BEGIN:VCALENDAR METHOD:PUBLISH PRODID:-//Apple Computer\, Inc//iCal 1.0//EN X-WR-CALNAME;VALUE=TEXT:USC VERSION:2.0 BEGIN:VEVENT DESCRIPTION:Speaker: Dimitri Papamoschou, UC Irvine Talk Title: Development of a Linear Surface-Based Model for the Jet Noise Source Abstract: The seminar will discuss an effort to formulate an elementary physical model for the jet noise source that can be used for practical prediction of aircraft noise. Although the present analysis is confined to a round single-stream jet, the basic principles can be extended to more complex configurations. The model is defined on a radiator surface at the rotational/irrotational boundary of the jet on which the footprint of the vortical eddies, including their convective speed, is captured. The models building block at a given frequency is a linear pressure event with random origin and random helical mode. The probability density function for the event's axial origin is derived from the statistics of coherent structures in shear layers. The distribution for the helical mode is currently empirical and driven by the need to match the polar directivity of sound emission in the far field. The generic form of the event is a self-similar wavepacket with convective speed based on the mean centerline velocity and shape parameters determined by least-squares matching of the far-field sound pressure level at a wide range of frequencies and polar angles. Initial results indicate that the model reproduces, in a qualitative sense, key statistics of the jet acoustic field, including the near-field space-time correlation, the broadening of the far-field spectral density with increasing polar angle from the jet axis, and the coherence between the near and far fields. For the latter, the analysis indicates that the rapid decline in the coherence with increasing polar angle is primarily due to the randomness of the event's axial origin. Biography: Dimitri Papamoschou is a professor of mechanical and aerospace engineering at University of California, Irvine (UCI). He received his PhD in Aeronautics at Caltech. His research interests include compressible turbulence, jet and fan aeroacoustics, and advanced noise source imaging methods. In jet aeroacoustics, he has shown the potential for noise reduction by asymmetric distortion of the jet velocity field, a concept that has led to several patents. He has also developed low-cost predictive methods for this type of noise reduction based on a special formulation of the acoustic analogy. At UCI he has served in various administrative roles, including department chair, associate dean, and interim dean. He is a Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and recipient of the 2017 AIAA Aeroacoustics Award. He serves as an associate editor of the AIAA Journal. Host: AME Department More Info: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09 Webcast: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09 SEQUENCE:5 DTSTART:20211110T153000 LOCATION:SSL 202 DTSTAMP:20211110T153000 SUMMARY:AME Seminar UID:EC9439B1-FF65-11D6-9973-003065F99D04 DTEND:20211110T163000 END:VEVENT END:VCALENDAR