Single and Hybrid Nanofluids to Enhance Performance of Flat Plate Solar Collectors: Application and Obstacles

Al-Yasiri, Qudama; Szabó, Márta; Arıcı, Müslüm

doi:10.3311/ppme.17312

Cited by 15 publications

(3 citation statements)

References 104 publications

(112 reference statements)

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“…Nevertheless, several limitations are reported, such as long-term degradation and optimal nano concentration to fulfil the desired properties, homogeneity issues/concerns, and cost consideration [99]. Preparation of PPCM-NPs is usually done using the same methods used to prepare nanofluids, such as sonication, magnetic stirrer, and so on [100,101]. However, stable PPCM-NPs is still one of the most challenging tasks, even in recent literature studies [102].…”

Section: Enhancement Techniques For Ppcm Poor Thermal Conductivitymentioning

confidence: 99%

Paraffin As a Phase Change Material to Improve Building Performance: An Overview of Applications and Thermal Conductivity Enhancement Techniques

Al-Yasiri

Szabó

2021

Renew. Energy Environ. Sustain.

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In recent years, phase change materials (PCMs) have increasingly received attention in different thermal energy storage and management fields. In the building sector, paraffin as a phase change material (PPCM) has been introduced as an efficient PCM incorporated in a building envelope, which showed remarkable results. However, the poor thermal conductivity of PPCM is still the topmost drawback in experimental and numerical investigations. In this paper, a general assessment of paraffins, their common uses and applications, have been presented with a particular focus on their potential in building envelope applications. Moreover, the general and desired properties of PPCM are highlighted and evaluated. The primary practical limitation of PPCM of poor thermal conductivity and their effect on PPCM performance is presented and discussed. Correspondingly, the popular techniques applied to improve the poor thermal conductivity are presented and discussed in four categories: the dispersion of nanoparticles, expanded graphite, metallic foam, and extended surfaces technique (fins). All in all, the analysed research works indicated that PPCM based building envelope applications could remarkably improve the thermal performance of buildings in terms of thermal load reduction, energy-saving and thermal comfort. Furthermore, the adoption of enhancement techniques is essential to improve the thermal performance of PPCM in building applications for better utilisation. This review provides a clear vision for the newcomers and interested parties about the main application aspects of PPCM in the building sector for further investigations towards technology commercialisation.

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Section: Enhancement Techniques For Ppcm Poor Thermal Conductivitymentioning

confidence: 99%

Paraffin As a Phase Change Material to Improve Building Performance: An Overview of Applications and Thermal Conductivity Enhancement Techniques

Al-Yasiri

Szabó

2021

Renew. Energy Environ. Sustain.

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“…Con el nanofluido TiO ଶ /H ଶ O, el estudio realizado por Said, Z., la fracción de volumen de las nanopartículas fue de 0.1% y 0.3% respectivamente, mientras que los caudales másicos del nanofluido variaron de 0.5 a 1.5 kg/min, por lo que calculando un promedio de caudal másico de 1 kg/min, es lo mismo que ‫01ݔ99.3‬ ି ݉ ଷ ‫ݏ/‬ [10].…”

Section: Estado Del Arteunclassified

Evaluación de fluidos caloportadores no convencionales para aplicación solar térmica: Un estudio numérico en Panamá

Chen¹,

Arcia²,

Díaz³

et al. 2021

RIC

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En este estudio se llevó a cabo la investigación para determinar el potencial de los nanofluidos como fluidos caloportadores no convencionales en colectores solares en un país con tanto potencial térmico como Panamá. Luego de hacer la investigación preliminar sobre cuatro posibles fluidos caloportadores, encontramos que los nanofluidos de CuO, Al2O3, SiO2 y TiO2 con agua como fluido base poseen propiedades térmicas de gran interés. Después se realizó la simulación de un sistema de colector solar simple a través del software TRNSYS y se utilizaron las condiciones climáticas de Panamá. Se utilizó un intercambiador de calor de contraflujo para suministrar el agua caliente sanitaria a una residencia estándar de cuatro personas, donde cada una consume 50 litros diarios. Se logró comprobar que los nanofluidos son fluidos caloportadores más eficientes que el fluido convencional (agua), siendo el SiO2 el mejor nanofluido a la hora de escoger el intercambiador de calor que vaya a utilizarse, por lo que estos fluidos caloportadores no convencionales podrían ser posibles sustitutos para nuevos colectores en un futuro.

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“…To offset the negative impact of anthropogenic activities associated with the extraction and burning of fossil fuels, alternative energy sources need to be exploited [5][6][7][8][9][10]. Solar energy is one of the cleanest and cheapest sources of energy [11][12][13][14][15]. Solar energy is much more predictable than its rival, i.e., wind energy [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Machine learning prediction approach for dynamic performance modeling of an enhanced solar still desalination system

Sohani

Hoseinzadeh

Samiezadeh

et al. 2021

J Therm Anal Calorim

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An enhanced design for a solar still desalination system which has been proposed in the previously conducted study of the research team is considered here, and the experimental data obtained during a year are employed to develop ANN models for that. Different types of artificial neural network (ANN), as one of the most popular machine learning approaches, are developed and compared together to find the best of them to predict the hourly produced distillate and water temperature in the basin, which are two key performance criteria of the system. Feedforward (FF), backpropagation (BP), and radial basis function (RBF) types of ANN are examined. According to the results, by having the coefficients of determination of 0.963111 and 0.977057, FF and RBF types are the best ANN structures for estimation of the hourly water production and water temperature in the basin, respectively. In addition, the annual error analysis done for the data not used to develop ANN models demonstrates that the average error in prediction of the hourly distillate production and water temperature in the basin varies from 9.03 and 5.13% in January (the highest values) to 4.06 and 2.07% in July (the lowest values), respectively. Moreover, the error for prediction of the daily water production is in the range of 2.41 to 5.84% in the year.

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Single and Hybrid Nanofluids to Enhance Performance of Flat Plate Solar Collectors: Application and Obstacles

Cited by 15 publications

References 104 publications

Paraffin As a Phase Change Material to Improve Building Performance: An Overview of Applications and Thermal Conductivity Enhancement Techniques

Paraffin As a Phase Change Material to Improve Building Performance: An Overview of Applications and Thermal Conductivity Enhancement Techniques

Evaluación de fluidos caloportadores no convencionales para aplicación solar térmica: Un estudio numérico en Panamá

Machine learning prediction approach for dynamic performance modeling of an enhanced solar still desalination system

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