Layout Optimization of Two Autonomous Underwater Vehicles for Drag Reduction with a Combined CFD and Neural Network Method

Table 3

CFD data for the training samples.

Sample
(1)	0.00	0.00	2.0000	2.0000	4.0000
(2)	0.00	0.25	2.0000	2.0000	4.0000
(3)	0.00	0.50	2.0000	2.0000	4.0000
(4)	0.00	0.75	2.0000	2.0000	4.0000
(5)	0.00	1.00	2.0000	2.0000	4.0000
(6)	0.00	1.25	0.7910	1.0972	1.8882
(7)	0.00	1.50	0.9392	0.9748	1.9141
(8)	0.00	1.75	0.9757	0.9602	1.9359
(9)	0.00	2.00	0.9885	0.9629	1.9514
(10)	0.10	0.00	2.0000	2.0000	4.0000
(11)	0.10	0.25	2.0000	2.0000	4.0000
(12)	0.10	0.50	2.0000	2.0000	4.0000
(13)	0.10	0.75	2.0000	2.0000	4.0000
(14)	0.10	1.00	2.0000	2.0000	4.0000
(15)	0.10	1.25	0.8245	1.1725	1.9970
(16)	0.10	1.50	0.9432	1.0604	2.0036
(17)	0.10	1.75	0.9765	1.0296	2.0061
(18)	0.10	2.00	0.9887	1.0188	2.0075
(19)	0.20	0.00	1.0552	1.0552	2.1104
(20)	0.20	0.25	1.7136	0.3598	2.0733
(21)	0.20	0.50	1.5153	0.5364	2.0517
(22)	0.20	0.75	1.4027	0.5841	1.9868
(23)	0.20	1.00	0.7591	1.2507	2.0098
(24)	0.20	1.25	0.8671	1.1107	1.9778
(25)	0.20	1.50	0.9450	1.0398	1.9848
(26)	0.20	1.75	0.9728	1.0150	1.9879
(27)	0.20	2.00	0.9841	1.0050	1.9891
(28)	0.30	0.00	1.0247	1.0247	2.0494
(29)	0.30	0.25	1.4041	0.6326	2.0367
(30)	0.30	0.50	1.3595	0.6702	2.0297
(31)	0.30	0.75	1.1989	0.7884	1.9873
(32)	0.30	1.00	0.9257	1.0920	2.0177
(33)	0.30	1.25	0.9135	1.0671	1.9806
(34)	0.30	1.50	0.9557	1.0297	1.9853
(35)	0.30	1.75	0.9761	1.0118	1.9879
(36)	0.30	2.00	0.9852	1.0037	1.9889
(37)	0.40	0.00	1.0146	1.0146	2.0292
(38)	0.40	0.25	1.2386	0.7859	2.0245
(39)	0.40	0.50	1.2489	0.7770	2.0259
(40)	0.40	0.75	1.1302	0.8617	1.9920
(41)	0.40	1.00	0.9947	1.0283	2.0229
(42)	0.40	1.25	0.9487	1.0354	1.9841
(43)	0.40	1.50	0.9669	1.0200	1.9869
(44)	0.40	1.75	0.9800	1.0086	1.9886
(45)	0.40	2.00	0.9871	1.0025	1.9896
(46)	0.50	0.00	1.0094	1.0095	2.0189
(47)	0.50	0.25	1.1488	0.8699	2.0187
(48)	0.50	0.50	1.1753	0.8506	2.0259
(49)	0.50	0.75	1.0950	0.9000	1.9951
(50)	0.50	1.00	1.0243	1.0032	2.0275
(51)	0.50	1.25	0.9723	1.0146	1.9868
(52)	0.50	1.50	0.9769	1.0118	1.9887
(53)	0.50	1.75	0.9843	1.0057	1.9900
(54)	0.50	2.00	0.9891	1.0016	1.9907
(55)	0.60	0.00	1.0062	1.0065	2.0127
(56)	0.60	0.25	1.0963	0.9170	2.0132
(57)	0.60	0.50	1.1263	0.8991	2.0253
(58)	0.60	0.75	1.0724	0.9245	1.9969
(59)	0.60	1.00	1.0327	0.9907	2.0235
(60)	0.60	1.25	0.9873	1.0018	1.9891
(61)	0.60	1.50	0.9850	1.0052	1.9903
(62)	0.60	1.75	0.9883	1.0029	1.9912
(63)	0.60	2.00	0.9911	1.0000	1.9911