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Plenary Lecture
The Aeroacoustics of Turbulent Flows

Professor
Marvin Goldstein
NASA Glenn Research Center
U.S.A.
E-mail: marvin.e.goldstein@nasa.gov
Abstract:
Aerodynamic noise prediction has been an important and challenging research
area since James Lighthill first introduced his Acoustic Analogy Approach
over fifty years ago. This talk attempts to provide a unified framework for
the subsequent theoretical developments in this field. It assumes that there
is no single approach that is optimal in all situations and uses the
framework as a basis for discussing the strengths weaknesses of the various
approaches to this topic. But the emphasis here will be on the important
problem of predicting the noise from high speed air jets. Specific results
will presented for round jets in the 0.5 to 1.4 Mach number range and
compared with experimental data taken on the Glenn SHAR rig. It is
demonstrated that non-parallel mean flow effects play an important role in
predicting the noise at the supersonic Mach numbers. The results explain the
failure of previous attempts based on the parallel flow Lilley model (which
has served as the foundation for most jet noise analyses during past two
decades).
Brief Biography of the Speaker:
Dr. Goldstein was chief scientist at the NASA Glenn Research Center from1980
to 2004. His technical accomplishments include a long list of "firsts,"
including the development of an explanation for boundary layer receptivity
to free stream disturbances, a rational analysis of oblique wave modal
interactions in shear layers, the theory for the so-called Klebanoff modes
that are observed in boundary layers at high to moderate levels of free
steam turbulence levels and an analytical solution for the problem of
flutter in a cascade with strong in passage shock waves. He also derived the
fundamental equation of the compressible rapid distortion theory, which is
frequently referenced and is the starting point for many papers in the
turbulence literature.
Goldstein is an adjunct professor of mathematics at Case Western Reserve
University (Cleveland) and has taught at MIT. A specialist in unsteady fluid
mechanics with emphasis on transition and stability, unsteady turbomachinery
flow, aeroacoustics and aeroelasticity, Goldstein has published over 120
refereed papers, and authored the book "Aeroacoustics" (McGraw-Hill Company,
1976), which has been translated into Russian and Japanese. This book has
become the classical reference book for engineers and scientists throughout
the world. He has presented many invited and keynote lectures at scientific
conferences, symposia and special celebratory events.
A Fellow of the American Institute of Aeronautics and Astronautics (AIAA),
Goldstein served on the Publications Committee and as chairman of the
Aeroacoustics Technical Committee. He is also a Fellow of the American
Physical Society (APS), where he served on the Executive Committee of the
Division of Fluid Dynamics and the Otto LaPorte Award Nominating Committees.
He recently chaired the AFOSR Fluid Mechanics Selection Panel, the Selection
Committee for the National Academy of Sciences Award in Aeronautical
Engineering and the American Physical Society’s Fluid Mechanics Prize
committee. He is also a member of Northeastern University’s Industrial
Advisory Board, of the Editorial Board of the International Journal of
Aeroacoustics, and of the Scientific Committee of the International Congress
of Sound and Vibration.
Among his honors is election to membership in the National Academy of
Engineering (1990), the APS Otto LaPorte Award for Research in Fluid
Dynamics (now the Fluid Dynamics Prize,1997), the AIAA Aeroacoustics Award
(1983), the AIAA Pendray Award (1983) ,Northeastern University's Outstanding
Engineering Alumnus Award (2002), and the ASME Fluids Engineering Award
(2003). Goldstein received his bachelor's degree in mechanical engineering
at Northeastern University (Boston), earned his master's degree in
mechanical engineering at the Massachusetts Institute of Technology, and his
doctorate at the University of Michigan..
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