More Like this

1. Lagrangian coherent structures and heat transport in compressible flows

   Lagares C. and Araya G. (September 2023, International Conference of Numerical Analysis and Applied Mathematics)

   In this study, we delve into the intricate relation between Lagrangian Coherent Structures (LCS), primarily represented by the finite-time Lyapunov exponent (FTLE), and instantaneous temperature in turbulent wall-bounded flow scenarios. Turbulence, despite its chaotic facade, houses coherent structures vital to understanding the dynamical behavior of fluid flows. Recognizing this, we leverage high-fidelity Direct Numerical Simulation (DNS) to investigate compressible flows, focusing on the attracting manifolds in FTLE and their correlation with instantaneous temperature. The consequent insights into the coupling between fluid dynamics and thermodynamics reveal the profound influence of vortex stretching, shearing, and compression on local thermodynamic characteristics. Notably, the interplay of instantaneous static temperature and fluid properties, along with the cascading nature of energy in turbulent flows, underpins the observed correlation. Furthermore, we leveraged a high-performance, scalable volumetric particle advection scheme for LCS determination in subsonic (M∞ = 0.8) and supersonic (M∞ = 1.6) turbulent boundary layers over adiabatic flat plates. 

   more » « less
2. Setting User Attributes in Virtual Reality for Fluid Dynamics Visualization

   Brandon Antron, David Paeres (September 2023, TACCSTER 2023 Proceedings)

   Early researchers applied visualization techniques based on smoke and dye injections in order to describe coherent structures in turbulent flows. Generally speaking, visualization techniques have substantially evolved in the last few decades, spanning all disciplines. In recent times, Virtual Reality (VR) has revolutionized the way that visualization is carried out. In this study, we are performing fully immersive visualization of high-fidelity numerical results of supersonic spatially-developing turbulent boundary layers (SDTBL) under strong concave and concave curvatures and Mach = 2.86. The selected numerical tool is Direct Numerical Simulation (DNS) with high spatial/temporal resolution. The comprehensive DNS information sheds important light on the transport phenomena inside turbulent boundary layers subject to strong deceleration or Adverse Pressure Gradient (APG) caused by concave walls as well as to strong acceleration or Favorable Pressure Gradient (FPG) caused by convex walls at different wall thermal conditions (i.e., cold, adiabatic and hot walls). Another fluid dynamics example to be discussed is the high-speed crossflow-jet problem. We are extracting vortex core iso-surfaces via the Q-criterion to convert them to a file format readable by the HTC Vive VR and Varjo toolkit. Amidst the backdrop of cutting-edge progressions in both capabilities and User Interface (UI) enhancements of the VWT, researchers are now poised to delve into a realm of comprehensive understanding concerning SDTBL. Within this dynamic, fully immersive environment, the intricacies of flow development unfold before their eyes. The elevated UI refinements have bestowed users with remarkable freedom of movement across six directions and database selection, effectively amplifying their capacity for meticulous observation and incisive analysis of the animated flow phenomena 

   more » « less
3. A GPU-Accelerated Particle Advection Methodology for 3D Lagrangian Coherent Structures in High-Speed Turbulent Boundary Layers

   https://doi.org/10.3390/en16124800  

   Lagares, Christian; Araya, Guillermo (June 2023, Energies)

   In this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian coherent structures (LCS) in large-scale direct numerical simulation (DNS) datasets across incompressible, supersonic, and hypersonic flow regimes. LCS play a significant role in turbulent boundary layer analysis, and our proposed methodology offers valuable insights into their behavior in various flow conditions. Our novel owning-cell locator method enables efficient constant-time cell search, and the algorithm draws inspiration from classical search algorithms and modern multi-level approaches in numerical linear algebra. The proposed method is implemented for both multi-core CPUs and Nvidia GPUs, demonstrating strong scaling up to 32,768 CPU cores and up to 62 Nvidia V100 GPUs. By decoupling particle advection from other problems, we achieve modularity and extensibility, resulting in consistent parallel efficiency across different architectures. Our methodology was applied to calculate and visualize the FTLE on four turbulent boundary layers at different Reynolds and Mach numbers, revealing that coherent structures grow more isotropic proportional to the Mach number, and their inclination angle varies along the streamwise direction. We also observed increased anisotropy and FTLE organization at lower Reynolds numbers, with structures retaining coherency along both spanwise and streamwise directions. Additionally, we demonstrated the impact of lower temporal frequency sampling by upscaling with an efficient linear upsampler, preserving general trends with only 10% of the required storage. In summary, we present a particle search scheme for particle advection workloads in the context of visualizing LCS via FTLE that exhibits strong scaling performance and efficiency at scale. Our proposed algorithm is applicable across various domains, requiring efficient search algorithms in large, structured domains. While this article focuses on the methodology and its application to LCS, an in-depth study of the physics and compressibility effects in LCS candidates will be explored in a future publication. 

   more » « less
4. A GPU-Accelerated Particle Advection Methodology for 3D Lagrangian Coherent Structures in High-Speed Turbulent Boundary Layers

   Lagares C. and Araya G. (May 2023, Preprints)

   In this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian Coherent Structures (LCS) in large-scale Direct Numerical Simulation (DNS) datasets across incompressible, supersonic, and hypersonic flow regimes. LCS play a significant role in turbulent boundary layer analysis, and our proposed methodology offers valuable insights into their behavior in various flow conditions. Our novel owning-cell locator method enables efficient, constant-time cell search, and the algorithm draws inspiration from classical search algorithms and modern multi-level approaches in numerical linear algebra. The proposed method is implemented for both multi-core CPUs and Nvidia GPUs, demonstrating strong scaling up to 32,768 CPU cores and up to 62 Nvidia V100 GPUs. By decoupling particle advection from other problems, we achieve modularity and extensibility, resulting in consistent parallel efficiency across different architectures. Our methodology was applied to calculate and visualize the FTLE on four turbulent boundary layers at different Reynolds and Mach numbers, revealing that coherent structures grow more isotropic proportional to the Mach number, and their inclination angle varies along the streamwise direction. We also observed increased anisotropy and FTLE organization at lower Reynolds numbers, with structures retaining coherency along both spanwise and streamwise directions. Additionally, we demonstrated the impact of lower temporal frequency sampling by upscaling with an efficient linear upsampler, preserving general trends with only 10% of the required storage. In summary, we present a particle search scheme for particle advection workloads in the context of visualizing LCS via FTLE that exhibits strong scaling performance and efficiency at scale. Our proposed algorithm is applicable across various domains requiring efficient search algorithms in large structured domains. While this manuscript focuses on the methodology and its application to LCS, an in-depth study of the physics and compressibility effects in LCS candidates will be explored in a future publication. 

   more » « less
5. Aquila-LCS: GPU/CPU-Accelerated Particle Advection Schemes for Large-Scale Simulations

   Christian Lagares and Guillermo Araya (March 2024, Software X)

   We introduce Aquila-LCS, GPU and CPU optimized object-oriented, in-house codes for volumetric particle advection and 3D Finite-Time Lyapunov Exponent (FTLE) and Finite-Size Lyapunov Exponent (FSLE) computations. The purpose is to analyze 3D Lagrangian Coherent Structures (LCS) in large Direct Numerical Simulation (DNS) data. Our technique uses advanced search strategies for quick cell identification and efficient storage techniques. This solver scales effectively on both GPUs (up to 62 Nvidia V100 GPUs) and multi-core CPUs (up to 32,768 CPU cores), tracking up to 8-billion particles. We apply our approach to four turbulent boundary layers at different flow regimes and Reynolds numbers. 

   more » « less