Publication:
Nanofluid heat transfer and machine learning: Insightful review of machine learning for nanofluid heat transfer enhancement in porous media and heat exchangers as sustainable and renewable energy solutions

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dc.citedby2
dc.contributor.authorRiyadi T.W.B.en_US
dc.contributor.authorHerawan S.G.en_US
dc.contributor.authorTirta A.en_US
dc.contributor.authorEe Y.J.en_US
dc.contributor.authorHananto A.L.en_US
dc.contributor.authorParistiawan P.A.en_US
dc.contributor.authorYusuf A.A.en_US
dc.contributor.authorVenu H.en_US
dc.contributor.authorIriantoen_US
dc.contributor.authorVeza I.en_US
dc.contributor.authorid55930344300en_US
dc.contributor.authorid17434542800en_US
dc.contributor.authorid36723162300en_US
dc.contributor.authorid57216252884en_US
dc.contributor.authorid57444363400en_US
dc.contributor.authorid57232788700en_US
dc.contributor.authorid57204941899en_US
dc.contributor.authorid57189525542en_US
dc.contributor.authorid58947149800en_US
dc.contributor.authorid57205548894en_US
dc.date.accessioned2025-03-03T07:41:23Z
dc.date.available2025-03-03T07:41:23Z
dc.date.issued2024
dc.description.abstractNanofluid, coupled with machine learning, is at the forefront of cutting-edge research in sustainable and renewable energy sector. This review paper examines the latest developments in the intersection of nanofluid and machine learning for heat transfer enhancement. This hybrid nanofluid-machine learning review investigates nanofluid heat transfer enhancement leveraged by machine learning both in porous media as well as heat exchangers. Several studies in porous media nanofluid transport utilize advanced methodologies that integrate machine learning and computational techniques. Machine learning and computational methods are employed to tackle complex thermodynamics, transport processes, and heat transfer challenges in complex multiphysics systems. An interesting hybrid nanofluid-machine learning application involves applying a machine learning method such as Support Vector Machine (SVM) to forecast movement of hybrid nanofluid flows across porous surfaces. Such hybrid nanofluid-machine learning technique involves utilising training data obtained from computational fluid dynamics (CFD) to decrease computational time and expenses. Machine learning offers a more efficient and cost-effective modelling for nanofluid heat transfer enhancement. Techniques such as scanning electron microscopy (SEM) along with X-ray diffraction (XRD) are also often used for assessing the forms as well as nanocomposites configurations in heat exchangers while studying nanofluids. The importance of machine learning models, especially artificial neural networks (ANNs) and genetic algorithms, is evident in their ability to predict and optimize thermal performance of nanofluid application for nanofluid heat transfer enhancement. Furthermore, integrating nanofluids into various heat exchanger designs has demonstrated significant enhancements in efficiency, decreased energy usage, and total cost reduction. These achievements align with the research goal in sustainable and renewable energy, highlighting the critical role of nanofluid-enhanced heat exchange systems in tackling current difficulties related to energy efficiency and sustainability. Overall, combining nanofluids with machine learning shows promising advancements, providing a route toward creating more efficient and eco-friendly heat exchange systems. ? 2024 The Authorsen_US
dc.description.natureFinalen_US
dc.identifier.ArtNo103002
dc.identifier.doi10.1016/j.rineng.2024.103002
dc.identifier.scopus2-s2.0-85205355348
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85205355348&doi=10.1016%2fj.rineng.2024.103002&partnerID=40&md5=18b18b4946b9f0378c67f358f6602605
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36101
dc.identifier.volume24
dc.publisherElsevier B.V.en_US
dc.relation.ispartofAll Open Access; Gold Open Access
dc.sourceScopus
dc.sourcetitleResults in Engineering
dc.subjectNanofluidics
dc.subjectTransfer learning
dc.subjectHeat Transfer enhancement
dc.subjectHeat-transfer characteristics
dc.subjectHybrid nanofluid
dc.subjectHybrid nanofluid heat transfer enhancement
dc.subjectHybrid nanofluid-machine learning heat transfer
dc.subjectMachine learning for sustainable and renewable energy
dc.subjectMachine-learning
dc.subjectNanofluid heat transfer characteristic and enhancement
dc.subjectNanofluid heat transfer numerical study
dc.subjectNanofluid-machine learning heat transfer enhancement
dc.subjectNanofluids
dc.subjectRenewable energies
dc.subjectSustainable energy
dc.subjectSupport vector machines
dc.titleNanofluid heat transfer and machine learning: Insightful review of machine learning for nanofluid heat transfer enhancement in porous media and heat exchangers as sustainable and renewable energy solutionsen_US
dc.typeReviewen_US
dspace.entity.typePublication
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