Enhanced functional binning for one- and two-point statistics using a posteriori Uncertainty Quantification of LPT data

In the evaluation of Lagrangian particle tracking (LPT) measurement data the use of spatially binned flow statistics in the form of one, two or multi-point statistics is often an essential step towards better understanding of the measured flow fields. Increasingly there is a focus towards uncertainty quantification of the measurement system however these evaluations are seldom used to directly improve the statistics by directly involving them into the calculation. We present our Functional Binning approach which makes use of such uncertainty information as a core component for the calculation of improved statistics. The improvements towards prior approaches are shown utilizing synthetic data as well as data from a real-world subsonic jet experiment. Beyond the initial formulation for one-point statistics, we show that this approach is readily extended towards two-point statistics and explore more advanced utilizations of uncertainty information for the optimal selection of particle pairs. Furthermore, the benefits of more individualized particle error estimations are investigated and some strategies for archiving such information are investigated.

Time-resolved Velocity Estimation from Inflow Pressure Measurements in a Subsonic Jet Using Machine-Learning Methods

The goal of this study is to estimate aspects of the time-resolved (TR) velocity field that is associated with pressure fluctuations measured in a subsonic jet using machine learning (ML) approaches. The experiments were conducted in the Anechoic Jet Test Facility at the University of Florida using a round converging nozzle operated at at a Mach number of 0.3 and ReD = 3.8 × 105. Planar PIV was utilized to record nonTR, 2D velocity snapshots on the streamwise plane. A B&K 4138 1/8” microphone and a GRAS 46DD 1/8” microphone were employed to measure inflow pressure fluctuations synchronously with the PIV. Both microphones were equipped with aerodynamically-shaped nosecones and were placed on the upper and lower jet liplines. The nosecone tips were streamwisely aligned and were placed just downstream of the PIV window (see Figure 1(a)). Pressure signals were recorded synchronously with PIV, but at different sampling rates, 80 kHz and 12 Hz, respectively. A total of 8000 PIV snapshots were acquired in the experiment.

LARGE EDDY SIMULATION OF ACOUSTIC CHARACTERISTICS OF A SUBSONIC JET OUTFLOWING FROM CONICAL NOZZLE

The calculation of noise generated by a jet of viscous compressible gas flowing out from a conical nozzle is considered. The calculations used the implicit version of the LES (Implicit LES, ILES), in which the role of the subgrid turbulence model performs numerical dissipation used finite-difference scheme. The distributions of the gas-dynamic and acoustic characteristics of the jet upon changing the conditions of its outflow are discussed. The analysis of the modal composition of the received noise is carried out and the correspondence between the features of the received directionality of the noise is determined by its various components and sources. The numerical simulation results are compared with the available experimental and calculated data.