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Dario Ambrosini

Publications and source records attributed to Dario Ambrosini.

4 recordsLinked to original sources

Deep learning approach for flow visualization in background-oriented schlieren

Diffractive optical element based background oriented schlieren (BOS) is a popular technique for quantitative flow visualization. This technique relies on encoding spatial density variations of the test medium in the form of an optical fringe pattern; and hence, its accuracy is directly influenced by the quality of fringe pattern demodulation. We introduce a robust deep learning assisted subspace method which enables reliable fringe pattern demodulation even in the presence of severe noise and uneven fringe distortions in recorded BOS fringe patterns. The method's effectiveness to handle fringe pattern artifacts is demonstrated via rigorous numerical simulations. Furthermore, the method's practical applicability is experimentally validated using real-world BOS images obtained from a liquid diffusion process.

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Quantitative flow visualization by hidden grid background oriented schlieren

The paper introduces hidden grid background oriented schlieren for quantitative study and visualization of natural convection heat transfer. In this technique, the refractive index variation, induced by the temperature gradient, is encoded in the recorded signal phase through the distortion of a background pattern. The background (undistorted) pattern is implicit (or hidden) in the light source. Quantitative estimation of the phase map is obtained by windowed Fourier transform. This method offers localized processing of the signal using joint space-frequency representation. The performance of hidden grid background oriented schlieren is practically demonstrated by investigating natural convective flow, a demanding task due to its comparatively small heat transfer.

eess.SP

Fast and robust method for flow analysis using GPU assisted diffractive optical element based background oriented schlieren (BOS)

The paper introduces a method for studying flow dynamics using diffractive optical element based background-oriented schlieren (BOS). Our method relies on fringe demodulation using root multiple signal classification technique which provides high robustness against noise. Further, a graphics processing unit (GPU) based implementation is proposed which offers significant improvement in computational efficiency, and thus enables high speed analysis of flows. The performance of the method is demonstrated via numerical simulations and the practical applicability is also shown by analyzing a diffusion phenomenon in liquids by BOS.

eess.IV

Multi-scale approach for analyzing convective heat transfer flow in background-oriented Schlieren technique

The paper introduces a multi-scale processing method for quantitative study and visualization of convective heat transfer using diffractive optical element based background-oriented schlieren technique. The method relies on robust estimation of phase encoded in the fringe pattern using windowed Fourier transform and subsequent multi-scale characterization of the obtained phase using continuous wavelet transform. As the phase is directly mapped to the refractive index fluctuations caused by the temperature gradients, the multi-scale inspection provides interesting insights about the underlying heat flow phenomenon. The performance of the proposed method is demonstrated for quantitative flow visualization.

eess.SP