Worst case analysis in robust design of NMR magnets

Ambrisi, Angelo; Formisano, A.; Martone, R.

doi:10.1109/cefc.2010.5481209

Search citation statements

Order By: Relevance

Paper Sections

Select...

A Example 1-a Simple Magnet2

B Treatment Of the Tolerance Domain1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2015

Publication Types

Select...

Article1

Relationship

Self Cite1

Independent0

Authors

Journals

Cited by 1 publication

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A combinatorial problem arises that, under suitable conditions, can be faced with effective tools (see [6]). …”

Section: B Treatment Of the Tolerance Domainmentioning

confidence: 99%

“…To show the effectiveness of the proposed procedure, the optimal design of a magnetic resonance imaging device [6]- [8] is here considered. For the sake of simplicity, the attention is focused here on a single, typical objective in the design of such magnets, i.e., the compactness, defined as I TOLERANCE RANGES TABLE II INITIAL POINT the largest square distance of the external coils from the center of the system…”

Section: A Example 1-a Simple Magnetmentioning

confidence: 99%

“…Here, both the objective function and tolerance domain have been approximated by quadratic equations to obtain the gradients of the (4) and (6). In particular, the parameters of the approximated objective function have been estimated using a best-fitting technique.…”

Section: B Example 2-a More Complex Magnetmentioning

confidence: 99%

See 2 more Smart Citations

Gradient-Based Worst Case Search Algorithm for Robust Optimization

Chiariello¹,

Formisano²,

Martone³

et al. 2015

IEEE Trans. Magn.

Self Cite

View full text Add to dashboard Cite

The worst case search plays a fundamental role in the design of electromagnetic devices when robustness versus tolerances has to be pursued. Here, an approach is proposed to evaluate in effective and fast way the worst solution, when both the performance function and tolerance constraint function gradients are available. The algorithm is then generalized for the cases when such information is not explicitly given.Index Terms-Robust design, tolerance analysis, worst case.

show abstract

“…A combinatorial problem arises that, under suitable conditions, can be faced with effective tools (see [6]). …”

Section: B Treatment Of the Tolerance Domainmentioning

confidence: 99%

Section: A Example 1-a Simple Magnetmentioning

confidence: 99%