Title :
Cellular neural network to model and solve direct non-linear problems of steady-state heat transfer
Author :
Krstic, Ivan ; Reljin, Branimir ; Kostic, Predrag
Author_Institution :
Fed. Inst. for Stand., Belgrade, Yugoslavia
Abstract :
Different non-electric problems can be efficiently modeled and solved by using their electric counterparts. The paper describes an original method to model and solve the direct nonlinear problem of heat transfer in solids by using the cellular neural network (CNN). By modifying constitutive equations of the hear transfer which are nonlinear functions of temperature, it is possible to rearrange them to become linear functions of some new variable. Similarly, by slightly modifying an original Chua CNN we can establish direct analogy between rearranged hear transfer equations and those of the modified CNN. Consequently, different heat transfer process in solids, having an arbitrary shape, can be solved by using CNN.
Keywords :
cellular neural nets; heat transfer; nonlinear differential equations; nonlinear functions; partial differential equations; Chua CNN; cellular neural network; direct nonlinear problem; nonlinear functions; steady-state heat transfer; Boundary conditions; Cellular neural networks; Heat sinks; Heat transfer; Nonlinear equations; Partial differential equations; Shape; Solids; Steady-state; Temperature;
Conference_Titel :
EUROCON'2001, Trends in Communications, International Conference on.
Conference_Location :
Bratislava, Slovakia
Print_ISBN :
0-7803-6490-2
DOI :
10.1109/EURCON.2001.938153