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The paper presents tools to model low speed airflow coming from a turbulent machine. This low speed flow have instabilities who generate noise disturbances in the environment. The aim of the study proposed in this paper, is the using of cyclostationary tools with audio signals to model this airflow and detect the noisy frequencies to eliminate this noise. This paper also deals with the extraction in real time of the frequency corresponding to the noise nuisance. This extraction makes it possible to build a software sensor. This software sensor can be used to estimate the air flow rate and also to control a future actuator which will reduce the intensity of the noise nuisance. This paper focuses on the characteristic of the sound signal (property of cyclostationarity) and on the development of a software sensor. The results are established using an experimental setup representative of the physical phenomenon to be characterised.

Impinging jets are encountered in ventilation systems and many other industrial applications. Their flows are three-dimensional, time-dependent, and turbulent. These jets can generate a high level of noise and often present a source of discomfort in closed areas. In order to reduce and control such mechanisms, one should investigate the flow dynamics that generate the acoustic field. The purpose of this study is to investigate the flow dynamics and, more specifically, the coherent structures involved in the acoustic generation of these jets. Model reduction techniques are commonly used to study the underlying mechanisms by decomposing the flow into coherent structures. The dynamic mode decomposition (DMD) is an equation-free method that relies only on the system’s data taken either through experiments or through numerical simulations. In this paper, the DMD technique is applied, and the spatial modes and their frequencies are presented. The temporal content of the DMD’s modes is then correlated with the acoustic signal. The flow is generated by a rectangular jet impinging on a slotted plate (for a Reynolds number Re = 4458) and its kinematic field is obtained via the tomographic particle image velocimetry technique (TPIV). The findings of this research highlight the coherent structures signature in the DMD’s spectral content and show the cross correlations between the DMD’s modes and the acoustic field.

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The complex cavity flow represented by the feedback mechanism and self-sustained oscillations of cavity shear layer are widely investigated in various publications either through analysing the aero-acoustic phenomenon occurring and its control or through examining the heat transfer mechanism in such a flow. Boundary layer separation, turbulence, unsteadiness, recirculation and reattachment complicate the flow phenomena at the cavity and may lead to substantial effects on heat transfer. Besides, in order to enhance the heat transfer in some applications, cavity flow was introduced, and thus the importance of understanding the cavity flow structure and its relation with heat transfer has become vital, where such a phenomenon occurs in many engineering applications. This paper presents a literature review on the studies that focus on examining heat transfer in cavity flow, by evaluating the effect of cavity geometry and inlet flow field on heat transfer at different cavity regions.