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

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maintaining multiple codes, which take different approaches to solving the same problem. it is<br />

crucial to verify a code be<strong>for</strong>e beginning tests against experimental results — however, it is not<br />

necessary or desirable to wait until each model is “complete” be<strong>for</strong>e proceeding. For fusion problems,<br />

no model will ever really be complete and testing of well-verified, though imperfect, models<br />

can help guide code development by focusing on areas of disagreement.<br />

The next element in this Thrust is the design and execution of validation experiments to assess<br />

the degree to which a calculation describes the real world. The essential activity is close and careful<br />

comparison between model output and experimental measurements, with an emphasis on<br />

quantitative measures and attention to errors and uncertainties in both code and experiment<br />

(see, <strong>for</strong> example, P.W. Terry et al, PoP 15, 062503, 2008). it is a physical problem, meant to build<br />

confidence in the models and one without a clearly defined endpoint. That is, validation is not a<br />

one-time test where a code is “approved” <strong>for</strong> all time if it passes or discarded if it fails, but is instead<br />

part of an iterative process <strong>for</strong> improving the fidelity of the models. identifying the cause<br />

of discrepancies will be among the most difficult of the challenges posed by this Thrust, but will<br />

also be among the most scientifically rewarding. For some fusion science problems, which require<br />

extrapolation past currently accessible regimes, we will need to infer the correctness of the<br />

underlying physical model to a higher degree than if we were only interpolating between accessible<br />

data points. The relation between the various processes can be illustrated in Figure 1. The<br />

first step in the validation ef<strong>for</strong>t, <strong>for</strong> each case study, will be the identification of critical physics<br />

issues requiring testing with due consideration to the uniqueness and sensitivity of particular<br />

measurements and model predictions. defining measurement needs is critical and will lead<br />

to requirements <strong>for</strong> innovative diagnostics to be developed and deployed as part of this Thrust.<br />

it is highly desirable to compare predictions at various levels of integration, sometimes called a<br />

“primacy hierarch.” For example, to validate a calculation of turbulent transport, one will want<br />

to compare fluctuation levels and spectra, correlations, fluxes and profiles. Thus, the diagnostic<br />

challenge will be significant and require substantial resources and attention.<br />

Increasing<br />

Realism in<br />

Physics and<br />

Geometry<br />

Coupling of<br />

Physics<br />

Complexity<br />

Complete<br />

Systems<br />

Subsystem<br />

Cases<br />

Unit<br />

Problems<br />

Figure 2. Validation hierarchy. Model testing is most effectively carried out by employing a set of experiments<br />

which probe the model at various levels of physical and geometric complexity.<br />

281<br />

Decreasing<br />

Number of<br />

Code Runs<br />

Quantity and<br />

Quality of Data<br />

Info on Initial<br />

and Boundary<br />

Conditions

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