Student Paper Competition: Modeling the Effects of Aircraft Noise

The noise from aircraft can have numerous unwanted effects on bystanders on the ground; a major question in noise research is how to reduce aircraft noise effectively and economically. In this episode, we interview Jiacheng Hou, one of the winners of the POMA Student Paper Competition from the 182nd meeting of the ASA, about his research regarding the numerical modeling of airplane noise around buildings.

Associated paper: Hou, Jiacheng and   Zheng, Zhongquan Charlie. Simulation of near-ground signals from a flying source on UAV over a building structure. Proc. Mtgs. Acoust. 46, 045004 (2022); https://doi.org/10.1121/2.0001604

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Music Credit: Min 2019 by minwbu from Pixabay. https://pixabay.com/?utm_source=link-attribution&utm_medium=referral&utm_campaign=music&utm_content=1022

Transcript

Kat Setzer (KS)

00:06

Welcome to Across Acoustics, the official podcast of the Acoustical Society of America’s Publications office. On this podcast, we will highlight research from our four publications, The Journal of the Acoustical Society of America, also known as JASA, JASA Express Letters, Proceedings of Meetings on Acoustics, also known as POMA, and Acoustics Today. I'm your host, Kat Setzer, Editorial Associate for the ASA.

Today we'll be talking to Jiacheng Hou about his article, “Simulation of near-ground signals from a flying source on UAV over a building structure,” which appeared in the 46th volume of the Proceedings of Meetings on Acoustics and was one of five winners of the POMA Student Paper Competition for the 182nd meeting of the Acoustical Society of America, which took place this past May in Denver, Colorado. This episode is part of a five-episode series highlighting winners of the POMA Student Paper Competition. So Jiacheng, congratulations, and thanks for chatting with me today. How are you?

Jiacheng Hou (JH)

01:05

Great, how are you?

KS

01:08

I'm good. Thanks. So first, tell us a bit about yourself. Where are you studying? And what do you research?

JH

01:15

I'm Jiacheng Hou, a PhD student from Utah State University. My research aims to use numerical methods to solve practical acoustic problems, including room acoustics, underwater acoustics, and physical acoustics.

KS

01:29

Okay, so your research ties into aircraft noise and how it affects folks on the ground near where the aircraft is flying over. Can you give us a bit of background about this area of research?

JH

01:39

Yes, modern transportation is becoming one of the major noise sources in our daily life. Amongst those noises, the low-frequency sound generated by aircraft could increase the risk for a wide range of exposure effects of people living near airports. There are also reports showing those effects among wild and domestic animals. Hence, there is an increasing need to understand, predict, and reduce the near-ground noise source signal from aircraft. We want to build a numerical solver that can simulate the sound signal from the flying-over aircraft over complicated geometries and provide a fast, precise prediction of the signal. Eventually, we want to find a way to reduce noise from aircraft effectively and economically.

KS

02:22

Yeah, that makes sense, wanting to reduce noise from aircraft to folks on the ground. So your goal with this research was to build a numerical model to simulate and predict a moving acoustic source in a real physical domain. How did you go about doing that?

JH

02:37

So, we first determined a set of partial differential equations to describe the wave propagation in the air and in the porous medium, so that we can solve for acoustic pressure and velocity based on those equations. The porous medium will be used to model a house later in this study. Porous medium or porous material is a material that contains pores or voids, for example, sponge. The wood in the typical house can also be seen as a porous material. We then use the finite-difference time-domain method to solve for this linearized partial differential equation set. The concept of the finite-difference time-domain method is using a finitely small difference in time and space, instead of an infinitely small differential, to solve for this equation set. The good thing about doing so is that this method makes the partial differential equations become a linear equation system. Next, we use the immerse boundary method for material change at the interface, since we want to add a house in our computational domain. The concept of the immersed boundary method is to add some so-called fictitious term into the equation sets that can switch equations from air and porous medium at the interface. By doing so, we can keep a simple Cartesian grid mesh while having a complicated grid geometry in our simulation. Finally, we used perfectly matched layers on boundaries excluding the ground for an artificially infinitely large domain.

KS

04:02

So tell us a bit about the methods you based your model on.

JH

04:06

So we first look at an unmanned aerial vehicle, or UAV, with a loudspeaker on it playing low-frequency sound to model a real aircraft flying over. This means we focused on a low-speed sound source as our starting point. In the simulations, we modeled the UAV as a point source, where we added a continuous source term to the equations as a multiplication of a moving Gaussian pulse and a summation of sinusoidal wave functions so that we can run one simulation and get results in numerous frequencies. This source acts very much like a siren, but they will cover a broadband frequency instead of just that annoying high frequency. The ground was set as acoustically rigid, and the other boundary were perfectly matched layers. In other words, we modeled this problem as a point source moving 11 meters above the ground in an open field. Since we want to know the effect on human beings, the receiver was set as two meters above the ground, which is a little bit closer to human ear height.

KS

05:14

Okay, so that all makes sense. How did you use simulations to test your model?

JH

05:18

So we tested several cases and compared them with existing analytical solutions first. The first one is the Doppler effect in free space, which is the shift in frequency of the wave from the source due to the relative movement of the source and the receiver. Next, we compared it with the ground effect, which is the source moving above flat ground. The ground effect is when a receiver is not exactly attached to the ground, this receiver will get two signals; one is directly from the source and the other is from the reflection of the ground. This will cause cancellation and enhancement of the sound at certain frequencies based on relative location of the source, receiver, and the ground. If the source is moving, those frequencies will be changed with time since the relative location of the source are moving. We call lines in the spectrogram that the sound cancelled out as destructive lines. A typically destructive line looks like a reverse parabolic line in a spectrogram plot with frequency versus time, which means when the source is far away, high-frequency noise is canceled, and the low-frequency noise will be reduced if the source is moving closer to the receiver. After the comparisons between the, from the analytical solutions, we then simulate some more complicated cases with a house in a computational domain involving two dimensions and three dimensions. In a 3d case, instead of moving above ground, the source is moving 11 meters south of the house. We then looked at how the location of the receiver relative to the house affects the destructive lines, namely a receiver on the source facade parallel to the UAV paths and the receiver on the east facade facing the UAV moving direction.

KS

07:10

So did your numerical solver end up working? What did you find?

JH

07:13

The good news is yes, our simulation matched up very nicely with the analytical solution of both Doppler effect and ground effect. Doppler effect was found in every single moving case, and the ground effect was matched with the mathematical expression given by previous literature for flat ground. And for the two-dimensional house cases, destructive lines were pretty close to the flat ground ones before UAV passed the house and it became a straight line after the UAV passed. 

The 3d house case was more interesting. The south facade receiver, which was parallel to the paths of the UAV and has had no blockage between the receiver and the source, had almost identical destructive lines to the flat ground. However, the east facade receiver, which was facing the UAV moving direction, had different spectrogram. The destructive lines were closer to the straight lines when UAV moved closer to the house, and dropped after the UAV passed, showing the opposite behavior of the flat ground case.

KS

08:24

That's super cool. So what is the significance of these findings?

JH

08:27

So our research results could be fundamental to future research to understand behavior of the near-ground signal from a moving source. And by figuring out the destructive lines, we might be able to find some noise-reduction material or device to help people living near the airport, since we now know that we only need to reduce noise at some certain frequencies, and we don't need to look at or ignore the frequency related to destructive lines. Also, these results show the capability of our numerical solver to deal with the material changes, complicated geometries, and moving sources. 

KS

So what are the next steps in your research? 

JH

The next steps in our research are to compare with experimental data and look for different source types because we were focusing on a monopole-type source for now. Another direction is to change acoustically rigid ground into more practical boundary conditions, for example, grassland or mud. We also want to look into the interior of the house and see what the moving effect from the outside to the inside would be.

KS

09:36

Awesome. Well, thanks again for taking the time to speak with me today about your research. It was great to hear a bit about one of the ways mathematical algorithms can be used to simulate real-world problems and their solutions. Good luck with your continued research. And of course, once again, congratulations on winning the award from POMA.

JH

Thank you.

KS

Oh, no problem! 

For any students or mentors listening from around the time this episode is airing we're actually holding another Student Paper Competition for the most recent meeting in Nashville. So, students, if you presented at the national meeting, now's the time to submit your POMA. We're accepting papers from all of the technical areas represented by the ASA. Not only will you get the respect of your peers, you’ll win $300, and perhaps the greatest reward of all, the opportunity to appear on this podcast. And even if you don't win, this is a great opportunity to boost your CV or resume with an editor-reviewed proceedings paper. The deadline is January 8, 2023. We'll include a link to the submission information on the show notes for this episode. 

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