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Unmanned Aerial Vehicles for Measuring Atmospheric Turbulence with Sean Bailey

January 14, 2020

Sean Bailey, associate professor in the Department of Mechanical Engineering, joined the UK College of Engineering faculty in 2010 after receiving his Ph.D. From the University of Ottawa and subsequently completing his postdoctoral work at Princeton University. In this interview, he discusses the advantages of using unmanned aerial vehicles to measure atmospheric conditions, his various projects that use UAVs and how UAVs may prove vital in the event of an airborne disaster. 

By Kel Hahn

You’re an investigator on multiple research projects involving several collaborators. What is the overarching research area that links these projects?

I would say that the common thread in my research is the experimental investigation of turbulent flows. However, recently we’ve been developing unmanned aerial vehicles (UAVs) for measurements of atmospheric turbulence. We have a few different projects in progress, but many of them now center on using these UAVs to perform our measurements.  

Why UAVs?

Our work with UAVs during the Great American Eclipse in 2017 is a good example of the kind of benefits you can get by using these vehicles. We were able to take four UAVs, three fixed-wing aircraft and a rotorcraft, to Russellville, Kentucky, which was in the path of the eclipse’s totality. We equipped them with sensors that measure pressure, temperature, humidity and wind speed and tracked what changes occurred in the lowest 100 meters of the atmosphere due to the eclipse. People have made observations at much higher altitudes and also at the ground level, but not in the lowest 100 meters of the atmosphere like we did. However, this region was where the most significant impact of the eclipse on the atmosphere occurs. As a result, we were able to directly observe very dynamic behavior that previous researchers had only hypothesized might occur.

You’re involved in work related to the emerging field of precision meteorology. What is precision meteorology, and what need does it meet? 

Over the years, we’ve developed capabilities to measure in-atmospheric flows using UAVs. A lot of that work is aimed at improving our understanding of micrometeorology. We are partnering with scientists who conduct simulations of meteorological flows on a much more local scale to help them better predict subtle changes that might be caused by topology and terrain features that aren’t captured in large-scale weather predictions.  What actually happens in valleys, for example, is often different from what was predicted for the region. These subtle differences can have big impact on things like fog formation or ice accumulation that can impact road and aviation safety.

How are you using UAVs to improve the field?

We’re currently collaborating with NASA and a company called Stratodynamics by using UAVs to develop sensors for identifying turbulence in the stratosphere. Ultimately, we’d like to build technology that aircraft can use to detect and avoid turbulence.

High-altitude measurements of the atmosphere are typically done using weather balloons. These are called radiosonde measurements. However, although these sorts of measurements are valuable for feeding information into weather models, they don’t have the detail we need for what we’d like to do.

Stratodynamics has developed technology that lets them put a UAV in the form of a glider on a weather balloon and release it. When the balloon bursts or gets to a predetermined altitude, the UAV will descend, recording measurements all the way down. You get a lot more detail on the way down than you do going up because the rate of descent is slower than the rate of ascent. 

We’re going to take a balloon up to 100,000 feet, which is roughly the lower limit of the stratosphere, and test our turbulence-sensing technology as it comes down. We’re using some of our sensors that we’ve used for the lower-atmosphere, and NASA will add their sensors. Then, we’ll fuse the data together to see if we can get a better picture of what’s going on in that space.

How collaborative is your research?

I do a lot of collaborating. One of my other projects is a $1.2 million National Science Foundation project with Jesse Hoagg and Alexandre Martin from the Department of Mechanical Engineering and Michael Sama from the Department of Biosystems and Agricultural Engineering. Dr. Hoagg is a lead investigator on that project. We’re collaborating on developing a system able to conduct real-time simulations of chemical plumes.

Can you give an example of where such simulations would be needed?

The Fukushima Daiichi nuclear disaster in 2011 and the Aliso Canyon natural gas leak in 2015 were situations where invisible toxins were released into the air. In such emergencies, you want to know where the contaminant is moving so you can evacuate people in harm’s way. But it’s difficult to make accurate predictions because you have changing wind conditions, atmospheric turbulence and a variety of terrain.

How can UAVs help?

We can use UAVs to take measurements in the atmosphere, feed the data into a simulation and adapt the simulation based on the experimental data to provide a more realistic map. With a better picture, we can fly the aircraft with the contaminant to provide continual feedback on the plume dispersion. Then first responders can determine more precisely where to evacuate. 

One of the things we’re working on for this project is getting real-time feedback from the aircraft to the ground. Right now, we measure and log all the data as we fly, but then there’s a lot of post-processing that we have to do after the flight. Especially in an emergency, we need to be able to do that post-processing in-flight and quickly retrieve the information. That involves a lot of computation. That’s really the next big step for us.

Are there any drawbacks to using UAVs?

As with any measurement technology, there are drawbacks. A big one is that we’re really only getting measurements where the UAV actually is. Another one is that UAVs can have limitations in terms of flight time and the type of weather in which they can fly. We’re continually working to address these drawbacks. In the past few years, we’ve been able to quadruple the flight time of our UAVs and by flying several aircraft at once, we’re improving the spatial distribution of our measurements. This includes working with Dr. Hoagg to develop formation flying capabilities that will let us better control the relative spacing between our measurements. We’re also continually working on our sensors to improve the quality and quantity of the data we can acquire. 

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