Heat Transfer in Rotary Combustion Engines

1975 ◽  
Vol 97 (2) ◽  
pp. 288-293 ◽  
Author(s):  
K. M. Atesmen

In the first part of this study, a one-dimensional quasi-steady-state heat transfer model is developed for an axial forced flow system in rotary combustion engines. This computer model is useful in optimizing the cooling system in accordance with the heat input from the combustion chambers. In the second part of this study, a two-dimensional quasi-steady-state heat transfer model is developed for an axial forced flow cooling system in a rotor housing in an effort to minimize the thermal stresses and the thermal distortions of the trochoidal surfaces. In the third part of this study, a two-dimensional transient heat transfer model is developed for an axial forced flow cooling system in a critical portion of the rotor housing in order to determine the critical thermal loads that occur in the through-bolts during the sudden acceleration of a cold rotating combustion engine.

2016 ◽  
Vol 685 ◽  
pp. 90-93
Author(s):  
Alexander Yu. Chebotarev ◽  
Andrey E. Kovtanyuk

A boundary multiplicative control problem for a nonlinear steady-state heat transfer model accounting for heat radiation effects is considered. The aim of control consists in obtaining a prescribed temperature or radiative intensity distributions in a part of the model domain by controlling the boundary reflectivity. The solvability of this control problem is proved, and optimality conditions are derived.


2016 ◽  
Vol 112 ◽  
pp. 12-20 ◽  
Author(s):  
Gabriel Năstase ◽  
Alexandru Şerban ◽  
George Dragomir ◽  
Sorin Bolocan ◽  
Alin Ionuţ Brezeanu

2014 ◽  
Vol 926-930 ◽  
pp. 802-805
Author(s):  
Jun Li Jia ◽  
Jin Hong Zhang ◽  
Guo Zhen Wang

Efficient secondary cooling water control level slab continuous casting process and quality are closely related. Casting solidification heat transfer model is the basis of process control and optimization, heat transfer model based on determining the secondary cooling system is the most widely used method for casting production process can be simulated. However, when considering the many factors affecting the production and input conditions change significantly, real-time and strain of this method is not guaranteed. Therefore, the artificial intelligence optimization algorithms such as genetic algorithms, neural networks, fuzzy controllers, introducing continuous casting secondary cooling water distribution and dynamics of optimal control methods, the rational allocation of caster secondary cooling water and dynamic control is important.


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