Hi everyone,
I’m running simulations in FAST.Farm to calculate fatigue damage and I am conducting a convergence analysis to determine how many simulations are needed for reliable results.
So far, I’ve run simulations with 30 different random seed numbers, for different wind directions. However, I’ve noticed that a few simulations produce fatigue damage results that are significantly different from the others. For example, in the attached image, you can see that seeds 23, 24, and 25 yield values that deviate noticeably from the rest.
The seed numbers were chosen randomly by me, and I’m wondering if this variability could be related to the specific seed numbers I selected. Is there a recommended method for choosing seed numbers to ensure consistent and representative results?
Intuitively, I wouldn’t expect the seed numbers to have such a significant impact, but since I’m unsure, I wanted to reach out to the forum for insights. Has anyone else encountered similar behavior, or could anyone provide guidance on whether seed selection plays a role in convergence for fatigue damage analysis?
Below are the seed values (seed1 and seed2) I used for these simulations:
seed_dict1 = {
1: (2073448544, -75384093),
2: (1532865329, 65454852),
3: (456789, -5054),
4: (34, 456),
5: (-65453, -5),
6: (-1, -2345),
7: (456345, 344),
8: (6456347, 445654),
9: (2345, 6674),
10: (23452456, 78565),
11: (-456345656, -4534546),
12: (2357, -45634563),
13: (987689, 787666),
14: (-98756545, 6756),
15: (-1234545, -45636574),
16: (-118803747, 247504697),
17: (-171161675, 206919021),
18: (-184742058, 904353589),
19: (-295269453, 555203102),
20: (-301652503, 634537670),
21: (-540227741, 58744843),
22: (-592844958, 878708298),
23: (-677123190, 662101981),
24: (992948224, 95641675),
25: (504323988, -466215084),
26: (717061322, -259797599),
27: (-944537124, 174755444),
28: (268945319, -336690441),
29: (-838449676, 902207459),
30: (925578245, 854775900)
}
Thank you in advance for your help!
Best regards,
Tiago Lucas