Validation in Fusion Research: Towards Guidelines and Best Practices

TL;DR

This paper discusses the development of guidelines and best practices for validating mathematical models and numerical algorithms in magnetic confinement fusion, emphasizing new concepts like primacy hierarchy and sensitivity analysis.

Contribution

It introduces a comprehensive validation framework incorporating primacy hierarchy, sensitivity analysis, and composite validation metrics tailored for fusion research.

Findings

Identification of key validation concepts like primacy hierarchy and sensitivity analysis.

Proposal of a composite validation metric for experimental comparisons.

Emphasis on establishing a validation culture in fusion research.

Abstract

Because experiment/model comparisons in magnetic confinement fusion have not yet satisfied the requirements for validation as understood broadly, a set of approaches to validating mathematical models and numerical algorithms are recommended as good practices. Previously identified procedures, such as verification, qualification, and analysis of error and uncertainty, remain important. However, particular challenges intrinsic to fusion plasmas and physical measurement therein lead to identification of new or less familiar concepts that are also critical in validation. These include the primacy hierarchy, which tracks the integration of measurable quantities, and sensitivity analysis, which assesses how model output is apportioned to different sources of variation. The use of validation metrics for individual measurements is extended to multiple measurements, with provisions for the primacy hierarchy and sensitivity. This composite validation metric is essential for quantitatively evaluating comparisons with experiments. To mount successful and credible validation in magnetic fusion, a new culture of validation is envisaged.