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doc. Mgr. Jan Březina, Ph.D.

doc. Mgr. Jan Březina, Ph.D.
Institute of New Technologies and Applied Informatics (NTI): Academic staff

E-mail:
jan.brezina@tul.cz
Office:
A03002
Tel.:
+420 48535 6804
Specialisation

 

  • continuum-fracture method, a combination of 3D and discrete fractures
  • coupled processes in fractured rocks
  • stochastic simulations:
    • multilevel Monte Carlo method
    • Bayes inversion
  • deep neural networks as simulation surrogates
  • applications:
    • deep underground repositories of radioactive waste
    • enhanced geothermal systems

Software

Flow123d - a simulator of coupled processes in fractured media
BParser - C++ formula parser with Numpy like algebra and SIMD evaluation
Genie - tool for ERT and ST inversions in mines
VISIP - Python based functional language for complex simulations and workflows

 

 

Achieved education

2003 - 2008 doctoral study of mathematics, Charles University in Prague, Faculty of Mathematics and Physics, specialization Mathematical Modeling, Ph.D. thesis: Selected mathematical problems in the thermodynamics of viscous compressible fluids.

2004 - 2007 18 month scholarship "cotutelle de these" provided by the French government at Universite de Sud-Toulon-Var

1998 - 2003 master study of mathematics, Charles University in Prague, Faculty of Mathematics and Physics, specialization Mathematical modelling in physics and technology, Shape optimization of bodies circumfluented by a compressible fluid and connected problems

Publications
  • ŠPETLÍK, M. , and BŘEZINA, J. Convolutional surrogate for 3D discrete fracture-matrix tensor upscaling COMPUTERS & GEOSCIENCES Elsevier BV, 2026, vol. 209, issue MAR. P. neuvedeny (14 stran). ISSN: 0098-3004.
  • BŘEZINA, J. et al. HLAVO [software]. Available from: https://github.com/GeoMop/HLAVO.
  • BŘEZINA, J. , and BURDA, P. Analytical Solution for Darcy Flow in a Bounded Fracture-Matrix Domain Transport in Porous Media Springer, 2024, vol. 151, issue 15. P. 2777 – 2794. ISSN: 0169-3913.
  • ŠPETLÍK, M., BŘEZINA, J. , and LALOY, E. Deep learning surrogate for predicting hydraulic conductivity tensors from stochastic discrete fracture-matrix models COMPUTATIONAL GEOSCIENCES Springer Nature, 2024, vol. 28, issue 6. P. 1425 – 1440. ISSN: 1420-0597.
  • BŘEZINA, J. , and STEBEL, J. Discrete fracture-matrix model of poroelasticity ZAMM Zeitschrift fur Angewandte Mathematik und Mechanik Wiley-VCH GmbH, 2024, vol. 104, issue 4. P. e202200469. ISSN: 0044-2267.

Topics of Student work
  • Generování náhodných fyzikálních polí, NTI, 2025
  • Generování náhodného pole z malé množiny náhodných polí, NTI, 2025
Správa studentských prací a projektů
General partners
  • ČEZ
    ČEZ
  • Škoda Auto
    Škoda Auto
Partners
  • ABB
    ABB
  • Actis
    Actis
  • Adient
    Adient
  • INISOFT
    INISOFT
  • MicroNova
    MicroNova
  • T-MC66
    T-MC66
  • Unicorn
    Unicorn
  • ZF
    ZF
  • Centrum Radius
    Centrum Radius
Schools
  • SPŠ Česká Lípa
    SPŠ Česká Lípa
  • SPŠ a VOŠ Jičín
    SPŠ a VOŠ Jičín
  • SPŠ a VOŠ Liberec
    SPŠ a VOŠ Liberec
  • SOUS Škoda Auto
    SOUS Škoda Auto
  • SPŠ Mladá Boleslav
    SPŠ Mladá Boleslav
  • SPŠ Ústí nad Labem
    SPŠ Ústí nad Labem
  • SOŠ, SPŠ Varnsdorf
    SOŠ, SPŠ Varnsdorf