A soft computing approach for estimating the specific heat capacity of molten salt-based nanofluids

Hassan, Muhammed A.; Banerjee, Debjyoti

doi:10.1016/j.molliq.2019.02.106

Cited by 52 publications

(17 citation statements)

References 41 publications

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“…An important point to note is that the particle concentration and particle size with the most specific heat enhancements were 1% and 20 nm, respectively. [155]. The study aimed to predict the specific heat capacity of metal oxide molten nitrate salt nanofluids using a multilayer perceptron neural network (MLP-ANN).…”

Section: Specific Heat Of Nanofluidsmentioning

confidence: 99%

“…The study aimed to predict the specific heat capacity of metal oxide molten nitrate salt nanofluids using a multilayer perceptron neural network (MLP-ANN). The ANN model proposed was more accurate when compared to classical prediction methods [155]. Alade et al [156] also considered a machine learning approach by applying a support vector regression model optimised with a Bayesian algorithm to predict the specific heat capacity of Al 2 O 3 ethylene glycol nanofluids.…”

Section: Specific Heat Of Nanofluidsmentioning

confidence: 99%

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An updated review of nanofluids in various heat transfer devices

Okonkwo

Wole‐Osho

Almanassra

et al. 2020

J Therm Anal Calorim

239

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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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Section: Specific Heat Of Nanofluidsmentioning

confidence: 99%

Section: Specific Heat Of Nanofluidsmentioning

confidence: 99%

An updated review of nanofluids in various heat transfer devices

Okonkwo

Wole‐Osho

Almanassra

et al. 2020

J Therm Anal Calorim

239

View full text Add to dashboard Cite

show abstract

“…The results of the BSVR model proposed showed little deviation compared to the experimental results. Applying backpropagation multilayered perceptron (MLP) artificial neural network, Hassan and Banerjee [83], excellently predicted the specific heat of molten salt nanofluid. While the exact model for accurate specific heat prediction is yet to be obtained, some outlines can be drawn from available experimental data.…”

Section: Nanofluid Specific Heat Capacity (C P )mentioning

confidence: 99%

Nanofluids in Solar Thermal Collectors: Review and Limitations

et al. 2020

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Solar thermal collectors are systems that allow for the use of solar energy in thermal applications. These collectors utilize a heat transfer fluid to transport absorbed solar radiation to applications where they are needed. Scientists in a bid to improve the conversion efficiency of solar collectors have suggested different collector designs and improved collector materials. Over the last 25 years, the study of nanofluids and their applications have revolutionized material science, and nanotechnology has found applications in improving solar collector materials. This article reviews the impact of different nanomaterials on the efficiency of solar collectors. The study also outlines the limitations of applying nanofluids and discusses the long-term challenges of their application to solar collectors. Nanofluids have the potential to improve the overall efficiency of most solar collectors, however, the full potential of nanofluids in heat transfer applications cannot be completely achieved until some of the questions regarding hysteresis, stability, and the overall predictability of nanofluids are answered.

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“…During the cross-validation process, the number of folds was varied from 1 to 5, and the closest fold to the mean was taken as the final fold [36,37]. The training is based on the backpropagation technique to set the optimum weights of the feed-forward neural network [38,39]. Deciding the ANN topology is another critical step to avoid over and underfitting the data.…”

Section: Mrr= Vcmentioning

confidence: 99%

Towards an Adaptive Design of Quality, Productivity and Economic Aspects When Machining AISI 4340 Steel With Wiper Inserts

et al. 2020

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The continuous pursue of sustainable manufacturing is motivating the utilization of new advanced technology, especially for hard to cut materials. In this study, an adaptive approach for optimization of machining process of AISI 4340 using wiper inserts is proposed. This approach is based on advance yet intuitive modeling and optimization techniques. The approach is based on Artificial Neural Network (ANN), Multi-Objective Genetic Algorithm (MOGA), as well as Linear Programming Techniques for Multidimensional Analysis of Preference (LINMAP), for modeling, optimization and multicriteria decision making respectively. This integrated approach, to best of the authors' knowledge, has been deployed for the first time to adaptively serve different designs of manufacturing processes. Such designs have different orientations, namely cost, quality, productivity, and balanced orientation. The capability of the proposed approach to serving such diverse requirements answers one of the most accelerating demands in the manufacturing community due to the dynamics of the uprising smart production lines. Besides, the proposed approach is presented in a straightforward manner that can be extended easily to other design orientations as well as other engineering applications. Based on the proposed design, a balanced general setting of 197.4 m/min, 0.95 mm, and 0.168 mm/rev was recommended along with other settings for more sophisticated requirements. Confirmatory experiments showed a good agreement (i.e., no more than 7% deviation) with the predicted optimum responses. This shows the validity of the proposed approach as a viable tool for designers to promote holistic and sustainable process design. INDEX TERMS Adaptive design, Artificial neural networks, Genetic Algorithm, Modeling, Wiper inserts, Turning, NOMENCLATURE ANN Artificial Neural Network B Balanced design DOC Depth of Cut EC Intensive cost-oriented design EP Intensive productivity-oriented design EQ Intensive quality-oriented design f Feed GRA Gray Relation Analysis IC Intensive cost-oriented design IP Intensive productivity-oriented design IQ Intensive quality-oriented design LINMAP

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A soft computing approach for estimating the specific heat capacity of molten salt-based nanofluids

Cited by 52 publications

References 41 publications

An updated review of nanofluids in various heat transfer devices

An updated review of nanofluids in various heat transfer devices

Nanofluids in Solar Thermal Collectors: Review and Limitations

Towards an Adaptive Design of Quality, Productivity and Economic Aspects When Machining AISI 4340 Steel With Wiper Inserts

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