Multivariate Design of Experiments for Engineering Dimensional Analysis

被引:4
|
作者
Eck, Daniel J. [1 ]
Cook, R. Dennis [2 ]
Nachtsheim, Christopher J. [3 ]
Albrecht, Thomas A. [4 ]
机构
[1] Yale Univ, Dept Biostat, New Haven, CT 06510 USA
[2] Univ Minnesota, Sch Stat, Minneapolis, MN 55455 USA
[3] Univ Minnesota, Carlson Sch Management, Minneapolis, MN 55455 USA
[4] Boston Sci, Maple Grove, MN USA
关键词
Buckingham Pi-theorem; Coordinate exchange algorithm; I-optimality; Optimal design; Robust-DA design; ALGORITHM;
D O I
10.1080/00401706.2019.1585294
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We consider the design of dimensional analysis experiments when there is more than a single response. We first give a brief overview of dimensional analysis experiments and the dimensional analysis (DA) procedure. The validity of the DA method for univariate responses was established by the Buckingham Pi-Theorem in the early 20th century. We extend the theorem to the multivariate case, develop basic criteria for multivariate design of DA and give guidelines for design construction. Finally, we illustrate the construction of designs for DA experiments for an example involving the design of a heat exchanger.
引用
收藏
页码:6 / 20
页数:15
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