Advanced Building Simulation

law must be invariant to a transformation of the units. Dimensionless groups, such
as the Reynolds number or the Rayleigh number, serve to distinguish types of flow,
and thus cannot be tied to any one set of dimensions. With a reduced number of variables,
problems can often be reduced to ordinary differential equations, thus dramatically
simplifying the solution. The ability of CFD to solve nonlinear partial
differential equations may seem to supplant the usefulness of similarity analysis.
Nevertheless, a hallmark of a good validation case is its nondimensionality, as it
demonstrates that the case adheres fully to physical law.
CFD simulations of interior environments are almost exclusively dimensioned. Not
only is each simulation often treated as a unique case in that it represents a specific
situation in a particular building, but the combination of multiple behaviors into a
single simulation prevents nondimensionalization. Each behavior drives a similarity
transformation, such that multiple behaviors will lead to contradictory scaling. As a
result, this major method for CFD validation has not been incorporated into the
building simulation arsenal.
Benchmarking is the second and somewhat more problematic method for validation.
Benchmarks were traditionally physical experiments, although today there is a
great deal of argument as to whether empirical error is of the same order as or greater
than computational error. The ASME committee studying V&V has concluded that
benchmarking is more useful for verification—the determination that the code is
being used properly—rather than for validation (Oden 2003). Analytical benchmarks
are considered more accurate, but must of necessity be of a single phenomenon in a
straightforward and scalable domain.
Both these methods—similarity analysis and benchmarking—require a breaking
down of the problem into its smallest and most fundamental behaviors and domains.
A valid CFD model could thus be considered as the extents of its validated constituents.
The key issue facing CFD modelers trying to examine larger systems is the level at
which a model is no longer causally traceable to the discrete behaviors (Roache 1998).
Within the field of indoor air modeling, there has not been the longstanding tradition
of evaluating single behaviors either through similarity analysis or through discrete
physical models, and as a result, CFD modeling operates at the system level without any
linkage to a validated basis of fundamentals. Indeed, CFD is used in lieu of other methods
rather than being constructed from them. Furthermore, one of the current trends
for CFD modeling of interior environments is conflation, which basically expands the
simulation even more at the systems level by attempting to tie the results of the CFD
model into the boundary conditions for transfer models that determine energy use.
The consequences of disconnecting the CFD model from its fundamental constituents
are not so severe. Conventional technologies and normative design are predictable
enough and narrow enough that one does not have to do the aggressive validation so
necessary for the aerospace and nuclear disciplines. But CFD modeling demands a
change if it is to be used for more than this, and particularly if we wish to explore the
phenomena and open up the potential for developing new responses and technologies.
6.5 Potential applications
New perspectives on CFD simulation 153
By extending the realm of CFD simulation from the analysis of existing system
response to the investigation of extant thermal inputs, several opportunities may