Geometric aspects of turbulent wall-flows
Project Leader: Joseph Klewicki
Staff: Jimmy Philip
Student: Rina Perven
Sponsors: Australian Research Council
Primary Contact: Joseph Klewicki (firstname.lastname@example.org)
Keywords: fluid dynamics; turbulence
Disciplines: Mechanical Engineering
Predicting the complex behaviors of turbulent fluid flow over surfaces in relative motion is central to atmospheric modelling for climate and agriculture, and for reducing fossil fuel usage and its environmental impact. Wall-turbulence statistics have been recently evidenced to organise according to a predictable geometric structure. Can the notorious complexity of turbulent wall-flow dynamics be clarified through its inherent geometry? This research aims to unravel the connections between the statistical geometry of wall-turbulence, and the dynamical interactions of its instantaneous motions, with a broader objective to construct an efficient and theoretically well-founded basis for predicting engineering and atmospheric wall-flows.
The proposed analyses build upon recent findings that the dominant dynamical motions in wall-flows exhibit geometric properties that reflect their emergent self-similar mean dynamics. Existing evidence reveals that these features are not only reflected in the mean flow structure, but remarkably, in rudimentary turbulence statistics as well. This begs the question of how deeply within the turbulence these properties are embedded, and in particular, whether the observed statistical measures reflect ensembles of (approximately) self-similar interactions in the instantaneous flow. The practical implications of the proposed research pertain to developing a sustained capacity to derive new knowledge from the increasingly enormous and complex higher Reynolds number data sets that are now being produced (both numerically and experimentally), and to the development of computationally efficient predictive models that are both grounded in the governing equations, and inherently scale with Reynolds number.