Statistical analysis in robust design of superconducting magnets

Abstract

Purpose

To present a robust optimal design technique in the presence of system parameters uncertainties.

Design/methodology/approach

The properties of normally distributed random variables are exploited, together with surface response fitting techniques, with the aim to reduce the computational cost in assessing the effect of uncertainties.

Findings

A fast approximate method for computing statistical average is presented together with its implementation for the design of magnets for magnetic resonance imaging.

Research limitations/implications

Future research will be focused to multi‐dimensional problems and to the best choose of closed form expressions to evaluate statistical moments fitting.

Practical implications

Robust optimal design methodologies are receiving an increasing interest in both academic and industrial research, due to their capability of coping with construction uncertainties and tolerances.

Originality/value

The effectiveness of the simplified method has been demonstrated for an analytical example and on a simplified superconducting magnet design. The proposed strategy is quite general and it can be applied to a wide class of optimal design problems.

Citation

Cioffi, M., Formisano, A. and Martone, R. (2005), "Statistical analysis in robust design of superconducting magnets", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 24 No. 2, pp. 427-435. https://doi.org/10.1108/03321640510586060