of the references were not cited in the book.
Roache, P. J. (2004b),
“Calculation Verification: an Overview”, Proc.
Workshop on CFD Uncertainty Analysis, 21-22
October 2004. Instituto Superior Técnico, Lisbon, Portugal. L. Eça, and
M. Hoekstra, eds.
reference should have been cited with general references in Section 5.1
on Calculation Verification by the GCI.
Roache, P. J. (2004a), “Building PDE
Codes to be Verifiable and Validatable,” Computing in Science and Engineering,
Special Issue on Verification and Validation, September/October 2004, pp
reference should have been cited in Chapter 9 on Validation.
The following are excerpts. Some of these points are made
elsewhere in the book, but not as specifically or forcefull as made
The New Paradigm of Experiments Designed
Specifically for Code Validation
opinion, the most revolutionary concept in computational physics during
my career, other than simulation itself, has been the new paradigm of
experiments designed specifically for validation.1,2,5 The new paradigm recognizes that requirements for validation
are distinct and that validation experiments are much easier in some
respects but more demanding in others.
aerodynamics, for example, the emphasis in precomputational days was on
wind-tunnel experiments, which attempted to replicate free-flight
conditions. Great effort was expended on achieving near-uniform inflow
and model fidelity, and minimizing wall and blockage effects. The latter
required small models, which sacrificed parameter fidelity (Reynolds
number) and aggravated geometric fidelity.
paradigm approaches the problem differently, sacrificing some fidelity
between the wind-tunnel flow and free flight, but requiring that more
nearly complete details of the experimental conditions and field data be
obtained. No longer is it so important to achieve uniform inflow, but it
is critical to report in detail what those spatially varying inflow
conditions are, so that they may be input to the computational
simulation. The idea is that if the validation is good (by whatever
criteria are appropriate) for a flow perturbed from the free-flight
conditions, it will probably be good for the free-flight condition. Thus
blockage effects are not such major issues (and the tunnel wall itself
may be modeled), and models can be larger (or tunnels smaller and
therefore cheaper), thereby improving fidelity of Reynolds number and
model geometry. Analogous situations occur in other experimental
Unrealistic Expectations Placed on Experimentalists
unrealistic, even arrogant, for a code builder or user to require an
experimentalist to match idealized boundary conditions. Simple
constant-value boundary conditions that are a mere convenience for the
code builder can require major effort, cost, and time for an
experimentalist; they often compromise other more desirable qualities of
the experiment, and in fact may be literally impossible to achieve. A
major contribution by the code builder to the synergistic cooperation
between computationalists and experimentalists (which is also part of
the new paradigm) is achieved by the relatively simple work of building
the code with general boundary conditions. This also happens to be what
is most needed for independent code verification (or confirmation) using
Is Western Culture at Risk?
In an age of spreading pseudoscience and
anti-rationalism, it behooves those of us who believe in the good of
science and engineering to be above reproach whenever possible. Public
confidence is further eroded with every error we make. Although many of
society's problems can be solved with a simple change of values, major
issues such as radioactive waste disposal and environmental modeling
require technological solutions that necessarily involve computational
physics. As Robert Laughlin20 noted in this magazine,
“there is a serious danger of this power [of simulations] being misused,
either by accident or through deliberate deception.” Our intellectual
and moral traditions will be served well by conscientious attention to
verification of codes, verification of calculations, and validation,
including the attention given to building new codes or modifying
existing codes with specific features that enable these
Roache, Verification and Validation in
Computational Science and Engineering, Hermosa
Roache, “Quantification of Uncertainty in Computational Fluid Dynamics,”
Ann. Rev. Fluid Mechanics, vol. 29, 1997, pp. 123–160.
3.Guide for the
Verification and Validation of Computational Fluid Dynamics
Simulations, AIAA G-077-1998, Am. Inst.
Aeronautics and Astronautics, 1998.
Laughlin, “The Physical Basis of Computability,” Computing in Science & Eng., vol.
4, no. 3, 2002, pp. 22–25.