UniEqTURB SIGNED

Project "UniEqTURB" data sheet

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 Project objective

Turbulence is at a crossroads: The old, established ideas of Richardson and Kolmogorov have with accumulating evidence come under renewed scrutiny, especially in non-stationary and non-equilibrium flows. Many in the community seek new and more accurate ways to describe turbulence. This is a time of re-evaluation and opportunity!

The assumed statistical equilibrium of the smallest and intermediate scales is identified as the main cause of the potentially erroneous deductions. This problem was not previously noticed because experiments that confirmed the previous theories were all in statistical equilibrium. And those experiments and theories which disagreed were labelled ‘anomalous’, no matter how carefully performed or argued.

The proposed theory-intensive approach will therefore specifically use non-equilibrium and statistically non-stationary flows to: 1. Investigate the underlying mechanisms determining the level of dissipation 2. Quantify the resulting effects on the balance equations of central importance 3. Test the results against the established, as well as competing, theories

I will use stationary and accelerating jets well-suited for studying the non-linear interactions and quantifying departures to the assumed equilibrium and the non-stationary dissipation. The feasibility is demonstrated with preliminary results. The databases which will be established should contribute substantially to settling the long-lived ultimate question of turbulence: what are the true underlying mechanisms that set the level of dissipation.

The results will be ground breaking scientifically and economically. The impact for engineering applications is extensive, since Kolmogorov-based turbulence models are routinely used, and since developing flows constitute the rule rather than the exception in the majority of engineering applications. The potential economic consequences for e.g. transportation, climate predictions and power extraction are impossible to underestimate.