RQ-7 Shadow UAV Acoustic Analysis: CFD Simulation by Ansys Fluent

Description

Acoustic Analysis: RQ-7 Shadow UAV CFD Simulation Training

Introduction

In RQ-7 Shadow project, we analyze a RQ-7 Shadow UAV acoustically and examine the sources of sound production. We also define receivers around the drone to observe and examine the amount of sound received by the receivers.

The smallest of AAI’s RQ-7 Shadow family of unmanned aircraft systems is the RQ-7 Shadow 200. Targets can be found, recognized, and identified using Shadow 200 up to 125 kilometers away from a tactical center. The device can identify tactical vehicles day or night from a height of 8,000 feet and at a distance of 3.5 kilometers on a slant.

A trailer-mounted pneumatic launcher helps with takeoffs and has the ability to accelerate a 170-kilogram aircraft to 130 km/h in 12 m.

The Tactical Automatic Landing System, which consists of an aircraft-mounted transponder and a ground-based micro-millimeter wavelength radar, directs landings.

An AAI RQ-7 Shadow UAV is modeled in this simulation using ANSYS Fluent software. The device moves at a speed of 36.1 m/s while the propeller rotates at an angular velocity of 3800 rev/min.

The geometry of the present model is two-dimensional and has been designed using Design Modeler software. We do the meshing of the present model with Fluent Meshing software. The mesh type is Polyhedra, and the element number is 5,449,057.

Methodology

The topic of acoustics is a very widely used and interesting topic in computational fluid dynamics. In this topic, we deal with waves and consequently with pressure.

For this project, we have used two models, BroadBand Noise and Ffowcs Williams and Hawkings (FW_H), and we have explained the settings for both models and examined the differences between the two models.

First, we simulated the BroadBand Noise model steady, and after convergence and aerodynamic stability of the problem, we change the solution model to FW_H and perform the solution transient. If we activate the FW_H model from the beginning, we will hardly reach convergence and the solution may even diverge.

In the BroadBand Noise model for RQ-7 Shadow, we extracted the Acoustic pressure level contour in decibels for the blades and in the FW_H model, we defined 7 receivers around the UAV and extracted the following results:

• Acoustic Pressure vs Time: This pressure is actually the acoustic signal calculated from the Ffowcs–Williams–Hawkes (FW–H) equation, which is due to the fluctuations in the flow around the propellers.
• Sound Pressure Level: SPL is the “physical intensity of the produced sound” and is directly proportional to the sound energy, without the interference of the human ear.
• A-Weighted Sound Pressure Level: A-weighting is a filter-like function that simulates the sensitivity of the human ear. Instead of the physical SPL, the sound level in this graph is calculated to represent the “actual loudness perceived by the ear.”
• B-Weighted Sound Pressure Level: The B-weighted filter is weaker than the A-weighted filter and only attenuates a portion of the low frequencies.
• dpdt RMS: The values ​​in this contour indicate the intensity of the time-dependent pressure fluctuations at each point on the surface.

Results

In the BroadBand Noise model for RQ-7 Shadow, we can observe the Acoustic pressure level contour in decibels. Acoustic Power Level actually represents the sound power produced by the entire or part of the surface of an object and is expressed in decibels (dB).

Comparing this contour with the Turbulent intensity contour, we find the similarity between them. In reality, the Acoustic pressure level is calculated and displayed based on the Turbulent Intensity. Therefore, wherever the Turbulent intensity is high, the acoustic pressure is also high. Sometimes, slight differences appear between these two parameters, near the object (source area), the similarity is high and at greater distances, the patterns may different because the intensity depends on the direction of propagation and wave attenuation.

In the FW_H model for RQ-7 Shadow, the extracted data for one of the defined receivers can also be viewed.

SPL (Sound Pressure Level)  graph is obtained by applying a Fourier transform (FFT) to the time domain signal and shows the noise characteristics in the frequency domain. A very prominent and sharp peak is observed at low frequencies (around 100–200 Hz) reaching about 50 dB.

After this peak, several smaller peaks (harmonics) are observed at multiples of the fundamental frequency, gradually decreasing in amplitude. There are also broadband noise components between the peaks.This diagram shows the classic signature of rotating machinery noise. The dominant peak is the blade passing frequency (BPF) or its fundamental harmonic. The smaller peaks are harmonics of this frequency. The presence of these sharp and distinct peaks confirms the tonal nature of the noise, which corresponds to periodic pressure fluctuations in the time diagram. Broadband noise (the sub-level between the peaks) indicates turbulent flow phenomena (e.g. vortex shedding, turbulence-blade interaction).

The graphs below show the sound pressure level in wider frequency bands (octave) and use A and B weighting filters.  Octave bands collect noise energy in specific frequency ranges rather than representing individual frequencies.

A-weighting simulates the human auditory response, meaning it reduces low and very high frequencies to make the graph more consistent with what the human ear hears. B-weighting also simulates the human auditory response, but it provides less reduction at low frequencies than A-weighting and was used more for older measurements.

The A-weighting plot shows that the majority of the noise produced, from the human ear’s perspective, is concentrated in a specific low frequency band. This frequency is most likely the Blade Passing Frequency (BPF) or its first harmonic. The sharp decline before the peak indicates that frequencies well below the BPF are either heavily attenuated by the A-weighting filter or are naturally low in noise.

The B-weighting plot, like the A-weighting plot, shows the dominance of the low frequency component. The higher level at the B-weighting peak indicates that this low frequency has significant sound energy that is attenuated less by B-weighting than by A-weighting.

Finally, the SPL is the actual sound intensity from the drone, derived from the pressure field calculated by FW–H, the A-weighted SPL (dBA) is the sound level that humans actually hear (the hearing threshold is taken into account), and the B-weighted SPL (dBB) is an approximation of the perceived sound at medium intensities. Comparing these three shows the difference between the physical energy of the sound and the perceived energy; in drones, the lower frequency (BPF) is usually clear in SPL but less so in dBA.

The Acoustic Pressure graphs for RQ-7 Shadow project show the time variations of the sound pressure ( p'(t) ) at the receiver location. This pressure is actually the acoustic signal calculated from the Ffowcs–Williams–Hawkes (FW–H) equation, which is due to the fluctuations in the flow around the propellers. It shows a very regular, periodic, and nearly sinusoidal oscillation. The amplitude of these oscillations is relatively constant. The period of this oscillation appears to be about 0.025 to 0.03 seconds, which corresponds to a frequency of about 33 to 40 Hz.

This graph shows a very coherent, tonal noise source. This periodicity is characteristic of rotating machinery such as a propeller, which creates a pressure pulse with each pass of the blade. The frequency of this oscillation is the blade passage frequency (BPF).

Negative values ​​in decibels usually mean pressure below a certain reference level or, here, indicate pressure fluctuations relative to atmospheric pressure.

The last data that we will discuss in this report is the dpdt RMS contour. The values ​​in this contour indicate the intensity of the time-dependent pressure fluctuations at each point on the surface.High dp/dt values ​​indicate rapid and severe pressure changes at those points. These rapid pressure changes are the main source of acoustic noise generation. The concentration of high dp/dt values ​​at the blade tips and edges is quite logical and expected for a rotating propeller.

This contour clearly shows the physical sources of noise that lead to the tonal and broadband peaks observed in the frequency domain plots. That is, these pressure fluctuations at the propeller surface propagate sound waves into the environment that we see in the SPL plots.

This description is a brief overview of one of the receivers defined in this project. In the training video of RQ-7 Shadow UAV, we analyze and explain the extracted data and compare them with each other in more detail.