48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition
4 - 7 January 2010, Orlando, Florida
AIAA 2010-27
An Overview of the NPARC Alliance's Wind-US Flow
Solver
Christopher C Nelson1
Innovative Technology Applications Company, LLC
P.O. Box 6971
Chesterfield, MO 63017-6971
Abstract
The NPARC Alliance was begun in 1993 with the goal of providing a first-class CFD analysis tool to
the US aerospace community through a joint effort of NASA, DoD, industry, and academia. Because
this effort involves diverse teams at multiple sites, it has required the development and use of internetbased tools for communication and version management, as well as adherence to programming
standards and practices. This approach has been very successful, resulting in the NPARC Flow
Simulation System, centered on the Wind-US flow solver. Wind-US is a general Navier-Stokes flow
solver with a wide variety of numerical algorithms and physical models to choose from. Major features
include the ability to solve on structured grids, unstructured grids, or both. Ideal gas, equilibrium air,
frozen multi-species flows, and reacting flows can be modeled. Recent enhancements include an
improved unstructured grid solver, improved chemistry modeling, and improved stability of the
structured grid solver. In addition to the flow solver, the NPARC Flow Simulation System consists of
numerous utilities to prepare the grid and input files, modify these files, and process the resulting data.
The extensive capabilities of the code have been demonstrated through the many simulations of
diverse, physically and geometrically complex, real-world applications conducted by government,
industrial, and academic organizations around the United States.
Introduction
The NPARC (National Project for Applications-oriented
Research in CFD) Alliance1-5 has been developing,
validating, and supporting a computational system for
aerospace flow simulation since 1993. The Alliance is
made up of the Department of Defense's Arnold
Engineering Development Center (AEDC) and NASA's
Glenn Research Center (GRC).
The original flow solver was based on the NPARC Code6,
but is currently centered around the Wind-US code. Much
of the original technology in the code has been donated by McDonnell Douglas and the Boeing
Corporation, with other contributions by coming from both industry and academia (including my
company, Innovative Technology Applications Company, LLC).
Since the NPARC Alliance released version 1.0 of the Wind flow solver in 1997, development of the
code and related utilities has been continuous. With the addition of an unstructured grid solver to the
existing structured grid capability, what would have been Wind version 6.0 became version 1.0 of
Wind-US, which was released in October, 2004. Version 2.0 followed in June, 2007.
1 Chief Scientist for CFD, Associate Fellow, AIAA
Copyright © 2010 by C. C. Nelson
Published by the American Institute of Aeronautics and Astronautics, Inc. with permission.
Copyright © 2010 by C. C. Nelson. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.
Wind-US is available, free of charge, to any U.S. organization. As a U.S. government code, Wind-US is
export-controlled, so it is not available for use in other countries. Within the U.S., however, the solver
and related utilities are can be had (including source code) by any U.S. organization (see the license for
restrictions).
At this writing, the official production version of the code is version 2.220, and the Alliance is hard at
work putting together the next release (currently up to v3.129), which is expected in early 2010. In the
following sections, the major features of this CFD code and related utilities will be discussed:
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The various classes of problems which can be addressed with this CFD solver.
The computational mesh topologies supported by the code.
Available options for parallel processing.
Highlights of the upcoming version 3.0 of Wind-US.
The pre-processing utilities that are part of the Wind-US CFD analysis software package.
The CFPOST post-processing utility.
A brief overview of various other utilities supplied by the NPARC Alliance.
Wind-US: A Broadly Applicable CFD Solver
Finding a single CFD code that meets every need can be difficult if an organization does many different
types of work. The same thing applies if a single product or application encompasses a wide range of
physics. The Wind-US CFD solver, while it cannot do everything, can be applied to a wider range of
physics than many other codes.
Wind-US solves the governing equations in compressible (density-based) form. It has been successfully
applied to flows with Mach numbers ranging from the low subsonic (less than M = 0.1) to hypersonic.
As long as the fluid medium is not completely incompressible (no liquid flows) and can be treated as a
continuum (with or without particles and droplets), it is a candidate for solution with Wind-US.
Flow Physics Options
Depending on the case, one can model inviscid fluids, laminar flow, or turbulent flow. For the latter, a
selection of algebraic, one-, and two-equation RANS models are available, along with a Rumsy-Gatski
algebraic Reynolds stress model. If a time-accurate simulation is needed (as opposed to a steady-state
solution), one of the several available hybrid RANS/LES turbulence models may be suitable.
Spatial Discretization Algorithms
This CFD code has many different options governing the numerical algorithms used in a solution. For
many cases, however, it is not necessary to concern oneself with them, because the defaults are
reasonable for most configurations. For example, there are multiple algorithms for the treatment of the
explicit advection terms.
Currently, the default scheme for structured grids is a Roe scheme, but several others, including HLLC,
HLLE, and Rusanov, are available. These methods come with spatial differencing algorithms that range
from first order accurate in space (for flows with very strong discontinuities) to fifth order upwindbiased schemes (for more accuracy with less numerical dissipation).
For unstructured grids, HLLE is the default, with several others (including HLLC and Roe) being
available, and the code can be run with first or second order accuracy. In order to increase consistency
between the structured and unstructured portions of Wind-US, the developers are considering making
the HLLC scheme the default for both. This scheme is appropriate for a wide variety of applications
and performs well on both type of meshes.
Time Marching Algorithms
While Wind-US can be run in explicit mode using various Runge-Kutta methods, by far the most
common usage is to employ one of the implicit operators. For structured grids, these include an
Approximate Factorization method, Jacobi and Gauss-Seidel iterative solvers, and MacCormack's
modified first-order approximate factorization method. For unstructured grids, there are both pointimplicit and line implicit methods.
For unsteady (time accurate) flows, a global Newton time stepping or dual time stepping algorithm can
be used with implicit schemes that are second order accurate in time to obtain good temporal accuracy
with fairly large time steps. These options are available for both unstructured and structured grids.
Example Unsteady Flow Simulation
Figure 1: Mach number contours on the centerline of the
WICS bay
For an example of what this CFD code can do, see Figure 1 above, which shows Mach number
contours on the centerline of the Weapons Internal Carriage and Separation (WICS) bay. This test case
is modeled after the wind tunnel experiments of Dix and Bauer 7 and is frequently used as a check case
for unsteady flow solvers. The freestream Mach number for this case was 0.95, and the length to depth
ratio of the bay was 4.5.
This run employed a second order spatial differencing scheme on a structured grid with the HLLE
algorithm. Newton iterations were used with a Gauss-Seidel iterative solver to achieve second order
accuracy in time. The Nichols and Nelson hybrid RANS/LES turbulence model was used, along with
wall functions, to model the effects of turbulence for this case.
The results of the WICS bay simulation were compared both to the experimental data and also to the
results of simulations8 using the OVERFLOW9 solver. Figure 2 shows that the pressure coefficient
distribution on the floor centerline predicted by Wind-US is very close to both the experimental results,
and the OVERFLOW results. This is especially encouraging, because OVERFLOW was run using a
5th order WENO scheme for the inviscid convective terms, whereas Wind-US used only a second order
scheme.
Figure 2: Pressure coefficient on WICS bay floor centerline
Modeling the Chemistry Effects
In addition to conventional ideal gas simulations, Wind-US can model several more advanced
approaches to the fluid chemistry and thermodynamics. One option is to use the Liu-Vinokur
equilibrium air curve fits.
Another possibility is to specify arbitrary frozen (non-reacting) chemistry. The composition can vary
throughout the domain, which allows for studies of mixing and diffusion effects without the added cost
and complication of chemical reactions.
For fully reacting flows, this CFD code supports several variations of finite rate chemistry, and custom
chemical reaction mechanisms can be added simply by creating an appropriately formatted text file.
Recent improvements to the code have dramatically increased its viability for this class of problem.
Until recently, the improved finite rate chemistry capabilities of Wind-US were confined to structured
grids10. Recent work undertaken as part of an Air Force T&E/S&T project has resulted in these being
made available for unstructured grids as well11.
More Options
In addition the above, Wind-US has the ability to compute more sophisticated real gas effects for a
limited number of species, and, if needed, the code is structured such that additional species could be
added relatively painlessly.
A limited magneto-fluid dynamics capability has also been developed, and efforts are ongoing to
improve the multi-phase (particle tracking) algorithms. One recent improvement to the latter is the
addition of droplet evaporation.
Computational Mesh Options
Like most CFD codes, Wind-US requires a sufficiently detailed computational mesh which describes
the volume where the flow is to be computed. Any experienced CFD practitioner will tell you that it
usually takes a lot longer to create a good grid than to run the code, so it is notable that with the WindUS solver, you have a lot of flexibility in building computational mesh.
As mentioned above, with Wind-US version 1.0, the NPARC Alliance began adding the ability to solve
both structured and unstructured grids. Unlike some other codes the author has encountered which
claim this capability, the structured grids are actually solved with a true structured grid solver for
maximum efficiency. Structured grids can even be combined with unstructured grids in the same
simulation.
Model Flows Using Unstructured Meshes
The unstructured grid solver requires a 3-D grid consisting of tetrahedrons, prisms, and/or hexahedrons.
2-D simulations can be handled using a couple planes of cells. The very rudimentary capabilities of
Wind-US versions 1.0 and 2.0 have been greatly enhanced in version 3.0. Combined with the
improved MADCAP grid pre-processor, the NPARC Alliance Flow Simulation System can now be
considered for production applications using unstructured grids.
A sample unstructured grid used with Wind-US is shown below in Figure 3. This plot shows part of a
cross-section of the mesh for a rocket nozzle. As is recommended for many different unstructured CFD
solvers, hexahedral cells are used near solid surfaces. Away from walls, the grid transitions (generally
using layers of prisms) to a tetrahedral grid in the core regions.
Figure 3: Cross-section of an unstructured mesh showing
the different cell types supported by Wind-US
In order to have success with the unstructured solver, the NPARC Alliance recommends that users
adhere to the following rules of thumb:
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Layers of hexahedral cells should be used at all viscous wall boundaries
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Tetrahedral cells should be used in the core flow (away from boundaries)
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A transitional layer of prism cells should be added between the hexahedral layers and the core
tetrahedral grid.
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Beware of extremely skewed tetrahedral cells. They introduce inaccuracy and have been
known to cause stability problems.
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Do not transition the mesh to tetrahedral cells inside an attached boundary layer; this is known
to cause problems
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A straight conversion of a structured grid to an unstructured grid, while possible, usually results
in a suboptimal unstructured mesh which does not demonstrate the true capabilities of the
unstructured solver.
Figure 4 shows a portion of a mesh created for a simple fifteen degree supersonic ramp test case
(similar to the structured grid case found on the NPARC Verification and Validation web site). The
transition between the layers of hexahedral cells near the wall and the prismatic/tetrahedral cells in the
freestream is clearly visible.
Figure 4: Detail of an unstructured mesh for a supersonic
ramp case
A snapshot of the flowfield predicted for this geometry is shown in Figure 5. Mach number contours
are shown on the flowfield cross-section, while pressure contours are shown on the solid walls. While
this is, obviously, only a simple test case, the Mach number contours do show the ability of the
unstructured solver to cleanly resolve shocks, and neither they nor the pressure contours contain any
hints of carbuncles or other unexpected behavior at the leading edge of the ramp.
Figure 5: Surface pressure contours and flowfield Mach
number contours on a 15°, Mach 2.5 ramp
Structured Mesh Options
On the structured grid side, the code can run 2-D grids (i.e. just a single plane of points), 2-D axisymmetric, and full 3-D computational meshes. Multi-block grids are supported, with blocks both
abutting each other (point-matched or not) or overlapping each other CHIMERA fashion. Figure 6
shows a slice of a sample grid which uses several of the available options (point-matched abutting,
non-point-matched overlapping, and boundaries in the interior of a grid). A CHIMERA-type grid,
where the smaller grid cuts a hole in the larger, is illustrated in Figure 7 below.
Figure 6: Examples of structured grid options supported by
Wind-US
Figure 7: Sample overlapping structured grids with hole
cutting
The ability of Wind-US to handle many different classes of computational mesh gives the user the
ability to use the right grid topology for each different configuration. Users are not forced to take a onesize-fits-all approach.
Parallel Processing with Wind-US
Parallel processing has become a necessary tool for almost all production CFD work. It is required for
complex configurations in order to get timely results. Not everyone can afford a supercomputing
system, however, so it helps that Wind-US has a lot of flexibility in its parallel operation.
Masters and Slaves
When Wind-US is run in parallel, the various blocks in a multi-block grid are parceled out among the
available processors (illustrated in Figure 8 below). One processor acts as the “master,” and the others
are the “slaves.”
Figure 8: Master/slave parallel processing schematic
Wind-US has been programmed with two different parallel processing technologies: MPI and the older
PVM. On multiprocessor systems, Wind-US can be run using either of them as required to take
advantage of the faster inter-processor communication.
Most large systems these days are some variation of the Linux “Beowulf” concept, with hundreds or
thousands of separate boxes clustered together. On such a system, MPI is generally recommended for
parallel operation. This is especially true if there is a high-speed interconnect, because a customized
flavor of MPI is usually the only way to access it.
At the opposite end of the spectrum, PVM can be used to run Wind-US on a combination of
heterogeneous systems. As long as a compatible executable is available for each system, one can link
together Intel systems, AMD-based boxes, Sun SPARC-based systems...almost anything. Wind-US has
even been made to run on Microsoft Windows systems (although the NPARC Alliance does not itself
currently provide support for Windows systems).
Additional Options for Parallel Operation
When running in parallel, the “slave” processors do not need to have access to the file system with the
grid and run-control files, as long as the “master” processor does. Of course, if some sort of “global”
file system is used such that all the processors can “see” the same files, then the code can take
advantage of that for faster operation.
Recent improvements to the parallel algorithms in Wind-US have resulted in quite good performance
when run in parallel, even if each processor only works on a few thousand points.
Highlights of the Upcoming Wind-US 3.0
Since the release of version 2.0 of Wind-US back in 2007, the NPARC development team has been
adding new features and improving old ones. Following is a brief overview of the major changes.
Improved Unstructured Solver
The biggest change to Wind-US, in terms of lines of code, is undoubtedly the rewritten unstructured
solver. Wind-US benefited from the hard work undertaken at Boeing Saint Louis to improve the
robustness and accuracy of the unstructured solver in the closely-related BCFD code12.
Earlier versions of the unstructured solver in Wind-US were notoriously unstable, and as a result, they
were not widely used. With version 3.0, NPARC has a solver which has been successfully
demonstrated on a variety of test cases covering a wide range of flow physics. These include transonic
exterior flows like the ONERA M6 wing and the wing-body configuration used in the third Drag
Prediction Workshop13. Internal flows like the Sajben diffuser and Madic nozzle have also been run. In
addition, various simple configurations such as oblique shocks, expansion fans, and flat plate boundary
layers have been demonstrated.
Recently, the ability to model finite rate chemistry, consistent with the algorithms in the structured
solver, has been added to Wind-US. While the testing of this new capability is ongoing, it is expected
to be included in the eventual release of version 3.0.
Improved Finite Rate Chemistry Algorithms
Many NPARC Alliance developers were involved in a multi-year project to improve the robustness and
applicability of the chemistry modeling available in Wind-US. This work, funded by an Air Force
T&E/S&T contract, resulted in dramatic improvements to the stability of the code for reacting flow
simulations.
Many of these improvements are internal to the solver, and not directly visible by users of the code
except through being able to run with increased CFL numbers. The addition of an optional Damkohler
number limiter is one exception to this, as the user can now specify a maximum Damkohler number
allowed in the simulation. This has been found to greatly increase stability in some cases. Another
change is that the four coefficient viscosity curve fits by Svehla14 are now supported
Good results have been obtained using the improved algorithms for a variety of flows15, and with their
porting to the unstructured solver, Wind-US is well-suited for application to an even broader spectrum
of multi-species flows.
Improvements for Turbomachinery Simulations
As far back as Wind version 4.0, there existed a basic capability to model some blocks within a
computational mesh as rotating and use circumferential averaging to communicate with the
neighboring non-rotating zones. Unfortunately, these algorithms were fairly primitive, and when they
came into conflict with other algorithmic improvements that were desired for the solver, the capability
was allowed to lapse.
In Wind-US version 2.0, the basic rotational frame of reference capability was resurrected. For WindUS version 3.0, however, the ability to rotate on a zonal basis was re-added. Further, the algorithms to
allow communication between rotating and non-rotating blocks of unequal azimuthal extent have been
added. In Wind 4, an area averaging algorithm was used to communicate between blocks undergoing
relative rotation. In addition to this, Wind-US version 3.0 has implemented the industry standard
mixed-out averaging method16.
For better solution quality when waves in a zone attempt to cross into a neighboring zone through one
of these averaged interfaces, the Giles non-reflecting technique, as described by Zaki, et al 17 has been
implemented. Work is ongoing to extend this capability further to allow not only interfaces which are
roughly normal to an axis, but also those which are roughly of constant radius (for example, when a
non-rotating zone is wrapped around the outside of one that is rotating).
Structured Solver Stability Improvements
Wind-US, and Wind before it, has always been known as a code which would give a good answer...if it
would give an answer at all. Earlier versions were known for being picky about grid quality and often
being quite unstable unless a very small CFL number was used. Wind-US 3.0 brings some welcome
improvements in this area.
First, the aforementioned improvements to the chemistry algorithms have resulted in finite rate
simulations being able to run at CFL numbers close to, if not the same as, an ideal gas counterpart. In
addition, improvements to the algorithms which extrapolate flow variables to boundaries have resulted
in better behavior when first order extrapolation is used (rather than zeroth order, which is usually the
default). Within the interior numerical schemes themselves, a great deal of work has gone into
improving stability by, for example, avoiding division by very small numbers.
The new COUPLING MODE AVERAGE algorithm for abutting zone-to-zone communication has
resulted in dramatic stability improvements for many medium-to-large simulations. This mode is used
in place of the default Roe coupling algorithms or the older “characteristic” method. As the name
implies, this mode uses a very simple averaging technique to determine flow conditions at coupled
block boundaries.
The averaged coupling approach was developed in response to the observation that, particularly with
larger cases, there were often regions at block boundaries which, while they should have been benign,
exhibited unexpected behavior which caused instability in the overall simulation. When the Roe
coupling scheme is working as it should, it provides a superior capability for inviscid flow regions, as
has been demonstrated on numerous test cases. It is known to have significant limitations, however,
especially in the presence of strong viscous forces. Problems have been observed even in very smooth
regions of the flow.
Using the averaged coupling mode, impressive improvements in stability have been obtained. CFL
numbers can often be increased by an order of magnitude, without sacrificing solution quality. In fact,
without the bizarrely unstable block boundaries, the solution quality is improved compared to that
obtained with the other methods. The most accurate coupling method remains to use a double-fringed
point-matched grid, but such grids are not always easy (or even possible) to obtain. When abutting
blocks are used, especially for large problems, the averaged coupling mode appears to provide a stable
and reasonably accurate alternative.
New Software Interfaces
Among the many other upgrades to Wind-US, there are several which allow it to be used in
combination with other software. For example, the FOMOCO keyword allows the use of the
FOMOCO utilities to compute forces and moments. Other hooks have been added to allow the use of
the FD-CADRE software framework18. Other work has enabled Wind-US to interact with a conjugate
heat transfer code19.
Pre-Processing Utilities
The Wind-US code is just one part of the NPARC Flow Simulation System. In addition to the core
Navier-Stokes solver, there is a variety of tools to make it easier for users to set up cases and analyze
the results.
The NPARC Alliance does not provide grid generation utilities, per se, so users must accomplish this
task using some other package (e.g. Gridgen, CFD-GEOM, or ICEM, to name just a few). Many of
these packages can export grids directly to the “Common File Format” that the Wind-US CFD analysis
software uses. With others, it will be necessary to use a file conversion utility (more about that later).
Once a mesh has been created, there are two major utilities available for inspecting the mesh and
setting boundary conditions: GMAN and MADCAP. Note that some grid generators allow boundary
conditions to be specified as the mesh is generated; in that case, a separate utility might not be
necessary.
GMAN
GMAN is the original interactive menu-driven pre-processor that is used to specify boundary condition
types, and zone connectivity in multi-zone grids. It also provides important quality checking, display,
and reporting functions. GMAN is primarily used for structured grids, although it can also work with
single-block unstructured meshes (for multi-block, MADCAP is the only option).
GMAN has two user interface modes; a command line mode, and a graphical menu-driven mode. In the
command line mode, the user types commands in a text window or runs a script file containing the
commands to be performed. The commands are processed as they are entered.
In the menu-driven mode, the user operates in a graphical environment, and controls operations and
display functions using menu picks. This mode provides interactive display of a computational grid,
which greatly enhances boundary condition specification by allowing the user to see the boundaries
being specified. Figure 9 shows a screen shot of GMAN in menu driven mode. The figure shows a
single plane of a computational mesh with the boundary conditions applied at each point indicated by
different symbols.
Figure 9: Screen shot of GMAN's graphical mode
The user can switch between command line and graphic menu modes at any time. All operations except
display control are saved to a journal file in a readable format which can be easily edited and played
back to repeat a set of operations.
MADCAP
MADCAP (Modular Aerodynamic Design Computational Analysis Process) is a tool developed in the
Applied CFD group at Boeing Phantom Works in St. Louis as a successor to GMAN and several other
utilities. The Boeing version of MADCAP is linked with the (commercially available) AFLR3D mesh
generation package, but the public version distributed by NPARC has no grid generation capabilities.
Figure 10: Screen shot of a MADCAP session
While MADCAP's user interface and code infrastructure are new, relative to GMAN, the underlying
routines for structured grids are largely from the older code. On top of this, a significant amount of
new technology has been added to support unstructured grids. A screen shot of a typical user session is
shown in Figure 10.
The NPARC version of MADCAP got off to a bit of a rocky start, with many people struggling just to
get the software to run at all on their systems. More recent versions have largely addressed these issues,
and the software is proving itself useful as the unstructured solver in Wind-US becomes more capable.
In fact, MADCAP is required to set boundary conditions and inter-block connectivity for multi-block
unstructured grids (or grids which combine structured and unstructured meshes), as GMAN cannot read
such files. MADCAP is also required to import an unstructured grid file that is a format other than the
Common File Format. The UG_IO library from the SimCenter at Mississippi State University is used
for the import and export of a wide variety of unstructured grid formats.
The CFPOST Post-Processor
Once pre-processing has been accomplished with GMAN and/or MADCAP (and perhaps one or more
of the “minor” utilities), and the solver itself has run, the NPARC Alliance provides the CFPOST utility
for basic post-processing. There are, of course, several excellent commercial post-processors available;
some of them can even directly read the Common Files that Wind-US uses.
For example, FieldView has long had a built-in file reader for structured grids and solutions. A similar
reader for unstructured grids also exists, but isn't part of the official FieldView release yet. If needed it
can be obtained from the NPARC Alliance. More recently, a prototype Common File reader for Tecplot
360 has been written. While it is still at an early stage, it does read both structured and unstructured
grids and solutions. It is hoped that it will be ready for wider use when version 3.0 of Wind-US is
officially released. The author is unaware of Common File readers for other post-processors, but they
may exist.
CFPOST is no replacement for commercial post-processing software, but it has some unique features
that are especially useful when using the Wind-US CFD package. It can also be used to convert
structured grid and solution Common Files to PLOT3D format for use with other packages.
Post-Processing with CFPOST
CFPOST can perform many varied functions, such as listing and plotting results, generating reports,
and producing files for other plotting packages and post-processors. While it does create graphical
output, CFPOST's user interface (unlike those of GMAN and MADCAP) is almost entirely text-based.
At one time it was possible to link it into Visual3, but the author is unaware of anyone still doing so.
Figure 11 shows sample output generated by CFPOST. In this case, the figure shows Mach number
contours on a cross-section of an ONERA M6 wing simulation.
Figure 11: Screen shot of Mach number contours on the
ONERA M6 wing created by CFPOST
CFPOST provides commands for the user to precisely specify the information of interest (i.e. the
variable to be examined), the domain of interest, and the units of measure in which the results are to be
presented. These commands can be scripted in order to save work when repeatedly performing similar
analyses.
One nice feature of CFPOST is that it understands the relationships between the various variables
stored in the solution files (and the grids). Thus, if the grid dimensions are in inches, but heat transfer is
desired in SI units, CFPOST will automatically handle the unit conversion. Also, CFPOST can read in
the same chemistry data used by the solver so that the chemical makeup of the flow can be taken into
account when computing things like Mach number, pressure, and temperature.
Data can be displayed on 2-D cut-planes or “crinkle” cuts of the computational domain. The latter are
cross-sections which show the actual mesh cell faces closest to a given cut-plane definition. This can be
especially useful for examining solutions on unstructured grids.
Various line plots can be generated with CFPOST, and it can also perform a selection of surface and
volume integrations. In addition, if the desired function is not already available, a custom function can
be defined with the “calculate” command.
Additional Utilities
The NPARC Flow Simulation System comes with a variety of other useful utilities besides the “big
three” (pre-processors GMAN and MADCAP and post-processor CFPOST). Here is a very brief
overview of some of the more commonly used ones:
• cfappend—Append one Common File to another.
• cfcnvt—Convert between Common Files and various other file types.
• cfpart—Partition a single zone unstructured grid into multiple zones. This replaces the older
usplit-hybrid utility. The new utility is substantially faster than the older one, and produces the
same or better results.
• cfreorder—Re-order and/or delete zones in a grid or flow file.
• cfreset_iter—Reset the iteration count in a solution file to zero (useful when using a previous
solution as initial conditions for a new case).
• cfspart—This utility is used to re-partition unstructured solution (.cfl) and boundary data (.tda)
files so that, for example, a case can be restarted with a different number of processors but still
have one zone per processor.
• cfsplit and cfcombine—Split a specified structured grid zone (or zones) in a grid or flow file
into multiple zones or reverse the process.
• decompose and recombine—Automatically split a Wind-US structured grid system and,
optionally, the corresponding flow file, into smaller grid zones to improve the parallel
processing efficiency. Then, when the solution is run, recombine the split system back to its
original form.
• fpro—Perform various useful operations on Wind-US solution files (e.g. reinitialize and/or
smooth sections of the domain, copy or interpolate solutions from another file, etc.).
• gpro—Operate on common grid (.cgd) files in various ways (e.g. exchange coordinate
directions, rotate and/or translate blocks, etc.).
• resplt.pl—Extract various convergence data from the “list output file” of a simulation and
create plot files from it (plotted with CFPOST).
• thplt—Extract various saved data from a time history file (which is used to store user-specified
variables at specific locations at each time step in a solution) and create plot files from it
(plotted with CFPOST).
• tmptrn—Create a point-by-point wall temperature distribution and/or boundary layer transition
data, and write it into the common flow file for use by the Wind-US solver.
• USintrpltQ—Interpolate a solution from one unstructured grid to another.
• cfpart—Split a single-zone unstructured common grid file into multiple zones.
• windpar—Compute an estimate of the potential for parallel speed-up of a particular Wind-US
case as a function of the number of processors, based on the likely number of grid points per
processor.
There are other, less commonly used utilities as well. All of the above “minor” utilities have a
command line interface (no GUI). In most cases, however, there are only a limited number of options,
making them relatively easy to learn.
Conclusions
While the NPARC Simulation System is already an attractive solution for many applications,
developers at multiple sites continue to improve it by adding new capabilities and upgrading existing
ones. The upcoming production release Wind-US version 3.0 and the related upgrades to the various
utility codes represents a substantial improvement over previous versions in many respects. Any U.S.
organization currently using an older version of the NPARC Flow Simulation System or looking for a
low-cost but full-featured CFD solution would be well-served to consider it.
Additional Resources
The NPARC Alliance has made a significant effort to provide documentation and support for users of
their software. Most of these resources are accessible from the NPARC web site which is hosted by
NASA Glenn at http://www.grc.nasa.gov/WWW/wind/. The latest users guides for the solver and all
the utilities available in both HTML and PDF form, along with instructions on how to acquire the code.
In addition, the “NPARC Alliance CFD Verification and Validation” website provides a variety of test
cases which demonstrate the code's abilities.
Acknowledgments
The author would like to thank the Test Resource Management Center (TRMC) Test and
Evaluation/Science and Technology (T&E/S&T) Program for their support. This work was funded in
part by the T&E/S&T Program through the Advanced Propulsion Test Technology focus area.
The author would also like to thank Ramgen Power Systems for funding turbomachinery-related
improvements to Wind-US.
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Appendix
Over the years, Wind(-US) has been used by a wide variety of organizations and applied to a broad
spectrum of problems. The following list gathers together many of the papers which have resulted
from this work:
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Anderson, B., Tinapple, J., and Surber, L., “Optimal Control of Shock Wave Turbulent Boundary Layer Interactions
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Bhargava, C., Loth, E., and Potapczuk, M., “Simulating the Aerodynamics of the NASA John H. Glenn Icing
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Bush, R. H., Power, G. D., and Towne, C. E., “WIND: The Production Flow Solver of the NPARC Alliance,” AIAA
Paper 98-0935, 1998.
Cain, A. B., Vaporean, C. N., and Parekh, D. E., “Computational Characterization of Receptivity in Jet Flow Control,”
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Castner, R. S., “Analysis of Plume Effects on Sonic Boom Signature for Isolated Nozzle Configurations,” AIAA
2008-3729, 2008.
Chi, X. Slater, J. W., Shih, T. I.-P., Zhu, B., Addy, H. E., and Choo, Y. K., “Computing Aerodynamic Performance of a
2-D Iced Airfoil—Blocking Topology and Grid Generation,” AIAA Paper 2002-381, 2002.
Chung, J., Choo, Y., Reehorst, A., Potapczuk, M., and Slater, J., “Navier-Stokes Analysis of the Flowfield
Characteristics of an Ice Contaminated Aircraft Wing,” J. of Aircraft, Vol. 37, No. 6, pp 947-959, 2000. (Also AIAA
Paper 99-0375, 1999).
Churchfield, B., Tinapple, J., and Surber, L., “Optimal Control of Shock Wave Turbulent Boundary Layer Interactions
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Cosner, R. R., “Assessment of Vehicle Performance Predictions Using CFD,” AIAA Paper 2000-384, 2000.
Cosner, R. R., “Experimental Data Needs for Risk Management in CFD Applications,” AIAA Paper 98-2781, 1998.
DalBello, T. and Steffen, C. J., “Parametric Study of a Mixer/Ejector Nozzle with Mixing Enhancement Devices,”
AIAA Paper 2002-667, 2002.
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DalBello, T., “WIND Validation Cases: Computational Study of Thermally-Perfect Gases”, AIAA Paper 2003-546,
2003.
DalBello, T., Dippold, V., Georgiadis, N. J., “Computational Study of Separating Flow in a Planar Subsonic Diffuser,”
NASA/TM-2005-213894, 2005.
DalBello, T., Georgiadis, N. J., Yoder, D. A., and Keith, T. G., “Computational Study of Axisymmetric Off-Design
Nozzle Flows,”AIAA Paper 2004-0530, January 2004.
DeBonis, J. R., “Analysis and Parametric Study of a Mixer/Ejector Nozzle for Application to the High Speed Civil
Transport,” NASA TM 2000-210038, 2000.
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the GTX Air-Breathing Launch Vehicle Inlet,” Proceedings of the JANNAF 26th Airbreathing Propulsion
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Dippold, V., “CFD Analyses and Jet-Noise Predictions of Chevron Nozzles with Vortex Stabilization,” AIAA Paper
2008-37, 2008.
Dippold, V., “Investigation of Wall Function and Turbulence Model Performance within the Wind Code,” AIAA Paper
2005-1002, 2005.
Dippold, V., Foster, L., and Wiese, M., “Computational Analyses of Offset Stream Nozzles for Noise Reduction,”
AIAA Paper 2007-3589, 2007.
Dudek, J. C., Davis, D. O., and Slater, J. W., “Validation and Verificaiton of the WIND Code for Supersonic Diffuser
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Dudek, J., “An Empirical Model for Vane-Type Vortex Generators in a Navier-Stokes Code,” AIAA Paper 2005-1003,
2005.
Dudek, J., “Empirical Model for Vane-Type Vortex Generators in a Navier-Stokes Code,” AIAA Journal, Vol. 44, No.
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Engblom, W. A., Fletcher, B., and Georgiadis, N. J., “Validation of Conjugate Heat-Transfer Capability for WaterCooled High-Speed Flows,” AIAA Paper 2007-4392, 2007.
Engblom, W. A., O'Gara, M., Richards, A., Sypeck, D. J., and Platt, D., “Investigation of Microthruster Nozzle
Performance for Nanosatellite Applications,” AIAA Paper 2007-3985, 2007.
Engblom, W., Fletcher, B., Georgiadis, N., “Conjugate Conduction-Convection Heat Transfer for Water-Cooled HighSpeed Flows,” AIAA Paper 2008-4653, 2008.
Engblom, W., Frate, F., and Nelson, C., “Progress in Validation of Wind-US for Ramjet/Scramjet Combustion,” AIAA
Paper 2005-1000, 2005.
Engblom, W.A. and Georgiadis, N. J., Khavaran, A., “Investigation of Variable-Diffusion Turbulence Model
Correction for Round Jets,” AIAA Paper 2005-3085, 2005.
Franko, K.J. and Georgiadis, N. J., “Computational Investigation of Heated High-Speed Coaxial Jets,” AIAA Paper
2004-2980, 2004.
Frate, F. C. and Kim, H. D., “WIND Code Application to External Forebody Flowfields with Comparison to
Experimental Results,” AIAA Paper 2001-0226, 2001.
Frate, F. C. and Slater, J. W., “Supersonic Wind Tunnel Tests of an Axisymmetric Sector, 10o-Spike Inlet to a RocketBased Combined-Cycle Propulsion System,” Proceedings of the JANNAF 26th Airbreathing Propulsion
Subcommittee Meeting, Destin, FL, April, 2002.
Georgiadis, N. J, Rumsey, C. L., Yoder, D. A., and Zaman, K. B. M. Q., “Turbulence Modeling Effects on Calculation
of Lobed Nozzle Flowfields,” J. of Propulsion and Power, Vol. 22, No. 3, pp. 567-575, 2006.
Georgiadis, N. J, Yoder, D. A., and Engblom, W. A., “Evaluation of Modified Two-Equation Turbulence Models for
Jet Flow Predictions,” AIAA Journal, Vol. 44, No. 12, pp 3107-3114, 2006.
Georgiadis, N. J, Yoder, D. A., and Engblom, W. A., “Evaluation of Modified Two-Equation Turbulence Models for
Jet Flow Predictions,” AIAA Paper 2006-490, 2006.
Georgiadis, N. J. and D. Papamoschou, “Computational Investigations of High-Speed Dual Stream Jets,” AIAA Paper
2003-3311, 2003.
Georgiadis, N. J. and Papamoschou, D., “Computations of Dual-Stream Jets with Eccentric and Coaxial Bypass
Streams,” AIAA Paper 2004-2981, May 2004.
Georgiadis, N. J. Yoder, D. A., Towne, C. E., Engblom, W. A., Bhagwandin, V., Lankford, D. W., Power, G. D.,
Nelson, C. C., “Wind-US Code Enhancements to Complement Hypersonic Testing and Evaluation,” AIAA Paper
2009-193, 2009.
Georgiadis, N. J., DalBello, T., Trefny, C., and Johns, A., “Aerodynamic Design and Analysis of High Performance
Nozzles for Mach 4 Accelerator Vehicles,” AIAA Paper 2006-0016, 2006.
Georgiadis, N. J., Rumsey, C. L., Yoder, D. A., and Zaman, K. B. M. Q., “Effects of RANS Turbulence Modeling on
48.
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66.
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77.
Calculation of Lobed Nozzle Flowfields,” AIAA Paper 2003-1271, 2003.
Guo, D. and Cary, A. W., “Vectoring Control of a Primary Jet with Synthetic Jets,” AIAA Paper 2001-0738, 2001.
Guo, D., Kral, L. D., and Cary, A. W., “Numerical Simulation of the Interaction of Adjacent Synthetic Jet Actuators,”
AIAA Paper 2000-2565, 2000.
Hamed, A. and Mohamed, A., “Assessment of Shock Induced Flow Separation and Mixing Layer Predictions in
Nozzles and High Speed Jets,” AIAA Paper 2001-0225, 2001.
Hamed, A., “Numerical Simulation of Unsteady Flow Fluctuations in Resonance Tubes,” AIAA Paper 2002-1118,
2002.
Hamed, A., Basu, D., and Das, K., “Detached Eddy Simulations of Supersonic Flow over Cavity,” AIAA Paper 2003549, 2003.
Hamed, A., Das, K., and Basu, D., “Numerical Simulation and Parametric Study of Hartmann-Sprenger Tube Based
Powered Device,” AIAA Paper 2003-550, 2003.
Hamed, A., Li, Z., Manavasi, S., and Nelson, C., “Flow characteristics through porous bleed in supersonic turbulent
boundary layers,” AIAA 2009-1260, 2009.
Haroldsen, D. J., “Calculation of Vortices for Finned Missiles Using the WIND Flow Solver,” AIAA Paper 2000-752,
2000.
He, Y., Cary, A. W., and Peters, D. A., “Parametric and Dynamic Modeling for Synthetic Jet Control of a Post-Stall
Airfoil,” AIAA Paper 2001-0733, 2001.
Jin, W. and Taghavi, R., “A Computational Study of Icing Effects on the Performance of S-Duct Inlets,” AIAA Paper
2008-4584, 2008.
Kersey, J., Loth, E., and Lankford, D., “Effect of Evaporating Droplets on Shock Wave Attenuation,” AIAA Paper
2008-793, 2008.
Khavaran, A., Dippold, V., Bridges, J., and , “Effect of Free Jet on Refraction and Noise,” AIAA Paper 2005-2941,
2005.
Koch, L., Bridges, J., and Khavaran, A., “Flowfield Comparisons from Three Navier-Stokes Solvers for an
Axisymmetric Separated Flow Jet,” AIAA Paper 2002-0672, 2002.
Kral, L.D., Mani, M., and Ladd, J., “Application of Turbulence Models for Aerodynamic and Propulsion Flowfields,”
AIAA Journal, Vol. 34, No. 11, pp 2291-2298, 1996.
Kral, L.D., Mani, M., and Ladd, J., “On the Application of Turbulence Models for Aerodynamic and Propulsion
Flowfields,” AIAA Paper 96-0564, 1996.
Kube-McDowell, M. T., Lyrintzis, A. S., and Blaisdell, G. A., “Parametric Study of the Generation of Shocks in NearCritical Turbofan Nozzles,” AIAA 2008-2984, 2008.
Ladd, J. A. and Korakianitis, T., “On the Assessment of One- and Two-Equation Turbulence Models for the
Computation of Impinging Jet Flowfields,” AIAA Paper 96-2545, 1996.
Ladd, J. A. and Norby, W. P., “Dynamic Inlet Distortion Predictions Using a CFD/Distortion Synthesis Approach,”
AIAA Paper 98-2735, 1998.
Ladd, J. A., and Kral, L. D., “Development and Application of a Zonal k-ε Turbulence Model for Complex 3-D
Flowfields,” AIAA Paper 92-3176, 1992.
Ladd, J. A., and Kral, L. D., “Evaluation of Low Reynolds Number Two-Equation Turbulence Models for Calculation
of Compressible Flowfields,” Proc. Of the Symposium on Transitional and Turbulent Compressible Flows, ASME
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Ladd, J. and Mani, M., “A Comparison of Steady State and Time Accurate CFD Methods for the Performance
Prediction of a Transonic Pitot Inlet,” AIAA Paper 2004-0528, 2004.
Lankford, D. W. and Nelson, C. C., “Application of the Wind Flow Solver to Chemically Reacting Flows,” AIAA
Paper 2002-673, 2002.
Lankford, D., and Mani, M., “Wind Thermo-Chemical Models and Recent Improvements,” AIAA 2003-545, 2003.
Lankford, D., Powell, S., Hand, T., “Implementation of Real Gas Effects in the Wind-US Flow Solver,” AIAA Paper
2005-999, 2005.
Lee, V. and Loth, E., “Local Adaptive Timestepping for Lagrangian Particle Tracking,” AIAA Paper 2007-335, 2007.
Lee, V., Loth, E., Lankford, D., “Development of a Model for Multiphase Turbulent Particle Dispersion in WINDUS,” AIAA Paper 2006-635, 2006.
Mackle, S. and Taghavi, R., “Supersonic Impinging Jets: A Computational Investigation,” AIAA Paper 2002-671,
2002.
MacLean, M. and Holden, M., “Validation and Comparison of WIND and DPLR Results for Hypersonic, Laminar
Problems,” AIAA Paper 2004-0529, 2004.
Mani, M. and Paynter, G. C., “Hybrid Turbulence Models for Unsteady Simulation of Jet Flows,” AIAA Paper 20022959, 2002.
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Michal, T., Babcock, D., Oser, M., Mani, M., Roos, F., “BCFD Unstructured-Grid Predictions on the F-16 XL
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Miller, S. A. E., Veltin, J. Morris, P. J., McLaughlin, D. K., “Validation of Computational Fluid Dynamics for
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Mohler, S., “Wind-US Flow Calculations for the M2129 S-duct Using Structured and Unstructured Grids,” AIAA
Paper 2004-525, 2004.
Mohler, S., “Wind-US Unstructured Flow Solutions for a Transonic Diffuser,” AIAA Paper 2005-1004, 2005.
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Nelson, C. C., Cain, A. B., Kerschen, E. J., Raman, G., “Simulations of Helmholtz Resonator Powered Resonance
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Nelson, C. C., Cain, A. B., Patel, M. P., and Corke, T. C., “A Simplified Strategy for Optimizing Flow-ControlConfigured Airfoils,” AIAA Paper 2007-4274, 2007.
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Nelson, C., Cain, A., Patel, M. Corke, T., “Simulation of Plasma Actuators Using the Wind-US Code,” AIAA Paper
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Norby, W. P., Ladd, J. A., and Yuhas, A. J., “Dynamic Inlet Distortion Prediction with a Combined Computational
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Patel, M. P., Ng, T. T., and Cain, A. B., “A CFD Study of a Missile Aero Control Fin by Near-Wall Flow
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111. Slater, J. W., “CFD Methods for Computing the Performance of Supersonic Inlets,” AIAA Paper 2004-3404, 2004.
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