Blast waves generated from the muzzles of weapons may exert negative effects, such as shock waves and impulse noise. If the weapon is fired with a muzzle brake, these effects are recognized to be more severe. This paper discusses the influence of the muzzle brake on certain aeroacoustic noise characteristics based on numerical simulations and a corresponding experiment. The impulse noise, which is induced by complex jet flows discharging from small caliber rifles with muzzle brakes, is focused in this study. Computational fluid dynamics (CFD) and computational aeroacoustics (CAA) are combined to calculate the muzzle flow field and jet noise for cases with and without a muzzle brake, and then the data sets are carefully compared. The simulations indicate that the muzzle brake alters the muzzle flow field and directional distribution of the jet noise compared to a rifle sans muzzle brake. Deviations less than 7.6% between experimental data and simulation results validate the simulation model. The results presented in this paper may provide a workable reference for the prediction of muzzle noise and the optimization of muzzle brake designs.
The use of muzzle brakes represents an important innovation in combat systems as they force the forward momentum of muzzle gases rearward to offset the recoil load created by the weapons during firing. Redirecting the muzzle gases also increases the intensity of the shock wave, however, as well as the impulse noise behind the guns. These factors have various negative effects on human bodies and environments.
Early research on muzzle flow [
Advancements in computational performance and CAA have made numerical simulation methods better suited to jet noise research [
Preliminary research on muzzle jet flow noise based on both simulation and experimental data was conducted in this study to analyze the effects of the muzzle brake on the intensity and directivity of muzzle noise. A 5.8 mm caliber automatic rifle with a standard 5.8 mm cartridge was selected as the research object. A CFD-CAA hybrid method was used to calculate the muzzle flow field by the large eddy simulation (LES) method, and the noise attenuation was determined by using Ffowcs Williams and Hawkings (FW-H) equations based on the obtained source data. The jet noise induced by complex flows discharging from the rifle was analyzed. The effect of the muzzle brake on noise propagation characteristics is discussed below by comparison of the results with and without a muzzle brake. The simulation results were also compared against experimental data to validate the model. The results presented here may provide a useful reference for predicting the muzzle noise and optimizing muzzle brakes for small caliber weapon systems.
Due to the supersonic speed at which propellant gas exhausts from the gun barrel, an unsteady flow field with high temperature, high pressure, and high speed is formed around the muzzle as shown in Figure
High-speed shadow photo of muzzle flow field, 7.62 mm ballistic gun. 1: initial shock wave; 2: propellant gas flow; 3: propellant gas shock wave; 4: impulsive noise wave.
Muzzle noise has two main sources. The first is shock wave noise, which is mainly formed by the decay of muzzle shock wave below 6.9 kPa (170.7 dB) [
There are differences between the two kinds of muzzle noise in terms of sound source properties and calculation methods. They needed to be studied separately. Therefore, this research only focuses on impulse noise. During the simulation, a supersonic projectile of a rigid body was not considered as the impact of the projectile, and initial shock wave (produced as compressed air from a supersonic moving projectile exiting the barrel) on muzzle noise is very small compared to the two factors discussed above [
The CFD-CAA hybrid method provides the flexibility to select the most appropriate method for each problem. For simulating the sound source fields, the hybrid method utilizes flow solvers of CFD, such as direct numerical simulation (DNS) or large eddy simulation (LES). The far field sound is computed with CAA methods, such as the FW-H acoustic analogy method or extended Kirchhoff method. In this study, the LES method was used to compute the flow field and the propagation of acoustic waves in the far field was determined by solving the FW-H integration equations. Both methods are described in detail in the following sections.
The LES method is considered to be a suitable CFD approach to simulate a turbulent flow with high Reynolds number. The basic principle of the LES is to provide an alternative weighted average of the N-S equation in space. The large-scale and small-scale turbulent structures are calculated separately by a spatial filtering method. Eddies smaller than a preset scale are filtered out from the flow field and obtained by solving additional equations. Only the large eddies are calculated time-dependently. The continuity equation and N-S equation after filtering can be expressed as
Ffowcs Williams and Hawkings utilized the generalized function theory to obtain the classic equation associated with their names. According to the continuous equation and momentum equation, the FW-H equation is
The three terms on the right-hand side of the FW-H equation represent the acoustic radiation source: the first term indicates the turbulent stress of the fluid itself with quadrupole characteristics, the second one represents the dispersion of the unstable forces applied to some interfaces with dipole characteristics, and the third one indicates the unsteady mass flowing into the fluid with monopole characteristics.
Sound pressure level (SPL) is a basic measurement for the pressure fluctuations of a sound wave as it propagates through the air [
The SPL for the weapon muzzle noise is mostly determined by peak sound pressure level (SPLpeak) and overall sound pressure level (OASPL) [
The experiment was conducted in a semisilencing room, with an effective space of 9.32 m × 7.84 m × 5.26 m at the No. 208 Research Institute of China Ordnance Industries. The room has five surfaces equipped with sound-absorbing material (the ground is not) with effective sound insulation and vibration isolation performance. A 5.8 mm caliber automatic rifle was selected as the research object in this study. The muzzle brake of the rifle used in these tests is shown in Figure
Experimental rifle with the muzzle brake.
The test system mainly consists of acoustic sensors and an acquisition control system as shown in Figure
Schematic diagram of the test scheme.
Experimental setup.
Sound levels were measured with radii of 1.0 m, 1.5 m, 2.0 m, and 2.5 m at 0°, 45°, and 90° counterclockwise from the downstream direction of the jet. An overview of the measurement points and the corresponding field diagram are shown in Figures
Measurement point locations in the far field.
Field diagram (red line indicates the axis of different angles according to barrel axis; red circle indicates microphone location).
The same behavior was observed in all ten rounds of the experiment, so the result from the sixth round was taken as an example for further analysis. The pressure varies with time at different measurement points and their corresponding one-third octave frequency spectra are shown in Figure
Sound pressure level varying with time and the corresponding one-third octave frequency spectrum at different measurement points. (a)
As described in Section
This study focuses on the impulse noise; therefore, the shock wave noise has been filtered before calculating the OASPL at each point for comparison against the simulation results. According to the characteristics of the muzzle flow field, the initial shock wave and muzzle blast wave formed prior to gas jet propulsion and have a higher propagation speed. The shock wave can thus be excluded from the analysis by the first period of the measurements in the
Average measured SPLpeak and OASPL of impulse noise.
SPLpeak (dB) | OASPL (dB) | Difference (dB) | |
---|---|---|---|
Point | |||
P1 | 152.38 | 126.26 | 26.12 |
P2 | 151.21 | 124.83 | 26.38 |
P3 | 150.44 | 123.34 | 27.10 |
P4 | 150.35 | 121.82 | 28.53 |
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Point | |||
P5 | 156.08 | 131.73 | 24.35 |
P6 | 153.9 | 130.18 | 23.72 |
P7 | 152.54 | 128.65 | 23.89 |
P8 | 150.21 | 125.6 | 24.61 |
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Point | |||
P9 | 161.63 | 132.77 | 28.86 |
P10 | 159.85 | 131.01 | 28.84 |
P11 | 157.38 | 130.08 | 27.30 |
P12 | 156.11 | 129.2 | 26.91 |
As described in reference [
The muzzle brake used in the experiment was schematized in a 3D physical model as shown in Figure
Schematic diagram of the muzzle brake.
Schematic diagram of the computational domain and boundary condition.
Grid model of the computational domain.
As the initial shock wave and the projectile were not taken into consideration in this study, the start time of the muzzle flow field calculation was determined as the moment when the projectile leaves the muzzle and the propellant gas begins to flow outward (i.e., the end of the interior ballistics). The initial conditions such as pressure and velocity in the barrel were determined by using the internal ballistics equations below as shown in Figure
Initial condition.
An average temperature of 1800 K was used as the initial temperature in the chamber, and the atmosphere of the region out of the chamber was set to 101,325 Pa and 300 K. All the initial conditions are set through the user-defined function (UDF) program according to ANSYS FLUENT 15.0 UDF Manual.
The outer surfaces of the barrel and muzzle brake were specified as a wall boundary (Figure
To investigate the muzzle noise field with the muzzle brake, the same weapon with no muzzle brake was built for the sake of comparison. A schematic diagram of its computational domain, initial conditions, and boundary conditions is shown in Figure
Schematic diagram of the computational domain and boundary condition.
According to the CFD-CAA hybrid method, there are two steps in the analysis of aerodynamic noise. First, all computational domains are analyzed by the LES method. Here, unsteady flow parameters such as destiny, pressure, and velocity were collected on the source surface after obtaining stable unsteady solution during 10,000 time steps for a total time exploration of 50 ms. The sound propagation was computed by using the FW-H equation to obtain the sound pressure signal of each receiver. All calculations were completed in ANSYS-FLUENT software.
The location of the FW-H surface used as necessary inputs for acoustic calculations in the far fields is shown in Figures
Receiver locations in the far field.
Jet flow from the muzzle is instantaneous, high-pressure, and inconstant as shown in Figure
Muzzle flow field at
When the CFD calculation is relatively stable, the FW-H equation is applicable to calculate the sound pressure of each receiver location based on the source data obtained from the numerical LES results. The OASPL can then be determined by spectral analysis. A corresponding noise directivity diagram is shown in Figure
Noise directivity diagram.
For the receivers located at the radius equal to 0.5 m, which are nearest to the muzzle, the maximum OASPL value is 136.5 dB at 50°. As the radius increases, the angle of the maximum value gradually falls to the side. The maximum values of all the rest of the receivers are reached at 90°. One of the reasons for this difference is that turbulent jet noise is the most common quadrupole noise and has obvious directivity, which reaches its maximum value at about 45° [
The characteristics of noise are also closely related to the structure of muzzle flow field. Previous research [
A comparison of the simulated results at different angles and radii for cases with and without a muzzle brake is shown in Figure
Noise directivity diagrams with and without the muzzle brake. (a)
The simulated and experimental results were compared based on the peak frequency and peak sound pressure level to verify the accuracy and feasibility of the model.
Peak frequency is an important part of spectrum analysis and also the basis for noise source analysis. The spectra of points at different angles are shown in Figure
One-third octave frequency spectrum. Comparison between cases with and without the muzzle brake. (a) Point 1 at
The SPLpeak is commonly used as global standards for noise from weapons. The simulated data were further processed by combining the OASPL and typical difference value obtained from measured data to estimate SPLpeak. A comparison of SPLpeak values for different methods is shown in Table
Comparison between the calculated and experimental results of SPLpeak.
SPLpeak (dB) | Difference (%) | ||
---|---|---|---|
Measured | Calculated | ||
Point | |||
P1 | 152.38 | 154.69 | −1.5 |
P2 | 151.21 | 151.16 | 0.0 |
P3 | 150.44 | 148.65 | 1.2 |
P4 | 150.35 | 146.67 | 2.4 |
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Point | |||
P5 | 156.08 | 151.26 | 3.1 |
P6 | 153.9 | 147.22 | 4.3 |
P7 | 152.54 | 145.42 | 4.7 |
P8 | 150.21 | 142.35 | 5.2 |
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Point | |||
P9 | 161.63 | 153.59 | 5.0 |
P10 | 159.85 | 149.24 | 6.6 |
P11 | 157.38 | 146.4 | 7.0 |
P12 | 156.21 | 144.26 | 7.6 |
The simulated results of the points at
Based on Table
A CFD-CAA hybrid method was used in this study to simulate the impulse noise from a small caliber rifle with/without a muzzle brake. The model was validated by comparison with experimental data. The conclusions can be summarized as follows: In the case with a muzzle brake, the clear directivity of quadrupole noise can be observed within 0.5 m away from the muzzle’s central point. The directivity grows less intensely as the radius increases, and the peak emerges at Comparison of the peak frequency between the simulated and experimental results indicates that the impulse noise caused by the propellant gas jet flow is one of the main sources of muzzle noise. The deviation between simulated results and experimental data is within 7.6%, which indicates that the proposed simulation method is feasible.
The research presented in this paper may be helpful as future engineers seek to better understand impulse noise characteristics; they may also provide a workable reference for designing muzzle brakes for small caliber weapon systems.
All data included in this study are available from the corresponding author upon request.
The authors declare that there are no conflicts of interest regarding the publication of this paper.
This work was supported by the Natural Science Foundation of China (Grant No. 11802138).