Kriging Metamodeling in Rotordynamics: Application for Predicting Critical Speeds and Vibrations of a Flexible Rotor

Table 20

% of the relative errors on the mean of the critical speeds for different regression orders and correlation functions (max; mean). Symmetric case with 70 samples.

	Gaussian	Linear	Exponential	Cubic
Zero-order regression
	(29.99; 0.70)	(73.91; 4.26)	(63.94; 2.90)	(81.53; 6.72)
	(6.35; 0.11)	(9.65; 0.69)	(12.38; 0.68)	(13.18; 1.35)
	(4.11; 0.10)	(21.05; 1.74)	(16.76; 0.99)	(24.43; 3.36)
	(2.49; 0.08)	(12.49; 0.94)	(5.89; 0.39)	(20.81; 2.10)
	(1.14; 0.03)	(7.60; 0.60)	(3.46; 0.26)	(10.62; 1.32)
	(0.63; 0.02)	(7.64; 0.53)	(2.03; 0.19)	(10.91; 1.16)
	(0.16; 0.00)	(1.90; 0.14)	(0.53; 0.05)	(2.67; 0.32)
	(0.09; 0.00)	(1.10; 0.08)	(0.31; 0.03)	(1.55; 0.19)
First-order regression
	(31.26; 0.53)	(61.83; 2.45)	(56.66; 2.13)	(67.62; 3.49)
	(8.29; 0.21)	(15.34; 0.95)	(16.13; 0.89)	(12.85; 1.33)
	(1.93; 0.09)	(7.52; 0.40)	(6.52; 0.39)	(8.66; 0.77)
	(0.66; 0.05)	(2.88; 0.25)	(2.52; 0.22)	(3.39; 0.38)
	(0.46; 0.01)	(1.89; 0.09)	(1.64; 0.09)	(2.17; 0.15)
	(0.17; 0.00)	(0.59; 0.03)	(0.51; 0.03)	(0.68; 0.06)
	(0.07; 0.00)	(0.25; 0.01)	(0.22; 0.01)	(0.29; 0.02)
	(0.01; 0.00)	(0.02; 0.00)	(0.02; 0.00)	(0.03; 0.00)
Second-order regression
	(18.61; 0.31)	(47.31; 1.32)	(44.13; 1.26)	(50.93; 1.64)
	(9.74; 0.22)	(13.61; 0.59)	(14.11; 0.62)	(14.24; 0.70)
	(1.49; 0.07)	(2.55; 0.15)	(2.09; 0.14)	(2.68; 0.18)
	(1.50; 0.09)	(1.57; 0.10)	(1.58; 0.10)	(1.57; 0.11)
	(0.11; 0.00)	(0.44; 0.01)	(0.41; 0.01)	(0.49; 0.02)
	(0.06; 0.00)	(0.16; 0.01)	(0.16; 0.01)	(0.17; 0.02)
	(0.00; 0.00)	(0.00; 0.00)	(0.00; 0.00)	(0.01; 0.00)
	(0.00; 0.00)	(0.00; 0.00)	(0.00; 0.00)	(0.00; 0.00)