Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “RANS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

HLPW-4/GMGW-3: Mesh Adaptation for RANS Technology Focus Group Workshop Summary

The AIAA workshop series helps guide the Computational Fluid Dynamics (CFD) community through publicly available test cases and impartial evaluation to establish the state-of-the-art in applied CFD. A summary of the Mesh Adaptation Technical Focus Group submissions for the joint Fourth CFD High Lift Prediction and Third Geometry & Mesh Generation Workshop is provided. The Common Research Model High-Lift variant (CRM-HL) is the target of this investigation. A 2D high-lift airfoil solution verification case was extracted from the 3D CRM-HL. Low variation is shown between 2D solutions with mesh adaptation to control estimated solution interpolation and output errors. As expected, variation for these mesh adaptation techniques is larger for the 3D CRM-HL than the 2D airfoil. More importantly, the 3D mesh adapted results have a lower variation than expert-crafted meshes of equal or larger size. Suspected multiple solutions to Reynolds-averaged Navier-Stokes with the Spalart-Allmaras turbulence model appear to resolve into a common solution with mesh resolution.

HLPW-4↗
NASA NTRS2023

Unsteady RANS and Scale Resolving Simulations of Open Rotor Noise

Computational simulations using structured curvilinear overset grids with the Launch Ascent and Vehicle Aerodynamics (LAVA) framework are presented for predicting the aerodynamic and aeroacoustic behavior of a contra-rotating open rotor (CROR) propulsion system using a newly developed and computationally efficient sliding mesh technique. A comprehensive evaluation of two turbulence closure treatments is carried out as part of the scope of this work: Unsteady Reynolds-Averaged Navier-Stokes Simulation (URANS), and Hybrid RANS/LES (HRLES). The computed results are then validated against existing experimental measurements at both the nominal take-off and cruise flight conditions. To propagate the noise generated by the near-field CROR system, aeroacoustic analysis based on a frequency-domain permeable surface Ffowcs Williams-Hawkings (FW-H) approach is applied.

ARMD↗
NASA NTRS2023

Unsteady RANS and Scale Resolving Simulations of Open Rotor Noise

Computational simulations using structured curvilinear overset grids with the Launch Ascent and Vehicle Aerodynamics (LAVA) framework are presented for predicting the aerodynamic and aeroacoustic behavior of a contra-rotating open rotor (CROR) propulsion system using a newly developed and computationally efficient sliding mesh technique. A comprehensive evaluation of two turbulence closure treatments is carried out as part of the scope of this work: Unsteady Reynolds-Averaged Navier-Stokes Simulation (URANS), and Hybrid RANS/LES (HRLES). The computed results are then validated against existing experimental measurements at both the nominal take-off and cruise flight conditions. To propagate the noise generated by the near-field CROR system, aeroacoustic analysis based on a frequency-domain permeable surface Ffowcs Williams-Hawkings (FW-H) approach is applied.

ARMD↗
NASA NTRSDate not supplied

On Generalizably Improving RANS Predictions of Flow Separation and Reattachment

This work presents progress in an ongoing data-driven turbulence modeling effort at NASA Langley Research Center to improve predictions for separated flows. Two augmentation strategies are presented – one to improve predictions for the point of reattachment after smooth-body separation, and another to improve predictions for flow separation due to prolonged adverse pressure gradients. The reattachment augmentation was inspired from lessons learned during attempts at using field inversion and machine learning (FIML); however, it is prescribed as a conventional analytic closed-form expression. Results show that, when introduced into the SST k-w model, it shortens the otherwise overpredicted separation bubble length for three cases characterized by different Reynolds numbers and flow geometries. The second augmentation, which addresses flow separation under prolonged adverse pressure gradients, is inferred via FIML and applied as a neural network within the Spalart-Allmaras model. It uses features that are chosen such that the presented results show an improved predictive accuracy for the training case without affecting other cases where the augmentation is not needed. Further testing is required to establish the generalizability of this augmentation. The rationale behind the chosen features that serve as inputs to both these augmentations is also presented for the benefit of the reader.

machine learning↗
NASA NTRS2012

Large-Eddy / Reynolds-Averaged Navier-Stokes Simulations of a Dual-Mode Scramjet Combustor

Numerical simulations of reacting and non-reacting flows within a scramjet combustor configuration experimentally mapped at the University of Virginia s Scramjet Combustion Facility (operating with Configuration A ) are described in this paper. Reynolds-Averaged Navier-Stokes (RANS) and hybrid Large Eddy Simulation / Reynolds-Averaged Navier-Stokes (LES / RANS) methods are utilized, with the intent of comparing essentially blind predictions with results from non-intrusive flow-field measurement methods including coherent anti-Stokes Raman spectroscopy (CARS), hydroxyl radical planar laser-induced fluorescence (OH-PLIF), stereoscopic particle image velocimetry (SPIV), wavelength modulation spectroscopy (WMS), and focusing Schlieren. NC State's REACTMB solver was used both for RANS and LES / RANS, along with a 9-species, 19- reaction H2-air kinetics mechanism by Jachimowski. Inviscid fluxes were evaluated using Edwards LDFSS flux-splitting scheme, and the Menter BSL turbulence model was utilized in both full-domain RANS simulations and as the unsteady RANS portion of the LES / RANS closure. Simulations were executed and compared with experiment at two equivalence ratios, PHI = 0.17 and PHI = 0.34. Results show that the PHI = 0.17 flame is hotter near the injector while the PHI = 0.34 flame is displaced further downstream in the combustor, though it is still anchored to the injector. Reactant mixing was predicted to be much better at the lower equivalence ratio. The LES / RANS model appears to predict lower overall heat release compared to RANS (at least for PHI = 0.17), and its capability to capture the direct effects of larger turbulent eddies leads to much better predictions of reactant mixing and combustion in the flame stabilization region downstream of the fuel injector. Numerical results from the LES/RANS model also show very good agreement with OH-PLIF and SPIV measurements. An un-damped long-wave oscillation of the pre-combustion shock train, which caused convergence problems in some RANS simulations, was also captured in LES / RANS simulations, which were able to accommodate its effects accurately.

Fulton, Jesse A.↗
NASA NTRS2014

Turbulence Modeling Verification and Validation

Computational fluid dynamics (CFD) software that solves the Reynolds-averaged Navier-Stokes (RANS) equations has been in routine use for more than a quarter of a century. It is currently employed not only for basic research in fluid dynamics, but also for the analysis and design processes in many industries worldwide, including aerospace, automotive, power generation, chemical manufacturing, polymer processing, and petroleum exploration. A key feature of RANS CFD is the turbulence model. Because the RANS equations are unclosed, a model is necessary to describe the effects of the turbulence on the mean flow, through the Reynolds stress terms. The turbulence model is one of the largest sources of uncertainty in RANS CFD, and most models are known to be flawed in one way or another. Alternative methods such as direct numerical simulations (DNS) and large eddy simulations (LES) rely less on modeling and hence include more physics than RANS. In DNS all turbulent scales are resolved, and in LES the large scales are resolved and the effects of the smallest turbulence scales are modeled. However, both DNS and LES are too expensive for most routine industrial usage on today's computers. Hybrid RANS-LES, which blends RANS near walls with LES away from walls, helps to moderate the cost while still retaining some of the scale-resolving capability of LES, but for some applications it can still be too expensive. Even considering its associated uncertainties, RANS turbulence modeling has proved to be very useful for a wide variety of applications. For example, in the aerospace field, many RANS models are considered to be reliable for computing attached flows. However, existing turbulence models are known to be inaccurate for many flows involving separation. Research has been ongoing for decades in an attempt to improve turbulence models for separated and other nonequilibrium flows. When developing or improving turbulence models, both verification and validation are important steps in the process. Verification insures that the CFD code is solving the equations as intended (no errors in the implementation). This is typically done either through the method of manufactured solutions (MMS) or through careful step-by-step comparisons with other verified codes. After the verification step is concluded, validation is performed to document the ability of the turbulence model to represent different types of flow physics. Validation can involve a large number of test case comparisons with experiments, theory, or DNS. Organized workshops have proved to be valuable resources for the turbulence modeling community in its pursuit of turbulence modeling verification and validation. Workshop contributors using different CFD codes run the same cases, often according to strict guidelines, and compare results. Through these comparisons, it is often possible to (1) identify codes that have likely implementation errors, and (2) gain insight into the capabilities and shortcomings of different turbulence models to predict the flow physics associated with particular types of flows. These are valuable lessons because they help bring consistency to CFD codes by encouraging the correction of faulty programming and facilitating the adoption of better models. They also sometimes point to specific areas needed for improvement in the models. In this paper, several recent workshops are summarized primarily from the point of view of turbulence modeling verification and validation. Furthermore, the NASA Langley Turbulence Modeling Resource website is described. The purpose of this site is to provide a central location where RANS turbulence models are documented, and test cases, grids, and data are provided. The goal of this paper is to provide an abbreviated survey of turbulence modeling verification and validation efforts, summarize some of the outcomes, and give some ideas for future endeavors in this area.

Rumsey, Christopher L.↗