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NASA NTRS2017

Axial-Flow Turbine Rotor Discharge-Flow Overexpansion and Limit-Loading Condition, Part I: Computational Fluid Dynamics (CFD) Investigation

A Computational Fluid Dynamic (CFD) investigation is conducted over a two-dimensional axial-flow turbine rotor blade row to study the phenomena of turbine rotor discharge flow overexpansion at subcritical, critical, and supercritical conditions. Quantitative data of the mean-flow Mach numbers, mean-flow angles, the tangential blade pressure forces, the mean-flow mass flux, and the flow-path total pressure loss coefficients, averaged or integrated across the two-dimensional computational domain encompassing two blade-passages, are obtained over a series of 14 inlet-total to exit-static pressure ratios, from 1.5 (un-choked; subcritical condition) to 10.0 (supercritical with excessively high pressure ratio.) Detailed flow features over the full domain-of-computation, such as the streamline patterns, Mach contours, pressure contours, blade surface pressure distributions, etc. are collected and displayed in this paper. A formal, quantitative definition of the limit loading condition based on the channel flow theory is proposed and explained. Contrary to the comments made in the historical works performed on this subject, about the deficiency of the theoretical methods applied in analyzing this phenomena, using modern CFD method for the study of this subject appears to be quite adequate and successful. This paper describes the CFD work and its findings.

Axial Flow↗

NASA NTRS2009

Modeling Potential Carbon Monoxide Exposure Due to Operation of a Major Rocket Engine Altitude Test Facility Using Computational Fluid Dynamics

This viewgraph presentation reviews computational fluid dynamics as a tool for modelling the dispersion of carbon monoxide at the Stennis Space Center's A3 Test Stand. The contents include: 1) Constellation Program; 2) Constellation Launch Vehicles; 3) J2X Engine; 4) A-3 Test Stand; 5) Chemical Steam Generators; 6) Emission Estimates; 7) Located in Existing Test Complex; 8) Computational Fluid Dynamics; 9) Computational Tools; 10) CO Modeling; 11) CO Model results; and 12) Next steps.

Blotzer, Michael J.↗

NASA NTRS1989

Computational fluid dynamics

An overview of computational fluid dynamics (CFD) activities at the Langley Research Center is given. The role of supercomputers in CFD research, algorithm development, multigrid approaches to computational fluid flows, aerodynamics computer programs, computational grid generation, turbulence research, and studies of rarefied gas flows are among the topics that are briefly surveyed.

Source record↗

NASA NTRS1989

Supercomputer applications in computational fluid dynamics

The field of computational fluid dynamics (CFD) using large-scale supercomputer applications is discussed. Formulational and computational requirements for the various governing equations, including the Euler and Navier-tokes approaches, are examined for typical problems including the viscous flow field solution about a complete aerospace vehicle. Recent computed results and experimental comparisons are given to highlight the presentation. The future of CFD associated with three-dimensional applications is found to be rapidly expanding across a broad front, including internal and external flows and flows across the entire speed regime.

Holst, Terry L.↗

NASA NTRS1988

Potential applications of computational fluid dynamics to biofluid analysis

Computational fluid dynamics was developed to the stage where it has become an indispensable part of aerospace research and design. In view of advances made in aerospace applications, the computational approach can be used for biofluid mechanics research. Several flow simulation methods developed for aerospace problems are briefly discussed for potential applications to biofluids, especially to blood flow analysis.

Kwak, D.↗

NASA NTRS1992

Delaunay triangulation and computational fluid dynamics meshes

In aerospace computational fluid dynamics (CFD) calculations, the Delaunay triangulation of suitable quadrilateral meshes can lead to unsuitable triangulated meshes. Here, we present case studies which illustrate the limitations of using structured grid generation methods which produce points in a curvilinear coordinate system for subsequent triangulations for CFD applications. We discuss conditions under which meshes of quadrilateral elements may not produce a Delaunay triangulation suitable for CFD calculations, particularly with regard to high aspect ratio, skewed quadrilateral elements.

Posenau, Mary-Anne K.↗

NASA NTRS1994

Interpretation of waverider performance data using computational fluid dynamics

A computational study was conducted to better understand experimental results obtained from wind-tunnel tests of a Mach 4 conical-flow-derived waverider and a comparative reference configuration, which showed that the aerodynamic performance of the reference configuration was slightly better than that of the waverider. The computational results showed that the predicted surface pressure values and the integrated lift and drag coefficients were much lower for the reference model because the reference model bottom is an expansion surface. However, the lift-drag ratios for the reference model were higher due to a relatively low drag for a comparable amount of lift. The results also showed that the reference model exhibited the same shock attachment characteristics as the conical-flow-derived waverider, and is therefore also a waverider. The shock attachment characteristic gives the waverider a performance advantage over conventional hypersonic vehicles, and the results suggest that altering the bottom surface does not cause significant performance degradation. Flowfield solutions also show that the conical-flow waverider model has better propulsion/airframe integration characteristics than the reference configuration. The results also suggest that generating flowfields other than conical ones may be used to design waveriders with improved aerodynamic performance.

COMPUTATIONAL FLUID DYNAMICS↗

NASA NTRS1997

Flowfield-Dependent Mixed Explicit-Implicit (FDMEL) Algorithm for Computational Fluid Dynamics

Despite significant achievements in computational fluid dynamics, there still remain many fluid flow phenomena not well understood. For example, the prediction of temperature distributions is inaccurate when temperature gradients are high, particularly in shock wave turbulent boundary layer interactions close to the wall. Complexities of fluid flow phenomena include transition to turbulence, relaminarization separated flows, transition between viscous and inviscid incompressible and compressible flows, among others, in all speed regimes. The purpose of this paper is to introduce a new approach, called the Flowfield-Dependent Mixed Explicit-Implicit (FDMEI) method, in an attempt to resolve these difficult issues in Computational Fluid Dynamics (CFD). In this process, a total of six implicitness parameters characteristic of the current flowfield are introduced. They are calculated from the current flowfield or changes of Mach numbers, Reynolds numbers, Peclet numbers, and Damkoehler numbers (if reacting) at each nodal point and time step. This implies that every nodal point or element is provided with different or unique numerical scheme according to their current flowfield situations, whether compressible, incompressible, viscous, inviscid, laminar, turbulent, reacting, or nonreacting. In this procedure, discontinuities or fluctuations of an variables between adjacent nodal points are determined accurately. If these implicitness parameters are fixed to certain numbers instead of being calculated from the flowfield information, then practically all currently available schemes of finite differences or finite elements arise as special cases. Some benchmark problems to be presented in this paper will show the validity, accuracy, and efficiency of the proposed methodology.

Garcia, S. M.↗

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.↗

NASA NTRS1995

Visualization of unsteady computational fluid dynamics

The current computing environment that most researchers are using for the calculation of 3D unsteady Computational Fluid Dynamic (CFD) results is a super-computer class machine. The Massively Parallel Processors (MPP's) such as the 160 node IBM SP2 at NAS and clusters of workstations acting as a single MPP (like NAS's SGI Power-Challenge array) provide the required computation bandwidth for CFD calculations of transient problems. Work is in progress on a set of software tools designed specifically to address visualizing 3D unsteady CFD results in these super-computer-like environments. The visualization is concurrently executed with the CFD solver. The parallel version of Visual3, pV3 required splitting up the unsteady visualization task to allow execution across a network of workstation(s) and compute servers. In this computing model, the network is almost always the bottleneck so much of the effort involved techniques to reduce the size of the data transferred between machines.

Haimes, Robert↗

NASA NTRS1997

Visualization of Unsteady Computational Fluid Dynamics

The current compute environment that most researchers are using for the calculation of 3D unsteady Computational Fluid Dynamic (CFD) results is a super-computer class machine. The Massively Parallel Processors (MPP's) such as the 160 node IBM SP2 at NAS and clusters of workstations acting as a single MPP (like NAS's SGI Power-Challenge array and the J90 cluster) provide the required computation bandwidth for CFD calculations of transient problems. If we follow the traditional computational analysis steps for CFD (and we wish to construct an interactive visualizer) we need to be aware of the following: (1) Disk space requirements. A single snap-shot must contain at least the values (primitive variables) stored at the appropriate locations within the mesh. For most simple 3D Euler solvers that means 5 floating point words. Navier-Stokes solutions with turbulence models may contain 7 state-variables. (2) Disk speed vs. Computational speeds. The time required to read the complete solution of a saved time frame from disk is now longer than the compute time for a set number of iterations from an explicit solver. Depending, on the hardware and solver an iteration of an implicit code may also take less time than reading the solution from disk. If one examines the performance improvements in the last decade or two, it is easy to see that depending on disk performance (vs. CPU improvement) may not be the best method for enhancing interactivity. (3) Cluster and Parallel Machine I/O problems. Disk access time is much worse within current parallel machines and cluster of workstations that are acting in concert to solve a single problem. In this case we are not trying to read the volume of data, but are running the solver and the solver outputs the solution. These traditional network interfaces must be used for the file system. (4) Numerics of particle traces. Most visualization tools can work upon a single snap shot of the data but some visualization tools for transient problems require dealing with time.

Haimes, Robert↗

NASA NTRS1992

Modeling of solid/porous wall boundary conditions for the validation of computational fluid dynamics codes

A computational study has been undertaken to investigate method of modeling solid and porous wall boundary conditions in computational fluid dynamics (CFD) codes. The procedure utilizes experimental measurements at the walls to develop a flow field solution based on the method of singularities. This flow field solution is then imposed as a boundary condition in a CFD simulation of the internal flow field. The effectiveness of this method in describing the boundary conditions at the wind tunnel walls using only sparse experimental measurements has been investigated. Position and refinement of experimental measurement locations required to describe porous wall boundary conditions has also been considered.

Beutner, Thomas J.↗

NASA NTRS1994

Determination of solid/porous wall boundary conditions from wind tunnel data for computational fluid dynamics codes

A computational and experimental study has been undertaken to investigate methods of modelling solid and porous wall boundary conditions in computational fluid dynamics (CFD) codes. The procedure utilizes experimental measurements at the walls to develop a flow field solution based on the method of singularities. This flow field solution is then imposed as a pressure boundary condition in a CFD simulation of the internal flow field. The effectiveness of this method in describing the boundary conditions at the wind tunnel walls using only sparse experimental measurements has been investigated. Verification of the approach using computational studies has been carried out using an incompressible flow solver. The current work demonstrates this technique for low speed flows and compares the result with experimental data obtained from a heavily instrumented variable porosity test section. Position and refinement of experimental measurements required to describe porous wall boundary conditions have also been considered for application to other porous wall wind tunnels. The approach developed is simple, computationally inexpensive, and does not require extensive or intrusive measurements. It may be applied to both solid and porous wall wind tunnel tests. Some consideration is given to the extension of this method to three dimensions.

Beutner, Thomas J.↗

NASA NTRS1989

Computational Fluid Dynamics Program at NASA Ames Research Center

The Computational Fluid Dynamics (CFD) Program at NASA Ames Research Center is reviewed and discussed. The technical elements of the CFD Program are listed and briefly discussed. These elements include algorithm research, research and pilot code development, scientific visualization, advanced surface representation, volume grid generation, and numerical optimization. Next, the discipline of CFD is briefly discussed and related to other areas of research at NASA Ames including experimental fluid dynamics, computer science research, computational chemistry, and numerical aerodynamic simulation. These areas combine with CFD to form a larger area of research, which might collectively be called computational technology. The ultimate goal of computational technology research at NASA Ames is to increase the physical understanding of the world in which we live, solve problems of national importance, and increase the technical capabilities of the aerospace community. Next, the major programs at NASA Ames that either use CFD technology or perform research in CFD are listed and discussed. Briefly, this list includes turbulent/transition physics and modeling, high-speed real gas flows, interdisciplinary research, turbomachinery demonstration computations, complete aircraft aerodynamics, rotorcraft applications, powered lift flows, high alpha flows, multiple body aerodynamics, and incompressible flow applications. Some of the individual problems actively being worked in each of these areas is listed to help define the breadth or extent of CFD involvement in each of these major programs. State-of-the-art examples of various CFD applications are presented to highlight most of these areas. The main emphasis of this portion of the presentation is on examples which will not otherwise be treated at this conference by the individual presentations. Finally, a list of principal current limitations and expected future directions is given.

Holst, Terry L.↗

NASA NTRS1987

Computational fluid dynamics for hypersonic airbreathing airplanes

Computational fluid dynamics (CFD) technology is discussed as it relates to the computation of flowfields associated with hypersonic air-breathing airplanes. It is shown that the unique aerodynamics of these vehicles places different demands on CFD than reentry bodies do. The major areas requiring the use of advanced CFD techniques are the prediction of airframe aerodynamics, propulsion/airframe flowfield interaction, and internal engine flows.

Dwoyer, Douglas L.↗

NASA NTRS1993

Interpretation of waverider performance data using computational fluid dynamics

A computational study was conducted to better understand experimental results obtained from wind tunnel tests of a Mach 4 waverider model and a comparative reference configuration. The experimental results showed that the performance of the reference configuration was slightly better than that of the waverider model. These results contradict waverider design theory, which suggests that a waverider optimized for maximum lift-to-drag should provide better performance than any other non-waverider configuration at a given design point, especially at hypersonic speeds. The computational results showed that the predicted surface pressure values and the integrated lift and drag coefficients from the pressure distributions were much lower for the reference model than for the flat-top model, due to the reference model bottom surface having a slight expansion. The lift-to-drag ratios for the flat-top model were higher due to a relatively low drag for the same amount of lift. These results indicate that the performance advantage of the reference model was due to the shape of the bottom surface and not due to the flat top surface. The results also showed that the reference model exhibited the same shock attachment characteristics as the waverider because the planform shapes were identical. CFD predictions show that the planform shape gives the waverider an advantage in performance over conventional hypersonic vehicles and that altering the bottom surface of a waverider does not cause significant performance degradation.

Cockrell, Charles E., Jr.↗

NASA NTRS1999

Aeroservoelastic and Flight Dynamics Analysis Using Computational Fluid Dynamics

This document in large part is based on the Masters Thesis of Cole Stephens. The document encompasses a variety of technical and practical issues involved when using the STARS codes for Aeroservoelastic analysis of vehicles. The document covers in great detail a number of technical issues and step-by-step details involved in the simulation of a system where aerodynamics, structures and controls are tightly coupled. Comparisons are made to a benchmark experimental program conducted at NASA Langley. One of the significant advantages of the methodology detailed is that as a result of the technique used to accelerate the CFD-based simulation, a systems model is produced which is very useful for developing the control law strategy, and subsequent high-speed simulations.

Arena, Andrew S., Jr.↗

NASA NTRS1993

Interpretation of Waverider Performance Data Using Computational Fluid Dynamics

Cockrell, Charles E., Jr.↗