Numerical assessment of gun mufflers using finite element method, neural networks, and a genetic algorithm

Abstract

In order to enhance the acoustical performance of gun mufflers, a multi-chamber muffler internally inserting with expansion cones and perforated tubes ducts is presented. Because of the complicated geometry of gun muffler, traditional analytic method used in predicting a muffler’s acoustical performance is difficult; therefore, a finite element method using the COMSOL software is adopted to predict the gun muffler’s sound transmission loss. Moreover, because an objective function (or fitness function) is needed during the optimization process, a simplified mathematical model using Artificial Neural Network (ANN) is used. Here, a polynomial objective function is established by inputting the muffler’s geometric design parameters and the related simulated Sound Transmission Loss (STL) (run on the COMSOL) via the Artificial Neural Network. Furthermore, Genetic Algorithm (GA), an optimizer, is linked to the simplified mathematical model to maximize the gun muffler’s acoustical performance. To pursue a maximal STL at the targeted tones, the geometric parameters of cone’s horizontal length (L1) and first cone’s span (L2) is optimally adjusted. Results demonstrates the STL of gun muffler at the specified frequencies of 1000, 2000, and 4000 Hz can be improved from 15.8 dB, 72.6 dB, 184.8 dB to 18.2 dB, 112.6 dB, and 416.3 dB, respectively. The paper aims to provide an optimal design method of gun muffler using Finite Element Method (FEM), Artificial Neural Network, and Genetic Algorithm. Consequently, the simulated results reveal that the optimally shaped gun muffler can efficiently depress the gun’s shooting noise.

Performance Analysis of Different Firearm Suppressor Structures

“…However, suppressor geometries can become complex, consequently making computer simulated models hard to produce [12]. Making computer simulated models proves the design much faster and cheaper and is considered a standard practice at this point.…”

Investigation of the effects of volume change on flow structure and acoustic in a silencer

“…Generally, the simulated results from the three studies showed that the properly formed gun silencer may effectively reduce the gun's shooting noise. [16][17][18] When a propellant gas is in a turbulent flow, parameters like pressure, temperature, velocity density, and specific entropy continuously change. Experiment research findings are costly and do not demonstrate the detailed fluctuation of the fluid flow, nor do they sufficiently reproduce the evolution and diffusion of the firing acoustic field.…”

“…The study emphasised three acoustic properties: sound pressure, spectrum distribution of sound pressure, and zonal suppression efficacy. Min-Chiu and Chang, 18 investigated an internally located multi chamber silencer with expansion cones and perforated pipe ducts to improve the acoustic performance of pistol silencers. The purpose of this study is to present an optimal design technique for gun mufflers using the Finite Element technique (FEM), Artificial Neural Network, and Genetic Algorithm.…”

Rekreacinės paskirties šaunamojo ginklo slopintuvo efektyvumo tyrimai

“…Šio tipo slopintuvai įrodė savo veikimo patikimumą ir šūvių slopinimo efektyvumą visose aplinkosenuo profesionalaus naudojimo naudojant automatinius šautuvus iki įvairių tipų lengvųjų šaulių ginklų (Pylypenko et al, 2021). Tačiau slopintuvo geometrijos gali tapti sudėtingos, todėl kompiuteriu modeliuojamus modelius kartais sunku pagaminti (Chiu et al, 2023). Kompiuterinių modelių kūrimas įrodo, kad konstrukcijos tikrinimas yra daug greitesnis ir pigesnis, todėl šiuo metu tai laikoma įprasta praktika.…”