Christos Pervolianakis


Faculty of Mathematics and Computer Science
Friedrich-Schiller Universität Jena
Ernst-Abbe-Platz 2
Jena
Germany

Room: 3533
Tel.: +49 (0) 3641-9-46133
E-mail: christos.pervolianakis AT uni-jena.de

I am a postdoctoral researcher (Wissenschaftlicher Mitarbeiter) in the group of Prof. Dr. Dietmar Gallistl at Friedrich Schiller University Jena.

Teaching

Current teaching (Winter Semester 2024/25)
Past teaching
  • Exercises, at Department of Mathematics & Applied Mathematics, University of Crete,

Research

My research interests include:

  • numerical analysis
  • numerical solution of partial differential equations with finite element method
  • a posteriori error estimation and adaptivity

Publications

Peer-reviewed
Pre-prints
  • (2022, with P. Chatzipantelidis) Error analysis of a backward Euler positive preserving stabilized scheme for a Chemotaxis system. [Arxiv]
  • (2024) Error analysis of an Algebraic Flux Correction Scheme for a nonlinear Scalar Conservation Law Using SSP-RK2. [Arxiv]
  • (2024) A numerical study for the second order modified Patankar-Runge-Kutta method applied to a Chemotaxis system, submitted.
  • (2024) Error analysis of a positivity preserving numerical scheme for a viscous Hamilton-Jacobi equation, submitted.

Lecture Material

Lecture notes

Here you may find lecture notes from classes that I have taught. (Under construction)

  • Notes of numerical methods of ODEs
  • Notes of numerical methods of PDEs
Programming codes

Here you may find some collection of programming exercises and their solution that used during my lectures.

  • Approximating Ordinary Differential Equations. Some solved exercises.
    • Explicit Euler: pdf and here its implemetantion in Python.

    • Implicit Euler with Newton method: pdf and here its implemetantion in Python.

    • Explicit Euler (System): pdf and here its implemetantion in Python.

    • Implicit Euler with Newton method (System): pdf and here its implemetantion in Python.

    • Lotka-Volterra Equations: pdf and here its implemetantion in Python with Explicit Euler and Implicit Midpoint Method.

    • Explicit Multistep Methods (Adams-Bashforth): pdf and the implemetantion in Python of the corresponding cases for a scalar ODE Case 1, Case 2, Case 3 the implemetantion in Python of the corresponding cases for a system ODE Case 1, Case 2, Case 3.


  • Approximating Partial Differential Equations with Finite Element Method (Soon)
Plain Academic