摘要 :
A unified assessment of three turbulence treatments: Reynolds Averaged Navier-Stokes (RANS), Hybrid RANS/LES (HRLES) and Equilibrium Wall-Modelled Large Eddy Simulation (WMLES) is presented for the High-Lift Common Research Model ...
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A unified assessment of three turbulence treatments: Reynolds Averaged Navier-Stokes (RANS), Hybrid RANS/LES (HRLES) and Equilibrium Wall-Modelled Large Eddy Simulation (WMLES) is presented for the High-Lift Common Research Model (CRM-HL). For the free-air configuralion, steady-state RANS simulations show very accurate drag polar predictions in the Iow-α linear regime. However, strong grid sensitivity is reported near the maximum lift-state (C_(L_(max))), with finer-grids showing larger errors and predicting erroneous flow topologies on the wing. Our RANS simulations show that several corrections for the Spalart-Allmaras (SA) turbulence model widely used in the community lead to more erroneous results compared to the baseline closure, without exception. Both scale-resolving methods (HRLES and WMLES) address these drawbacks and predict an outboard separation pattern on the main element that is in good agreement with the oil flow photographs taken from the QinetiQ wind tunnel experiments, when LES-appropriate grids and numerical discretizations are used. While RANS simulations with the baseline SA closure do not show any wing-root separation post C_(L_(max)), both HRLES and WMLES show onset of corner flow separation with varying degrees of progression, along with a weak pitch break in the wing-contribution of the overall pitching moment. This post-C_(L_(max)) pitch break seen in the free-air simulations is weaker than the break observed in experiments, with a weaker break reported in WMLES for each iteration of grid-refinement. In-tunnel simulations using both SA-baseline RANS and WMLES show a much stronger post-C_(L_(max)) break with the WMLES predictions showing excellent agreement with the experiment in terms of both the flow-topology observed and the pressure-coefficients at various spanwise stations. Sensitivity to the tunnel wall boundary layer is characterized via comparisons between viscous and inviscid treatments for the tunnel walls. WMLES predictions show moderate sensitivity at the predicted inboard flow-state at C_(L_(max)) along with the progression towards a post-C_(L_(max)) stall; however, this stalled state at α≈20° (inside the tunnel) obtained with both tunnel wall treatments appears to be largely identical.
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A sliding mesh technique within the Launch, Ascent, and Vehicle Aerodynamics (LAVA) computational framework is validated using the experimental dataset collected as part of the NASA Source Diagnostic Test (SDT) campaign. Two model...
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A sliding mesh technique within the Launch, Ascent, and Vehicle Aerodynamics (LAVA) computational framework is validated using the experimental dataset collected as part of the NASA Source Diagnostic Test (SDT) campaign. Two modeling approaches are explored: the unsteady Reynolds-Averaged Navier Stokes (URANS) with Spalart-Allmaras (SA) turbulence model closure, and a hybrid Reynolds-Averaged Navier Stokes/Large Eddy Simulation (RANS/LES) paradigm employing a Zonal Detached Eddy Simulation (ZDES) closure with enhanced shielding protection. Fan stage performance metrics, aerodynamic quantities and turbulent flow structures are analyzed in this work. Initial studies focusing on grid and time-step sensitivity are presented. Sensitivity to different variants of the SA turbulence model is analyzed, supporting the use of the baseline SA model in the production runs. Two conditions are analyzed in detail using URANS and hybrid RANS/LES (HRLES). Mean How quantities are well-captured by both methods in the low-speed (approach) regime. While URANS misses all the upstream-propagating noise in the inlet due to the rotor-locked tones being evanescent in nature at subsonic fan tip speeds, HRLES captures this broadband component in its pressure field. At the high-speed (sideline) condition, URANS shows better agreement with the SDT data than HRLES in the interstage flow-field. In this regime, URANS captures the tonal content propagating through the inlet, since the tones are now cut-on. Both methods are suitable to capture fan stage performance metrics and mean flow quantities, but only HRLES is able to resolve the fine turbulent structures responsible for broadband noise. The results support the use of the sliding mesh technique implemented in this work for future turbomachinery applications within the LAVA solver framework.
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This paper is a joint effort between the National Aeronautics and Space Administration (NASA) Ames and Langley research centers to assess the capability of modern Computational Fluid Dynamic (CFD) codes to accurately simulate expe...
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This paper is a joint effort between the National Aeronautics and Space Administration (NASA) Ames and Langley research centers to assess the capability of modern Computational Fluid Dynamic (CFD) codes to accurately simulate experimental force and moment loads on the core stage rocket and Solid Rocket Boosters (SRBs) during the SRBs' separation from a Block IB configuration Space Launch System (SLS) exploration-class launch vehicle test article within a supersonic wind tunnel. Motivation for this work is linked to a database of runs representing SRB separation from the SLS's core performed within the Langley Unitary Plan Wind Tunnel (LUPWT) and efforts to quantify the uncertainty of CFD prediction in such conditions. Due to the fact that test article loading is influenced by the aerodynamic characteristics of its environment, the LUWPT itself is also assessed through CFD simulation to properly characterize the flow of the tunnel. Separate research groups at Ames and Langley independent of the SLS team were chosen to conduct these studies. The two CFD codes selected to assess the LUPWT's flow characteristics and the aerodynamic forces and moments on the test article within it representing the SRBs' separation from the SLS are the Launch, Ascent and Vehicle Aerodynamics (LAVA) framework and Fully Unstructured Navier-Stokes (FUN3D), both of which solve the Reynolds-averaged Navier-Stokes equations. The processes each team used to independently determine gridding and solution best practices are detailed. Results found using these best practices, as well as computational cost estimates associated with them, are presented and discussed.
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The Launch Ascent and Vehicle Aerodynamics (LAVA) solver, developed at NASA Ames Research Center, is introduced. The focus of the solver is Computational Fluid Dynamics (CFD), but it also features auxiliary modules for Conjugate H...
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The Launch Ascent and Vehicle Aerodynamics (LAVA) solver, developed at NASA Ames Research Center, is introduced. The focus of the solver is Computational Fluid Dynamics (CFD), but it also features auxiliary modules for Conjugate Heat Transfer (CHT) and Computational Aero-Acoustics (CAA) capabilities. LAVA is designed to be grid-flexible, i.e., it can handle Cartesian, block-structured curvilinear or unstructured grids either in stand-alone or by coupling different grid types through an overset interface. A description of the spatial discretizations utilized for each grid type, along with the available explicit and implicit time-stepping schemes, is provided. An overset grid coupling procedure of Cartesian and unstructured mesh types, as well as the CHT and CAA capabilities are outlined. Several NASA mission related applications are highlighted: pressure, thermal and acoustic analyses of the geometrically complex launch environment; steady and unsteady ascent aerodynamics; and plume-induced flow separation analyses of heavy lift launch vehicles. Two validation studies from NASA's fundamental aeronautics program are presented: MIT's fixed-wing D8 "double-bubble" aircraft, and the 1st AIAA Sonic Boom Prediction Workshop test cases.
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摘要 :
The Launch Ascent and Vehicle Aerodynamics (LAVA) solver, developed at NASA Ames Research Center, is introduced. The focus of the solver is Computational Fluid Dynamics (CFD), but it also features auxiliary modules for Conjugate H...
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The Launch Ascent and Vehicle Aerodynamics (LAVA) solver, developed at NASA Ames Research Center, is introduced. The focus of the solver is Computational Fluid Dynamics (CFD), but it also features auxiliary modules for Conjugate Heat Transfer (CHT) and Computational Aero-Acoustics (CAA) capabilities. LAVA is designed to be grid-flexible, i.e., it can handle Cartesian, block-structured curvilinear or unstructured grids either in stand-alone or by coupling different grid types through an overset interface. A description of the spatial discretizations utilized for each grid type, along with the available explicit and implicit time-stepping schemes, is provided. An overset grid coupling procedure of Cartesian and unstructured mesh types, as well as the CHT and CAA capabilities are outlined. Several NASA mission related applications are highlighted: pressure, thermal and acoustic analyses of the geometrically complex launch environment; steady and unsteady ascent aerodynamics; and plume-induced flow separation analyses of heavy lift launch vehicles. Two validation studies from NASA's fundamental aeronautics program are presented: MIT's fixed-wing D8 "double-bubble" aircraft, and the 1st AIAA Sonic Boom Prediction Workshop test cases.
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Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Descr...
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Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Description of the mesh generation techniques and numerical methods are provided along with a comparison of nearfield and far-field predictions with available experimental data as well as other workshop submissions. Strong consistency was observed between the Biconvex and C608 nearfield predictions across the two solvers used for this study, as well as validation and verification data. Additionally, near-field and farfield ground signature results using a combination of a truncated computational fluid dynamics (CFD) domain coupled to a mid-field space marching method and propagated to the ground using sBOOM will be discussed. This approach is shown to provide an efficient way to propagate near-field pressure signatures to the ground with the same accuracy as the near-field CFD coupled to sBOOM, but at less computational cost.
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Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Descr...
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Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Description of the mesh generation techniques and numerical methods are provided along with a comparison of nearfield and far-field predictions with available experimental data as well as other workshop submissions. Strong consistency was observed between the Biconvex and C608 nearfield predictions across the two solvers used for this study, as well as validation and verification data. Additionally, near-field and farfield ground signature results using a combination of a truncated computational fluid dynamics (CFD) domain coupled to a mid-field space marching method and propagated to the ground using sBOOM will be discussed. This approach is shown to provide an efficient way to propagate near-field pressure signatures to the ground with the same accuracy as the near-field CFD coupled to sBOOM, but at less computational cost.
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摘要 :
Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Descr...
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Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Description of the mesh generation techniques and numerical methods are provided along with a comparison of nearfleld and far-field predictions with available experimental data as well as other workshop submissions. Strong consistency was observed between the Biconvex and C608 nearfield predictions across the two solvers used for this study, as well as validation and verification data. Additionally, near-field and farfield ground signature results using a combination of a truncated computational fluid dynamics (CFD) domain coupled to a mid-field space marching method and propagated to the ground using sBOOM will be discussed. This approach is shown to provide an efficient way to propagate near-field pressure signatures to the ground with the same accuracy as the near-field CFD coupled to sBOOM, but at less computational cost.
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摘要 :
Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Descr...
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Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Description of the mesh generation techniques and numerical methods are provided along with a comparison of nearfleld and far-field predictions with available experimental data as well as other workshop submissions. Strong consistency was observed between the Biconvex and C608 nearfield predictions across the two solvers used for this study, as well as validation and verification data. Additionally, near-field and farfield ground signature results using a combination of a truncated computational fluid dynamics (CFD) domain coupled to a mid-field space marching method and propagated to the ground using sBOOM will be discussed. This approach is shown to provide an efficient way to propagate near-field pressure signatures to the ground with the same accuracy as the near-field CFD coupled to sBOOM, but at less computational cost.
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A joint effort between the NASA Ames and Langley Research Centers was undertaken to analyze the Mach 0.745 variant of the Boeing Transonic Truss-Braced Wing (TTBW) Design. Two different flow solvers, LAVA and USM3D, were used to p...
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A joint effort between the NASA Ames and Langley Research Centers was undertaken to analyze the Mach 0.745 variant of the Boeing Transonic Truss-Braced Wing (TTBW) Design. Two different flow solvers, LAVA and USM3D, were used to predict the TTBW flight performance. Sensitivity studies related to mesh resolution and numerical schemes were conducted to define best practices for this type of geometry and flow regime. Validation efforts compared the numerical simulation results of various modeling methods against experimental data taken from the NASA Ames 11-foot Unitary Wind Tunnel experimental data. The fidelity of the computational representation of the wind tunnel experiment, such as utilizing a porous wall boundary condition to model the ventilated test section, was varied to examine how different tunnel effects influence CFD predictions. LAVA and USM3D results both show an approximate 0.5° angle of attack shift from experimental lift curve data. This drove an investigation that revealed that the trailing edge of the experimental model was rounded in comparison to the CAD model, due to manufacturing tolerances, which had not been accounted for in the initial simulations of the experiment. Simulating the TTBW with an approximation of this rounded trailing-edge reduces error by approximately 60%. An accurate representation of the tested TTBW geometry, ideally including any wing twists and deflections experienced during the test under various loading conditions, will be necessary for proper validation of the CFD.
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