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Related Concept Videos

Efficiency of The Carnot Cycle01:16

Efficiency of The Carnot Cycle

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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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The Carnot Cycle01:30

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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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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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Thermodynamic Systems01:06

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A thermodynamic system is a set of objects whose thermodynamic properties are of interest. The system is considered to be embedded in its surroundings or the environment. The system and its environment can exchange heat and do work on each other through a boundary that separates them. However, the immediate surroundings of the system interact with it directly and therefore have a much stronger influence on its behavior and properties.
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The Carnot Cycle and the Second Law of Thermodynamics01:20

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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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Applying the conservation of energy principle or the work-energy theorem to an incompressible, inviscid fluid in laminar, steady, irrotational flow leads to Bernoulli's equation. It states that the sum of the fluid pressure, potential, and kinetic energy per unit volume is constant along a streamline.
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Multi-Objective Optimization of the Basic and Regenerative ORC Integrated with Working Fluid Selection.

Yuhao Zhou1,2, Jiongming Ruan3, Guotong Hong1,2

  • 1Key Laboratory of Technology on Space Energy Conversion, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China.

Entropy (Basel, Switzerland)
|July 27, 2022
PubMed
Summary
This summary is machine-generated.

This study optimizes organic Rankine cycles using multi-objective genetic algorithms. The turbine inlet temperature significantly impacts performance, with regenerative ORC offering higher thermal efficiency but increased costs.

Keywords:
NSGA-IIexergy efficiencylevelized energy costmulti-objective optimizationregenerative ORC systemthermal efficiencyworking fluid selection

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Area of Science:

  • Thermodynamics
  • Energy Systems Engineering
  • Optimization Algorithms

Background:

  • Organic Rankine cycles (ORC) are crucial for low-to-medium temperature heat recovery.
  • Multi-objective optimization is essential for balancing competing performance metrics in ORC systems.
  • Working fluid selection and system design parameters significantly influence ORC efficiency and cost.

Purpose of the Study:

  • To perform multi-objective optimization for basic (BORC) and regenerative (RORC) organic Rankine cycles.
  • To integrate working fluid selection into the optimization process.
  • To analyze the trade-offs between exergy efficiency, thermal efficiency, and levelized energy cost (LEC).

Main Methods:

  • Utilized the non-dominated sorting genetic algorithm II (NSGA-II) for multi-objective optimization.
  • Parameterized pure working fluids into a two-dimensional array for fluid selection.
  • Optimized five decision variables: turbine inlet temperature, vapor superheat, pinch temperature differences, and mixture mass fraction.

Main Results:

  • Turbine inlet temperature identified as the most influential parameter for both BORC and RORC.
  • A weak conflict between exergy efficiency and LEC suggests potential for single-objective optimization.
  • Regenerative ORC (RORC) achieved higher thermal efficiency than BORC at similar exergy efficiencies, but with increased LEC due to additional heat exchanger costs.

Conclusions:

  • Multi-objective optimization effectively balances performance and cost in ORC systems.
  • The choice between BORC and RORC depends on the specific application's priorities regarding efficiency and cost.
  • Further research can explore advanced working fluids and optimization strategies for enhanced ORC performance.