Thermo-economic modeling and optimization of an irreversible solar-driven heat engine

Ahmadi, Mohammad Hossein; Mehrpooya, Mehdi

doi:10.1016/j.enconman.2015.06.088

Cited by 36 publications

(5 citation statements)

References 38 publications

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“…More features about decision makers and more examples of their application can be found in the previous studies. 1,62,[64][65][66][67][68][70][71][72][74][75][76][77][78][79][82][83][84][85]92 4 | RESULTS AND DISCUSSION…”

Section: Optimization Algorithmmentioning

confidence: 99%

“…LINMAP and TOPSIS use the Euclidian and the Fuzzy employs the Fuzzy nondimensionalization technique. More features about decision makers and more examples of their application can be found in the previous studies …”

Section: Optimization Algorithmmentioning

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%

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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

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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.

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Section: Optimization Algorithmmentioning

confidence: 99%

Section: Optimization Algorithmmentioning

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

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“…[11][12][13][14] Recently, increasing the heat transfer rate (HTR) in renewable systems has been of interest to researchers. [15][16][17][18][19] One of these methods is to use nanofluids as an alternative to conventional liquids. [20][21][22][23][24][25][26][27][28] Nanofluids are widely used in micromixers, 29 heat exchangers, 30 and solar systems.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, increasing the heat transfer rate (HTR) in renewable systems has been of interest to researchers 15–19 . One of these methods is to use nanofluids as an alternative to conventional liquids 20–28 .…”

Section: Introductionmentioning

confidence: 99%

Simulation of a parabolic trough solar collector containing hybrid nanofluid and equipped with compound turbulator to evaluate exergy efficacy and thermal‐hydraulic performance

Khetib

Alahmadi

Alzaed

et al. 2021

Energy Science & Engineering

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This research is mainly aimed at investigating the numerical modeling of thermal‐hydraulic and exergy efficiencies of parabolic trough solar collectors (P‐SCs) filled with magnetic hybrid nanofluid. The k‐epsilon turbulence, S2S, and mixture models were used to simulate the turbulence equations, radiation, and two‐phase nanofluid, respectively. The experiments were run using magnetic nanofluid in Reynolds numbers of 5000‐20 000, the volume fractions of 1%‐3%, and the ratios of pitch (ROPs) of 1, 2, and 3 of the combined turbulator. According to the results, there is a significant increase in average Nusselt number (Nu) and pressure drop (ΔP) with increasing Reynolds number, nano‐additive concentration, and ROP. Moreover, the use of the hybrid magnetic turbulator and hybrid nanofluid increased the thermal performance of the P‐SC. It was also found that the Reynolds number of 20 000 and volume fraction of 3% of nanoparticles resulted in the optimal exergy efficiency mode in using a hybrid turbulator.

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Multi-Objective Optimization and Cluster-Wise Regression Analysis to Establish Input–Output Relationships of a Process

Das

Pratihar

2018

Multi-Objective Optimization

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Thermo-economic modeling and optimization of an irreversible solar-driven heat engine

Cited by 36 publications

References 38 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

Simulation of a parabolic trough solar collector containing hybrid nanofluid and equipped with compound turbulator to evaluate exergy efficacy and thermal‐hydraulic performance

Multi-Objective Optimization and Cluster-Wise Regression Analysis to Establish Input–Output Relationships of a Process

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