MHD natural convection and entropy generation of non-Newtonian ferrofluid in a wavy enclosure

Heat transfer and entropy generation analysis of three-dimensional nanofluids flow in a cylindrical annulus filled with porous media

Employing a new micro-spray model and (MWCNTs - SWCNTs) - H2O nanofluid on Si-IGBT power module for energy storage: A numerical simulation

Nanostructured magnetic suspensions have superior thermophysical properties, which have attracted widespread attention owing to their industrial applications for heat transfer enhancement and thermal management. However, experimental measurements of the thermophysical properties of magnetic-based nanofluids, especially under an external magnetic field, are significantly complicated, expensive, and time consuming. Currently, the method of predicting and summarizing material properties through machine learning has accelerated the development of materials and practical industrial applications. This study aims to predict the thermophysical properties of magnetic nanofluids by establishing an artificial neural network (ANN) using experimental data on viscosity, thermal conductivity, and specific heat. The results based on the ANN model agree with the experimental results according to the different evaluation criteria. Different previous theoretical thermophysical models are reviewed, and the ANN model is proven to be more accurate by comparing the values of the ANN model and previous thermophysical models, which can also provide a theoretical basis for explaining the heat transfer of magnetic nanofluids. In the present study, a neural network model was developed for predicting the thermophysical properties of magnetic nanofluids and using material informatics to study functional materials.

Thermo-physical properties prediction of carbon-based magnetic nanofluids based on an artificial neural network

The primary objective of the present paper is to examine the combined effect of a uniform magnetic field and nanoparticle volume fraction on the melting process of copper-water (ice) as Nano-enhanced Phase Change Material (NePCM). The NePCM is enclosed in a rectangular cavity subjected to a fluctuating temperature at the hot wall. The phase change process is formulated and solved using the Lattice Boltzmann Method. The numerical outcomes of the developed code are validated by comparing them with available experimental and numerical results in the literature. For the melting process of NePCM, the considered parameters include Hartmann number (Ha=0, 30, 60 and 90), nanoparticle volume fraction (ϕ=0, 2, 4 and 6 vol%), and Rayleigh number (Ra=103, 104 and 105). The results showed that the melting time is considerably extended at high Ra as the Ha is increased. Furthermore, addition of nanoparticles notably contributes to the shortening of melting time at low Ra, while they have an adverse effect and extends the melting time up to 7% at high Ra in the existence of magnetic field (MF). However, they decrease melting time up to 10% at Ra=105 when the MF is not applied (Ha=0). It is also noted that the influences of examined parameters become prominent for Fo>0.5. These results may help understanding the control of melting process of electrically-conducting materials, specifically the nano-enhanced energy storage materials.

Effect of Magnetic Field and Nanoparticle Concentration on Melting of Cu-Ice in a Rectangular Cavity under Fluctuating Temperatures

Effect of heat generation and heat absorption on natural convection of Cu-water nanofluid in a wavy enclosure under magnetic field

خصص هذا البحث لدراسة معامل انتقال الحرارة لجريان خليط ذو ثلاثة اطوار خلال وسط مسامي طوله 20 سم، وكانت المادة المستعملة كحشوة ((chrome-steel وبثلاثة اقطار (2, 6, 10) ملم خلال انبوب شفاف عمودي ذو قطر 175و3 سم وطوله الكلي 2 م تم استخدام زيت والماء والهواء كموائع تشغيل. تم استنتاج ان قيمة معامل انتقال الحرارة لحالة 2 ملم هي اعلى قيمة مقارنة مع 6,10 ملم بسبب قيمة معامل التوصيل العالية لقطر 2 ملم. كما ايضا تم ملاحظة العلاقة العكسية بين معامل انتقال الحرارة واقطار الكريات. وايضا تم ملاحظة تأثير وجود الوسط المسامي على معامل انتقال وتناقصه في هذه المنطقة بسبب الاخماد الكبير لسرعة في هذه المنطقة. الحل العددي تم باستخدام برنامج الانسزز فلونت وموديل VOF لثلاث اقطار. واخير تم اجراء مقارنه ما توصل اليه مع باحثين اخرين وكانت نسبة (04و17 %).

Esam M. Abed

Papers

Effect of heat generation and heat absorption on natural convection of Cu-water nanofluid in a wavy enclosure under magnetic field

Effect of Changing Particle Diameters in Porous Media on Heat Transfer Coefficient for Three-Phase Flow in Vertical Pipe.