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1. Performance characterization of a laminar gas-inlet

   https://doi.org/10.5194/amt-2023-196  

   Yang, Da; Reza, Margarita; Mauldin, Roy; Volkamer, Rainer; Dhaniyala, Suresh (September 2023, Copernicus Publications)

   Abstract. Aircraft-based measurements enable large-scale characterization of gas-phase atmospheric composition, but these measurements are complicated by the challenges of sampling from high-speed flow. Under such sampling conditions, the sample flow will likely experience turbulence, accelerating | mixing of potential contamination of the gas-phase from the condensed-phase components on walls and reduced vapor transmission due to losses to the inner walls of the sampling line. While a significant amount of research has gone into understanding aerosol sampling efficiency for aircraft inlets, a similar research investment has not been made for gas sampling. Here, we analyze the performance of a forward-facing laminar flow gas inlet to establish its performance as a function of operating conditions, including ambient pressure, freestream velocities, and sampling conditions. Using computational fluid dynamics (CFD) modeling we simulate flow inside and outside the inlet to determine the extent of freestream turbulent interaction with the sample flow and its implication for gas sample transport. The CFD results of flow features in the inlet are compared against measurements of air speed and turbulent intensity from full-sized high-speed wind-tunnel experiments. These comparisons suggest that the Reynolds Averaged Navier-Stokes (RANS) CFD simulations using the Shear Stress Transport (SST) modeling approach provide the most reasonable prediction of the turbulence characteristics of the inlet. 

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2. Turbulence Model Assessment in Compressible Flows around Complex Geometries with Unstructured Grids

   https://doi.org/10.3390/fluids4020081  

   Araya, Guillermo (June 2019, Fluids)

   One of the key factors in simulating realistic wall-bounded flows at high Reynolds numbers is the selection of an appropriate turbulence model for the steady Reynolds Averaged Navier–Stokes equations (RANS) equations. In this investigation, the performance of several turbulence models was explored for the simulation of steady, compressible, turbulent flow on complex geometries (concave and convex surface curvatures) and unstructured grids. The turbulence models considered were the Spalart–Allmaras model, the Wilcox k- ω model and the Menter shear stress transport (SST) model. The FLITE3D flow solver was employed, which utilizes a stabilized finite volume method with discontinuity capturing. A numerical benchmarking of the different models was performed for classical Computational Fluid Dynamic (CFD) cases, such as supersonic flow over an isothermal flat plate, transonic flow over the RAE2822 airfoil, the ONERA M6 wing and a generic F15 aircraft configuration. Validation was performed by means of available experimental data from the literature as well as high spatial/temporal resolution Direct Numerical Simulation (DNS). For attached or mildly separated flows, the performance of all turbulence models was consistent. However, the contrary was observed in separated flows with recirculation zones. Particularly, the Menter SST model showed the best compromise between accurately describing the physics of the flow and numerical stability. 

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3. Assessment of turbulent boundary layer detachment due to wall-curvature-driven pressure gradient

   Paeres, David (December 2022, Theses)

   Advisor: Dr. Guillermo Araya (Ed.)

   The present study provides fundamental knowledge on an issue in fluid dynamics that is not well understood: flow separation and its association with heat and contaminant transport. In the separated region, a swirling motion increases the fluid drag force on the object. Very often, this is undesirable because it can seriously reduce the performance of engineered devices such as aircraft and turbines. Furthermore, Computational Fluid Dynamics (CFD) has gained ground due to its relatively low cost, high accuracy, and versatility. The principal aim of this study is to numerically elucidate the details behind momentum and passive scalar transport phenomena during turbulent boundary layer separation resulting from a wall-curvature-driven pressure gradient. With Open- FOAM CFD software, the numerical discretization of Reynolds-Averaged Navier-Stokes and passive scalar transport equations will be described in two-dimensional domains via the assessment of two popular turbulence models (i.e., the Spalart-Allmaras and the K-w SST model). The computational domain reproduces a wind tunnel geometry from previously performed experiments by Baskaran et al. (JFM, vol. 182 and 232 “A turbulent flow over a curved hill.” Part 1 and Part 2). Only the velocity and pressure distribution were measured there, which will be used for validation purposes in the present study. A second aim in the present work is the scientific visualization of turbulent events and coherent structures via the ParaView toolkit and Unity game engine. Thus, fully immersive visualization approaches will be used via virtual reality (VR) and augmented reality (AR) technologies. A Virtual Wind Tunnel (VWT), developed for the VR approach, emulates the presence in a wind tunnel laboratory and has already employed fluid flow visualization from an existing numerical database with high temporal/spatial resolution, i.e., Direct Numeric Simulation (DNS). In terms of AR, a FlowVisXR app for smartphones and HoloLens has been developed for portability. It allows the user to see virtual 3D objects (i.e., turbulent coherent structures) invoked into the physical world using the device as the lens. 

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4. Implicit Subgrid-Scale Modeling of a Mach 2.5 Spatially Developing Turbulent Boundary Layer

   https://doi.org/10.3390/e24040555  

   Araya, Guillermo; Lagares, Christian (April 2022, Entropy)

   We employ numerically implicit subgrid-scale modeling provided by the well-known streamlined upwind/Petrov–Galerkin stabilization for the finite element discretization of advection–diffusion problems in a Large Eddy Simulation (LES) approach. Whereas its original purpose was to provide sufficient algorithmic dissipation for a stable and convergent numerical method, more recently, it has been utilized as a subgrid-scale (SGS) model to account for the effect of small scales, unresolvable by the discretization. The freestream Mach number is 2.5, and direct comparison with a DNS database from our research group, as well as with experiments from the literature of adiabatic supersonic spatially turbulent boundary layers, is performed. Turbulent inflow conditions are generated via our dynamic rescaling–recycling approach, recently extended to high-speed flows. Focus is given to the assessment of the resolved Reynolds stresses. In addition, flow visualization is performed to obtain a much better insight into the physics of the flow. A weak compressibility effect is observed on thermal turbulent structures based on two-point correlations (IC vs. supersonic). The Reynolds analogy (u′ vs. t′) approximately holds for the supersonic regime, but to a lesser extent than previously observed in incompressible (IC) turbulent boundary layers, where temperature was assumed as a passive scalar. A much longer power law behavior of the mean streamwise velocity is computed in the outer region when compared to the log law at Mach 2.5. Implicit LES has shown very good performance in Mach 2.5 adiabatic flat plates in terms of the mean flow (i.e., Cf and UVD+). iLES significantly overpredicts the peak values of u′, and consequently Reynolds shear stress peaks, in the buffer layer. However, excellent agreement between the turbulence intensities and Reynolds shear stresses is accomplished in the outer region by the present iLES with respect to the external DNS database at similar Reynolds numbers. 

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5. Remote Visualization and Optimization in Fluid Dynamics via Mixed Reality

   https://doi.org/10.20944/preprints202505.2232.v1  

   More, Sakshi Sandeep; Antron, Brandon; Paeres, David; Araya, Guillermo (May 2025, Preprints.org)

   The study presents an innovative pipeline for processing, compressing, and remotely visualizing large-scale numerical simulations of fluid dynamics in a virtual wind tunnel (VWT), leveraging Virtual and Augmented Reality (VR/AR) for enhanced analysis and high-end visualization. The workflow addresses the challenges of handling massive databases obtained via Direct Numerical Simulation (DNS) while maintaining visual fidelity, promoting full immersion, and ensuring efficient rendering for user interaction. We are performing fully immersive visualization of high-fidelity numerical results of supersonic spatially-developing turbulent boundary layers (SDTBL) under strong concave/convex curvatures at a freestream Mach number of 2.86 (i.e., supersonic flow). 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). The process begins with .vts file input from DNS, which is visualized using the ParaView software. Multiple iso-contours for parameters such as velocity and temperature are generated, applying custom formulas to create visualizations at various floating-point precisions (16-bit, 32-bit, 64-bit). These visualizations, representing different fluid behaviors based on DNS with high spatial/temporal resolution and millions of “numerical sensors”, are treated as individual time frames and exported in GLTF format. Our approach demonstrates significant improvements in rendering speed and user experience, particularly when dealing with datasets comprising hundreds of high-resolution frames from Computational Fluid Dynamics (CFD) simulations. By utilizing server-side compression and cloud rendering, we overcome the limitations of on-device processing, enabling smooth and responsive interactions even with large, complex fluid dynamics datasets. This pipeline represents a substantial advancement in scientific visualization of fluid dynamics, offering researchers and engineers a powerful tool for exploring and analyzing large-scale CFD simulations in an immersive, intuitive environment. Additionally, we leverage Unity’s Profile Analyzer and Memory Profiling tools with the purpose of identifying major bottlenecks and resource-consuming events during contour running, with a keen focus on enhancing GPU and CPU efficiency. In conclusion, the materials and methods employed in this project were instrumental in systematically collecting, analyzing, and interpreting performance data from DNS databases. Future work will focus on optimizing compression algorithms for fluid-specific data and expanding the range of supported simulation parameters to enhance the pipeline’s versatility across various fluid dynamics applications. 

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