Understanding turbulence for better flow prediction and control

Understanding turbulence for better flow prediction and control Junlin Yuan Favier et al. JFM 09 Lee & Li 13, NASA/JPL ME Retreat, Aug. 22, 2016

Outline Resolving physics Fundamental studies • Integrating important mechanisms; • Calibration database West & Yuan, 2016 Modeling techniques Smooth Rough Design / analysis / control Simulating complex flows using models 2

Fundamental studies Objective - Turbulence response to disturbances? - Coupling mechanisms? § Roughness, pressure gradients, curvature, unsteadiness, rotation, transition, … Acceleration + Deceleration Yuan & Piomelli, Po. F, 2013 Mottaghian, Ph. D thesis, 2015 Mesh Approaches - Problem simplification - Resolved simulation - Manipulation of flow/boundary conditions Yuan & Piomelli, Jo. T, 2014

Fundamental studies Acceleration Eddy Roughness wake Results (a) Low turbulent time scale - Turbulence production & redistribution mechanisms Wake production Enhanced isotropy (b) High turbulent time scale - Physics-based parameterization of topography Sand grains Important role of roughness topography Turbine roughness

Modeling ● Integrating physics in one-point turbulent closures Negative wake field Physics-based Friction Geometry-based Hope for a universal correlation! 5

Design/analysis/control ● Analysis of hydraulic turbine performance Roughness model calibration Accurate loss estimation ● Design of vertical-axis wind turbine Power output calculation Angle-of-attack optimization ● Interested in other fluid-related problems Non-equilibrium, unsteady, complex geometry, . . Yuan et al. , IOP Conf. Series 2014