Presentation of new thermal conductivity expression for 
                
                  
                
                $$\hbox {Al}_2\hbox {O}_3$$
                
                  
                    
                      
                        Al
                        2
                      
                      
                        O
                        3
                      
                    
                  
                
              –water and

Motlagh, Saber Yekani; Sharifi, Abbas; Ahmadi, Mohsen; Badfar, Homayoun

doi:10.1007/s10973-018-7305-9

Cited by 19 publications

(2 citation statements)

References 30 publications

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“…Mirsaeidi and Yousef [120] used ANN to predict the thermal conductivity, density and viscosity of carbon quantum dots nanofluids using water, ethylene glycol and EG-water (60:40) as base fluids. Motlagh et al [121] used gene expression programming to propose a correlation that estimates the thermal conductivity of Al 2 O 3 and CuO-water-based nanofluid based on experimental data from the literature. Going forward, it is expected that there will be an increase in research and development exploring the possible advantages of using ternary hybrid nanofluids.…”

mentioning

confidence: 99%

An updated review of nanofluids in various heat transfer devices

Okonkwo

Wole‐Osho

Almanassra

et al. 2020

J Therm Anal Calorim

257

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The field of nanofluids has received interesting attention since the concept of dispersing nanoscaled particles into a fluid was first introduced in the later part of the twentieth century. This is evident from the increased number of studies related to nanofluids published annually. The increasing attention on nanofluids is primarily due to their enhanced thermophysical properties and their ability to be incorporated into a wide range of thermal applications ranging from enhancing the effectiveness of heat exchangers used in industries to solar energy harvesting for renewable energy production. Owing to the increasing number of studies relating to nanofluids, there is a need for a holistic review of the progress and steps taken in 2019 concerning their application in heat transfer devices. This review takes a retrospective look at the year 2019 by reviewing the progress made in the area of nanofluids preparation and the applications of nanofluids in various heat transfer devices such as solar collectors, heat exchangers, refrigeration systems, radiators, thermal storage systems and electronic cooling. This review aims to update readers on recent progress while also highlighting the challenges and future of nanofluids as the next-generation heat transfer fluids. Finally, a conclusion on the merits and demerits of nanofluids is presented along with recommendations for future studies that would mobilise the rapid commercialisation of nanofluids.

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mentioning

confidence: 99%

An updated review of nanofluids in various heat transfer devices

Okonkwo

Wole‐Osho

Almanassra

et al. 2020

J Therm Anal Calorim

257

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“…The primary distinction between the GP and GEP is in the individuals' encoding method. GEP's capability has been successfully demonstrated in dealing with a variety of engineering problems (Ferreira, 2006a;Gandomi et al, 2011;Gharagheizi et al, 2012;Maghbooli et al, 2015;Mart ı et al, 2013;Mattar and Alamoud, 2017;Mehdizadeh et al, 2019;Xu et al, 2009;Yekani Motlagh et al, 2019).…”

Section: Gene Expression Programming (Gep)mentioning

confidence: 99%

Gene expression programming (GEP) as novel tool for thermal analysis and kinetic modeling of pyrolysis reactions: coal pyrolysis case study

Najafi,

Golrokh Sani,

Sobati

2024

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PurposeIn this study, a different approach is introduced to generate the kinetic sub-model for the modeling of solid-state pyrolysis reactions based on the thermogravimetric (TG) experimental data over a specified range of heating rates. Gene Expression Programming (GEP) is used to produce a correlation for the single-step global reaction rate as a function of determining kinetic variables, namely conversion, temperature, and heating rate.Design/methodology/approachFor a case study on the coal pyrolysis, a coefficient of determination (R2) of 0.99 was obtained using the generated model according to the experimental benchmark data. Comparison of the model results with the experimental data proves the applicability, reliability, and convenience of GEP as a powerful tool for modeling purposes in the solid-state pyrolysis reactions.FindingsThe resulting kinetic sub-model takes advantage of particular characteristics, to be highly efficient, simple, accurate, and computationally attractive, which facilitates the CFD simulation of real pyrolizers under isothermal and non-isothermal conditions.Originality/valueIt should be emphasized that the above-mentioned manuscript is not under evaluation in any journals and submitted exclusively for consideration for possible publication in this journal. The generated kinetic model is in the final form of an algebraic correlation which, in comparison to the conventional kinetic models, suggests several advantages: to be relatively simpler, more accurate, and numerically efficient. These characteristics make the proposed model computationally attractive when used as a sub-model in CFD applications to simulate real pyrolizers under complex heating conditions.

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