in The Condor: Ornithological Applications, the availability of food in campgrounds significantly alters jays' behavior and may even change how they interact with other bird species.
A new tool for forecasting the behavior of the microbiome
A team of investigators from Brigham and Women's Hospital and the University of Massachusetts have developed a suite of computer algorithms that can accurately predict the behavior of the microbiome -- the vast collection of microbes living on and inside the human body.
Is risk-taking behavior contagious?
Why do we sometimes decide to take risks and other times choose to play it safe?
Neural connectivity dictates altruistic behavior
A new study suggests that the specific alignment of neural networks in the brain dictates whether a person's altruism was motivated by selfish or altruistic behavior.

Related Behavior Reading:

Best Science Podcasts 2019

We have hand picked the best science podcasts for 2019. Sit back and enjoy new science podcasts updated daily from your favorite science news services and scientists.
Now Playing: TED Radio Hour

Do animals grieve? Do they have language or consciousness? For a long time, scientists resisted the urge to look for human qualities in animals. This hour, TED speakers explore how that is changing. Guests include biological anthropologist Barbara King, dolphin researcher Denise Herzing, primatologist Frans de Waal, and ecologist Carl Safina.
Now Playing: Science for the People

#532 A Class Conversation
This week we take a look at the sociology of class. What factors create and impact class? How do we try and study it? How does class play out differently in different countries like the US and the UK? How does it impact the political system? We talk with Daniel Laurison, Assistant Professor of Sociology at Swarthmore College and coauthor of the book "The Class Ceiling: Why it Pays to be Privileged", about class and its impacts on people and our systems.