Eddy-Current NDE Inverse Problem with Sparse Grid Algorithm

被引：1

作者：

Zhou, Liming ^{[1
]}

Sabbagh, Harold A. ^{[1
]}

Sabbagh, Elias H. ^{[1
]}

Murphy, R. Kim ^{[1
]}

Bernacchi, William ^{[2
]}

Aldrin, John C. ^{[3
]}

Forsyth, David ^{[4
]}

Lindgren, Eric ^{[5
]}

机构：

[1] Victor Technol LLC, Bloomington, IN 47404 USA

[2] Minds Edge LLC, Indianapolis, IN 46268 USA

[3] Computat Tools, Gurnee, IL USA

[4] Texas Reserch Inst Austin, Austin, TX 78733 USA

[5] Air Force Res Lab AFRL RXLP, Wright Patterson AFB, OH 45433 USA

来源：

42ND ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION: INCORPORATING THE 6TH EUROPEAN-AMERICAN WORKSHOP ON RELIABILITY OF NDE | 2016年 / 1706卷

关键词：

D O I：

10.1063/1.4940553

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

In model-based inverse problems, the unknown parameters (such as length, width, depth) need to be estimated. When the unknown parameters are few, the conventional mathematical methods are suitable. But the increasing number of unknown parameters will make the computation become heavy. To reduce the burden of computation, the sparse grid algorithm was used in our work. As a result, we obtain a powerful interpolation method that requires significantly fewer support nodes than conventional interpolation on a full grid.

引用

页数：6

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