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CFD Publications - PDF
CFD Publications in PDF format

The following is a partial list of NEAR papers related to CFD and CFD methods development. Most are available in PDF format and can be downloaded to your system. PDF format allows you to view the downloaded document on most computers. You will need Adobe's freely available Acrobat Reader or browser plug-in to view and print PDF files.

  • Probabilistic Error Modeling in Computational Fluid Dynamics,
    Robert. E. Childs and Patrick H. Reisenthel
    [available as RTO-MP-AVT-147 Paper 1]
Copyright © 2007 Nielsen Engineering & Research

ABSTRACT: The work reported here uses error modeling, both deterministic and probabilistic, as a means of quantifying the inaccuracy in computational fluid dynamics (CFD) results. The two fundamental elements of error modeling are the quantification of error sources and the propagation of error through a solution. The present research focuses on the error sources and treats error propagation either in a deterministic manner or by using a Monte Carlo approach. A nonintrusive form of error modeling based on the concept of “defect correction” is used. The truncation errors, or other error sources, are computed and added to the residual. The equations modified by error sources are then solved, and the error in the solution is the difference between the truncation-error-forced solution and the normal one. The present methods have been applied to four CFD solvers that use structured and unstructured grids, and address examples of truncation error and turbulence modeling error. Both deterministic error correction and probabilistic error modeling are discussed.

  • A High-Accuracy Solution-Adaptive Unstructured Macro-Cell Algorithm for CFD,
    Robert. E. Childs, John A. Ekaterinaris, and Patrick H. Reisenthel
    [available as AIAA Paper 99-0917] [PDF file, 320 KB]
Copyright © 1999 Nielsen Engineering & Research

ABSTRACT: This paper describes an unstructured macro-cell (UMC) algorithm for solving partial differential equations, and its application to computational fluid dynamics. A macro-cell is an intermediate-sized domain, consisting of roughly 10 or more grid points in each spatial direction in a structured array. The governing equations are solved on this structured grid within a macro-cell. A complete computational domain is composed of perhaps 10s to 1000s of macro-cells which are arranged in an unstructured manner. Local grid refinement is achieved by splitting a macro-cell, recursively as needed, in a manner similar to that of adaptive mesh refinement (AMR) schemes. The UMC algorithm has features of structured and unstructured grid methods, and it is intended to retain the benefits and avoid the drawbacks of purely structured and unstructured methods. Because the equations are solved on a structured array of grid points, high-accuracy finite-volume and implicit methods can be used. The use of unstructured macro-cells enables the use of several geometry- and solution-adaptive strategies. Thus, a UMC method offers many significant benefits for CFD. The principal difficulty which must be overcome is the need for methods of achieving high accuracy at macro-cell boundaries. This paper addresses the general concepts of the macro-cell solver with emphasis on boundary issues. Companion papers by Treidler et al. (1999) and Reisenthel and Childs (1999) describe aspects of the computational efficiency and the solution-adaption algorithm, respectively.

  • Wave Number-Based Criterion for Dynamic Mesh Refinement in CFD,
    Patrick H. Reisenthel and Robert E. Childs
    [available as AIAA Paper 99-0300] [PDF file, 944 KB]
Copyright © 1999 Nielsen Engineering & Research

ABSTRACT: Three local spectral estimation schemes were compared for their ability to accurately detect the presence of excess energy in high frequency modes lying outside the accuracy bandwidth of a given discretization scheme: the windowed Fast Fourier Transform (FFT), the Discrete Wavelet Transform (DWT), and the Maximum Entropy Method (MEM). Systematic deterministic and statistical tests were carried out, indicating the MEM to be the most accurate. An MEM-based on-the-fly grid refinement / derefinement scheme was developed. Its capabilities are demonstrated in terms of local grid refinement, local grid coarsening, and dynamic adaptation.

  • Efficient Solution Algorithms for High-Accuracy Central Difference CFD Schemes,
    Burke Treidler, John A. Ekaterinaris and Robert E. Childs
    [available as AIAA Paper 99-0302] [PDF file, 270 KB]
Copyright © 1999 Nielsen Engineering & Research

ABSTRACT: Preliminary results are presented from application of implicit integration schemes to high-accuracy CFD methods. High-accuracy refers to spatial discretization methods which are optimized for spectral bandwidth, rather than order of accuracy based on a Taylor series expansion. The results show that reductions of more than 90% in computational effort, as measured by CPU time, can be achieved. The reduction is relative to second-order methods for obtaining steady solutions to the same level of accuracy. In addition, a variety of time integration methods have been evaluated for their use in time-accurate and steady-state simulations with the high-accuracy central difference schemes.

CFD-Based Multidisciplinary Design Optimization:

  • Novel Concepts for a CFD-Enhanced ASTROS Capability,
    Patrick H. Reisenthel
    [available as NEAR TR 510]
Copyright © 1996 Nielsen Engineering & Research

ABSTRACT: The objective of this study was to demonstrate the feasibility of integrating modern CFD aerodynamic prediction technology in ASTROS. A detailed analysis is presented of how to make use of both steady and unsteady CFD-generated air loads in the design disciplines of ASTROS. In the first part of this work, two Aerodynamic Influence Coefficient (AIC) alternatives were evaluated. The first one is based on the Direct Iterative Surface Curvature (DISC) method, which relates a local perturbation in surface curvature to a corresponding pressure perturbation. The second alternative was the use of CFD automatic code differentiation to compute sensitivities to geometric design variables. In the second part of this work, a demonstration of a Computational Fluid Interface was carried out by coupling ASTROS with the transonic small disturbance computational aeroelasticity program CAPTSD. This demonstration involved the redesign of a composite wing under transonic load conditions, subject to static aeroelastic constraints. The results demonstrate that it is possible to successfully couple the design disciplines of ASTROS with Computational Fluid Dynamics codes, and point to possible improvements of the trim module for successful integration with CFD.


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