Numerical modeling and simulations

Institute of Space Systems

The numerical modeling and simulations at the IRS deals with the properties and effects of gas flows in re-entry processes. A specialty of the institute is the simulation code "PICLas" with its spin-off company "boltzplatz".

Entry missions into the atmospheres of planets and those of other celestial bodies represent future goals in space travel. They can only be safely accomplished with improved knowledge of the behavior, properties, and effects of gas flows around spacecrafts. Additionally, the design of advanced space propulsion systems requires a sound knowledge of the behavior of the engine exhaust gas stream. Numerical methods enable the possibility to simulate flows, where suitable experiments are usually very limited or associated with high costs. Therefore, numerical investigation methods are gaining more importance.

Simulation of the DLR-REX-Free Flyer
Simulationen of the DLR-REX-Free Flyer

One focus of the "Numerical modeling and simulation" group is modeling non-equilibrium effects in gases and plasmas. These always occur when large local differences in surrounding conditions are involved, e.g. large temperature differences. Examples related to space travel have been mentioned considering entry missions or space propulsion systems. However, understanding these effects also becomes increasingly important in other industrial sectors. The spectrum ranges from micro- and nanotechnology, including plasma-based coating processes for nanotechnology production itself, to next-generation lithography.

Within a cooperation between the Institute of Space Systems (IRS) and the Institute of Aerodynamics and Gas Dynamics (IAG), the particle code "PICLas" is being developed as a flexible simulation tool to calculate three-dimensional gas and plasma flows. Meanwhile, the company "boltzplatz" has established itself as a university spin-off, founded by former employees of the numerics departments of IRS and IAG. This ensures a direct exchange between industry and university as well as a continuously growing number of users of PICLas in either field. More information and contact details can be found at the boltzplatz homepage.

Simulation of an atmospheric entry at Titan
Simulation of an atmospheric entry at Titan

PICLas couples different field and particle solvers to provide numerically efficient solution methods in different gas and plasma regimes. Since PICLas historically started as a tool for simulating diluted gases and plasmas, its two largest components are the Particle-In-Cell (PIC) and the Direct Simulation Monte Carlo (DSMC) modules. While the PIC part models electromagnetic interactions of particles in plasmas, the DSMC part models collisions and chemical reactions. Both methods have been used for many years in a wide range of numerical applications and are constantly being developed.

Another development of PICLas deals with the numerical investigation of flows and plasmas in the context of multiscale phenomena. This includes for example extremely large density gradients as they occur in nozzle expansions. Another example are large temporal gradients of the physical effects occurring in the flows. The time scales of plasma oscillation and advection of ions, which is relevant in electric space propulsion systems, can be several orders of magnitude apart. For these purposes, different particle-continuum methods like the Bhatnagar-Gross-Krook (BGK) or the Fokker-Planck method are being coupled with PIC and DSMC. In addition, various implicit procedures are being developed to further increase the effectiveness of the implemented methods.
Furthermore, in some of the flows under investigation, radiation effects play an important role. Therefore, the working group also deals separately with the further development of radiative energy transfer solvers.

Various applications simulated with PICLas

Streamer formation in a spark plug

Laser-plasma interaction

Entering the Titan atmosphere

Gyrotron microwave generator

Ion thruster

Current projects

The Collaborative Research Center (CRC) 1667 “ATLAS - Advanced Technologies of Very Low Altitude Satellites” deals with the scientific and technical challenges for the development of very low Earth orbits (VLEO, about 200 km to 450 km altitude). As part of the ATLAS project, the Numerics Group is developing detailed gas-surface interaction model and conducting numerical studies of VLEO test facilities.

ATLAS

Recently Completed Projects

European Research Council

The objective is to develop particle-based multiscale methods for thermo-chemical non-equilibrium gas and plasma flows, which for the first time enable the simulation of a large number of high-tech applications.

MEDUSA

DROPIT is a research training group that deals with the investigation of droplet interaction phenomena. The aim is to understand how microscale transport processes influence macroscopic flow properties.

GRK 2160/2: DROPIT

Numerical methods

Stochastic particle methods are the focus of the numerics group at the IRS. They often offer advantages, especially for higher-dimensional problems such as the solution of the Boltzmann equation.

 

Particle methods

The development of noise reduction methods for stochastic particle methods is of great importance for slow or low-mach flows.

 

Discrete Velocity Methods

During atmospheric entry, spacecraft encounter high enthalpy flow. This ionizes and excites internal degrees of freedom in atoms and molecules, causing radiation that significantly affects surface heat flux. The PICLas radiation module uses a Monte Carlo method for accurate energy transfer in complex geometries, ensuring precise heat flux predictions.

 

Radiation solver and radiative energy transfer solver

Heat shields are essential for atmospheric spacecraft entry. The choice of material is crucial for extreme conditions and weight minimization. Heterogeneous processes between gas and surface influence the heat flow. A catalytic reaction model developed in PICLas estimates this influence, as experiments are cost-intensive.

 

Surface chemistry

Very Low Earth Orbit (VLEO), typically defined as altitudes below 450 km, presents unique challenges and opportunities for satellite missions. One of the critical aspects of operating in VLEO is understanding gas-surface interactions, which significantly impact the design and operation of satellites.

 

GSI-Model in VLEO

Particle-based multiphase methods offer an efficient way to visualize non-equilibrium effects in multiphase flows.

 

Particle-based multiphase methods

Plasma effects play a major role in highly enthalpy flows. The Particle-In-Cell method is therefore used to simulate non-equilibrium effects in plasmas.

 

Particle-In-Cell

Plasma Kinetic Code PICLas

All models developed within the numerics group are available on GitHub in the open source code PICLas. In addition, detailed documentation can be found at piclas.readthedocs.io. 

PICLas Logo

Publications

  1. 2026

    1. 1. N. Barth et al., “PICLas-Based Intake Simulation Activities for the Development of an ABEP Specular Intake,” in Rarefied Gas Dynamics, M. Grabe, G. Oblapenko, and M. Torrilhon, Eds., Cham: Springer Nature Switzerland, 2026, pp. 203–211. doi: https://doi.org/10.1007/978-3-032-00094-1_20.
    2. 2. C. H. B. Civrais, M. Pfeiffer, C. White, and R. Steijl, “Vibronic Modelling in Direct Simulation Monte Carlo,” in Rarefied Gas Dynamics, M. Grabe, G. Oblapenko, and M. Torrilhon, Eds., Cham: Springer Nature Switzerland, 2026, pp. 531–539.
    3. 3. F. Garmirian and M. Pfeiffer, “Combining Stochastic Particle BGK and Discrete Velocity Method for Efficient Multiscale Simulations,” in Rarefied Gas Dynamics, M. Grabe, G. Oblapenko, and M. Torrilhon, Eds., Cham: Springer Nature Switzerland, 2026, pp. 481–489.
    4. 4. S. Lauterbach, S. Fasoulas, and M. Pfeiffer, “Adaptive Particle Discretization Methods for Multiscale Non-equilibrium Flows,” in Rarefied Gas Dynamics, Cham: Springer Nature Switzerland, 2026, pp. 629–637.
    5. 5. T. Ott, H. Gorji, and M. Pfeiffer, “An Improved Particle Scheme for Solving Fokker-Planck Models of the Boltzmann Equation,” in Rarefied Gas Dynamics, M. Grabe, G. Oblapenko, and M. Torrilhon, Eds., Cham: Springer Nature Switzerland, 2026, pp. 491–500.
    6. 6. M. Schütte, I. Hörner, S. Löhle, S. Fasoulas, and M. Pfeiffer, “Numerical Simulation of the Flow Field Around a Sounding Rocket for the PMWE Project,” in Rarefied Gas Dynamics, M. Grabe, G. Oblapenko, and M. Torrilhon, Eds., Springer Nature Switzerland, 2026, pp. 193–201.
    7. 7. F. Tuttas and M. Pfeiffer, “Comparison of Stochastic BGK and FP Methods for the Simulation of Non-Equilibrium Multi-species Molecular Gas Flows,” in Rarefied Gas Dynamics, M. Grabe, G. Oblapenko, and M. Torrilhon, Eds., Cham: Springer Nature Switzerland, 2026, pp. 421–429. doi: 10.1007/978-3-032-00094-1_40.

  2. 2025

    1. 8. N. Barth et al., “Solar activity dependency of a specular intake for an ABEP system,” Journal of electric propulsion, vol. 4, p. 57, 2025, doi: 10.1007/s44205-025-00157-7.
    2. 9. C. H. B. Civrais, M. Pfeiffer, C. White, and R. Steijl, “Development of a chemistry model for vibronically excited species in direct simulation Monte Carlo,” Physics of fluids, vol. 37, Art. no. 10, 2025, doi: 10.1063/5.0295298.
    3. 10. K.-S. Ellenberger, A. Schlitzer, M. Pfeiffer, and S. Fasoulas, “Numerical Study on the Setup of an Atomic Oxygen Ground Testing Facility,” in 3rd International Conference on Flight Vehicles, Aerothermodynamics and Re-entry (FAR), May 2025. [Online]. Available: https://www.researchgate.net/publication/393786584_NUMERICAL_STUDY_ON_THE_SETUP_OF_AN_ATOMIC_OXYGEN_GROUND_TESTING_FACILITY
    4. 11. F. Garmirian and M. Pfeiffer, “Implementation of asymptotic preserving discrete velocity methods into the simulation code PICLas,” Computer physics communications, vol. 314, Art. no. September, 2025, doi: 10.1016/j.cpc.2025.109648.
    5. 12. S. Lauterbach, S. Fasoulas, and M. Pfeiffer, “Modeling of heterogeneous catalytic reactions with the simulation tool PICLas,” Computer physics communications, vol. 311, p. 109560, 2025, doi: 10.1016/j.cpc.2025.109560.
    6. 13. T. Ott and M. Pfeiffer, “Coupled PIC-DSMC Simulation of Hypersonic Reentry Flows with Ionization,” in 3rd International Conference on Flight Vehicles, Aerothermodynamics and Re-entry (FAR), 2025.
    7. 14. M. Pfeiffer, F. Garmirian, and T. Ott, “Crank-Nicolson Bhatnagar-Gross-Krook integrator for multiscale particle-based kinetic simulations,” Physics of fluids, vol. 37, Art. no. 2, 2025, doi: 10.1063/5.0251345.
    8. 15. M. Schütte, S. Hocker, H. Lipp, J. Roth, S. Fasoulas, and M. Pfeiffer, “A machine learning framework for scattering kernel derivation using molecular dynamics data in very low Earth orbit,” Physics of Fluids, Sep. 2025, doi: 10.1063/5.0287359.
    9. 16. M. Schütte, S. Fasoulas, and M. Pfeiffer, “Enhanced gas-surface scattering modeling for VLEO satellites in DSMC simulations,” CEAS Space Journal, Jun. 2025, doi: 10.1007/s12567-025-00629-4.
    10. 17. R. Tietz, R. Stierle, K. S. Ellenberger, S. Fasoulas, and M. Pfeiffer, “A Multi-Species Enskog-Vlasov Solver to Determine Evaporation Coefficients of Fluids in High Pressure Environments.” arXiv, 2025. doi: 10.48550/ARXIV.2506.22162.
    11. 18. F. Turco, C. Traub, M. Schütte, M. Pfeiffer, and S. Fasoulas, “Assessment of the Practicality of Optimal Aerodynamic Orbit Control in VLEO,” in IAF Astrodynamics Symposium : held at the 76th International Astronautical Congress (IAC 2025) : Sydney, Australia, 29 September-3 October 2025, Curran Associates, Inc., 2025, pp. 312–325. doi: 10.52202/083087-0029.
    12. 19. F. Tuttas and M. Pfeiffer, “Modeling of Particle-Based BGK Methods for the Simulation of Chemically Reactive Gas Mixtures in Multi-Scale Flows,” May 2025. [Online]. Available: https://www.researchgate.net/publication/391316219_Modeling_of_Particle-Based_BGK_Methods_for_the_Simulation_of_Chemically_Reactive_Gas_Mixtures_in_Multi-Scale_Flows
    13. 20. F. Tuttas and M. Pfeiffer, “Multi-Scale Gas Kinetic Simulations for Chemically Reactive Flows.” 22nd International Planetary Probe Workshop, 2025. doi: 10.13140/RG.2.2.16441.28000.

  3. 2024

    1. 21. J. Beyer, P. Nizenkov, S. Fasoulas, and M. Pfeiffer, “Simulation of Radiating Non-equilibrium Flows around a Capsule Entering Titan′s Atmosphere,” in 32nd International Symposium on Rarefied Gas Dynamics, R. S. Myong, K. Xu, and J.-S. Wu, Eds., in AIP Conference Proceedings. American Institute of Physics, 2024, p. 200002. doi: 10.1063/5.0187531.
    2. 22. C. H. B. Civrais, M. Pfeiffer, C. White, and R. Steijl, “Modeling of the electronic excited states in high-temperature flows,” Physics of fluids, vol. 36, Art. no. 8, 2024, doi: 10.1063/5.0215853.
    3. 23. F. Garmirian, H. Gorji, and M. Pfeiffer, “Exponential BGK Integrator for Multiscale Flow Simulation,” in 32nd International Symposium on Rarefied Gas Dynamics, R. S. Myong, K. Xu, and J.-S. Wu, Eds., in AIP Conference Proceedings. American Institute of Physics, 2024, p. 60005. doi: 10.1063/5.0187429.
    4. 24. G. Herdrich et al., “System design study of a VLEO satellite platform using the IRS RF helicon-based plasma thruster,” Acta Astronautica, Feb. 2024, doi: 10.1016/j.actaastro.2023.11.009.
    5. 25. F. Hild and M. Pfeiffer, “Multi-species modeling in the particle-based ellipsoidal statistical Bhatnagar-Gross-Krook method including internal degrees of freedom,” Journal of Computational Physics, vol. 514, p. 113226, 2024, doi: 10.1016/j.jcp.2024.113226.
    6. 26. F. Hild and M. Pfeiffer, “Simulation of Multi-species Non-equilibrium Gas Flows with the Particle-based Ellipsoidal Statistical Bhatnagar-Gross-Krook Method,” in 32nd International Symposium on Rarefied Gas Dynamics, R. S. Myong, K. Xu, and J.-S. Wu, Eds., in AIP Conference Proceedings, vol. 2996. American Institute of Physics, 2024, p. 60001. doi: 10.1063/5.0187423.
    7. 27. S. Lauterbach, S. Fasoulas, and M. Pfeiffer, “Surface Chemistry Modeling ith the SimulationTool PICLas,” in 32nd International Symposium on Rarefied Gas Dynamics, R. S. Myong, K. Xu, and J.-S. Wu, Eds., in AIP Conference Proceedings, vol. 2996. American Institute of Physics, 2024, p. 80011. doi: 10.1063/5.0187425.
    8. 28. C. Marianowski, C. Traub, M. Pfeiffer, J. Beyer, and S. Fasoulas, “Satellite design optimization for differential lift and drag applications,” CEAS space journal, 2024, doi: 10.1007/s12567-024-00550-2.
    9. 29. M. Pfeiffer et al., “Numerical simulation of an iron meteoroid entering into Earth’s atmosphere using DSMC and a radiation solver with comparison to ground testing data,” Icarus, vol. 407, p. 115768, 2024, doi: 10.1016/j.icarus.2023.115768.
    10. 30. R. Tietz, S. Fasoulas, and M. Pfeiffer, “Symmetric Simulations of Droplets with a Particle based Vlasov-Enskog-Solver,” in 32nd International Symposium on Rarefied Gas Dynamics, R. S. Myong, K. Xu, and J.-S. Wu, Eds., in AIP Conference Proceedings. American Institute of Physics, 2024, p. 120002. doi: 10.1063/5.0187426.

  4. 2023

    1. 31. F. Garmirian and M. Pfeiffer, “Exponential Differencing BGK Method for Multiscale Flow Simulation,” 2023, doi: 10.13009/EUCASS2023-615.
    2. 32. T. Ott and M. Pfeiffer, “PIC schemes for multi-scale plasma simulations,” 2023, doi: 10.13009/EUCASS2023-770.

  5. 2022

    1. 33. J. Beyer, M. Pfeiffer, and S. Fasoulas, “Non-equilibrium radiation modeling in a gas kinetic simulation code,” Journal of quantitative spectroscopy & radiative transfer, vol. 280, Art. no. April, 2022, doi: 10.1016/j.jqsrt.2022.108083.
    2. 34. F. Hild, C. Traub, M. Pfeiffer, J. Beyer, and S. Fasoulas, “Optimisation of satellite geometries in Very Low Earth Orbits for drag minimisation and lifetime extension,” Acta astronautica, vol. 201, Art. no. December, 2022, doi: 10.1016/j.actaastro.2022.09.032.
    3. 35. F. Hild, M. Pfeiffer, C. Traub, J. Beyer, and S. Fasoulas, “Results of a VLEO Satellite Design Optimisation for Drag Minimisation,” in 2nd International Conference on Flight Vehicles, Aerothermodynamics and Re-entry Missions & Engineering (FAR), Heilbronn, Germany, Jun. 2022. [Online]. Available: https://www.researchgate.net/publication/362620800_Results_of_a_VLEO_Satellite_Design_Optimisation_for_Drag_Minimisation
    4. 36. P. Kopper, S. M. Copplestone, M. Pfeiffer, C. Koch, S. Fasoulas, and A. Beck, “Hybrid parallelization of Euler-Lagrange simulations based on MPI-3 shared memory,” Advances in engineering software, vol. 174, Art. no. December, 2022, doi: 10.1016/j.advengsoft.2022.103291.
    5. 37. J. Mathiaud, L. Mieussens, and M. Pfeiffer, “An ES-BGK model for diatomic gases with correct relaxation rates for internal energies,” European journal of mechanics. B, Fluids, vol. 96, Art. no. November/December, 2022, doi: 10.1016/j.euromechflu.2022.07.003.
    6. 38. M. Pfeiffer, “An optimized collision-averaged variable soft sphere parameter set for air, carbon, and corresponding ionized species,” Physics of fluids, vol. 34, Art. no. 11, 2022, doi: 10.1063/5.0118040.
    7. 39. M. Pfeiffer, F. Garmirian, and M. H. Gorji, “Exponential Bhatnagar-Gross-Krook integrator for multiscale particle-based kinetic simulations,” Physical review. E, Statistical, nonlinear, and soft matter physics, vol. 106, Art. no. 2, 2022, doi: 10.1103/PhysRevE.106.025303.

  6. 2021

    1. 40. P. Kopper, M. Pfeiffer, S. Copplestone, and A. Beck, “An efficient halo approach for Euler-Lagrange simulations based on MPI-3 shared memory,” in HPC Asia 2021: The International Conference on High Performance Computing in Asia-Pacific Region Companion, Association for Computing Machinery, 2021, pp. 3–4. doi: 10.1145/3440722.3440904.
    2. 41. M. Pfeiffer, A. R. Mirza, and P. Nizenkov, “Multi-species modeling in the particle-based ellipsoidal statistical Bhatnagar–Gross–Krook method for monatomic gas species,” Physics of fluids, vol. 33, Art. no. 3, 2021, doi: 10.1063/5.0037915.
    3. 42. M. Sadr, M. Pfeiffer, and M. H. Gorji, “Fokker-Planck-Poisson kinetics : multi-phase flow beyond equilibrium,” Journal of fluid mechanics, vol. 920, p. A46, 2021, doi: 10.1017/jfm.2021.461.

  7. 2020

    1. 43. M. Pfeiffer, “A particle-based ellipsoidal statistical Bhatnagar-Gross–Krook solver with variable weights for the simulation of large density gradients in micro- and nano-nozzles,” Physics of fluids, vol. 32, p. 112009, 2020, doi: 10.1063/5.0023905.

  8. 2019

    1. 44. T. Binder, M. Pfeiffer, and S. Fasoulas, “Validation of grid current simulations using the particle-in-cell method for a miniaturized ion thruster,” in 31ST INTERNATIONAL SYMPOSIUM ON RAREFIED GAS DYNAMICS: RGD31, AIP Publishing, 2019. doi: 10.1063/1.5119534.
    2. 45. S. M. Copplestone, M. Pfeiffer, S. Fasoulas, and C.-D. Munz, “High-order Particle-In-Cell simulations of laser-plasma interaction,” in Particle Methods in Natural Science and Engineering, in European Physical Journal Special Topics. Springer, 2019, pp. 1603–1614. doi: 10.1140/epjst/e2019-800160-y.
    3. 46. S. Fasoulas et al., “Combining Particle-In-Cell and Direct Simulation Monte Carlo for the Simulation of Reactive Plasma Flows,” Physics of Fluids, vol. 31, Art. no. 7, 2019, doi: 10.1063/1.5097638.
    4. 47. E. Jun, M. Pfeiffer, L. Mieussens, and M. H. Gorji, “Comparative Study Between Cubic and Ellipsoidal Fokker-Planck Kinetic Models,” AIAA JOURNAL, vol. 57, Art. no. 6, 2019, doi: 10.2514/1.J057935.
    5. 48. M. Pfeiffer, F. Hindenlang, T. Binder, S. M. Copplestone, C.-D. Munz, and S. Fasoulas, “A Particle-in-Cell solver based on a high-order hybridizable discontinuous Galerkin spectral element method on unstructured curved meshes,” Computer Methods in Applied Mechanics and Engineering, vol. 349, pp. 149–166, 2019, doi: 10.1016/j.cma.2019.02.014.
    6. 49. M. Pfeiffer and P. Nizenkov, “Coupled ellipsoidal statistical BGK-DSMC simulations of a nozzle expansion,” in 31ST INTERNATIONAL SYMPOSIUM ON RAREFIED GAS DYNAMICS: RGD31, AIP Publishing, 2019, p. 70019. doi: 10.1063/1.5119573.
    7. 50. M. Pfeiffer, A. Mirza, and P. Nizenkov, “Evaluation of Particle-Based Continuum Methods for a Coupling with the Direct Simulation Monte Carlo Method Based on a Nozzle Expansion,” Physics of Fluids, vol. 31, Art. no. 7, 2019, doi: 10.1063/1.5098085.
    8. 51. M. Pfeiffer, P. Nizenkov, and S. Fasoulas, “Extension of particle-based BGK models to polyatomic species in hypersonic flow around a flat-faced cylinder,” in 31ST INTERNATIONAL SYMPOSIUM ON RAREFIED GAS DYNAMICS: RGD31, AIP Publishing, 2019, p. 100001. doi: 10.1063/1.5119596.
    9. 52. J. Zhang, B. John, M. Pfeiffer, F. Fei, and D. Wen, “Particle-based hybrid and multiscale methods for nonequilibrium gas flows,” Advances in Aerodynamics, vol. 1, Art. no. 1, May 2019, doi: 10.1186/s42774-019-0014-7.

  9. 2018

    1. 53. M. Pfeiffer, “Extending the particle ellipsoidal statistical Bhatnagar-Gross-Krook method to diatomic molecules including quantized vibrational energies,” Physics of Fluids, vol. 30, Art. no. 11, 2018, doi: 10.1063/1.5054961.
    2. 54. M. Pfeiffer, “Particle-based fluid dynamics : Comparison of different Bhatnagar-Gross-Krook models and the direct simulation Monte Carlo method for hypersonic flows,” Physics of Fluids, vol. 30, Art. no. 10, 2018, doi: 10.1063/1.5042016.

  10. 2017

    1. 55. T. Binder, M. Pfeiffer, S. Fasoulas, and H. J. Leiter, “High-Fidelity Particle-In-Cell Simulations of Ion Thruster Optics,” in 35th International Electric Propulsion Conference, 2017.
    2. 56. A. Mirza, P. Nizenkov, M. Pfeiffer, and S. Fasoulas, “Three-dimensional implementation of the Low Diffusion method for continuum flow simulations,” Computer physics communications, vol. 220, pp. 269–278, 2017, doi: 10.1016/j.cpc.2017.07.018.
    3. 57. P. Nizenkov, M. Pfeiffer, A. Mirza, and S. Fasoulas, “Modeling of chemical reactions between polyatomic molecules for atmospheric entry simulations with direct simulation Monte Carlo,” Physics of fluids, vol. 29, Art. no. 7, 2017, doi: 10.1063/1.4995468.
    4. 58. M. Pfeiffer and M. H. Gorji, “Adaptive particle-cell algorithm for Fokker-Planck based rarefied gas flow simulations,” Computer physics communications, vol. 213, pp. 1–8, 2017, doi: 10.1016/j.cpc.2016.11.003.

  11. 2016

    1. 59. S. Copplestone et al., “Coupled PIC-DSMC Simulations of a Laser-Driven Plasma Expansion,” in High Performance Computing in Science and Engineering ’15, W. E. Nagel, D. H. Kröner, and M. M. Resch, Eds., Cham: Springer International Publishing, 2016, pp. 689–701.
    2. 60. S. Copplestone, C.-D. Munz, and M. Pfeiffer, “PIC-DSMC simulations of plasma plume expansions with ionization and recombination processes,” in 2016 IEEE International Conference on Plasma Science (ICOPS), IEEE, 2016, p. 1. doi: 10.1109/plasma.2016.7534047.
    3. 61. M. Pfeiffer, S. Copplestone, T. Binder, S. Fasoulas, and C.-D. Munz, “Comparison of plasma plume expansion simulations using fully kinetic electron treatment and electron fluid models,” in AIP Conference Proceedings, Author(s), 2016, p. 130005. doi: 10.1063/1.4967631.
    4. 62. M. Pfeiffer, P. Nizenkov, A. Mirza, and S. Fasoulas, “Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases,” Physics of fluids, vol. 28, Art. no. 2, 2016, doi: 10.1063/1.4940989.

  12. 2015

    1. 63. P. Ortwein et al., “Parallel performance of a discontinuous Galerkin spectral element method based PIC-DSMC solver,” in High performance computing in science and engineering ’14 : transactions of the High Performance Computing Center, Stuttgart (HLRS) 2014, W. E. Nagel, D. H. Kröner, and M. Resch, Eds., Cham: Springer, 2015, pp. 671–681. doi: 10.1007/978-3-319-10810-0_44.
    2. 64. M. Pfeiffer, C.-D. Munz, and S. Fasoulas, “Hyperbolic divergence cleaning, the electrostatic limit, and potential boundary conditions for particle-in-cell codes,” Journal of computational physics, vol. 294, pp. 547–561, 2015, doi: 10.1016/j.jcp.2015.04.001.
    3. 65. M. Pfeiffer, A. Mirza, C.-D. Munz, and S. Fasoulas, “Two statistical particle split and merge methods for Particle-in-Cell codes,” Computer physics communications, vol. 191, pp. 9–24, 2015, doi: 10.1016/j.cpc.2015.01.010.

  13. 2014

    1. 66. C.-D. Munz et al., “Coupled Particle-In-Cell and Direct Simulation Monte Carlo method for simulating reactive plasma flows,” Comptes Rendus. Mécanique, vol. 342, Art. no. 10–11, Aug. 2014, doi: 10.1016/j.crme.2014.07.005.

  14. 2013

    1. 67. M. Pfeiffer, A. Mirza, and S. Fasoulas, “A grid-independent particle pairing strategy for DSMC,” Journal of Computational Physics, vol. 246, pp. 28–36, Aug. 2013, doi: 10.1016/j.jcp.2013.03.018.

You can find our publications also here:

ResearchGate

Teaching

Simulation of Rarefied Gases and Plasmas
Master's Program in Aerospace Engineering

Specializations:

  • B (Experimental and Numerical Simulation Methods in Aerospace Engineering)
  • H (Space Flight Technology and Space Utilization)

Modeling of Re-entry Flow
Master's Program in Aerospace Engineering

Specializations:

  • A (Mathematical and Physical Modeling in Aerospace Engineering)
  • H (Space Technology and Space Applications)

Possible topics:

We are looking for:

  • Bachelor or Master students in STEM,
  • interested in code development,
  • able to work independently and autonomously,
  • and optional: experience with Fortran

Please send applications to

Kim-Sophie Ellenberger, M. Sc.
Mail: ellenbergerk@irs.uni-stuttgart.de

Contact

This image showsMarcel Pfeiffer

Marcel Pfeiffer

Dr.-Ing.
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