Source Term-Based Turbulent Flow Simulation on GPU with Link-Wise Artificial Compressibility Method

References

• Adams, N. A. 1998. “Direct Numerical Simulation of Turbulent Compression Ramp Flow.” Theoretical & Computational Fluid Dynamics 12 (2): 109–129.
   Web of Science ®Google Scholar
• Asinari, P., T. Ohwada, E. Chiavazzo, and A. F. Di Rienzo. 2012. “Link-wise Artificial Compressibility Method.” Journal of Computational Physics 231 (15): 5109–5143. doi:https://doi.org/10.1016/j.jcp.2012.04.027
   Web of Science ®Google Scholar
• Chen, Z., C. Shu, and D. Tan. 2017. “Three-Dimensional Simplified and Unconditionally Stable Lattice Boltzmann Method for Incompressible Isothermal and Thermal Flows.” Physics of Fluids 29 (5): 053601.
   Google Scholar
• Chen, Z., C. Shu, and D. Tan. 2018. “Highly Accurate Simplified Lattice Boltzmann Method.” Physics of Fluids 30 (10): 103605.
   Google Scholar
• Chen, Z., C. Shu, D. Tan, and C. Wu. 2018. “On Improvements of Simplified and Highly Stable Lattice Boltzmann Method: Formulations, Boundary Treatment, and Stability Analysis.” International Journal for Numerical Methods in Fluids 87 (4): 161–179.
   Web of Science ®Google Scholar
• Chen, Z., C. Shu, Y. Wang, L. Yang, and D. Tan. 2017. “A Simplified Lattice Boltzmann Method Without Evolution of Distribution Function.” Advances in Applied Mathematics and Mechanics 9 (1): 1–22.
   Web of Science ®Google Scholar
• Chorin, A. J. 1967. “A Numerical Method for Solving Incompressible Viscous Flow Problems.” Journal of Computational Physics 2 (1): 12–26. doi:https://doi.org/10.1016/0021-9991(67)90037-X
   Google Scholar
• Guo, Y., L. Kleiser, and N. Adams. 1994. “A Comparison Study of an Improved Temporal DNS and Spatial DNS of Compressible Boundary Layer Transition.” Fluid Dynamics Conference, 2371.
   Google Scholar
• Habich, J., C. Feichtinger, H. Köstler, G. Hager, and G. Wellein. 2013. “Performance Engineering for the Lattice Boltzmann Method on Gpgpus: Architectural Requirements and Performance Results.” Image & Vision Computing New Zealand 80: 276–282.
   Google Scholar
• Habich, J., T. Zeiser, G. Hager, and G. Wellein. 2011. “Performance Analysis and Optimization Strategies for a D3q19 Lattice Boltzmann Kernel on Nvidia GPUs Using Cuda.” Advances in Engineering Software 42 (5): 266–272.
   Web of Science ®Google Scholar
• Harwood, A. R., J. O'Connor, J. S. Munoz, M. C. Santasmasas, and A. J. Revell. 2018. “Luma: A Many-core, Fluid–structure Interaction Solver Based on the Lattice-Boltzmann Method.” SoftwareX 7 (7): 88–94.
   Google Scholar
• Harwood, A., P. Wenisch, and A. Revell. 2018. “A Real-Time Modelling and Simulation Platform for Virtual Engineering Design and Analysis.” Proceedings of 6th European Conference on Computational Mechanics (ECCM 6) and 7th European Conference on Computational Fluid Dynamics (ECFD 7).
   Google Scholar
• Januszewski, M., and M. Kostur. 2014. “Sailfish: A Flexible Multi-GPU Implementation of the Lattice Boltzmann Method.” Computer Physics Communications 185 (9): 2350–2368. doi:https://doi.org/10.1016/j.cpc.2014.04.018
   Web of Science ®Google Scholar
• Jarrin, N., S. Benhamadouche, D. Laurence, and R. Prosser. 2006. “A Synthetic-Eddy-Method for Generating Inflow Conditions for Large-Eddy Simulations.” International Journal of Heat and Fluid Flow 27 (4): 585–593.
   Web of Science ®Google Scholar
• Kawamura, H. 2008. “Direct Numerical Simulation Data Base for Turbulent Channel Flow With Heat Transfer.” Accessed May 27 2021. https://www.rs.tus.ac.jp/t2lab/db/
   Google Scholar
• Khani, M., and T.-H. Wu. 2018. “A D3Q19 Lattice Boltzmann Solver on a GPU Using Constant-Time Circular Array Shifting.” Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA).
   Google Scholar
• Klein, M., A. Sadiki, and J. Janicka. 2003. “A Digital Filter Based Generation of Inflow Data for Spatially Developing Direct Numerical Or Large Eddy Simulations.” Journal of Computational Physics 186 (2): 652–665. doi:https://doi.org/10.1016/S0021-9991(03)00090-1
   Web of Science ®Google Scholar
• Kuznik, F., C. Obrecht, G. Rusaouen, and J. J. Roux. 2010. “LBM Based Flow Simulation Using GPU Computing Processor.” Computers & Mathematics with Applications 59 (7): 2380–2392.
   Web of Science ®Google Scholar
• Li, W., X. Wei, and A. Kaufman. 2003. “Implementing Lattice Boltzmann Computation on Graphics Hardware.” The Visual Computer 19 (7–8): 444–456. doi:https://doi.org/10.1007/s00371-003-0210-6
   Web of Science ®Google Scholar
• Matyas, A. 2018. “Large Eddy Simulation of Flow Around a Cylinder With Fractional Step Lattice Boltzmann Methods.” International Conference of Numerical Analysis and Applied Mathematics.
   Google Scholar
• Matyas, A. 2019. “Fractional Step Lattice Boltzmann Methods with Coarse Corrective Steps.” Computers & Fluids 187 (1): 60–68. doi:https://doi.org/10.1016/j.compfluid.2019.05.002
   Google Scholar
• Mawson, M. J., and A. J. Revell. 2014. “Memory Transfer Optimization for a Lattice Boltzmann Solver on Kepler Architecture Nvidia GPUs.” Computer Physics Communications 185 (10): 2566–2574.
   Web of Science ®Google Scholar
• McIntosh-Smith, S., and D. Curran. 2014. “Evaluation of a Performance Portable Lattice Boltzmann Code Using Opencl.” Proceedings of the International Workshop on OpenCL 2013 & 2014, 1–12.
   Google Scholar
• N. B. Computationally Intensive Research. 2021. “Bede Case Study.” Accessed April 16 2021. https://n8cir.org.uk/documents/97/2021_01_28_santasmasas_case_study_2.pdf
   Google Scholar
• Nvidia. 2021. “Compute Unified Device Architecture Programming Guide.” Accessed May 27 2021. https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html
   Google Scholar
• Obrecht, C., P. Asinari, F. Kuznik, and J.-J. Roux. 2014. “High-Performance Implementations and Large-scale Validation of the Link-wise Artificial Compressibility Method.” Journal of Computational Physics 275 (15): 143–153. doi:https://doi.org/10.1016/j.jcp.2014.06.062
   Google Scholar
• Obrecht, C., P. Asinari, F. Kuznik, and J.-J. Roux. 2016. “Thermal Link-Wise Artificial Compressibility Method: GPU Implementation and Validation of a Double-population Model.” Computers & Mathematics with Applications 72 (2): 375–385, the Proceedings of ICMMES 2014.
   Web of Science ®Google Scholar
• Obrecht, C., F. Kuznik, B. Tourancheau, and J. J. Roux. 2013. “Multi-GPU Implementation of the Lattice Boltzmann Method.” Computers & Mathematics with Applications 65 (2): 252–261.
   Web of Science ®Google Scholar
• Riesinger, C., A. Bakhtiari, M. Schreiber, P. Neumann, and H.-J. Bungartz. 2017. “A Holistic Scalable Implementation Approach of the Lattice Boltzmann Method for CPU/GPU Heterogeneous Clusters.” Computation 5 (4): 48.
   Web of Science ®Google Scholar
• Schmidt, S., and M. Breuer. 2017. “Source Term Based Synthetic Turbulence Inflow Generator for Eddy-resolving Predictions of An Airfoil Flow Including a Laminar Separation Bubble.” Computers & Fluids 146 (6): 1–22.
   Google Scholar
• Shu, C., X. D. Niu, Y. T. Chew, and Q. D. Cai. 2006. “A Fractional Step Lattice Boltzmann Method for Simulating High Reynolds Number Flows.” Mathematics and Computers in Simulation (MATCOM) 72 (2–6): 201–205.
   Web of Science ®Google Scholar
• Skillen, A., A. Revell, and T. Craft. 2016. “Accuracy and Efficiency Improvements in Synthetic Eddy Methods.” International Journal of Heat and Fluid Flow 62 (1–3): 386–394.
   Google Scholar
• Tãulke, J. 2009. “Implementation of a Lattice Boltzmann Kernel Using the Compute Unified Device Architecture Developed by Nvidia.” Computing and Visualization in Science 13: 1–11.
   Google Scholar
• Tölke, J., and M. Krafczyk. 2008. “TeraFLOP Computing on a Desktop PC with GPUs for 3D CFD.” International Journal of Computational Fluid Dynamics 22 (7): 443–456. doi:https://doi.org/10.1080/10618560802238275
   Web of Science ®Google Scholar
• Tomczak, T., and R. G. Szafran. 2018. “Sparse Geometries Handling in Lattice Boltzmann Method Implementation for Graphic Processors.” IEEE Transactions on Parallel and Distributed Systems 29 (8): 1865–1878.
   Web of Science ®Google Scholar
• Tran, N. P., M. Lee, and S. Hong. 2017. “Performance Optimization of 3d Lattice Boltzmann Flow Solver on a GPU.” Scientific Programming 2017: 1–16. doi:https://doi.org/10.1155/2017/1205892.
   Web of Science ®Google Scholar
• Xian, W., and A. Takayuki. 2011. “Multi-GPU Performance of Incompressible Flow Computation by Lattice Boltzmann Method on GPU Cluster.” Parallel Computing 37: 521–535.
   Web of Science ®Google Scholar
• Yu, Z., Z. Lin, X. Shao, and L.-P. Wang. 2016. “A Parallel Fictitious Domain Method for the Interface-resolved Simulation of Particle-laden Flows and Its Application to the Turbulent Channel Flow.” Engineering Applications of Computational Fluid Mechanics 10 (1): 160–170.
   Web of Science ®Google Scholar