- Applications Other Than Stirling Engines

2016 ◽  
pp. 360-369
Keyword(s):  
2014 ◽  
Vol 2 ◽  
pp. 134-137
Author(s):  
Hisashi Kada ◽  
Hiromasa Hojyo ◽  
Isao T. Tokuda
Keyword(s):  

2015 ◽  
Vol 785 ◽  
pp. 576-580 ◽  
Author(s):  
Liaw Geok Pheng ◽  
Rosnani Affandi ◽  
Mohd Ruddin Ab Ghani ◽  
Chin Kim Gan ◽  
Jano Zanariah

Solar energy is one of the more attractive renewable energy sources that can be used as an input energy source for heat engines. In fact, any heat energy sources can be used with the Stirling engine. Stirling engines are mechanical devices working theoretically on the Stirling cycle, or its modifications, in which compressible fluids, such as air, hydrogen, helium, nitrogen or even vapors, are used as working fluids. When comparing with the internal combustion engine, the Stirling engine offers possibility for having high efficiency engine with less exhaust emissions. However, this paper analyzes the basic background of Stirling engine and reviews its existing literature pertaining to dynamic model and control system for parabolic dish-stirling (PD) system.


2016 ◽  
Vol 100 ◽  
pp. 961-971 ◽  
Author(s):  
Iván Mesonero ◽  
Susana López ◽  
Francisco J. García-Granados ◽  
Francisco J. Jiménez-Espadafor ◽  
David García ◽  
...  

2018 ◽  
Vol 54 (11) ◽  
pp. 1-5 ◽  
Author(s):  
Kyu-Seok Lee ◽  
Sung-Ho Lee ◽  
Jung-Hyung Park ◽  
Jang-Young Choi ◽  
Kyu-Ho Sim

Author(s):  
Vassili V. Toropov ◽  
Henrik Carlsen

Abstract The ideal Stirling working cycle has the maximum obtainable efficiency defined by Carnot efficiency, and highly efficient Stirling engines can therefore be built, if designed properly. To analyse the power output and the efficiency of a Stirling engine, numerical simulation programs (NSP) have been developed, which solve the thermodynamic equations. In order to find optimum values of design variables, numerical optimization techniques can be used (Bartczak and Carlsen, 1991). To describe the engine realistically, it is necessary to consider several tens of design variables. As even a single call for NSP requires considerable computing time, it would be too time consuming to use conventional optimization techniques, which require a very large number of calls for NSP. Furthermore, objective and constraint functions of the optimization problem present some level of noise, i.e. can only be estimated with a finite accuracy. To cope with these problems, the multipoint explicit approximation technique is used.


2000 ◽  
Author(s):  
Gianfranco Angelino ◽  
Costante Invernizzi

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