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Four-Objective Optimization of an Irreversible Stirling Heat Engine with Linear Phenomenological Heat-Transfer Law
Haoran Xu1,2,3, Lingen Chen1,2,3, Yanlin Ge1,2,3
1Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Entropy (Basel, Switzerland)
|July 8, 2023
Summary
This study optimizes irreversible Stirling heat engines using combined theories, finding multi-objective optimization superior. Advanced decision-making strategies yield better engine performance and efficiency.
Area of Science:
- Thermodynamics
- Mechanical Engineering
- Heat Transfer
Background:
- Irreversible Stirling heat engines suffer from mechanical losses, heat leakage, thermal resistance, and regeneration loss.
- Optimizing these engines requires balancing multiple performance objectives simultaneously.
Purpose of the Study:
- To perform multi-objective optimization on an irreversible Stirling heat engine cycle.
- To evaluate the effectiveness of different decision-making strategies in achieving optimal performance.
Main Methods:
- Combined mechanical efficiency theory and finite time thermodynamic theory.
- Utilized the NSGA-II algorithm for multi-objective optimization.
- Applied TOPSIS, LINMAP, and Shannon Entropy for decision-making.
Main Results:
- Multi-objective optimization using TOPSIS and LINMAP yielded a deviation index (D) of 0.1683.
- This multi-objective result was superior to single-objective optimizations.
- The Shannon Entropy strategy performed less effectively than TOPSIS and LINMAP.
Conclusions:
- Multi-objective optimization provides superior results for irreversible Stirling heat engines.
- The choice of decision-making strategy significantly impacts the optimization outcome.
- TOPSIS and LINMAP are effective strategies for this type of thermodynamic optimization.
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