Research Needs for Magnetic Fusion Energy Sciences - US Burning ...

maintaining multiple codes, which take different approaches to solving the same problem. it is
crucial to verify a code before beginning tests against experimental results — however, it is not
necessary or desirable to wait until each model is “complete” before proceeding. For fusion problems,
no model will ever really be complete and testing of well-verified, though imperfect, models
can help guide code development by focusing on areas of disagreement.
The next element in this Thrust is the design and execution of validation experiments to assess
the degree to which a calculation describes the real world. The essential activity is close and careful
comparison between model output and experimental measurements, with an emphasis on
quantitative measures and attention to errors and uncertainties in both code and experiment
(see, for example, P.W. Terry et al, PoP 15, 062503, 2008). it is a physical problem, meant to build
confidence in the models and one without a clearly defined endpoint. That is, validation is not a
one-time test where a code is “approved” for all time if it passes or discarded if it fails, but is instead
part of an iterative process for improving the fidelity of the models. identifying the cause
of discrepancies will be among the most difficult of the challenges posed by this Thrust, but will
also be among the most scientifically rewarding. For some fusion science problems, which require
extrapolation past currently accessible regimes, we will need to infer the correctness of the
underlying physical model to a higher degree than if we were only interpolating between accessible
data points. The relation between the various processes can be illustrated in Figure 1. The
first step in the validation effort, for each case study, will be the identification of critical physics
issues requiring testing with due consideration to the uniqueness and sensitivity of particular
measurements and model predictions. defining measurement needs is critical and will lead
to requirements for innovative diagnostics to be developed and deployed as part of this Thrust.
it is highly desirable to compare predictions at various levels of integration, sometimes called a
“primacy hierarch.” For example, to validate a calculation of turbulent transport, one will want
to compare fluctuation levels and spectra, correlations, fluxes and profiles. Thus, the diagnostic
challenge will be significant and require substantial resources and attention.
Increasing
Realism in
Physics and
Geometry
Coupling of
Physics
Complexity
Complete
Systems
Subsystem
Cases
Unit
Problems
Figure 2. Validation hierarchy. Model testing is most effectively carried out by employing a set of experiments
which probe the model at various levels of physical and geometric complexity.
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Decreasing
Number of
Code Runs
Quantity and
Quality of Data
Info on Initial
and Boundary
Conditions