scnews: "Asia-Pacific Analysis and PDE Seminar: Jorn Wichmann -- Temporal regularity of power-law fluids under stochastic perturbations" by Sanjana Bhardwaj

  Dear friends and colleagues,   

on Monday, 29 May 2023 at
    • 1:00 PM for Beijing, Hong Kong and Perth
    • 02:00 PM for Seoul and Tokyo
   • 03:00 PM for Canberra, Melbourne and Sydney
  • 05:00 PM for Auckland  

Postdoctoral Research Fellow Jörn Wichmann is giving a talk in our Asia-Pacific Analysis and  PDE Seminar on   

Temporal regularity of power-law fluids under stochastic perturbations

Abstract:

Humans have always been interested in fluids. However, many interesting aspects have not been understood yet. In this talk we focus on regularity results for power-law fluids in the regime of laminar flow. These are modelled by the $p$-Stokes system. Already in the absence of turbulence, additional difficulties arise through the non-linear structure of the system as well as the low regularity of the stochastic perturbation. We will elaborate on the difficulties and try to build up an intuition on what regularity is natural. Finally, we present the temporal regularity results and give an application of the natural regularity within the development of numerical algorithms.

Chair: Ben Goldys (Professor @ University of Sydney, Australia)

More information and how to attend this talk can be found at the seminar webpage

Sanjana
On behalf of Daniel H. and Ben

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Webinar Speaker

Jörn Wichmann

Postdoctoral Research Fellow @ School of Mathematical Sciences, University of Monash

Dr. Jörn Wichmann works in the School of Mathematical Sciences at Monash University as a postdoctoral Research Fellow. Before joining Monash University, he did his undergraduate and PhD studies at the University of Bielefeld, Germany. He obtained his PhD in 2022 under the supervision of Prof. Martina Hofmanova and Prof. Lars Diening. In March 2023 he joined Prof. Jerome Droniou and Dr. Ngan Le at Monash University to work on regularity and numerics for non-Newtonian fluids. His main area of interest lies in the design and analysis of numerical methods for the approximation of stochastic nonlinear partial differential equations.