Insertion loss (IL) is a more useful acoustic index than noise reduction and transmission loss for muffler design, but it is harder to predict because the prediction of IL requires knowing the characteristics of the muffler itself and the acoustic source. A muffler with porous material and complex meanflow makes the prediction even more challenging. Although calculation of noise reduction and transmission loss with the transient computational fluid dynamics (CFD) can naturally solve the flow–acoustic interaction problem, the published CFD methods have not been adopted to evaluate the IL of the dissipative muffler with exhaust flow. In this paper, a time-domain simulation method is developed to predict the IL of a complex engine muffler with porous material. The noise reduction and load impedance of the muffler were first calculated using a three-dimensional CFD model, in which the porous material was simulated by the governing equations modified with the material porosity and flow resistivity. The IL was then predicted from the noise reduction, the load impedance, and the engine source extracted from the measured exhaust noise. This developed method explores the application of the three-dimensional CFD method in calculating noise reduction, load impedance, and insertion loss of complex dissipative mufflers with exhaust flow.

Compared to the linear frequency domain method, the transient Computational Fluid Dynamics (CFD) method is more effective when analyzing the effect of complex flow in the muffler on its acoustic characteristics. However, most of the existing CFD methods focus on the calculation of the transmission loss (TL) for the muffler only. The other evaluation parameters, such as noise reduction (NR), are rarely investigated. In this paper, a CFD approach was developed systematically for charactering TL, NR, and transfer matrix (TM) of the muffler in the cases without and with exhaust flow. In the proposed approach, only one mesh model with a correction pipe is needed based on two simulation runs. The non-reflective boundary was used as the termination of the correction pipe in the calculation for the TL, while the reflective pressure boundary was set on the correction pipe end in the calculation for the NR. The TM was then derived from the time-domain pressure and mass velocity obtained in the previous runs for calculating TL and NR. The proposed CFD approach was applied to two simple expansion chambers, and the computational predictions of TL, NR, and TM were validated successfully both with the measured results and the analytical results. In conclusion, the proposed CFD approach is effective for full characterization (TL, NR, and TM) of exhaust mufflers without and with exhaust flow.

A multi-dimensional computational fluid dynamics (CFD) approach was proposed in this study aiming to calculate the transfer matrix of an engine exhaust muffler in the conditions with and without mean flow. The CFD model of the muffler with absorptive material defined as porous zone was calibrated with the measured noise reduction without mean flow, and was further employed to study the effect of the mean flow on the acoustic performance of the muffler. Furthermore, the exhaust acoustical source was derived from the calculated transfer matrices of six different additional acoustic loads obtained by the proposed CFD approach as well as the measured tail noise based on a multiload least squares method. Finally, the exhaust noise was predicted based on Thevenin’s theorem. The proposed CFD approach was suggested to be able to predict the acoustic performance of a complex muffler considering mean flow (without and with mean flow) and heat transfer, and provide reasonable results of the exhaust noise.

Orbital angular momentum (OAM) multiplexing/demultiplexing technology is crucial in increasing the data transmission rate for acoustic communication. However, the existing acoustic OAM multiplexing/demultiplexing is still limited to eight channels, and its combination with other communication techniques has not been verified experimentally. Here, we experimentally demonstrate the demultiplexing of up to 40 data channels using OAM multiplexing combined with wavelength-division multiplexing (WDM). The proposed demultiplexing method is improved from the virtual rotating receiver method used to detect the rotational Doppler effect of the OAM waves by a static array of microphones. The improved method has overcome the challenges of insufficient response, cross-talk, and signal aliasing, which often hinder the existing demultiplexing methods in the low-frequency region. The proposed demultiplexing method can be used to quickly decode the massive information concealed in a large number of acoustic OAM-WDM channels. Our work also shows practical prospects in underwater communication applications, especially in long-range communication using acoustic waves at low frequencies.