# Advances in Vibroacoustics and Aeroacustics of Marine, Aerospace and Automotive Systems
## 2 The Present Issue
The results were compared in terms of preprocessing time and accuracy, showing that each of the three modelling procedures presented pros and cons, whereas the 1D modelling could be considered as the recommended one in most of cases. Localization and quantification of noise sources are important to fulfill customer and regulation requirements in a such competitive sector such as automotive manufacturing. Wind tunnel testing and acoustic mapping techniques based on microphone arrays can provide accurate information on these aspects. In the investigation presented in [10], an inverse method tailored to a volumetric approach was presented with the aim to investigate wind tunnel testing for the automotive industry. Two different kinds of problem were tackled: on the one hand, the results of inverse methods are strongly influenced by the problem definition and, on the other hand, experimental conditions very often mandatory to improve accuracy of results. These aspects were studied making use of simulated experiments. Finally, a set of scores was defined to evaluate the resulting maps with objective metrics. Currently, it is a hot research topic to retrieve the wave parameters by using X-band marine radar. However, non-negligible rainfall noise usually exists in the collected marine radar images, which seriously interferes with the extraction of the wave parameters. To reduce the influence of rainfall noise, the zero-pixel percentage (ZPP) method can be used to detect rainfall in radar images, but the detection accuracy is limited, and the selection of the threshold needs to be further studied. Based on the ZPP method, the ratio of zero intensity to echo (RZE) method for rainfall detection was proposed in [11]. The detection threshold is determined by statistical analysis of a large amount of radar data. Additionally, the rainfall intensity level was retrieved from X-band marine radar images directly. The data obtained from the experimental data measured in Fujian Province, China, were used to verify the effectiveness of the proposed method, showing that the detection accuracy of the proposed method was 11.7% higher than that of the traditional method. In [12], the numerical simulation of the vibroacoustics evaluation of an innovative material for a sports car roof was performed. The objective was to evaluate the feasibility of the newly designed roof against the traditional one made of fiberglass. Similarly to [13], the evaluation was carried out using numerical and experimental analysis techniques,with cross-comparison between the corresponding results. An accurate model of the car roof of the Alfa Romeo 4C car, made with the new material, was implemented and analyzed from the vibroacoustic point of view. The mere switch to the new material, with no changes in the geometry/structure of the car roof, did not allow for the preserving of the original performances and, therefore, a geometric/structural optimization of the component was also performed. The excellent damping capacity of the proposed material led to an improvement in the vibroacoustic transfer functions and to a reduction in the weight of the pavilion. The low density of the new material and the geometric optimization led to a 14% weight reduction compared to the previous design, but also to a reduction of the transfer functions peaks of these functions across the whole frequency range of interest (50 to 400 Hz). Understanding local phenomena connected with airflow around road vehicles allows to reduce the negative impact of transportation on the environment. The work presented in [14] used numerical tools for computational fluid dynamics (CFD) and computational aeroacoustic (CAA) calculations. The simplified car geometry \"Ahmed body\" was used for two different purposes: a validation process and a CAA analysis using the Ffowcs Williams-Hawkings (FW-H) analogy. The research was performed using the k\(-\omega\) Shear Stress Transport (SST) and the Large Eddy Simulation (LES) turbulence model.