Young Investigator Group Advanced Modeling and Simulation of Transfer Processes for Next Generation Energy Systems

Research Group Lead:   Dr. rer. nat. Marten Klein  

Room 3.02, Building AZFD, Main Campus Cottbus, Siemens-Halske-Ring 15A, 03046 Cottbus, Germany  -  e-mail


Key competences

• Development, analysis, and application of efficient stochastic and multiscale approaches in CFD
• Modeling and simulation of complex mixing in turbulent flows

Research focus

• Heat transfer in heat pumps and heat exchangers
• Fluctuating wind fields in atmospheric boundary layers
• Muliphysics boundary layers in electrochemical reactors


The Young Investigator Group (YIG) Advanced Modeling and Simulation of Transfer Processes for Next Generation Energy Systems exists since 16 September 2022. It is part of the Scientific Computing Lab (SC Lab) at the Energy Innovation Center (EIZ) funded by the Federal Ministry of Education and Research (BMBF). The YIG is hosted by the Chair of Numerical Fluid and Gas Dynamis of BTU Cottbus-Senftenberg. The predecessor of the YIG was the Stochastic Modelling and Simulation of Atmospheric Boundary Layer Processes division.

The YIG performs research in the direction of new modeling strategies for applications in the energy sector in which an accurate representation of fluctuations and small-scale prozesses is crucial. The research focuses on wind energy applications, such as time-resolved volatiliy analysis and prediction dependent on location by an account of atmospheric boundary layer processes. Further research topics of the YIG address mixing-dependent and transfer-limited energy applications in which boundary layers and turbulence need to be considered. This includes but is not limited to heat exchangers and heat pipes, chemical and catalytic reactors for liquid and gas phase precipitation/deposition, as well as electrochemically affected flows in electrolyte batteries or at membranes.

Altogether, research activities are focusing on the detailed but economical modeling and simulation of coupled mass, momentum, and heat transport in free and wall-bounded shear flows, jets, rotating and stratified boundary layers, as well as free and forced convection. We strive to numerically more accurately capture fundamental statistical properties of theses flows by utilizing physics-based forward modeling approaches. The fundamental research outcome consists of new numerical tools for and physical insight that can be transfered to various energy application cases.

Numerical challenges are due to

  • turbulence,
  • multiscale dynamics,
  • scale interactions and intermittency,
  • multiphysics  phenomena, as well as
  • fluid-wall (fluid-surface) interactions.

Advanced (next generation) modeling approaches should be numerically efficient, have predictive capabilities, but should also respect fundamental physical principles. Reduced-order modeling is used here to achieve this goal by focusing on the representation of the key dynamical properties on all relevant scales of the flow problem at hand. Stochastic turbulence modeling approaches (e.g., HiPS, ODT, AME) are utilized for idealized flows and then further developed by the YIG members for the application cases at hand.

In addition to stochastic modeling, also estsablished Large-Eddy Simulation (LES) and finestructure-resolving Direct Numerical Simulation (DNS) are used, e.g., to obtain reference solutions. The mid-term goal is to couple LES-based approaches with the new stochastic methods in order to provide a cost-efficient high-fidelity simulation tool for energy applications.

Team

M.Sc. Pei-Yun Tsai (Research Associate, PreDoc)

B.Sc. Robert Kessler (Study Project Intern)

B.Sc. Maharun Nesa Shampa (Student Research Assistant)

Alumni

B.Sc. Roshni Bhatia

M.Sc. Sreenivasa Chary Thatikonda

B.Sc. Thierry Tchouto

B.Sc. Sascha Zell

B.Sc. Roland E. Maier

M.Sc. Christian Zenker

Relevant publications

2022

  • M. Klein, and H. Schmidt. Exploring stratification effects in stable Ekman boundary layers using a stochastic one-dimensional turbulence model. Adv. Sci. Res., 19:117–136, 2022. In: Special Issue “21st EMS Annual Meeting – virtual: European Conference for Applied Meteorology and Climatology 2021”. DOI: 10.5194/asr-19-117-2022
  • M. Klein, J. A. Medina Méndez, and H. Schmidt. Modeling electrohydrodynamically enhanced drag in channel and pipe flows using one-dimensional turbulence. In: Janos Vad (Ed.), Proc. Conference on Modelling Fluid Flow (CMFF’22), 18:82–91, CMFF22-015, 2022. University of Technology and Economics, Department of Fluid Mechanics, Budapest, Hungary. ISBN 978-9634218814. URL: https://www.cmff.hu/pdf/CMFF22_Conference_Proceedings.pdf
  • M. Klein, C. Zenker, T. Starick, and H. Schmidt. Stochastic modeling of three-scalar mixing in a coaxial jet using one-dimensional turbulence. In: Proc. TSFP-12, Osaka (online), Japan, July 2022. Session 13C, Jets II, ID 208.
  • S. Sharma, M. Klein, and H. Schmidt. Features of far-downstream asymptotic velocity fluctuations in a round jet: A one-dimensional turbulence study. Phys. Fluids, 34:085134, 2022. DOI: 10.1063/5.0101270.
  • M. Klein, H. Schmidt, and D. O. Lignell. Stochastic modeling of surface scalar-flux fluctuations in turbulent channel flow using one-dimensional turbulence. Int. J. Heat Fluid Flow, 93:108889, 2022. In: Special Issue "Wall-bounded Reactive Flows '21". DOI: 10.1016/j.ijheatfluidflow.2021.108889. Preprint: arXiv:2111.15359

2021

  • M. Klein, and H. Schmidt. Stochastic modeling of passive scalars in turbulent channel flows: predictive capabilities of one-dimensional turbulence. In: A. Dillmann, G. Heller, E. Krämer, C. Wagner (Eds.), New Results in Numerical and Experimental Fluid Mechanics XIII, volume 151 of Notes on Numerical Fluid Mechanics and Multidisciplinary Design, Springer Nature, Cham, 2021, pp. 47–57. STAB/DGLR Symposium 2020. URL: https://link.springer.com/chapter/10.1007%2F978-3-030-79561-0_5. doi:10.1007/978-3-030-79561-0_5. Preprint: arXiv:2011.04818
  • M. Klein, and H. Schmidt. Investigating Schmidt number effects in turbulent electroconvection using one-dimensional turbulence. Proc. Appl. Math. Mech., 21:e202100147, 2021. DOI: 10.1002/pamm.202100147
  • M. Klein, Roland E. Maier, and H. Schmidt. Stochastic modeling of transient neutral and stably-stratified Ekman boundary layers. Proc. Appl. Math. Mech., 21:e202100146, 2021. DOI: 10.1002/pamm.202100146
  • S. Sharma, M. Klein, and H. Schmidt. Modelling turbulent jets at high-Reynolds number using one-dimensional turbulence. AIAA 2021-2104. AIAA AVIATION 2021 FORUM. August 2021. URL: https://arc.aiaa.org/doi/10.2514/6.2021-2104
  • M. Klein, C. Zenker, K. Hertha, and H. Schmidt. Modeling one and two passive scalar mixing in turbulent jets using one-dimensional turbulence. In: WCCM-ECCOMAS 2020, published online, 2021. URL: https://www.scipedia.com/public/Klein_et_al_2021a
  • H. Schmidt, J. A. Medina Méndez, and M. Klein. EHD Turbulence in channel flows with inhomogeneous electrical fields: a one-dimensional turbulence study. In: WCCM-ECCOMAS 2020, published online, 2021. URL: https://www.scipedia.com/public/Schmidt_et_al_2021a
  • J. A. Medina Méndez, M. Klein, and H. Schmidt. The one-dimensional turbulence aspects of internal forced convective flows. In: WCCM-ECCOMAS 2020, published online, 2021. URL: https://www.scipedia.com/public/Mendez_et_al_2021a

2020

  • M. V. Kurgansky, T. Seelig, M. Klein, A. Will, and U. Harlander. Mean flow generation due to longitudinal librations of sidewalls of a rotating annulus. Geophys. Astro. Fluid Dyn.114(6), 742–762, 2020. DOI: 10.1080/03091929.2019.1692829
  • M. Klein, and H. Schmidt. Towards a stochastic model for electrohydrodynamic turbulence with application to electrolytes. Proc. Appl. Math. Mech., 20:e202000128, 2020. DOI: 10.1002/pamm.202000128
  • M. Klein, and H. Schmidt. A stochastic modeling strategy for intermittently unstable Ekman boundary layers. Proc. Appl. Math. Mech., 20:e202000127, 2020. DOI: 10.1002/pamm.202000127

2019

  • M. Vincze, N. Fenyvesi, M. Klein, J. Sommeria, S. Viboud, and Y. Ashkenazy. Evidence for wind-induced Ekman layer resonance based on rotating tank experiments. EPL, 125:44001, 2019.
  • J. A. Medina Méndez, M. Klein, and H. Schmidt. One-dimensional turbulence investigation of variable density effects due to heat transfer in a low Mach number internal air flow. Int. J. Heat Fluid Flow, 80:108481, 2019.
  • Rakhi, M. Klein, J. A. Medina M., and H. Schmidt. One-dimensional turbulence modeling of incompressible temporally developing turbulent boundary layers with comparison to DNS. J. Turbul., 20(8):506–543, 2019.
  • M. Klein, C. Zenker, and H. Schmidt. Small-scale resolving simulations of the turbulent mixing in confined planar jets using one-dimensional turbulence. Chem. Eng. Sci., 204:186–202, 2019.
  • M. Klein, and H. Schmidt. Investigating Rayleigh–Bénard convection at low Prandtl numbers using one-dimensional turbulence modeling. In: 11th Int. Symp. Turb. Shear Flow Phen. (TSFP11), 1:1–6, 2019.

2018

  • A. Ghasemi, M. Klein, A. Will, and U. Harlander. Mean flow generation by an intermittently unstable boundary layer over a sloping wall. J. Fluid Mech., 853:111–149, 2018.
  • D. O. Lignell, V. Lansinger, J. Medina, M. Klein, A. R. Kerstein, H. Schmidt, M. Fistler, and M. Oevermann. One-dimensional turbulence modeling for cylindrical and spherical flows: model formulation and application. Theo. Comp. Fluid Dyn., 32(4):495–520, 2018.
  • M. Klein, H. Schmidt, and D. O. Lignell. Map-based modeling of high-Rayleigh-number turbulent convection in planar and spherical confinements. In: Conf. Model. Fluid Flow (CMFF’18), J. Vad (Ed.), 2018. ISBN: 978-963313297-5
  • M. Klein, and H. Schmidt. Investigating the Reynolds number dependency of the scalar transfer to a wall using a stochastic turbulence model. Proc. Appl. Math. Mech., 18:e201800238, 2018.

2017

  • M. Klein, and H. Schmidt. Stochastic modeling of passive scalar transport in turbulent channel flows at high Schmidt numbers.In: 10th Int. Symp. Turb. Shear Flow Phen. (TSFP10), 1:1B-2, 2017.
  • M. Klein, and H. Schmidt. Stochastic modeling of passive scalar transport at very high Schmidt numbers. Proc. Appl. Math. Mech., 17(1):639–640, 2017.

2016

  • M. Klein (2016). Inertial wave attractors, resonances, and wave excitation by libration: direct numerical simulations and theory. Ph.D. thesis. Faculty 2, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany. Published online. URN: http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-41712
  • A. Ghasemi, M. Klein, U. Harlander, E. Schaller, and A. Will. Mean flow generation by Görtler vortices in a rotating annulus with librating side-walls. Phys. Fluids, 28(5):055603, 2016.

2014

  • M. Klein, T. Seelig, M. V. Kurgansky, A. Ghasemi, I. D. Borcia, A. Will, E. Schaller, C. Egbers, and U. Harlander. Inertial wave excitation and focusing in a liquid bounded bounded by a frustum and a cylinder. J. Fluid Mech., 751:255–297, 2014.