This work aims to estimate time-resolved velocity field that is directly associated with pressure fluctuations in a subsonic round jet. To achieve this goal, synchronous measurements of the velocity field and in-flow pressure fluctuations were performed at Mach number 0.3. Two different experiment campaigns were conducted, the first experimental campaign aims to explore the time-resolved dynamics of the axisymmetric velocity components, and second experiment focuses on the time-resolved, 2D velocity estimates on a streamwise plane. Two different methods were utilized to estimate the input-output relation between velocity and in-flow pressure measurements. A hybrid approach based on the spectral linear stochastic estimation and the proper orthogonal decomposition was applied to setup the model in a linear manner, and a wavelet-based filter was implemented to attenuate the noise level in the cross-correlation functions. In addition, the pressure-velocity relationship was also described by neural network architectures based on the multi-layer perceptron (MLP) and bidirectional long-short-term-memory (LSTM). In both experimental sets, pressure fluctuations inside the flow are found to be connected to the streamwise convection of large-scale coherent structures in the flow. A unique advantage of the bidirectional LSTM method was found among all estimation schemes is also reported in this work. The estimation result represents the space-time dynamics of the acoustic sources in the jet flow field, and it is of great importance to understand the noise generation mechanism.

39 pages, 25 figures This draft was prepared for the submission to Physical Review Fluids