The goal of this project is to discover new fundamental phenomena in turbulent flow by generating new high fidelity data and by making these new data available to the whole scientific community of the Nation. Basic features of turbulence that depend on the multiple time and length scales observed in turbulent flows will be explored, and software tools that enable such analysis will be developed and offered to the research community.
Lagrangian chaos and transition to turbulence will be studied using datasets arising from massive computer simulations that are ingested into web-accessible, open numerical laboratories. It is known that the transition to turbulence occurs through a sequence of phenomena characterized by high spatio-temporal complexity. However, very little is known about how Lagrangian chaos manifests itself at the multiple scales of turbulence, and how transitional behavior of turbulence may be better characterized. Turbulence also is known to contain vortical structures at the smallest scales, and at large-scales. This project aims to answer fundamental questions about the hierarchical organization of vortical structures at multiple scales and their relationship to the energy cascade. The co-PIs have developed an open, computational data-enabled turbulence laboratory where the entire space-time data is available to the wider research community. The project will further develop multiscale versions of the 4D flow datasets, effectively adding a 5th dimension (scale) to the data. While the currently available resource at Johns Hopkins is focused on isotropic turbulence, the proposed effort will extend the data to other more complex cases than isotropic turbulence, like channel flow data. Availability of data and availability of analysis tools will enable a step change in turbulence research, possibly transforming the way researchers work in this area by democratizing access to high-quality simulation data. Educational modules, mostly based on Matlab, will also allow students to query simulation datasets in unprecedented detail.
