Abstract
The bivariate two dimensional empirical mode decomposition (Bivariate 2D-EMD) is extended to estimate the turbulent fluctuations and to identify cycle-to-cycle variations (CCV) of in-cylinder flow. The Bivariate 2D-EMD is an adaptive approach that is not restricted by statistical convergence criterion, hence it can be used for analyzing the nonlinear and non-stationary phenomena. The methodology is applied to a high-speed PIV dataset that measures the velocity field within the tumble symmetry plane of an optically accessible engine. The instantaneous velocity field is decomposed into a finite number of 2D spatial modes. Based on energy considerations, the in-cylinder flow large-scale organized motion is separated from turbulent fluctuations. This study is focused on the second half of the compression stroke. For most of the cycles, the maximum of turbulent fluctuations is located between 50 and 30 crank angle degrees before top dead center (TDC). In regards to the phase-averaged velocity field, the contribution of CCV to the fluctuating kinetic energy is approximately 55% near TDC.
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