dr.ir. P. Cifani (Paolo)

I am interested in the (differential) geometric structure of fluid dynamical systems and their statistical properties in relation to turbulence. The quantitative analysis of such complex systems, which span a wide range of scales of motion, requires numerical simulation. From a mathematical viewpoint, it is natural to require for the discrete system to preserve symmetries and invariants of motion of the underlying analytical problem. This is key for a correct representation of fundamental physical mechanisms and their long-time behaviour. The core of my research finds its place in the process that goes from the design of structure-preserving numerical methods all the way to their implementation onto modern supercomputers.

Active collaborations:

Gran Sasso Science Institute, mathematics
Chalmers University of Technology, department of mathematical sciences
Scuola Normale Superiore di Pisa

Engineering & Materials Science

# Channel Flow
# Direct Numerical Simulation
# Turbulence
# Volume Fraction

Physics & Astronomy

# Bubbles
# Channel Flow
# Direct Numerical Simulation

Mathematics

# Direct Numerical Simulation

Main fields of reasearch:

Geometric integration of geophysical flows
Simulation of turbulence
Stochastic Lie transport modeling of fluid systmes

Ephrati, S. R. (2023). Data-driven Stochastic Modeling for Coarsened Computational Geophysical Fluid Dynamics. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036557030

Cifani, P., Viviani, M., & Modin, K. (2023). An efficient geometric method for incompressible hydrodynamics on the sphere. Journal of computational physics, 473, Article 111772. https://doi.org/10.1016/j.jcp.2022.111772

Ephrati, S. R. , Cifani, P., Luesink, E. , & Geurts, B. J. (2023). Data‐Driven Stochastic Lie Transport Modeling of the 2D Euler Equations. Journal of Advances in Modeling Earth Systems, 15(1), Article e2022MS003268. https://doi.org/10.1029/2022MS003268

Cifani, P., Viviani, M., Modin, K. , & Geurts, B. J. (2022). Structure-preserving integration for high-performance DNS of geophysical flows. In DLES 13: 13th ERCOFTAC Workshop on Direct & Large Eddy Simulation, 26-28 October 2022, Udine, Italy ERCOFTAC.

Viviani, M., Modin, K. , Cifani, P. , Ephrati, S. R. , & Geurts, B. J. (2022). Coarse-grained modelling via canonical scale separation in 2D incompressible hydrodynamics. In DLES 13: 13th ERCOFTAC Workshop on Direct & Large Eddy Simulation, 26-28 October 2022, Udine, Italy ERCOFTAC.

Franken, A. D. , Ephrati, S. R. , Cifani, P. , & Geurts, B. J. (2022). DNS of dispersed bubbly Taylor-Couette turbulence. In DLES 13: 13th ERCOFTAC Workshop on Direct & Large Eddy Simulation, 26-28 October 2022, Udine, Italy ERCOFTAC.

Trautner, E., Hasslberger, J. , Cifani, P., & Klein, M. (2022). Volume conservation methods for VOF-based long-term simulations of turbulent bubble-laden flows on coarse grids. In DLES 13: 13th ERCOFTAC Workshop on Direct & Large Eddy Simulation, 26-28 October 2022, Udine, Italy ERCOFTAC.

Biferale, L., Buzzicotti, M. , Geurts, B. J. , Cifani, P., & Leahy, J-M. (2022). Machine learning models for subgrid scale tensors of 2D Rayleigh-Bérnard convection. In DLES 13: 13th ERCOFTAC Workshop on Direct & Large Eddy Simulation, 26-28 October 2022, Udine, Italy ERCOFTAC.

Ephrati, S. R. , Cifani, P. , & Geurts, B. J. (2022). Stochastic data-driven POD-based modeling for high-fidelity coarsening of two-dimensional Rayleigh-Bénard turbulence. Manuscript in preparation. In DLES 13: 13th ERCOFTAC Workshop on Direct & Large Eddy Simulation, 26-28 October 2022, Udine, Italy ERCOFTAC.

Ephrati, S. R., Luesink, E., Wimmer, G. , Cifani, P. , & Geurts, B. J. (2022). Computational modeling for high-fidelity coarsening of shallow water equations based on subgrid data. Multiscale Modeling and Simulation, 20(4). https://doi.org/10.1137/21M1452871

+31534895274

p.cifani@utwente.nl