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The astronauts need to re pressurize the sealed cabin after returning to the sealed cabin. The noise generated in the process of re pressurization is too large, so a silencer shall be set to reduce the noise in the cabin. Through theoretical analysis, this paper selects the small hole injection muffler, makes theoretical calculation, and determines the specific structural size of the muffler. The test shows that when the cabin pressure rises to 85kpa, the use of the small hole injection silencer can reduce the cabin noise from 85.7db to 66.3db, which meets the medical requirements of astronauts.

Traditional sound-absorbing materials, which are intended to address the issue of low-frequency noise control in automobile air-conditioning duct mufflers, have limited noise reduction effects in small spaces. Because of their straightforward structure and excellent controllability, acoustic metamaterials—particularly Helmholtz resonators—have emerged as a research hotspot in low-frequency noise reduction. However, existing technologies have issues such as restricted structural scale, narrow absorption frequency bands, and conflicts with ventilation requirements. To address these, this paper proposes a new type of Helmholtz perforated and tortuous-characteristic duct muffler for the unit cell of acoustic metamaterials. Through the innovative structural design combining a perforated panel with a multi-channel tortuous cavity, the length of the channel is changed in a limited space, thereby extending the sound wave propagation path and enhancing the dissipation of sound wave energy. Meanwhile, for the muffler, acoustic theoretical modeling, finite element simulation, and parametric optimization methods are adopted to systematically analyze the influence of its key structural parameters on the sound transmission loss (STL) of the muffler. Compared with the traditional folded-channel metamaterial, the two differ in resonance frequency by 38 Hz, in transmission loss by 1.157 dB, and in effective bandwidth by 1 Hz. This research provides theoretical support and design basis for solving the problem of low-frequency noise control in ventilation ducts, improves low-frequency broadband sound absorption performance, and promotes the engineering application of high-efficiency noise reduction devices.

As technology advances and transportation becomes more convenient, the total production and per capita ownership of cars have been increasing rapidly. This trend brings both benefits and drawbacks. On the positive side, it has made travel more convenient and saved a significant amount of time. However, on the negative side, it has caused significant noise pollution to the environment and affected people’s living conditions. The variety of car types is expanding, and their performance has greatly improved, offering more and better options for potential buyers. Conversely, this has presented many new challenges for car design [1]. Regarding the muffler of car exhaust, many researchers have achieved significant results in muffler design, and the noise reduction of car exhaust systems can now be well controlled. However, buyers are not satisfied with these achievements and have proposed some subjective requirements, making the improvement of the sound quality of car exhaust mufflers a current research hotspot. To address the issue of traditional muffler designs that overly rely on sound pressure level (SPL) indicators while neglecting subjective sound quality, this study proposes a muffler sound quality evaluation method based on psychoacoustic parameters. By setting up a semi-anechoic chamber experimental platform, noise was collected from a specific type of car exhaust muffler, and a comprehensive evaluation model was constructed using parameters such as Zwicker loudness, sharpness, and roughness [2].

Radar display console is an equipment which is closely associated with people as a medium of human-computer interaction. However, for the sake of heat dissipation, draught fans in display console make continuous noise when radar is on operation, the noise dose harm to human health. In order to reduce the noise, an impedance compound muffler is designed in this paper, and then the acoustic characteristics of muffler is studied by simulation method. In the end, the simulation results are verified by means of noise spectrum analyser, as a result, the muffler obtains good silencing effect and the maximum sound level of the radar display console is reduced by 3dB.

The chip muffler demonstrates dual functionality in cooling tower applications, serving not only as an effective noise reduction device but also exerting a significant influence on the thermal characteristics of natural draft wet cooling towers. This study investigates the aerodynamic and thermodynamic impacts of four distinct shading configurations (non-shaded, quarter-shaded, half-shaded, and three-quarter-shaded) on cooling tower performance under crosswind conditions ranging from 0 to 12 m/s. Through comprehensive three-dimensional numerical modeling of the modified muffler structure, we systematically analyzed airflow patterns, temperature distribution, and cooling efficiency enhancement mechanisms. Our findings reveal that the strategic implementation of chip mufflers can optimize airflow uniformity within the tower while effectively mitigating adverse crosswind effects. The half-shaded configuration demonstrated optimal performance, achieving a maximum cooling efficiency improvement of 4.49% at 7 m/s wind speed compared to conventional unmodified towers, accompanied by a substantial ventilation capacity increase of 1196.54 kg/s.

Aiming at the problems of large volume, high exhaust resistance and difficulty in suppressing noise in the 500 Hz to 100 Hz frequency band of traditional internal combustion engine exhaust mufflers, a noise reduction unit design based on acoustic metamaterials is proposed. Based on the equivalent medium theory, an acoustic model with a ring structure and multi-region variable refractive index was established. Phase control is achieved by helically winding the acoustic channel to change the refractive index, and the basic dimensions of the acoustic metamaterial muffling unit are calculated. The sound field distribution, transmission loss and flow field characteristics of the muffling unit are simulated and analyzed. This structure utilizes a multi-layer acoustic channel structure, effectively alleviating the problem of insufficient low-frequency noise elimination caused by the asymmetry of Fano interference. It achieved a transmission loss of over 10 dB within 85 % of the 500 Hz to 1000 Hz frequency band, and still maintained excellent noise reduction performance under high-frequency conditions through multi-level phase control. By connecting multiple units in series, a transmission loss of 10 dB can be achieved within 85 % of the 500 Hz to 1000 Hz frequency band. The exhaust flow field of the muffling unit was simulated and analyzed. Whether used alone or in series with the traditional muffling structure, the exhaust resistance remained within the range of 360 Pa to 370 Pa. Experimental tests show that when the metamaterial muffler unit is used in combination with the traditional muffler, it effectively achieves targeted noise elimination in the 500 Hz to 1000 Hz frequency band, and also demonstrates clear noise reduction capabilities in higher frequency ranges. The high noise suppression characteristics, high gas passage characteristics and compact volume characteristics of this structure provide more potential analysis methods and design schemes for the research and development of internal combustion engine mufflers and noise reduction accessories.

South Africa’s electrical infrastructure deficit and poor maintenance plans have resulted in frequently occurring power outages, which has caused a decline in productivity, alongside an increase in vandalism. As a result, many households and businesses have resorted to alternative energy sources, such as petrol generators. However, petrol generators are loud, reaching acoustic levels of roughly 90 dB, and have proven negative impacts on society and the environment. To reduce the noise intensity produced by small petrol generators, a noise reduction mechanism has been designed. The mechanism incorporates several noise attenuation materials such as porous absorbers and perforated panels. The design also features both passive and active ventilation features for optimal cooling of the generator during use. With flow simulating software embedded in SolidWorks, the temperature, pressure and acoustic power level within the noise reduction mechanism was investigated. The sound box is shown to reduce the noise of the generator to approximately 10 dB, whereas the muffler, can reduce the noise intensity to 37 dB. The overall temperature within the sound box is roughly 75 ˚C, and the maximum pressure was determined to be 103 kPa, which is sufficient for operation of the generator, without compromising its performance and functionality. A modified experimental model was built to validate the numerical results. The results from the experiment produced similar results in terms of decrease in sound when the insulator is added.

Over the last two decades, several experimental and numerical studies have been performed in order to investigate the acoustic behavior of different muffler materials. However, there is a problem in which it is necessary to perform large, important, time-consuming calculations particularly if the muffler was made from advanced materials such as composite materials. Therefore, this work focused on developing the concept of the indirect dual-chamber muffler made from a basalt fiber reinforced polymer (BFRP) laminated composite, which is a monitoring system that uses a deep learning algorithm to predict the acoustic behavior of the muffler material in order to save effort and time on muffler design optimization. Two types of deep neural networks (DNNs) architectures are developed in Python. The first DNN is called a recurrent neural network with long short-term memory blocks (RNN-LSTM), where the other is called a convolutional neural network (CNN). First, a dual-chamber laminated composite muffler (DCLCM) model is developed in MATLAB to provide the acoustic behavior datasets of mufflers such as acoustic transmission loss (TL) and the power transmission coefficient (PTC). The model training parameters are optimized by using Bayesian genetic algorithms (BGA) optimization. The acoustic results from the proposed method are compared with available experimental results in literature, thus validating the accuracy and reliability of the proposed technique. The results indicate that the present approach is efficient and significantly reduced the time and effort to select the muffler material and optimal design, where both models CNN and RNN-LSTM achieved accuracy above 90% on the test and validation dataset. This work will reinforce the mufflers’ industrials, and its design may one day be equipped with deep learning based algorithms.

Air Pollution produced from automobiles has become one of the most critical problems of environmental concern and likely to increase as vehicle population is assumed to grow approximately by 1300 million by the year 2030. In India, automobiles will have to meet the BS-VI emission standards to reduce vehicular pollution that impacts on environment and human health. These norms impose various restrictions on emissions of exhaust gases like NOx, HCs, particulate matter. Many recent exhaust control devices are being developed to meet the required needs. Therefore, the present study aims to reduce CO2 emissions generated in SI engine automobiles using activated carbon/calcite in a muffler. The backpressure parameter of the muffler affects the efficiency of an internal combustion engine. The porosity and diameter of the inner tube of the muffler has a prominent effect on backpressure. Therefore, the muffler with 48, and 60 holes, respectively and 1mm and 2mm diameter, respectively on a perforated tube have been investigated. The result shows that the concentration of CO2 and back pressure is greatly reduced by increasing porosity and diameter, respectively of the tube. Thus, an environmentally friendly and efficient muffler is modeled and simulated.

This research aims to measure OEM, HPLPM and Free flow mufflers under several noise level testing. In this study, the factory-installed exhaust was replaced with a free-flow type and HPLPM exhaust. The research employed a quantitative method with an experimental approach. Testing was carried out under three different vehicle conditions that correspond to their usage: normal condition, exhaust condition, and acceleration condition. Each type of exhaust was tested three times for each testing condition. Subsequently, the collected data were analyzed and compared against the established quality standard in Indonesia, which stipulates that the noise level must not exceed 90 db. Based on the average noise levels produced by the free-flow exhaust type, it was found that under normal vehicle conditions, the average noise level was 28.08% higher compared to the OEM exhaust type. Under exhaust conditions, the free-flow exhaust type resulted in an average noise level 23.13% higher than the OEM type. During acceleration, the free-flow exhaust type generated an average noise level 14.54% higher than the OEM type. Employing the HPLPM exhaust type under normal vehicle conditions yielded an average noise level 25.9% higher than the OEM type. Under exhaust conditions, the HPLPM exhaust type led to an average noise level 21.2% higher than the OEM type. Finally, during acceleration, the OEM exhaust type produced an average noise level 0.03% higher than the HPLPM type. Based on this data, HPLPM can reduce noise levels better than free flow muffler. At the higher RPM HPLPM can produce almost the same noise as the OEM type.