3D direct numerical simulation of multi-component droplet interaction including phase change as a basis for sub-scale models for data-integrated multiphase simulations

PN 1-2 B

Project description

Many processes in nature and engineering are determined by a strong coupling of multiphase flow dynamics with interfacial transport processes on small scales, which have a huge impact on large-scale system behaviour. An important aspect of this is the interaction of droplets with each other and with surfaces as well as phase change phenomena during droplet interaction. Often the drops might contain several species. Relevant technical applications are the injection of water spray into the compressor inlet of industrial gas turbines for rapid power augmentation or the injection of fuel into combustors. The impact of multi-component droplets on structured surfaces is also an issue in engineered geosystems, which is one visionary example (Vision 1) of EXC 2075. Multi-component droplet interactions, also with walls, its phase change and the corresponding interfacial phenomena can be described in detail by means of Direct Numerical Simulation (DNS). Sub-scale models deduced from the DNS can be used later in more complex large-scale simulations and for interface modelling. We thus create the basis for the development of data-integrated simulations for multiphase flow applications in this project. The above-described work will be done by using the incompressible DNS program FS3D. PN1-2B hereby interacts strongly with PN1-2A where compressible methods are used. Especially, the comparisons between the different approaches will be very fruitful. In addition to the above-mentioned tasks, this project will also support the experiments in PN1-3 with numerical calculations of the single-phase, turbulent flow interaction with a porous medium. For this support function, the open source program OpenFOAM will be used.

Project information

Project title 3D direct numerical simulation of multi-component droplet interaction including phase change as a basis for sub-scale models for data-integrated multiphase simulations
Project leaders Kathrin Schulte
Bernhard Weigand
Project duration October 2019 - March 2023
Project number PN 1-2 B
  • Follow-up project 1-2 (II)
    3D direct numerical simulation of multi-component droplet interaction including phase change as a basis for sub-scale models for data-integrated multiphase simulations

Publications of PN 1-2 B and PN 1-2 (II)

  1. 2025

    1. P. Palmetshofer, J. Wurst, A. K. Geppert, K. Schulte, G. E. Cossali, and B. Weigand, “Wetting behavior in the inertial phase of droplet impacts onto sub-millimeter microstructured surfaces,” Journal of Colloid and Interface Science, vol. 682, pp. 413–422, Mar. 2025, doi: 10.1016/j.jcis.2024.11.154.

  2. 2024

    1. J. Potyka and K. Schulte, “A volume of fluid method for three dimensional direct numerical simulations of immiscible droplet collisions,” International Journal of Multiphase Flow, vol. 170, p. 104654, Jan. 2024, doi: 10.1016/j.ijmultiphaseflow.2023.104654.
    2. H. Mandler and B. Weigand, “A review and benchmark of feature importance methods for neural networks,” ACM Computing Surveys, vol. 56, Art. no. 12, Oct. 2024, doi: https://doi.org/10.1145/3679012.
    3. H. Mandler and B. Weigand, “Generalized field inversion strategies for data-driven turbulence closure modeling,” Physics of Fluids, vol. 36, p. 105188, Oct. 2024, doi: https://doi.org/10.1063/5.0231494.
    4. H. Mandler and B. Weigand, “Generalization Limits of Data‑Driven Turbulence Models,” Flow, Turbulence and Combustion, 2024, doi: https://doi.org/10.1007/s10494-024-00595-7.

  3. 2023

    1. J. L. Stober, J. Potyka, M. Ibach, B. Weigand, and K. Schulte, “DNS of the Early Phase of Oblique Droplet Impact on Thin Films with FS3D,” High Performance Computing in Science and Engineering ’23, Springer International Publishing, 2023. [Online]. Available: /brokenurl# https://doi.org/10.48550/arXiv.2311.17690
    2. A. Schlottke, M. Ibach, J. Steigerwald, and B. Weigand, “Direct numerical simulation of a disintegrating liquid rivulet at a trailing edge,” in High Performance Computing in Science and Engineering ’21, W. E. Nagel, D. H. Kröner, and M. M. Resch, Eds., Cham: Springer International Publishing, 2023, pp. 239–257. doi: 10.1007/978-3-031-17937-2_14.
    3. H. Mandler and B. Weigand, “Feature importance in neural networks as a means of interpretation for data-driven turbulence models,” Computers & Fluids, p. 105993, Jul. 2023, doi: 10.1016/j.compfluid.2023.105993.
    4. A. Straub, G. K. Karch, J. Steigerwald, F. Sadlo, B. Weigand, and T. Ertl, “Visual Analysis of Interface Deformation in Multiphase Flow,” Journal of Visualization, vol. 26, Art. no. 6, 2023, doi: 10.1007/s12650-023-00939-x.
    5. J. Potyka, K. Schulte, and C. Planchette, “Liquid distribution after head-on separation of two colliding immiscible liquid droplets,” Physics of Fluids, vol. 35, Art. no. 10, Oct. 2023, doi: 10.1063/5.0168080.
    6. J. Kromer, J. Potyka, K. Schulte, and D. Bothe, “Efficient sequential PLIC interface positioning for enhanced performance of the three-phase VoF method,” Computers & Fluids, vol. 266, p. 106051, Nov. 2023, doi: 10.1016/j.compfluid.2023.106051.

  4. 2022

    1. J. Potyka et al., “Towards DNS of Droplet-Jet Collisions of Immiscible Liquids with FS3D,” High Performance Computing in Science and Engineering ’22, Springer International Publishing, 2022. [Online]. Available: https://arxiv.org/abs/2212.09727
    2. H. Mandler and B. Weigand, “On frozen-RANS approaches in data-driven turbulence modeling: Practical relevance of turbulent scale consistency during closure inference and application,” International Journal of Heat and Fluid Flow, vol. 97, p. 109017, 2022, doi: https://doi.org/10.1016/j.ijheatfluidflow.2022.109017.
    3. V. Vaikuntanathan et al., “An Analytical Study on the Mechanism of Grouping of Droplets,” Fluids, vol. 7, Art. no. 5, 2022, doi: 10.3390/fluids7050172.
    4. M. Ibach, V. Vaikuntanathan, A. Arad, D. Katoshevski, J. B. Greenberg, and B. Weigand, “Investigation of droplet grouping in monodisperse streams by direct numerical simulations,” Physics of Fluids, vol. 34, Art. no. 8, 2022, doi: 10.1063/5.0097551.
    5. E. de Botton et al., “An investigation of grouping of two falling dissimilar droplets using the homotopy analysis method,” Applied Mathematical Modelling, vol. 104, pp. 486–498, 2022, doi: 10.1016/j.apm.2021.12.001.
    6. H. Mandler and B. Weigand, “A realizable and scale-consistent data-driven non-linear eddy viscosity modeling framework for arbitrary regression algorithms,” International Journal of Heat and Fluid Flow, vol. 97, p. 109018, 2022, doi: https://doi.org/10.1016/j.ijheatfluidflow.2022.109018.

  5. 2021

    1. J. Steigerwald, M. Ibach, J. Reutzsch, and B. Weigand, “Towards the Numerical Determination of the Splashing Threshold of Two-component Drop Film Interactions,” in High Performance Computing in Science and Engineering ’20, Springer, 2021, pp. 261–279. doi: 10.1007/978-3-030-80602-6_17.

Data and software publications PN 1-2 B and PN 1-2 (II)

  1. Palmetshofer, P., & Wurst, J. (2024). Replication Data for: Wetting behavior in the inertial phase of droplet impacts onto sub-millimeter microstructured surfaces. https://doi.org/10.18419/darus-4178
  2. Potyka, J., Schulte, K., & Planchette, C. (2023). Simulation and Experimental data on liquid distribution after the head-on separation of immiscible liquid droplet collisions. https://doi.org/10.18419/darus-3594
  3. Potyka, J., & Schulte, K. (2023). Setups for and Outcomes of Immiscible Liquid Droplet Collision Simulations. https://doi.org/10.18419/darus-3557
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