Closed-form solution for free vibration of variable-thickness cylindrical shells rotating with a constant angular velocity

2021 ◽  
Vol 166 ◽  
pp. 108062
Author(s):  
Ehsan Taati ◽  
Famida Fallah ◽  
Mohamad Taghi Ahmadian
Keyword(s):  
Angular Velocity ◽  
Free Vibration ◽  
Closed Form ◽  
Variable Thickness ◽  
Cylindrical Shells ◽  
Closed Form Solution ◽  
Form Solution ◽  
Constant Angular Velocity

NEUROFUZZY MODELING OF NATURAL FREQUENCIES OF CYLINDRICAL SHELLS APPLIED TO EVOLUTIONARY BASED OPTIMAL DESIGN OF SR MOTORS

2006 ◽  
Vol 03 (03) ◽  
pp. 263-277 ◽  
Author(s):  
HOSSEIN ROUHANI ◽  
MANSOUR NIKKHAH BAHRAMI ◽  
BABAK NADJAR ARAABI ◽  
CARO LUCAS
Keyword(s):  
Finite Element ◽  
Optimal Design ◽  
Closed Form ◽  
Natural Frequencies ◽  
Cylindrical Shells ◽  
Closed Form Solution ◽  
Form Solution ◽  
Design Problems ◽  
Special Cases ◽  
Wide Range

A thorough analysis of cylindrical shells' dynamical behavior is essential in many different industrial design problems, and particularly in electric motor design. Shell vibration equations form a set of partial differential equations of order eight, where their closed form solution is only known for few special cases with a few known boundary conditions along with many not necessarily realistic assumptions. On the other hand, finite element based numerical solutions does not yield a lumped model that can be regarded as a general solution for natural frequencies of cylindrical shells. In this paper, a neurofuzzy model for natural frequencies of cylindrical shells is developed. At first, natural frequencies are calculated for a wide range of cylindrical shells' dimensions, using either closed form solution or finite element method. Gathered data is exploited for training of a Locally Linear Neurofuzzy Network, which yields a general model for calculation of natural frequencies of cylindrical shells. While the developed neurofuzzy model may be used in different design problems that deals with cylindrical shells, as a case study, the proposed model along with an evolutionary algorithm are utilized in the optimal design of a Switched Reluctance motor.

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