Engineering topics

Roy, Christopher J.

Publications and source records attributed to Roy, Christopher J..

3 records

NASA NTRS2019

Turbulence Model Implementation and Verification in the SENSEI CFD Code

This paper outlines the implementation and verification of the negative Spalart-Allmaras turbulence model into the SENSEI CFD code. The SA-neg turbulence model is implemented in a flexible, object-oriented framework where additional turbulence models can be easily added. In addition to outlining the new turbulence modeling framework in SENSEI, an overview of the other general improvements to SENSEI is provided. The results for four 2D test cases are compared to results from CFL3D and FUN3D to verify that the turbulence models are implemented properly. Several differences in the results from SENSEI, CFL3D, and FUN3D are identified and are attributed to differences in the implementation and discretization order of the boundary conditions as well as the order of discretization of the turbulence model. When a solid surface is located near or intersects an inflow or outflow boundary, higher order boundary conditions should be used to limit their effect on the forces on the surface. When the turbulence equations are discretized using second order spatial accuracy, the edge of the eddy viscosity profile seems to be sharper than when a first order discretization is used. However, the discretization order of the turbulence equation does not have a significant impact on output quantities of interest, such as pressure and viscous drag, for the cases studied.

Jackson, Charles W.↗

NASA NTRS2017

Summary of Data from the Sixth AIAA CFD Drag Prediction Workshop: CRM Cases 2 to 5

Results from the Sixth AIAA CFD Drag Prediction Workshop Common Research Model Cases 2 to 5 are presented. As with past workshops, numerical calculations are performed using industry-relevant geometry, methodology, and test cases. Cases 2 to 5 focused on force/moment and pressure predictions for the NASA Common Research Model wing-body and wing-body-nacelle-pylon configurations, including Case 2 - a grid refinement study and nacelle-pylon drag increment prediction study; Case 3 - an angle-of-attack buffet study; Case 4 - an optional wing-body grid adaption study; and Case 5 - an optional wing-body coupled aero-structural simulation. The Common Research Model geometry differed from previous workshops in that it was deformed to the appropriate static aeroelastic twist and deflection at each specified angle-of-attack. The grid refinement study used a common set of overset and unstructured grids, as well as user created Multiblock structured, unstructured, and Cartesian based grids. For the supplied common grids, six levels of refinement were created resulting in grids ranging from 7x10(exp 6) to 208x10(exp 6) cells. This study (Case 2) showed further reduced scatter from previous workshops, and very good prediction of the nacelle-pylon drag increment. Case 3 studied buffet onset at M=0.85 using the Medium grid (20 to 40x10(exp 6) nodes) from the above described sequence. The prescribed alpha sweep used finely spaced intervals through the zone where wing separation was expected to begin. Although the use of the prescribed aeroelastic twist and deflection at each angle-of-attack greatly improved the wing pressure distribution agreement with test data, many solutions still exhibited premature flow separation. The remaining solutions exhibited a significant spread of lift and pitching moment at each angle-of-attack, much of which can be attributed to excessive aft pressure loading and shock location variation. Four Case 4 grid adaption solutions were submitted. Starting with grids less than 2x10(exp 6) grid points, two solutions showed a rapid convergence to an acceptable solution. Four Case 5 coupled aerostructural solutions were submitted. Both showed good agreement with experimental data. Results from this workshop highlight the continuing need for CFD improvement, particularly for conditions with significant flow separation. These comparisons also suggest the need for improved experimental diagnostics to guide future CFD development.

Tinoco, Edward N.↗

NASA NTRS2016

Development and Use of Engineering Standards for Computational Fluid Dynamics for Complex Aerospace Systems

Computational fluid dynamics (CFD) and other advanced modeling and simulation (M&S) methods are increasingly relied on for predictive performance, reliability and safety of engineering systems. Analysts, designers, decision makers, and project managers, who must depend on simulation, need practical techniques and methods for assessing simulation credibility. The AIAA Guide for Verification and Validation of Computational Fluid Dynamics Simulations (AIAA G-077-1998 (2002)), originally published in 1998, was the first engineering standards document available to the engineering community for verification and validation (V&V) of simulations. Much progress has been made in these areas since 1998. The AIAA Committee on Standards for CFD is currently updating this Guide to incorporate in it the important developments that have taken place in V&V concepts, methods, and practices, particularly with regard to the broader context of predictive capability and uncertainty quantification (UQ) methods and approaches. This paper will provide an overview of the changes and extensions currently underway to update the AIAA Guide. Specifically, a framework for predictive capability will be described for incorporating a wide range of error and uncertainty sources identified during the modeling, verification, and validation processes, with the goal of estimating the total prediction uncertainty of the simulation. The Guide's goal is to provide a foundation for understanding and addressing major issues and concepts in predictive CFD. However, this Guide will not recommend specific approaches in these areas as the field is rapidly evolving. It is hoped that the guidelines provided in this paper, and explained in more detail in the Guide, will aid in the research, development, and use of CFD in engineering decision-making.

Lee, Hyung B.↗