This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Numerical Computational Optimization Applied To The Dynamic Behavior of an Articulated Cursor, Connecting Rod and Crank Mechanism - Case Studies for Implementing a Beta Stirling Engine
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 30, 2014 by SAE International in United States
Annotation ability available
The Stirling engine is a device that has great potential for being used in applications where energy (heat) is available in the system. As an example, a Stirling motor can use the energy available in the gases from the combustion process of an automotive engine by using exhaust manifold as hot source. The Stirling motor consists of a piston that can move along a cylinder that is fulfilled by a working fluid and a displacer installed between the hot and cold chambers. Due to the large temperature difference between the chambers, it becomes feasible to use the corresponding energy to drive the Stirling engine. For design purposes, a multi-objective problem is formulated so that the maximization of thermodynamic efficiency, the minimization of energetic loss associated with the movement of the displacer set, and the minimization of energetic loss related to the fluid displacement between the two chambers is obtained for the optimal configuration of the system. To solve this optimal design problem, the Non- dominated Sorting Genetic Algorithm is used. The preliminary results demonstrated that the methodology proposed represents a promising approach for the design of Stirling engines. The theoretical results were used to construct a prototype of a Stirling engine for evaluating the whole design process.
Citationde Paula Brito, G. and Borges, J., "Numerical Computational Optimization Applied To The Dynamic Behavior of an Articulated Cursor, Connecting Rod and Crank Mechanism - Case Studies for Implementing a Beta Stirling Engine," SAE Technical Paper 2014-36-0282, 2014, https://doi.org/10.4271/2014-36-0282.
- LOBATO , F.S. 2007 Otimização multi-objetivo para o projeto de sistemas de engenharia Tese (Doutorado) Faculdade de Engenharia Mecânica de Uberlândia Uberlândia-MG
- Gen Cheng , Mitsuo and Cheng Runwei Genetic Algorithms & Engineering Optimization 2000 John Wiley & Sons, inc.
- DEB K. , PRATAP A. , AGARWAL S. , MEYARIVAN T. A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II KanGAL - Kanpur Genetic Algorithms Laboratory KanGAL Report Number 2000001 2000
- Incropera , Frank P. Fundamentos de Transferencia de calor 4a México 1999