The aim of the present work was to investigate the influence of pressures and temperature on cavitation in an orifice flow. In particular image analysis and frequency analysis of the experimental pressure signals were used to identify different flow behaviors at different operating conditions. . In order to show the effect of the temperature at different cavitation numbers, the waterfall diagrams of the frequency components of the downstream and upstream pressure at 293-348 K were investigated. Bubbles growth and collapse generate pressure fluctuations so frequency spectra can be related to cavitation behavior. The amplitude of the upstream FFT is higher than the downstream one. In particular the frequency range 0-10 kHz is investigated. The amplitude of FFT were used to training an ANN. ANN permitted to identify the different cavitation regimes and to lightly the influence of each input parameters about the learning of the network and then about the cavitation phenomenon. Following, a theoretical analysis was performed to justify the results of the experimental observations. In this approach the nonlinear dynamics of the bubbles growth were described by the Rayleigh-Plesset equation in a one-dimensional code, so to couple the effects of the internal dynamic bubble with the other flow parameters (pressure, velocity, void fraction, temperature, etc..).

COMPUTATIONAL MODELING OF THERMO AND FLUID DYNAMIC EFFECT IN CAVITATING NOZZLES AND EXPERIMENTAL CHARACTERIZATION

DE GIORGI, Maria Grazia;BELLO, DANIELA;FICARELLA, Antonio
2012-01-01

Abstract

The aim of the present work was to investigate the influence of pressures and temperature on cavitation in an orifice flow. In particular image analysis and frequency analysis of the experimental pressure signals were used to identify different flow behaviors at different operating conditions. . In order to show the effect of the temperature at different cavitation numbers, the waterfall diagrams of the frequency components of the downstream and upstream pressure at 293-348 K were investigated. Bubbles growth and collapse generate pressure fluctuations so frequency spectra can be related to cavitation behavior. The amplitude of the upstream FFT is higher than the downstream one. In particular the frequency range 0-10 kHz is investigated. The amplitude of FFT were used to training an ANN. ANN permitted to identify the different cavitation regimes and to lightly the influence of each input parameters about the learning of the network and then about the cavitation phenomenon. Following, a theoretical analysis was performed to justify the results of the experimental observations. In this approach the nonlinear dynamics of the bubbles growth were described by the Rayleigh-Plesset equation in a one-dimensional code, so to couple the effects of the internal dynamic bubble with the other flow parameters (pressure, velocity, void fraction, temperature, etc..).
2012
9788890767609
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/374291
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