Three-dimensional CFD analysis for simulating the greenhouse effect in solar chimney power plants using a two-band radiation model

Gholamalizadeh, Ehsan; Kim, Man-Hoe

doi:10.1016/j.renene.2013.10.011

Cited by 110 publications

(27 citation statements)

References 17 publications

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“…Lebbi et al [174] Analyzing an inclined roof-top solar chimney was an interesting work which was done by AlKayiem et al [175] by studying the effects of the collector dimensions and chimney height on the system. Gholamalizadeh and Kim [176] studied the greenhouse effect on the natural convection heat transfer characteristics in solar chimney. They used unsteady CFD model for analyzing SCPP.…”

Section: Analytical and Simulation Studiesmentioning

confidence: 99%

A review on solar chimney systems

Kasaeian

Molana

Rahmani

et al. 2017

Renewable and Sustainable Energy Reviews

143

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The increased utilization of solar energy has gained the attention of researchers to develop the solar chimney (SC) technology in recent years. Many studies have been conducted in this aear both experimentally and theoretically, whereas experimental studies are mainly focused on small-scale systems. This work provides a comprehensive and updated review that include most of the experimental studies, analytical and simulation works, the solar chimney applications, hybrid systems and geographical case studies based on extended references, citation of the updated works and the specified way of looking at different sections. The technological gaps in differnet sections are identified and a summary of suggestions is given for the future work, including more experimental works on the large-scale systems, and CFD analyses for optimization between the geometrical parameters and the output power. More studies on new applications of solar chimney technology including hybrid systems are also recommended.

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Section: Analytical and Simulation Studiesmentioning

confidence: 99%

A review on solar chimney systems

Kasaeian

Molana

Rahmani

et al. 2017

Renewable and Sustainable Energy Reviews

143

View full text Add to dashboard Cite

show abstract

“…Most of the preliminary simulations were carried out in an axisymmetric system by imposing some non-physical boundary conditions, such as a thin layer as a heat source to model the ground, heat fluxes, specific wall temperatures profiles, and a uniform heat source within the airflow [21][22][23][24]. Gholamalizadeh and Kim [25] developed a more accurate three-dimensional (3-D) model using CFD that predicts heat transfer inside of the solar collector by taking into account the greenhouse effect using discrete ordinates for radiation and a solar load model. A 3-D CFD approach was also carried out by Guo et al [23] which predicted the maximum value of the turbine pressure drop at a certain solar irradiance.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of CFD Models of a Real Wind Turbine in Solar Chimney Power Plants

Gholamalizadeh

Chung

2017

Energies

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A solar chimney power plant consists of four main parts, a solar collector, a chimney, an energy storage layer, and a wind turbine. So far, several investigations on the performance of the solar chimney power plant have been conducted. Among them, different approaches have been applied to model the turbine inside the system. In particular, a real wind turbine coupled to the system was simulated using computational fluid dynamics (CFD) in three investigations.

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“…The increasing problems of greenhouse effect and ozone depletion have drawn people's great attentions during the past decades [2][3][4][5]. In the field of heating, ventilation, air conditioning, and refrigeration (HVAC and R) [6][7][8], scientists started to use 1,1,1,2,3,3,3-heptafluoropropane (R227ea) [9][10][11] as a substitute in order to replace other refrigerants that are harmful to the ozone (like R114, R12, and R12B1), because R227ea has a zero ozone depletion potential (ODP) [12].…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on Theoretical and Machine Learning Methods for Acquiring Compressed Liquid Densities of 1,1,1,2,3,3,3-Heptafluoropropane (R227ea) via Song and Mason Equation, Support Vector Machine, and Artificial Neural Networks

Tang

Wang

et al. 2016

Applied Sciences

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1,1,1,2,3,3,3-Heptafluoropropane (R227ea) is a good refrigerant that reduces greenhouse effects and ozone depletion. In practical applications, we usually have to know the compressed liquid densities at different temperatures and pressures. However, the measurement requires a series of complex apparatus and operations, wasting too much manpower and resources. To solve these problems, here, Song and Mason equation, support vector machine (SVM), and artificial neural networks (ANNs) were used to develop theoretical and machine learning models, respectively, in order to predict the compressed liquid densities of R227ea with only the inputs of temperatures and pressures. Results show that compared with the Song and Mason equation, appropriate machine learning models trained with precise experimental samples have better predicted results, with lower root mean square errors (RMSEs) (e.g., the RMSE of the SVM trained with data provided by Fedele et al.[1] is 0.11, while the RMSE of the Song and Mason equation is 196.26). Compared to advanced conventional measurements, knowledge-based machine learning models are proved to be more time-saving and user-friendly.

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Three-dimensional CFD analysis for simulating the greenhouse effect in solar chimney power plants using a two-band radiation model

Cited by 110 publications

References 17 publications

A review on solar chimney systems

A review on solar chimney systems

A Comparative Study of CFD Models of a Real Wind Turbine in Solar Chimney Power Plants

Comparative Study on Theoretical and Machine Learning Methods for Acquiring Compressed Liquid Densities of 1,1,1,2,3,3,3-Heptafluoropropane (R227ea) via Song and Mason Equation, Support Vector Machine, and Artificial Neural Networks

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