2024/09/02

The PhD committee (from left to right): Patrick Keuchel, research scientist at ZARM; Philipp Schlatter, Chair of Fluid Mechanics at FAU Erlangen-Nürnberg; Daniel Morón, research scientist at ZARM; ZARM Director Marc Avila, Chair of Fluid Mechanics at University of Bremen; IWT Director Lutz Mädler, Professor of Production Engineering at University of Bremen; Miguel Pérez Encinar, visiting professor at Universidad Carlos III de Madrid.

Congratulations to Daniel Morón on his PhD

Daniel Morón Montesdeoca joined the research group "Fluid Simulation and Modeling" at ZARM in January 2020. On September 2, 2024, he successfully defended his PhD thesis entitled "The transitional regime of pulsatile pipe flow". He studies the transition of laminar flows (ordered and regular) to turbulent flows (chaotic and irregular).

Turbulent flows result in increased drag and energy losses. Turbulence is estimated to account for about 10% of energy losses worldwide. Understanding the conditions under which a flow becomes turbulent is therefore critical for industrial applications (such as transporting liquids in pipes), but also in our own bodies, where turbulent blood flow has been linked to cardiovascular disease.

In his research, Daniel Morón studies the mechanisms by which laminar flows transition to turbulence, and how turbulence behaves once triggered. He focuses on the case of flow in a pipe that is pushed with a pulsating force, very similar to the pulsation of our heart. He performs precise simulations using high performance computers (at ZARM and other research institutes) to integrate the complex (partial differential) equations that model the movement of the fluid. His work identifies the characteristics of a pulsation that either promotes or decreases the transition.

Daniel Morón: "During my time at ZARM, I gained profound insights into the intricate nature of turbulence and the challenges of simulating such complex phenomena. I am fascinated by how turbulent flows, and other chaotic systems like the weather, are very sensitive to measurement noises and initial conditions; and how unpredictable they can be."

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