Publications

Refereed Articles

• M. J. Krause. “Through Numerical Simulation to Scientific Knowledge”. In: Measurement and Understanding in Science and Humanities: Interdisciplinary Approaches. Ed. by Marcel Schweiker, Joachim Hass, Anna Novokhatko, and Roxana Halbleib. Wiesbaden: Springer Fachmedien Wiesbaden, 2024, pp. 201–215. isbn: 978-3-658-36974-3. doi: 10.1007/978-3-658-36974-3_16. url: https://doi.org/10.1007/978-3-658-36974-3_16.
• M. J. Krause and S. Becker. “Conclusion: Measuring and Understanding the World Through Science”. In: Measurement and Understanding in Science and Humanities: Interdisciplinary Approaches. Ed. by Marcel Schweiker, Joachim Hass, Anna Novokhatko, and Roxana Halbleib. Wiesbaden: Springer Fachmedien Wiesbaden, 2024, pp. 237–244. isbn: 978-3-658-36974-3. doi: 10.1007/978-3-658-36974-3_18. url: https://doi.org/10.1007/978-3-658-36974-3_18.
• J. E. Marquardt, N. Hafen, and M. J. Krause. “A novel particle decomposition scheme to improve parallel performance of fully resolved particulate flow simulations”. In: Journal of Computational Science 78 (2024), p. 102263. issn: 1877-7503. doi: https://doi.org/10.1016/j.jocs.2024.102263. url: https://www.sciencedirect.com/science/article/pii/S1877750324000565.
• E. S. Moreira Pinto, A. T. Mangini, L. Chaves Costa Novo, F. Guimaraes Cavatao, M. J. Krause, and M. Dorn. “Assessment of Kaistella jeonii esterase conformational dynamics in response to poly(ethylene terephthalate) binding”. In: Current Research in Structural Biology 7 (2024), p. 100130. issn: 2665-928X. doi: https://doi.org/10.1016/j.crstbi.2024.100130. url: https://www.sciencedirect.com/science/article/pii/S2665928X24000072.
• D. Teutscher, A. Kummerl¨ander, F. Bukreev, M. Dorn, and M. J. Krause. “Just–in–Time Fluid Flow Simulation on Mobile Devices Using OpenVisFlow and OpenLB”. In: Applied Sciences 14.5 (2024). issn: 2076-3417. doi: 10.3390/app14051784. url: https://www.mdpi.com/2076-3417/14/5/1784.
• F. Bukreev, F. Raichle, H. Nirschl, and M.J. Krause. “Simulation of adsorption processes on moving particles based on an Euler–Euler description using a lattice Boltzmann discretization”. In: Chemical Engineering Science 270 (2023), p. 118485. issn: 0009-2509. doi: https://doi.org/10.1016/j.ces.2023.118485. url: https://www.sciencedirect.com/science/article/pii/S0009250923000416.
• F. Bukreev, S. Simonis, A. Kummerl¨ander, J. Jessberger, and M. J. Krause. “Consistent lattice Boltzmann methods for the volume averaged Navier–Stokes equations”. In: Journal of Computational Physics 490 (2023), p. 112301. issn: 0021-9991. doi: https://doi.org/10.1016/j.jcp.2023.112301. url: https://www.sciencedirect.com/science/article/pii/S0021999123003960.
• N. Hafen, J. E. Marquardt, A. Dittler, and M. J. Krause. “Simulation of Dynamic Rearrangement Events in Wall–Flow Filters Applying Lattice Boltzmann Methods”. In: Fluids 8.7 (2023). issn: 2311-5521. doi: 10.3390/fluids8070213. url: https://www.mdpi.com/2311-5521/8/7/213.
• N. Hafen, J. E. Marquardt, A. Dittler, and M. J. Krause. “Simulation of Particulate Matter Structure Detachment from Surfaces of Wall-Flow Filters for Elevated Velocities Applying Lattice Boltzmann Methods”. In: Fluids 8.3 (2023). issn: 2311-5521. doi: 10 . 3390 / fluids8030099. url: https://www.mdpi.com/2311-5521/8/3/99.
• N. Hafen, J.R.D. Thieringer, J. Meyer, M.J. Krause, and A. Dittler. “Numerical investigation of detachment and transport of particulate structures in wall-flow filters using lattice Boltzmann methods”. In: Journal of Fluid Mechanics 956 (2023), A30. doi: 10.1017/jfm. 2023.35.
• A. Kummerl¨ander, M. Dorn, M. Frank, and M.J. Krause. “Implicit propagation of directly addressed grids in lattice Boltzmann methods”. In: Concurrency and Computation: Practice and Experience 35.8 (Mar. 2023), e7509. doi: https://doi.org/10.1002/cpe.7509. eprint: https : / / onlinelibrary . wiley . com / doi / pdf / 10 . 1002 / cpe . 7509. url: https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.7509.
• J. E. Marquardt, U. J. R¨omer, H. Nirschl, and M. J. Krause. “A discrete contact model for complex arbitrary-shaped convex geometries”. In: Particuology 80 (2023), pp. 180–191. issn: 1674-2001. doi: https://doi.org/10.1016/j.partic.2022.12.005. url: https://www.sciencedirect.com/science/article/pii/S1674200122002784.
• M. A. Riveros Escalona, J. Poloni, M. J. Krause, and M. Dorn. “Meta–analyses of host metagenomes from colorectal cancer patients reveal strong relationship between colorectal cancer-associated species”. In: Mol. Omics 19 (5 2023), pp. 429–444. doi: 10 . 1039 / D3MO00021D. url: http://dx.doi.org/10.1039/D3MO00021D.
• S. Simonis, M. Frank, M. J. Krause. "Constructing relaxation systems for lattice Boltzmann methods". In: Applied Mathematics Letters 137 (2023), p. 108484. issn: 0893-9659. doi: 10.1016/j.aml.2022.108484. url: https://www.sciencedirect.com/science/article/pii/S0893965922003470.
• A. Kummerländer, M. Dorn, M. Frank, and M.J. Krause. "Implicit Propagation of Directly Addressed Grids in Lattice Boltzmann Methods". In: Concurrency and Computation (2023). doi: 10.1002/cpe.7509.
• R. Ditscherlein, O. Furat, E. Löwer, R. Mehnert, R. Trunk, T. Leissner, M.J. Krause, V. Schmidt, and U.A. Peuker. “PARROT: A Pilot Study on the Open Access Provision of Particle-Discrete Tomographic Datasets”. In: Microscopy and Microanalysis 28.2 (2022), pp. 350–360. doi: 10.1017/S143192762101391X.
• N. Hafen, A. Dittler, and M. J. Krause. “Simulation of particulate matter structure detachment from surfaces of wall-flow filters applying lattice Boltzmann methods”. In: Computers & Fluids 239 (2022), p. 105381. issn: 0045-7930. doi: https : / / doi . org / 10 . 1016 / j . compfluid.2022.105381. url: https://www.sciencedirect.com/science/article/ pii/S0045793022000573.
• J. Jeßberger, J. E. Marquardt, L. Heim, J. Mangold, F. Bukreev, and M. J. Krause. “Optimization of a Micromixer with Automatic Differentiation”. In: Fluids 7.5 (2022). issn: 2311-5521. doi: 10.3390/fluids7050144. url: https://www.mdpi.com/2311-5521/7/5/144.
• M. Lehmann, M. J. Krause, G. Amati, M. Sega, J. Harting, and S. Gekle. “Accuracy and performance of the lattice Boltzmann method with 64-bit, 32-bit, and customized 16-bit number formats”. In: Phys. Rev. E 106 (1 July 2022), p. 015308. doi: 10.1103/PhysRevE. 106.015308. url: https://link.aps.org/doi/10.1103/PhysRevE.106.015308.
• A. Mink, K. Schediwy, C. Posten, H. Nirschl, S. Simonis, and M. J. Krause. “Comprehensive Computational Model for Coupled Fluid Flow, Mass Transfer, and Light Supply in Tubular Photobioreactors Equipped with Glass Sponges”. In: Energies 15.20 (2022). issn: 1996-1073. doi: 10.3390/en15207671. url: https://www.mdpi.com/1996-1073/15/20/7671.
• F. Reinke, N. Hafen, M. Haussmann, M. Novosel, M. J. Krause, and A. Dittler. “Applied Geometry Optimization of an Innovative 3D-Printed Wet-Scrubber Nozzle with a Lattice Boltzmann Method”. In: Chemie Ingenieur Technik 94.3 (2022), pp. 348–355. doi: https://doi.org/10.1002/cite.202100151. eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/cite.202100151. url: https://onlinelibrary.wiley.com/doi/abs/10.1002/cite.202100151.
• S. Simonis, D. Oberle, M. Gaedtke, P. Jenny, and M.J. Krause. “Temporal large eddy simulation with lattice Boltzmann methods”. In: Journal of Computational Physics 454 (2022), p. 110991. issn: 0021-9991. doi: https://doi.org/10.1016/j.jcp.2022.110991. url: https://www.sciencedirect.com/science/article/pii/S0021999122000535.
• E. Asylbekov, R. Trunk, M. J. Krause, and H. Nirschl. “Microscale Discrete Element Method Simulation of the Carbon Black Aggregate Fracture Behavior in a Simple Shear Flow”. In: Energy Technology (2021), p. 2000850. doi: https://doi.org/10.1002/ente.202000850. eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ente.202000850. url: https://onlinelibrary.wiley.com/doi/abs/10.1002/ente.202000850.
• D. Dapelo, S. Simonis, M. J. Krause, and J. Bridgeman. “Lattice–Boltzmann coupled models for advection–diffusion flow on a wide range of Peclet numbers”. In: Journal of Computational Science 51 (2021), p. 101363. issn: 1877-7503. doi: https://doi.org/10.1016/j.jocs.2021.101363. url: https://www.sciencedirect.com/science/article/pii/S1877750321000557.
• B. I. Grisci, M. J. Krause, and M. Dorn. “Relevance aggregation for neural networks interpretability and knowledge discovery on tabular data”. In: Information Sciences 559 (2021), pp. 111–129. issn: 0020-0255. doi: https://doi.org/10.1016/j.ins.2021.01.052. url: https://www.sciencedirect.com/science/article/pii/S0020025521000906.
• M. Haussmann, P. Reinshaus, S. Simonis, H. Nirschl, and M.J. Krause. “Fluid–Structure Interaction Simulation of a Coriolis Mass Flowmeter Using a Lattice Boltzmann Method”. In: Fluids 6.4 (2021). issn: 2311-5521. doi: https://doi.org/10.3390/fluids6040167. url: https://www.mdpi.com/2311-5521/6/4/167.
• M.-L. Maier, R. A. Patel, N. I. Prasianakis, S. V. Churakov, H. Nirschl, and M. J. Krause. “Coupling of multiscale lattice Boltzmann discrete–element method for reactive particle fluid flows”. In: Phys. Rev. E 103 (3 Mar. 2021), p. 033306. doi: https://doi.org/10.1103/PhysRevE.103.033306. url: https://link.aps.org/doi/10.1103/PhysRevE.103.033306.
• M.-L. Maier, S. Milles, S. Schuhmann, G. Guthausen, H. Nirschl, and M. J. Krause. “Fluid flow simulations verified by measurements to investigate adsorption processes in a static mixer”. In: Computers & Mathematics with Applications 76(11):2744–2757, 2018. doi: https://doi.org/10.1016/j.camwa.2018.08.066. url: https://www.sciencedirect.com/science/article/abs/pii/S089812211830498X.
• Marquardt, J. E., Arlt, C.-R., Trunk, R., Franzreb, M., Krause, M. J. “Numerical and experimental examination of the retention of magnetic nanoparticles in magnetic chromatography”. In: Computers & Mathematics with Applications 89 (2021), p. 34-43. doi:https://doi.org/10.1016/j.camwa.2021.02.010. url: https://www.sciencedirect.com/science/article/abs/pii/S0898122121000523?via%3Dihub.
• J. Ross–Jones, M. Gaedtke, S. Sonnick, M. Meier, M. Rädle, H. Nirschl, and M.J. Krause. “Pore–scale conjugate heat transfer simulations using lattice Boltzmann methods for industrial applications”. In: Applied Thermal Engineering 182 (2021), p. 116073. issn: 1359-4311. doi: https://doi.org/10.1016/j.applthermaleng.2020.116073. url: http://www.sciencedirect.com/science/article/pii/S1359431120335535.
• S. Schutera, M. Schnierle, M. Wu, T. Pertzel, J. Seybold, P. Bauer, D. Teutscher, M. Raedle, N. Hess–Mohr, S. Röck, and M.J. Krause. “On the Potential of Augmented Reality for Mathematics Teaching with the Application cleARmaths”. In: Education Sciences 11.8 (2021). issn: 2227-7102. doi: https://doi.org/10.3390/educsci11080368. url: https://www.mdpi.com/2227-7102/11/8/368.
• S. Simonis, M. Haussmann, L. Kronberg, W. Dörfler, and M.J. Krause. “Linear and brute force stability of orthogonal moment multiple–relaxation–time lattice Boltzmann methods applied to homogeneous isotropic turbulence”. In: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 379.2208 (2021), p. 20200405. doi: https://doi.org/10.1098/rsta.2020.0405. eprint: https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2020.0405. url: https://royalsocietypublishing.org/doi/abs/10.1098/rsta.2020.0405.
• M. Siodlaczek, M. Gaedtke, S. Simonis, M. Schweiker, M. Homma, and M. J. Krause. “Numerical evaluation of thermal comfort using a large eddy lattice Boltzmann method”. In: Building and Environment 192 (2021), p. 107618. issn: 0360-1323. doi: https://doi.org/10.1016/j.buildenv.2021.107618. url: http://www.sciencedirect.com/science/article/pii/S0360132321000317.
• A. Zarth, F. Klemens, G. Thäter, and M. J. Krause. “Towards shape optimisation of fluid flows using lattice Boltzmann methods and automatic differentiation”. In: Computers & Mathematics with Applications 90 (2021), pp. 46–54. issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2021.02.016. url: https://www.sciencedirect.com/science/article/pii/S089812212100064X.
• J. Ross-Jones, T. Teumer, S. Wunsch, L. Petri, H. Nirschl, M.J. Krause, F.-J. Methner, and M. Rädle. “Feasibility Study for a Chemical Process Particle Size Characterization System for Explosive Environments Using Low Laser Power”. In: Micromachines 11.10 (2020). issn: 2072-666X. doi: https://doi.org/10.3390/mi11100911. url: https://www.mdpi.com/2072-666X/11/10/911.
• M. Gaedtke, S. Wachter, S. Kunkel, S. Sonnick, M. Rädle, H. Nirschl, and M.J. Krause. “Numerical study on the application of vacuum insulation panels and a latent heat storage for refrigerated vehicles with a large Eddy lattice Boltzmann method”. In: Heat and Mass Transfer (Dec. 2019), pp. 1–13. issn: 1432-1181. doi: https://doi.org/10.1007/s00231-019-02753-4. url: https://doi.org/10.1007/s00231-019-02753-4.
• M. Haussmann, S. Simonis, H. Nirschl, and M.J. Krause. “Direct numerical simulation of decaying homogeneous isotropic turbulence – numerical experiments on stability, consistency and accuracy of distinct lattice Boltzmann methods”. In: International Journal of Modern Physics C 30.09 (2019), p. 1950074. doi: https://doi.org/10.1142/S0129183119500748. eprint: https://doi.org/10.1142/S0129183119500748. url: https://doi.org/10.1142/S0129183119500748.
• P. Nathen, M. Haussmann, M.J. Krause, and N.A. Adams. “Adaptive filtering for the simulation of turbulent flows with lattice Boltzmann methods”. In: Computers & Fluids 172 (2018), pp. 510–523. issn: 0045-7930. doi: https://doi.org/10.1016/j.compfluid.2018.03.042. url: http://www.sciencedirect.com/science/article/pii/S0045793018301464.
• R. Trunk, J. Marquardt, G. Thäter, H. Nirschl, and M.J. Krause. “Towards the Simulation of arbitrarily shaped 3D particles using a homogenised lattice Boltzmann method”. In: Computers & Fluids 172 (2018), pp. 621–631. issn: 0045-7930. doi: https://doi.org/10.1016/j.compfluid.2018.02.027. url: http://www.sciencedirect.com/science/article/pii/S0045793018300823.
• Trunk, R., Weckerle, T., Hafen, N., Thäter, G., Nirschl, H., Krause, M. J. “Revisiting the Homogenized Lattice Boltzmann Method with Applications on Particulate Flows”. In: Computation 9(2) (2021), 11. doi:https://doi.org/10.3390/computation9020011. url: https://www.mdpi.com/2079-3197/9/2/11.
• Trunk, R., Bretl, C., Thäter, G., Nirschl, H., Dorn, M., Krause, M. J. “A Study on Shape-Dependent Settling of Single Particles with Equal Volume Using Surface Resolved Simulations”. In: Computation 9(4) (2021), 40. doi:https://doi.org/10.3390/computation9040040. url: https://www.mdpi.com/2079-3197/9/4/40.
• F. Klemens. “Combining computational fluid dynamics and magnetic resonance imaging data using lattice Boltzmann based topology optimisation”. PhD Thesis. Kaiserstraße 12, 76131 Karlsruhe, Germany: Karlsruhe Institute of Technologie (KIT), November 2020. doi: 10.5445/IR/1000125499. url: https://publikationen.bibliothek.kit.edu/1000125499.
• D. Dapelo, R. Trunk, M. J. Krause, N. Cassidy, and J. Bridgeman. “The application of Buckingham /pi theorem to Lattice–Boltzmann modelling of sewage sludge digestion”. In: Computers & Fluids 209 (2020), p. 104632. issn: 0045-7930. doi: https://doi.org/10.1016/j.compfluid.2020.104632. url: http://www.sciencedirect.com/science/article/pii/S0045793020302048.
• M. Gaedtke, S. Abishek, R. Mead-Hunter, A.J.C. King, B.J. Mullins, H. Nirschl, and M.J. Krause. “Total enthalpy–based lattice Boltzmann simulations of melting in paraffin/metal foam composite phase change materials”. In: International Journal of Heat and Mass Transfer 155 (2020), p. 119870. issn: 0017-9310. doi:https://doi.org/10.1016/j.ijheatmasstransfer.2020.119870. url: http://www.sciencedirect.com/science/article/pii/S0017931019361927.
• M. Haussmann, N. Hafen, F. Raichle, R. Trunk, H. Nirschl, and M.J. Krause. “Galilean invariance study on different lattice Boltzmann fluid–solid interface approaches for vortexinduced vibrations”. In: Computers & Mathematics with Applications 80.5 (2020), pp. 671–691. issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2020.04.022. url: http://www.sciencedirect.com/science/article/pii/S0898122120301693.
• M. Haussmann, F. Ries, J.B. Jeppener–Haltenhoff, Y. Li, M. Schmidt, C. Welch, L. Illmann, B. Böhm, H. Nirschl, M.J. Krause, and A. Sadiki. “Evaluation of a Near–Wall–Modeled Large Eddy Lattice Boltzmann Method for the Analysis of Complex Flows Relevant to IC Engines”. In: Computation 8.43 (2020). doi: 10.3390/computation8020043. url: https://doi.org/10.3390/computation8020043.
• F. Klemens, S. Schuhmann, R. Balbierer, G. Guthausen, H. Nirschl, G. Thäter, and M.J. Krause. “Noise reduction of flow MRI measurements using a lattice Boltzmann based topology optimisation approach”. In: Computers & Fluids 197 (2020), p. 104391. issn: 0045-7930. doi: https://doi.org/10.1016/j.compfluid.2019.104391. url: http://www.sciencedirect.com/science/article/pii/S0045793019303494.
• F. Klemens, B Förster, M. Dorn, G. Thäter, and M.J. Krause. “Solving fluid flow domain identification problems with adjoint lattice Boltzmann methods”. In: Computers & Mathematics with Applications 79.1 (2020), pp. 17–33. issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2018.07.010. url: http://www.sciencedirect.com/science/article/pii/S0898122118303754.
• M.J. Krause, A. Kummerländer, S.J. Avis, H. Kusumaatmaja, D. Dapelo, F. Klemens, M. Gaedtke, N. Hafen, A. Mink, R. Trunk, J.E. Marquardt, M.L. Maier, M. Haussmann, and S. Simonis. “OpenLB–Open source lattice Boltzmann code”. In: Computers & Mathematics with Applications (2020). issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2020.04.033. url: http://www.sciencedirect.com/science/article/pii/S0898122120301875.
• A. Mink, C. McHardy, L. Bressel, C. Rauh, and M.J. Krause. “Radiative transfer lattice Boltzmann methods: 3D models and their performance in different regimes of radiative transfer”. In: Journal of Quantitative Spectroscopy and Radiative Transfer 243 (2020), p. 106810. issn: 0022-4073. doi: https://doi.org/10.1016/j.jqsrt.2019.106810. url: http://www.sciencedirect.com/science/article/pii/S0022407319308052.
• S. Simonis, M. Frank, and M.J. Krause. “On relaxation systems and their relation to discrete velocity Boltzmann models for scalar advection–diffusion equations”. In: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378.2175 (June 2020), p. 20190400. doi: 10.1098/rsta .2019.0400. eprint: https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2019.0400. url: https://royalsocietypublishing.org/doi/abs/10.1098/rsta.2019.0400.
• S. Sonnick, L. Erlbeck, M. Gaedtke, F. Wunder, C. Mayer, M.J. Krause, H. Nirschl, and M. Rädle. “Passive room conditioning using phase change materials–Demonstration of a long-term real size experiment”. In: International Journal of Energy Research 44.8 (Apr. 2020), pp. 7047–7056. doi: 10.1002/er.5406. eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.5406. url: https://onlinelibrary.wiley.com/doi/abs/10.1002/er.5406.
• D. Dapelo, R. Trunk, M.J. Krause, and J. Bridgeman. “Towards Lattice-Boltzmann Modelling of Unconfined Gas Mixing in Anaerobic Digestion”. In: Computers & Fluids 180 (2019), pp. 11–21. issn: 0045-7930. doi: https://doi.org/10.1016/j.compfluid.2018.12.008. url: http://www.sciencedirect.com/science/article/pii/S0045793018306728.
• M. Gaedtke, T. Hoffmann, V. Reinhardt, G. Thäter, H. Nirschl, and M.J. Krause. “Flow and heat transfer simulation with a thermal large eddy lattice Boltzmann method in an annular gap with an inner rotating cylinder”. In: International Journal of Modern Physics C 30.02n03 (2019), p. 1950013. doi: 10.1142/S012918311950013X. eprint: https://doi.org/10.1142/S012918311950013X. url: https://doi.org/10.1142/S012918311950013X.
• M. Haussmann, A. Claro Berreta, G. Lipeme Kouyi, N. Riviere, H. Nirschl, and M.J. Krause. “Large-eddy simulation coupled with wall models for turbulent channel flows at high Reynolds numbers with a lattice Boltzmann method –Application to Coriolis mass flowmeter”. In: Computers & Mathematics with Applications (2019). issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2019.04.033. url: http://www.sciencedirect.com/science/article/pii/S0898122119302494.
• M. Mohrhard, G. Thäter, J. Bludau, B. Horvat, and M.J. Krause. “An Auto-Vecotorization Friendly Parallel Lattice Boltzmann Streaming Scheme for Direct Addressing”. In: Computers & Fluids 181 (2019), pp. 1–7. issn: 0045-7930. doi: http://www.sciencedirect.com/science/article/pii/S0045793018308727">https://doi.org/10.1016/j.compfluid.2019.01.001. url: http://www.sciencedirect.com/science/article/pii/S0045793018308727.
• J. Ross-Jones, M. Gaedtke, S. Sonnick, M. Rädle, H. Nirschl, and M.J. Krause. “Conjugate heat transfer through nano scale porous media to optimize vacuum insulation panels with lattice Boltzmann methods”. In: Computers & Mathematics with Applications 77 (2019), pp. 209–221. issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2018.09.023. url: http://www.sciencedirect.com/science/article/pii/S0898122118305352.
• M. Gaedtke, S. Wachter, M. Rädle, H. Nirschl, and M.J. Krause. “Application of a lattice Boltzmann method combined with a Smagorinsky turbulence model to spatially resolved heat flux inside a refrigerated vehicle”. In: Computers & Mathematics with Applications 76.10 (Nov. 2018), pp. 2315–2329. issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2018.08.018. url: http://www.sciencedirect.com/science/article/pii/S089812211830436X.
• S.B. Höcker, R. Trunk, W. Dörfler, and M.J. Krause. “Towards the simulations of inertial dense particulate flows with a volume-averaged lattice Boltzmann method”. In: Computers & Fluids 166 (2018), pp. 152–162. issn: 0045-7930. doi: https://doi.org/10.1016/j.compfluid.2018.02.011. url: https://www.sciencedirect.com/science/article/pii/S0045793018300665.
• F. Klemens, S. Schuhmann, G. Guthausen, G. Thäter, and M.J. Krause. “CFD-MRI: A coupled measurement and simulation approach for accurate fluid flow characterisation and domain identification”. In: Computers & Fluids 166 (2018), pp. 218–224. issn: 0045-7930. doi: https://doi.org/10.1016/j.compfluid.2018.02.022. url: https://www.sciencedirect.com/science/article/pii/S004579301830077X.
• F. Klemens, B Förster, M. Dorn, G. Thäter, and M.J. Krause. “Solving fluid flow domain identification problems with adjoint lattice Boltzmann methods”. In: Computers & Mathematics with Applications (2018). issn: 0898-1221. doi: https://doi.org/10.1016/j.camwa.2018.07.010. url: http://www.sciencedirect.com/science/article/pii/S0898122118303754.
• R. Ligabue-Braun, B. Borguesan, H. Verli, M.J. Krause, and M. Dorn. “Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures”. In: Journal of Computational Biology 25.4 (Apr. 2018). PMID: 29267011, pp. 451–465. doi:10.1089/cmb.2017.0182. eprint: https://doi.org/10.1089/cmb.2017.0182. url: https://doi.org/10.1089/cmb.2017.0182.
• L. de Lima Corrêa, B. Borguesan, M.J. Krause, and M. Dorn. “Three-Dimensional Protein Structure Prediction Based on Memetic Algorithms”. In: Computers & Operations Research 91 (2018), pp. 160–177. issn: 0305-0548. doi: https://doi.org/10.1016/j.cor.2017.11.015. url: https://www.sciencedirect.com/science/article/pii/S0305054817302897.
• M.J. Krause, F. Klemens, T. Henn, R. Trunk, and R. Nirschl. “Particle flow simulations with homogenised lattice Boltzmann methods”. In: Particuology 34 (Oct. 2017), pp. 1–13. issn: 1674-2001. doi: http://doi.org/10.1016/j.partic.2016.11.001. url:http://www.sciencedirect.com/science/article/pii/S167420011730041X.
• L. de Luca Xavier Augusto, J. Ross-Jones, G. Cantarelli Lopes, P. Tronville, J.A. Silveira Gonçalves, M. Rädle, and M.J. Krause. “Microfiber Filter Performance Prediction using a Lattice-Boltzmann Method”. In: Communications in Computational Physics (2017).
• M.-L. Maier, T. Henn, G. Thaeter, H. Nirschl, and M. J. Krause. “Towards Validated Multiscale Simulation with a Two-Way Coupled LBM and DEM”. In: Chemical Engineering & Technology 40.9 (Sept. 2017), pp. 1591–1598. issn: 1521-4125. doi: 10.1002/ceat.201600547. url:http://dx.doi.org/10.1002/ceat.201600547.
• P. Nathen, D. Gaudlitz, M.J. Krause, and N.A. Adams. “On the Stability and Accuracy of the BGK, MRT and RLB Boltzmann Schemes for the Simulation of Turbulent Flows”. In: Communications in Computational Physics 23.3 (Mar. 2017), pp. 846–876. doi: 10.4208/cicp.OA-2016-0229.
• T. Henn, G. Thäter, W. Dörfler, H. Nirschl, and M.J. Krause. “Parallel dilute particulate flow simulations in the human nasal cavity”. In: Computers & Fluids 124 (2016), pp. 197–207. issn: 0045-7930. doi: http://dx.doi.org/10.1016/j.compfluid.2015.08.002. url:http://www.sciencedirect.com/scienc/article/pii/S0045793015002728.
• A. Loewe, M. Wilhelms, J. Schmid, M.J. Krause, F. Fischer, D. Thomas, E.P. Scholz, O. Dössel, and G. Seemann. “Parameter estimation of ion current formulations requires hybrid optimization approach to be both accurate and reliable”. In: Frontiers in Bioengineering and Biotechnology 3.209 (2016). issn: 2296-4185. doi: 10.3389/fbioe.2015.00209. url: http://www.frontiersin.org/computational_physiology_and_medicine/10.3389/fbioe.2015.00209/abstract.
• A. Mink, G. Thäter, H. Nirschl, and M.J. Krause. “A 3D Lattice Boltzmann Method for Light Simulation in Participating Media”. In: Journal of Computational Science 17, Part 2(2016), pp. 431–437. doi: http://dx.doi.org/10.1016/j.jocs.2016.03.014. url:http://www.sciencedirect.com/science/article/pii/S1877750316300357.
• H. Mirzaee, T. Henn, M.J. Krause, L. Goubergrits, C. Schumann, M. Neugebauer, T. Kuehne, T. Preusser, and A. Hennemuth. “MRI-based computational hemodynamics in patients with aortic coarctation using the lattice Boltzmann methods: Clinical validation study”. In: Journal of Magnetic Resonance Imaging (2016). issn: 1522-2586. doi: 10.1002/jmri.25366. url:http://dx.doi.org/10.1002/jmri.25366.
• R. Trunk, T. Henn, W. Dörfler, H. Nirschl, and M.J. Krause. “Inertial Dilute Particulate Fluid Flow Simulations with an Euler-Euler Lattice Boltzmann Method”. In: Journal of Computational Science 17, Part 2 (2016), pp. 438–445. doi: http://dx.doi.org/10.1016/j.jocs.2016.03.013. url: http://www.sciencedirect.com/science/article/pii/S1877750316300345.
• M.J. Krause and V. Heuveline. “Parallel Fluid Flow Control and Optimisation with Lattice Boltzmann Methods and Automatic Differentiation”. In:Computers and Fluids 80 (2013),pp. 28–36. issn: 0045-7930. doi: 10.1016/j.compfluid.2012.07.026. url: http://www.sciencedirect.com/science/article/pii/S0045793012002940?v=s5.
• M.J. Krause, G. Thäter, and V. Heuveline. “Adjoint-based Fluid Flow Control and Optimisation with Lattice Boltzmann Methods”. In: Computers & Mathematics with Applications 65.6 (2013), pp. 945–960. issn: 0898-1221. doi: 10 . 1016 / j . camwa . 2012 . 08 . 007. url:http://www.sciencedirect.com/science/article/pii/S0898122112005421.
• M.J. Krause, T. Gengenbach, R. Mayer, S. Zimney, and V. Heuveline. “How to Breathe Life into CT-Data”. In: Computer Aided Medical Engineering 4 (2011), pp. 29–33.
• M.J. Krause. “Fluid Flow Simulation and Optimisation with Lattice Boltzmann Methods on High Performance Computers: Application to the Human Respiratory System”. eng.https://publikationen.bibliothek.kit.edu/1000019768. PhD thesis. Kaiserstraße 12, 76131 Karlsruhe, Germany: Karlsruhe Institute of Technology (KIT), Universität Karlsruhe (TH), July 2010. url: https://publikationen.bibliothek.kit.edu/1000019768.
• V. Heuveline, M.J. Krause, and J. Latt. “Towards a Hybrid Parallelization of Lattice Boltzmann Methods”. In: Computers & Mathematics with Applications 58 (2009), pp. 1071–1080. doi:10.1016/j.camwa.2009.04.001. url: http://dx.doi.org/10.1016/j.camwa.2009.04.001.

Refereed Proceedings and Book Chapters

• S. Simonis and M. J. Krause. “Forschungsnahe Lehre unter Pandemiebedingungen”. In: Mitteilungen der Deutschen Mathematiker-Vereinigung 30.1 (2022), pp. 43–45. doi: 10.1515/dmvm-2022-0015. url: https://doi.org/10.1515/dmvm-2022-0015.
• C. Bretl, R. Trunk, H. Nirschl, G. Thäter, M. Dorn, and M. J. Krause. “Preliminary Study of Particle Settling Behaviour by Shape Parameters via Lattice Boltzmann Simulations”. In: High Performance Computing in Science and Engineering 20. Ed. by Wolfgang E. Nagel, Dietmar H. Kröner, and Michael M. Resch. Cham: Springer International Publishing, 2021, pp. 245–259. isbn: 978-3030-80602-6.
• M.J. Krause, A. Mink, P. Weisbrod, F. Klemens, J. Jeppener–Haltenhoff, and B. Förster. “Charakterisierung von durchströmten Gefäßen und der Hämodynamik mittels modell- und simulationsbasierter Fluss-MRI (CFD-MRI)”. In: Heidelberger Akademie der Wissenschaften Jahrbuch 2019, 2020. Chap. 8, pp. 380–383. isbn: 978-3-00-065427-5.
• Narloch, P.H. and Krause, M.J. and Dorn, M. “Multi–Objective Differential Evolution Algorithms for the Protein Structure Prediction Problem”. In: IEEE Congress on Evolutionary Computation (CEC). 2020. doi: 10.1109/CEC48606.2020.9185711.
• M. J. Krause, F. Klemens, A. Mink, and J. Jeppener–Haltenhoff. “Charakterisierung von durchströmten Gefäßen und der Hämodynamik mittels modell- und simulationsbasierter Fluss-MRI (CFD-MRI): Validierung der Wandschubspannungsberechnung und Anwendung auf medizinisches Einsatzgebiet”. In: Heidelberger Akademie der Wissenschaften Jahrbuch 2018, 2019. Chap. 11, pp. 373–376. isbn: 978-3-00-062676-0.
• M.J. Krause, F. Klemens, and A. Mink. “Charakterisierung von durchströmten Gefäßen und der Hämodynamik mittels modell- und simulationsbasierter Fluss-MRI (CFD-MRI): Qualitative Analyse des Genauigkeitsgewinns der kombinierten Methode”. In: Heidelberger Akademie der Wissenschaften Jahrbuch 2017, 2018. Chap. 14, pp. 338–342. isbn: 978-3-8253-6902-6.
• M.J. Krause, A. Mink, P. Weisbrod, F. Klemens, J. Jeppener–Haltenhoff, and B. Förster. “Charakterisierung von durchströmten Gefäßen und der Hämodynamik mittels modell- und simulationsbasierter Fluss-MRI (CFD-MRI)”. In: Heidelberger Akademie der Wissenschaften Jahrbuch 2019, 2020. Chap. 8, pp. 380–383. isbn: 978-3-00-065427-5.
• P.H. Narloch, M.J. Krause, and M. Dorn. “Multi-Objective Differential Evolution Algorithms for the Protein Structure Prediction Problem”. In: IEEE Congress on Evolutionary Computation (CEC). 2020.
• M.J. Krause. “Durch Numerische Simulation zur wissenschaftlichen Erkenntnis”. In: Messen und Verstehen in der Wissenschaft: Interdisziplinäre Ansätze. Ed. by Marcel Schweiker, Joachim Hass, Anna Novokhatko, and Roxana Halbleib. Wiesbaden: Springer Fachmedien Wiesbaden, 2017, pp. 237–253. isbn: 978-3-658-18354-7. doi: 10.1007/978-3-658-18354-7_16. url: http://dx.doi.org/10.1007/978-3-658-18354-7_16.
• M.J. Krause and S. Becker. “Fazit – Messen und Verstehen der Welt durch Wissenschaft”. In: Messen und Verstehen in der Wissenschaft: Interdisziplinäre Ansätze. Ed. by Marcel Schweiker, Joachim Hass, Anna Novokhatko, and Roxana Halbleib. Wiesbaden: Springer Fachmedien Wiesbaden, 2017, pp. 277–286. isbn: 978-3-658-18354-7. doi: 10.1007/978-3-658-18354-7_18. url: http://dx.doi.org/10.1007/978-3-658-18354-7_18.
• M.J. Krause, A. Mink, B. Förster, and F. Klemens. “Charakterisierung von durchströmten Gefäßen und der Hämodynamik mittels modell- und simulationsbasierter Fluss-MRI (CFDMRI): Verbesserung des Modellsystems und erste Machbarkeitsstudie zur Anwendung in der Medizin”. In: Heidelberger Akademie der Wissenschaften Jahrbuch 2016, 2017. Chap. 14, pp. 269–272.
• M.J. Krause, B. Förster, A. Mink, and H. Nirschl. “Towards Solving Fluid Flow Domain Identification Problems with Adjoint Lattice Boltzmann Methods”. In: High Performance Computing in Science and Engineering´ 16. Springer, 2016, pp. 337–353.
• M.J. Krause, M.-L. Maier, and A. Mink. “Charakterisierung von durchströmten Gefäßen und der Hämodynamik mittels modell- und simulationsbasierter Fluss-MRI (CFD-MRI): Grundlegende Methodenentwicklung zur optimal-kalibrierten CFD-Simulation”. In: Heidelberger Akademie der Wissenschaften Jahrbuch 2015, 2016. Chap. 14, pp. 301–304.
• N. Nadim, T.T. Chandratilleke, and M.J. Krause. “LBM-LES Modelling of Low Reynolds Number Turbulent Flow Over NACA0012 Aerofoil”. English. In: Fluid-Structure-Sound Interactions and Control. Ed. by Y. Zhou, A.D. Lucey, Y. Liu, and L. Huang. Lecture Notes in Mechanical Engineering. Springer Berlin Heidelberg, 2016, pp. 205–210. isbn: 978-3-662-48866-9. doi:10.1007/978-3-662-48868-3_33. url: http://dx.doi.org/10.1007/978-3-662-48868-3_33.
• U. Römer, C. Kuhs, M.J. Krause, and A. Fidlin. “Simultaneous optimization of gait and design parameters for bipedal robots”. In: 2016 IEEE International Conference on Robotics and Automation (ICRA). May 2016, pp. 1374–1381. doi: 10.1109/ICRA.2016.7487271.
• M.J. Krause, A. Mink, and P. Weisbrod. “Charakterisierung von durchströmten Gefäßen und der Hämodynamik mittels modell- und simulationsbasierter Fluss-MRI (CFD-MRI)”. In: Heidelberger Akademie der Wissenschaften Jahrbuch 2014, 2015. Chap. 14, pp. 291–293.
• P. Nathen, D. Gaudlitz, M.J. Krause, and J. Kratzke. “An extension of the Lattice Boltzmann Method for simulating turbulent flows around rotating geometries of arbitrary shape”. In: 21st AIAA Computational Fluid Dynamics Conference, San Diego. American Institute of Aeronautics and Astronautics. 2013. doi: doi : 10 . 2514 / 6 . 2013 - 2573. url: http://dx.doi.org/10.2514/6.2013-2573.
• J. Fietz, M.J. Krause, C. Schulz, P. Sanders, and V. Heuveline. “Optimized Hybrid Parallel Lattice Boltzmann Fluid Flow Simulations on Complex Geometries”. In: Euro-Par 2012 Parallel Processing. Ed. by C. Kaklamanis, T. Papatheodorou, and P.G. Spirakis. Vol. 7484. Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012, pp. 818–829. isbn: 978-3-642-32819-0. doi: 10.1007/978-3-642-32820-6_81. url: http://dx.doi.org/10.1007/978-3-642-32820-6_81.
• T. Henn, M.J. Krause, S. Ritterbusch, and V. Heuveline. “Lattice Boltzmann Method Meets Aortic Coarctation Model”. In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. Ed. by O. Camara, T. Mansi, M. Pop, K. Rhode, M. Sermesant, and A. Young. Vol. 7746. Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012, pp. 34–43. isbn: 978-3-642-23628-0.
• M. Wilhelms, J. Schmid, M.J. Krause, N. Konrad, J. Maier, E.P. Scholz, V. Heuveline, O. Dossel, and G. Seemann. “Calibration of human cardiac ion current models to patch clamp measurement data”. In: Computing in Cardiology (CinC), 2012. Vol. 39. 2012, pp. 229–232.
• V. Heuveline and M.J. Krause. “OpenLB: Towards an Efficient Parallel Open Source Library for Lattice Boltzmann Fluid Flow Simulations”. In: PARA’08 Workshop on State-of-the-Art in Scientific and Parallel Computing, May 13-16, 2008. Ed. by J. Dongarra A.C. Elster and J. Wasniewski. Springer series Lecture Notes in Computer Science (LNCS) 6126, 6127. Published online 2011, https://para08.idi.ntnu.no/docs/submission_37.pdf. 2011. url: https://para08.idi.ntnu.no/docs/submission%5C_37.pdf.
• M.J. Krause, T. Gengenbach, and V. Heuveline. “Hybrid Parallel Simulations of Fluid Flows in Complex Geometries: Application to the Human Lungs”. In: Euro-Par 2010 Parallel Processing Workshops. Ed. by M. Guarracino, F. Vivien, J. Traeff, M. Cannatoro, M. Danelutto, A. Hast, F. Perla, A. Knuepfer, B. Di Martino, and M. Alexander. Vol. 6586. Lecture Notes in Computer Science. Springer Berlin / Heidelberg, 2011, pp. 209–216. isbn: 978-3-642-21877-4. url: http://dx.doi.org/10.1007/978-3-642-21878-1_26.

Software Releases

• A. Kummerländer, S. Avis, H. Kusumaatmaja, F. Bukreev, M. Crocoll, D. Dapelo, N. Hafen, S. Ito, J. Jeßberger, J.E. Marquardt, J. Mödl, T. Pertzel, F. Prinz, F. Raichle, M. Schecher, S. Simonis, D. Teutscher, and M.J. Krause. OpenLB Release 1.6: Open Source Lattice Boltzmann Code. doi: 10.5281/zenodo.7773497.
• A. Kummerländer, S. Avis, H. Kusumaatmaja, Bukreev. F., D. Dapelo, S. Großmann, N. Hafen, C. Holeksa, A. Husfeldt, J. Jeßberger, L. Kronberg, J.E. Marquardt, J. Mödl, J. Nguyen, T. Pertzel, S. Simonis, L. Springmann, N. Suntoyo, D. Teutscher, M. Zhong, and M.J. Krause. OpenLB Release 1.5: Open Source Lattice Boltzmann Code. Version 1.5. Apr. 2022. doi: 10.5281/zenodo.6469606. url: https://doi.org/10.5281/zenodo.6469606.
• M.J. Krause, S. Avis, H. Kusumaatmaja, D. Dapalo, M. Gaedtke, N. Hafen, M. Haußmann, J. Jeppener-Haltenhoff, L. Kronberg, A. Kummerländer, J. Marquardt, T. Pertzel, S. Simonis, R. Trunk, M. Wu, and A. Zarth. OpenLB Release 1.4: Open Source Lattice Boltzmann Code. online. Nov. 2020. url: https://doi.org/10.5281/zenodo.4279263.
• M.J. Krause, S. Avis, D. Dapalo, N. Hafen, M. Haußmann, M. Gaedtke, F. Klemens, A. Kummerländer, M.-L. Maier, A. Mink, J. Ross-Jones, S. Simonis, and R. Trunk. OpenLB Release 1.3: Open Source Lattice Boltzmann Code. online. May 2019. url: https://doi.org/10.5281/zenodo.3625967.
• M.J. Krause, A. Mink, R. Trunk, F. Klemens, M.-L. Maier, M. Mohrhard, A. Claro Barreto, M. Haußmann, M. Gaedtke, and J. Ross-Jones. OpenLB Release 1.2: Open Source Lattice Boltzmann Code. online. Feb. 2018. url: https://doi.org/10.5281/zenodo.3625960.
• M.J. Krause, T. Henn, A. Mink, R. Trunk, P. Nathen, F. Klemens, M.-L. Maier, M. Mohrhard, A. Claro Barreto, M. Haußmann, M. Gaedtke, and J. Ross-Jones. OpenLB Release 1.1: Open Source Lattice Boltzmann Code. online. Apr. 2017. url: https://doi.org/10.5281/zenodo.3625955.
• M.J. Krause, N. Bogutzki, and A. Mink. OpenGPI Release 0.4: An Open and Generic Parameter Interface. online. Mar. 2017. url: https://doi.org/10.5281/zenodo.3629111.
• M.J. Krause, N. Bogutzki, and A. Mink. OpenGPI Release 0.3: An Open and Generic Parameter Interface. online. Dec. 2016. url: https://doi.org/10.5281/zenodo.3629104.
• M.J. Krause, T. Henn, A. Mink, R. Trunk, P. Weisbrod, P. Nathen, F. Klemens, and M.-L. Maier. OpenLB Release 1.0: Open Source Lattice Boltzmann Code. online. Mar. 2016. url: https://doi.org/10.5281/zenodo.3625943.
• M.J. Krause, T. Henn, A. Mink, R. Trunk, P. Weisbrod, P. Nathen, F. Klemens, and M.-L. Maier. OpenLB Release 0.9: Open Source Lattice Boltzmann Code. online. Mar. 2015. url: https://doi.org/10.5281/zenodo.3625941.
• M.J. Krause, T. Henn, L. Baron, A. Mink, P. Weisbrod, P. Nathen, and G. Zahnd. OpenLB Release 0.8: Open Source Lattice Boltzmann Code. online. Nov. 2013. url: https://doi.org/10.5281/zenodo.3625938.
• M.J. Krause, T. Henn, L. Baron, J. Kratzke, J. Fietz, and T. Dornieden. OpenLB Release 0.7: Open Source Lattice Boltzmann Code. online. Feb. 2012. url: https://doi.org/10.5281/zenodo.3625936.
• M.J. Krause, S. Zimny, T. Henn, and J. Fietz. OpenLB Release 0.6: Open Source Lattice Boltzmann Code. online. May 2011. url: https://doi.org/10.5281/zenodo.3625929.
• M.J. Krause, J. Fietz, U. Zeltmann, M. Wlozka, M. Baumann, and H. Bockelmann. OpenGPI Release 0.2: An Open and Generic Parameter Interface. online. Aug. 2010. url: https://doi.org/10.5281/zenodo.3627128.
• J. Latt, M.J. Krause, O. Malaspinas, and B. Stahl. OpenLB Release 0.5: Open Source Lattice Boltzmann Code. online. May 2008. url: https://doi.org/10.5281/zenodo.3625925.
• J. Latt and M.J. Krause. OpenLB Release 0.4: Open Source Lattice Boltzmann Code. online. Jan. 2008. url: https://doi.org/10.5281/zenodo.3625909.
• J. Latt and M.J. Krause. OpenLB Release 0.3: Open Source Lattice Boltzmann Code. online. July 2007. url: https://doi.org/10.5281/zenodo.3625765.

Miscellaneous

• A. Mink, K. Schediwy, M. Haussmann, C. Posten, H. Nirschl, and M.J. Krause. Fresnel reflection boundary for radiative transport lattice Boltzmann methods in highly scattering volume. 2021. arXiv: 2107.09411 physics.comp-ph. url: https://arxiv.org/abs/2107.09411
• S. Fuchs, A. Dittler, and M. J. Krause Um bis zu 95% können Mund-Nasen-Masken das Corona-Ansteckungsrisiko reduzieren – Wissenschaftler am KIT haben die Ausbreitung in geschlossenen Räumen untersucht – Campus-Report am 11.08.2020. 2020. url: https://publikationen.bibliothek.kit.edu/1000122509"
• T. Gengenbach, M.J. Krause, and V. Heuveline. Numerical Simulation of the Human Lung: A Two–scale Approach. EMCL Preprint Series. http://dx.doi.org/10.11588/emclpp.2011.11.11687. 2011. url: http://dx.doi.org/10.11588/emclpp.2011.11.11687.
• M.J. Krause, T. Gengenbach, R. Mayer, S. Zimney, and V. Heuveline. A Preprocessing Approach for Innovative Patient-specific Intranasal Flow Simulations. EMCL Preprint Series. http://dx.doi.org/10.11588/emclpp.2011.07.11691. 2011. url: http://dx.doi.org/10.11588/emclpp.2011.07.11691.
• M.J. Krause. “Fluid Flow Simulation and Optimisation with Lattice Boltzmann Methods on High Performance Computers: Application to the Human Respiratory System”. eng. https://publikationen.bibliothek.kit.edu/1000019768. PhD thesis. Kaiserstraße 12, 76131 Karlsruhe, Germany: Karlsruhe Institute of Technology (KIT), Universität Karlsruhe (TH), July 2010. url: https://publikationen.bibliothek.kit.edu/1000019768.
• V. Heuveline and M.J. Krause. Biotechnologie und Numerik auf Hochleistungsrechnern: ein zukünftiges Gespann in Baden-Württemberg, Marktstudie für HWW GmbH. 2006.