Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell–Boltzmann gases

Ahmadi, Mohammad Hossein; Nabakhteh, Mohammad Amin; Ahmadi, Mohammad Ali; Pourfayaz, Fathollah; Bidi, Mokhtar

doi:10.1016/j.physa.2017.04.079

Cited by 22 publications

(7 citation statements)

References 119 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More details on the Stirling engines and how they work can be found in previous works. 1,34,58,59,[62][63][64][65]69,77,83,89,92 In the next step, the thermodynamic parameters of this system must be calculated. Equations (11) and (12) where θ is the heat conductance (W m −2 K −1 ), n is the mole number, x is the compression ratio (x = V max /V min ), T 1 and T 2 are average temperatures of the compression and expansion processes, and t 1 and t 2 are the times spent on the two isothermal branches.…”

Section: Analysis Of the Stirling Enginementioning

confidence: 99%

“…In addition, a conductive heat transfer occurs between the heat source and sink, namely conductive thermal bridge loss. More details on the Stirling engines and how they work can be found in previous works . In the next step, the thermodynamic parameters of this system must be calculated.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Generally, in multi‐objective optimization problems, a numerous set of answers called Pareto frontier is examined, to represent the closest match in the objective function area. On this subject, researchers have evaluated multi‐objective optimization for different energy systems in order to determine the best optimal operation conditions of the system …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi‐objective performance optimization of irreversible molten carbonate fuel cell–Stirling heat engine–reverse osmosis and thermodynamic assessment with ecological objective approach

Ahmadi

Sameti

Pourkiaei

et al. 2018

Energy Science & Engineering

Self Cite

View full text Add to dashboard Cite

This paper aims to investigate a hybrid cycle consisting of a molten carbonate fuel cell (FC) and a Stirling engine which, by connecting to a seawater reverse osmosis desalination unit, provides fresh water. First, a parametric evaluation is performed to study the effect of some key parameters, including the current density and the working temperature of the FC and the thermal conductance between the working substance and the heat reservoirs in the Stirling engine, on the objective functions. The objective functions include the energy efficiency, the exergy destruction rate density, the fresh water production rate, and the ecological function density. After investigating each double combination of these objective functions, two scenarios are defined in quest to concurrently optimize three functions together. The first scenario aims to optimize the energy efficiency, the exergy destruction rate density, and the fresh water production rate; and the second scenario attempts to optimize the energy efficiency, the fresh water production rate, and the ecological function density. A multi‐objective evolutionary algorithm joined with the nondominated sorting genetic algorithm (NSGA‐II) approach is employed to obtain Pareto fronts in each case scenario. In order to ascertain final solutions between Pareto fronts, three fast and robust decision‐making methods are employed including TOPSIS, LINMAP, and Fuzzy. Finally, a sensitivity analysis is conducted to critically analyze the performance of the system.

show abstract

Section: Analysis Of the Stirling Enginementioning

confidence: 99%

Section: Model Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi‐objective performance optimization of irreversible molten carbonate fuel cell–Stirling heat engine–reverse osmosis and thermodynamic assessment with ecological objective approach

Ahmadi

Sameti

Pourkiaei

et al. 2018

Energy Science & Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…Ahmadi et al and Sadatsakkak et al obtained results related to the performance optimization and thermodynamic analysis of Stirling and Brayton's cycle operating with Ideal Maxwell‐Boltzmann gas respectively. Ahmadi et al performed multiobjective optimization of nanoscale irreversible Stirling refrigeration cycle. Guo et al worked on the nanoscale heat engine system with ideal quantum gases.…”

Section: Introductionmentioning

confidence: 99%

“…In this situation, multiobjective optimizations using evolutionary algorithms have proven helpful in obtaining an optimum set of parameters that satisfy conflicting objectives. Multiobjective optimization is also studied to find the optimum solution for environmental effects in various thermal systems . Further, the multiobjective optimization of the various system like refrigerators, heat engine, cryogenic cycle, irreversible Brayton cycle, irreversible Diesel cycle, Stirling engine, heat pump, and power cycles have been carried out using evolutionary algorithms.…”

Section: Introductionmentioning

confidence: 99%

A multiobjective thermodynamic optimization of a nanoscale Stirling engine operated with Maxwell‐Boltzmann gas

Shah

Saliya

Raja

et al. 2019

Heat Trans. Asian Res.

View full text Add to dashboard Cite

Recent developments in nanotechnology provided an opportunity to solve many complex problems in the field of energy. Performance investigation of the nanoscale thermal cycles can prove crucial in the development of efficient and less polluting energy system. Due to the influence of boundary phenomenon and quantum degeneracy effects, a nanoscale engine performs according to statistical quantum thermodynamics instead of classical thermodynamics. In this study, a nanoscale Stirling engine operating on an ideal Maxwell-Boltzmann gas is investigated for multiobjective optimization.Optimization problem of Stirling cycle is formed considering the thermal efficiency, ecological coefficient of performance and entropy generation. An application example of a nanoscale Stirling engine is presented and solved using Heat Transfer Search algorithm. Maxwell-Boltzmann gas restricted in a finite domain is studied and the effect of different parameters, such as surface area ratio, volume ratio, and temperature ratio of the domain, is investigated. Sensitivity analysis is carried out to identify the effect of design variables on the performance parameters. Further, influence of the source temperature and the number of particles of working fluid on the objective functions is studied and presented.

show abstract

Thermal Design and Optimization of Refrigeration Systems

Patel

Savsani

Tawhid

2019

Thermal System Optimization

View full text Add to dashboard Cite

Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell–Boltzmann gases

Cited by 22 publications

References 119 publications

Multi‐objective performance optimization of irreversible molten carbonate fuel cell–Stirling heat engine–reverse osmosis and thermodynamic assessment with ecological objective approach

Multi‐objective performance optimization of irreversible molten carbonate fuel cell–Stirling heat engine–reverse osmosis and thermodynamic assessment with ecological objective approach

A multiobjective thermodynamic optimization of a nanoscale Stirling engine operated with Maxwell‐Boltzmann gas

Thermal Design and Optimization of Refrigeration Systems

Contact Info

Product

Resources

About