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The hypothetical Carnot cycle consists of an ideal gas subjected to two isothermal and two adiabatic processes. Since the internal energy of an ideal gas depends only on its temperature, which is the same before and after the completion of the Carnot cycle, there is no change in its internal energy. Hence, using the first law of thermodynamics, the total heat exchanged by the ideal gas equals the total work done. Thus, we can quantify the efficiency of the Carnot cycle via the heat exchanged...
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Converting work to heat is an irreversible process, and the purpose of a heat engine is to reverse the effect partially. Heat engines aim to increase the efficiency of the reversal, that is, maximize the work retrieved from heat. If the efficiency of a heat engine were 100%, it would imply reversing the process completely without introducing any other effect. Thus, it would violate the second law of thermodynamics.
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The Carnot engine works between two heat reservoirs of fixed temperatures. The Carnot cycle begs the following question: Is it possible to devise a heat engine that is more efficient than a Carnot engine between two fixed temperatures? The answer lies in designing a Carnot refrigerator.
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An Otto engine is a four-stroke engine that uses a mixture of gasoline and air as the working fuel. The fuel is injected into the cylinder, and the piston is moved completely down so that the cylinder is at maximum volume. By moving the piston up, adiabatic compression takes place. The spark plug ignites the gasoline-air mixture, and the burning fuel adds heat to the system at a constant volume. The heated mixture expands adiabatically and gets further cooled by exhausting heat, and this cyclic...
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A heat engine is a device used to extract heat from a source and then convert it into mechanical work used for various applications. For example, a steam engine on an old-style train can produce the work needed for driving the train.
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Four-Objective Optimizations for an Improved Irreversible Closed Modified Simple Brayton Cycle.

Chenqi Tang1,2,3, Lingen Chen1,2, Huijun Feng1,2

  • 1Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China.

Entropy (Basel, Switzerland)
|March 3, 2021
PubMed
Summary
This summary is machine-generated.

This study presents an improved Brayton cycle model considering irreversible losses. Optimization reveals that higher compressor and turbine efficiencies enhance performance, with turbine efficiency having a greater impact.

Keywords:
closed simple Brayton cycleecological functionmulti-objective optimizationpower densitypower outputthermal efficiency

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Area of Science:

  • Thermodynamics
  • Energy Systems Engineering

Background:

  • The Brayton cycle is a fundamental thermodynamic cycle for gas turbines.
  • Real-world applications necessitate accounting for irreversible losses in components like compressors and turbines.
  • Variable-temperature heat reservoirs introduce complexities in cycle analysis.

Purpose of the Study:

  • To establish an improved irreversible closed modified simple Brayton cycle model with isothermal heating.
  • To analyze the impact of irreversible losses on cycle performance using finite time thermodynamics.
  • To perform multi-objective optimization of the cycle based on power output, efficiency, power density, and ecological function.

Main Methods:

  • Development of an improved irreversible closed modified simple Brayton cycle model.
  • Application of finite time thermodynamics principles.
  • Analysis of irreversible losses in compressors, turbines, and heat exchangers.
  • Multi-objective optimization using the NSGA-II algorithm and decision-making methods (Shannon Entropy, maximum ecological function).

Main Results:

  • All four objective functions (dimensionless power output, thermal efficiency, dimensionless power density, dimensionless ecological function) increase with compressor and turbine efficiencies.
  • Turbine efficiency has a more significant impact on cycle performance than compressor efficiency.
  • The dimensionless power density and dimensionless ecological function represent a trade-off with dimensionless power output and thermal efficiency.
  • The Shannon Entropy method and maximum ecological function method yielded equal deviation indices.

Conclusions:

  • The developed Brayton cycle model provides a more realistic assessment of performance under irreversible conditions.
  • Component efficiencies are critical for optimizing Brayton cycle performance, with turbine efficiency being particularly influential.
  • Multi-objective optimization highlights inherent trade-offs between different performance metrics, guiding practical design choices.