Fluid Mechanics Tour of the Alps : Coherent structures in natural and forced turbulent jets
Event details
| Date | 07.05.2026 |
| Hour | 10:15 › 11:15 |
| Speaker | Prof. Tim Colonius |
| Location | |
| Category | Conferences - Seminars |
| Event Language | English |
Bio :
Tim Colonius is the Frank and Ora Lee Marble Professor of Mechanical Engineering at the California Institute of Technology. He received his B.S. from the University of Michigan in 1987 and M.S and Ph.D. in Mechanical Engineering from Stanford University in 1988 and 1994, respectively. He and his research team use numerical simulations to study a range of problems in fluid dynamics, including aeroacoustics, flow control, instabilities, shock waves, and bubble dynamics. Prof. Colonius also investigates medical applications of ultrasound and is a member of the Medical Engineering faculty at Caltech. He is a Fellow of the American Physical Society and the Acoustical Society of America. He is the recipient of the AIAA Aeroacoustics Award, the APS Stanley Corrsin Award, and the ASME Freeman Scholar Award.
Abstract :
Across a wide range of engineering and environmental flows, predictive modeling hinges on isolating the components of turbulent motion that evolve coherently in space and time. Turbulence is inherently stochastic, but not all fluctuations contribute equally: a relatively small subset exhibits correlated dynamics and accounts for a disproportionate share of transport, mixing, and noise. This talk presents a framework for identifying, interpreting, and modeling those components in a way that connects statistical description to underlying dynamics. Spectral proper orthogonal decomposition (SPOD) provides a statistically optimal description of structures that evolve coherently in space and time, isolating the dynamically relevant motions embedded within turbulence. When viewed alongside resolvent analysis of the linearized Navier–Stokes equations, a more complete picture emerges: SPOD reveals what the flow does, while the resolvent framework explains why—linking observed structures to amplification mechanisms and to the nonlinear interactions that sustain them. Together, these tools expose how Kelvin–Helmholtz instability, Orr amplification, and lift-up mechanisms compete and interact across frequency and azimuthal wavenumber, illustrated here in the canonical setting of high-speed jets. Building on this interpretation, we show how resolvent models, augmented with eddy-viscosity closures, can predict dominant flow structures directly from the mean flow, offering a practical route toward reduced-order models with predictive capability. Finally, we extend the framework to time-periodic and forced flows using cyclo-stationary statistics, enabling analysis of more realistic, externally driven configurations.
Tim Colonius is the Frank and Ora Lee Marble Professor of Mechanical Engineering at the California Institute of Technology. He received his B.S. from the University of Michigan in 1987 and M.S and Ph.D. in Mechanical Engineering from Stanford University in 1988 and 1994, respectively. He and his research team use numerical simulations to study a range of problems in fluid dynamics, including aeroacoustics, flow control, instabilities, shock waves, and bubble dynamics. Prof. Colonius also investigates medical applications of ultrasound and is a member of the Medical Engineering faculty at Caltech. He is a Fellow of the American Physical Society and the Acoustical Society of America. He is the recipient of the AIAA Aeroacoustics Award, the APS Stanley Corrsin Award, and the ASME Freeman Scholar Award.
Abstract :
Across a wide range of engineering and environmental flows, predictive modeling hinges on isolating the components of turbulent motion that evolve coherently in space and time. Turbulence is inherently stochastic, but not all fluctuations contribute equally: a relatively small subset exhibits correlated dynamics and accounts for a disproportionate share of transport, mixing, and noise. This talk presents a framework for identifying, interpreting, and modeling those components in a way that connects statistical description to underlying dynamics. Spectral proper orthogonal decomposition (SPOD) provides a statistically optimal description of structures that evolve coherently in space and time, isolating the dynamically relevant motions embedded within turbulence. When viewed alongside resolvent analysis of the linearized Navier–Stokes equations, a more complete picture emerges: SPOD reveals what the flow does, while the resolvent framework explains why—linking observed structures to amplification mechanisms and to the nonlinear interactions that sustain them. Together, these tools expose how Kelvin–Helmholtz instability, Orr amplification, and lift-up mechanisms compete and interact across frequency and azimuthal wavenumber, illustrated here in the canonical setting of high-speed jets. Building on this interpretation, we show how resolvent models, augmented with eddy-viscosity closures, can predict dominant flow structures directly from the mean flow, offering a practical route toward reduced-order models with predictive capability. Finally, we extend the framework to time-periodic and forced flows using cyclo-stationary statistics, enabling analysis of more realistic, externally driven configurations.
Practical information
- General public
- Free