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Anastasios (Tasos) Lyrintzis

Anastasios (Tasos) Lyrintzis. Ph.D. Aerospace Engineering, Cornell University (1988) Helicopter blade-vortex interactions Professor, School of Aeronautics and Astronautics Graduate Chair Faculty Scholar Areas of Research: Computational Aeroacoustics (CAA) Computational Fluid Dynamics (CFD)

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Anastasios (Tasos) Lyrintzis

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  1. Anastasios (Tasos) Lyrintzis • Ph.D. Aerospace Engineering, Cornell University (1988) • Helicopter blade-vortex interactions • Professor, School of Aeronautics and Astronautics • Graduate Chair • Faculty Scholar • Areas of Research: • Computational Aeroacoustics (CAA) • Computational Fluid Dynamics (CFD) • Applications: • Jet noise, jet engine mixer and nozzle flows, rotorcraft flows, high-speed boundary layers and shock-boundary layer interactions • Funding: NASA, AARC (Aeroacoustics Research Consortium), 21st Century Research & Technology Fund (with Rolls-Royce) • http://roger.ecn.purdue.edu/~lyrintzi/

  2. Gregory Blaisdell • Ph.D. Mechanical Engineering, Stanford University (1991) • Compressible turbulence simulations • Associate Professor, School of Aeronautics and Astronautics • Areas of Research: • Turbulence simulation and modeling • Computational fluid dynamics (CFD) • Applications: • Jet noise, jet engine mixer and nozzle flows, aircraft wake vortices, high-speed boundary layers and shock-boundary layer interactions • Funding: NASA, AARC (Aeroacoustics Research Consortium), 21st Century Research & Technology Fund (with Rolls-Royce) • https://engineering.purdue.edu/AAE/FacultyStaff/Faculty/showFaculty?resource_id=1446

  3. Current Research Areas Goal Improve engine design methodology for noise reduction Objectives Develop accurate first-principles simulations to understand mechanisms of jet noise generation Develop a noise prediction method for complex jet configurations (e.g. lobed mixers) that does not depend on experiments Engine flow mixing Lobe scalloping

  4. Jet Noise Simulations Large eddy simulations (LES) + surface integral method for the acoustic far-field Typical Run Time: 5 days to run 50,000 time steps using 200 POWER3 processors on an IBM-SP Typical Grid Size: 12 million points

  5. Jet Noise Modeling Reynolds Averaged Navier-Stokes (RANS) with a two-equation model + noise model based on single jet components

  6. Future Directions • Supersonic jet noise (777, 787, Joint Strike Fighter) • Flows with chevrons • Hybrid methods (detached eddy simulations) for flows with complicated geometries (e.g. mixers, ejectors) • Noise control devices GOAL: - Increase the level of understanding of jet noise in order to develop a quieter design

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