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March 13, 2021 at 1:18 pm
omidrastkhiz
SubscriberHi everyone,nI am finished my model in ANSYS and now I have natural frequencies and mode shapes and since I have the result of the experiment for the same structure (Stator Segment of generator) , I want to calculate MAC value (Modal Assurance Criterion), and I need EigenVector matrix or Phi Value for that, Does anyone know how to calculate that?.Thank you in advance,nOmid.n -
March 15, 2021 at 8:52 am
1shan
Ansys Employee,nYou can get the mass and stiffness matrices, as shown in and then post process the in MATLAB.nRegards,nIshan.n -
March 15, 2021 at 9:31 am
ErKo
Ansys EmployeeHinnJust to add in case this could be of help.Ansys can calculate the MAC values - see the help manual for more info under RSTMAC apdl command.nnGood lucknnErikn -
March 15, 2021 at 11:17 am
omidrastkhiz
SubscribernThank you so much Ishan, That was helpful.n -
March 15, 2021 at 11:29 am
omidrastkhiz
SubscribernHi Erik,nThank you so much,nThat is great, although I am looking for what you said in the manual, but I am not sure if I am in a right directory in Ansys manual, can you please give me some keywords, or a link. nAnd do you know what kind of data it might need from experiment to calculate the MAC value, I mean only natural frequency result from experiment or something else as well? since MAC is basically comparison between mode shapes from the experiment and simulation in Ansys, and I am not sure what information or data, does Ansys need from experiment or acquisition system in order to give the MAC values?.Again Thank you so much, That was really helpful Erik.nOmid.n -
March 15, 2021 at 11:49 am
1shan
Ansys Employee,nThis is the link RSTMAC (ansys.com). MAC is kind of like the dot product between 2 vectors (eigen vectors/mode shapes) generally one from the experiment and second from the simulation. Please check the literature on how to find the mode shapes experimentally, once you have that you can use RSTMAC.nRegards,nIshan.n -
March 22, 2021 at 12:43 pm
omidrastkhiz
SubscriberThank You So much 1shan, that is really helpfull.n
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