Author
Muneer A. Ismael
Bio: Muneer A. Ismael is an academic researcher from University of Basrah. The author has contributed to research in topics: Nusselt number & Nanofluid. The author has an hindex of 25, co-authored 56 publications receiving 1949 citations.
Papers
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TL;DR: In this article, the authors studied the conjugate natural convection-conduction heat transfer in a square domain composed of nanofluids filled porous cavity heated by a triangular solid wall under steady-state conditions.
Abstract: The conjugate natural convection–conduction heat transfer in a square domain composed of nanofluids filled porous cavity heated by a triangular solid wall is studied under steady-state conditions. The vertical and horizontal walls of the triangular solid wall are kept isothermal and at the same hot temperature Th. The other boundaries surrounding the porous cavity are kept adiabatic except the right vertical wall where it is kept isothermally at the lower temperature Tc. Equations governing the heat transfer in the triangular wall and heat and nanofluid flow, based on the Darcy model, in the nanofluid-saturated porous medium together with the derived relation of the interface temperature are solved numerically using the over-successive relaxation finite-difference method. A temperature independent nanofluids properties model is adopted. Three nanoparticle types dispersed in one base fluid (water) are investigated. The investigated parameters are the nanoparticles volume fraction φ (0–0.2), Rayleigh number Ra (10–1000), solid wall to base-fluid saturated porous medium thermal conductivity ratio Kro (0.44, 1, 23.8), and the triangular wall thickness D (0.1–1). The results are presented in the conventional form; contours of streamlines and isotherms and the local and average Nusselt numbers. At a very low Rayleigh number Ra = 10, a significant enhancement in heat transfer within the porous cavity with φ is observed. Otherwise, the heat transfer may be enhanced or deteriorated with φ depending on the wall thickness D and the Rayleigh number Ra. At high Rayleigh numbers and low conductivity ratios, critical values of D, regardless of φ, are observed and accounted.
168 citations
TL;DR: In this article, a differentially heated and vertically partially layered porous cavity filled with a nanofluid is studied numerically based on double-domain formulation, and the conservation of mass, momentum, and energy with the entity of nanoparticles in the fluid filling the cavity and that are saturated in the porous layer are modeled and solved numerically using under successive relaxation upwind finite difference scheme.
Abstract: Natural convection heat transfer in a differentially heated and vertically partially layered porous cavity filled with a nanofluid is studied numerically based on double–domain formulation. The left wall, which is adjacent to the porous layer, is isothermally heated, while the right wall is isothermally cooled. The top and bottom walls of the cavity are thermally insulated. Impermeable cavity walls are considered except the interface between the porous layer and the nanofluid layer. The Darcy–Brinkman model is invoked for the porous layer which is saturated with the same nanofluid. Equations govern the conservation of mass, momentum, and energy with the entity of nanoparticles in the fluid filling the cavity and that are saturated in the porous layer are modeled and solved numerically using under successive relaxation upwind finite difference scheme. The contribution of five parameters are studied, these are; nanoparticle volume fraction ϕ (0–0.1), porous layer thickness Xp(0–0.9), Darcy number Da (10−7–1...
144 citations
TL;DR: In this paper, the authors investigated the entropy generation due to conjugate natural convection-conduction heat transfer in a square domain under steady-state condition, and the results showed that both the average Nusselt number and entropy generation are increasing functions of K ro while they are maxima at some critical values of D.
Abstract: Entropy generation due to conjugate natural convection–conduction heat transfer in a square domain is numerically investigated under steady-state condition. The domain composed of porous cavity heated by a triangular solid wall and saturated with a CuO–water nanofluid. Equations governing the heat transfer in the triangular solid together with the heat and nanofluid flow in the nanofluid-saturated porous medium are solved numerically using the over-successive relaxation finite-difference method. A temperature dependent thermal conductivity and modified expression for the thermal expansion of nanofluid are adopted. A new criterion for assessment of the thermal performance is proposed. The investigated parameters are the nanoparticles volume fraction φ (0–0.05), modified Rayleigh number Ra (10–1000), solid wall to base-fluid saturated porous medium thermal conductivity ratio K ro (0.44, 1, 23.8), and the triangular solid thickness D (0.1–1). The results show that both the average Nusselt number and the entropy generation are increasing functions of K ro , while they are maxima at some critical values of D . It is also found that the addition of nanoparticles increases the entropy generation. According to the new proposed criterion, the results show that the largest solid thickness ( D = 1.0) and the lower wall thermal conductivity ratio manifest better thermal performance.
142 citations
135 citations
TL;DR: In this article, a lid-driven laminar mixed convection inside a cavity filled with water is studied numerically, and the results have showed that there are critical values for the partial slip parameter at which the convection is declined.
Abstract: Steady laminar mixed convection inside a lid-driven square cavity filled with water is studied numerically. The lid is due to the movement of the isothermal top and bottom walls which are maintained at T c and T h , respectively, with T h is higher than T c . A partial slip condition was imposed in these two moving walls. The vertical walls of the cavity are kept adiabatic. The appliance of the numerical analysis was USR finite difference method with upwind scheme treatments of the convective terms included in the momentum and energy equations. The studied relevant parameters were: the partial slip parameter S (0–∞); Richardson number Ri (0.01–100) and the direction of the moving walls ( λ t = 1, λ b = ±1). The results have showed that there are critical values for the partial slip parameter at which the convection is declined.
129 citations
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TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.
Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …
33,785 citations
01 Jan 1997
TL;DR: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems and discusses the main points in the application to electromagnetic design, including formulation and implementation.
Abstract: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.
1,820 citations
28 Jan 2005
TL;DR: The Q12-40 density: ρ ((kg/m) specific heat: Cp (J/kg ·K) dynamic viscosity: ν ≡ μ/ρ (m/s) thermal conductivity: k, (W/m ·K), thermal diffusivity: α, ≡ k/(ρ · Cp) (m /s) Prandtl number: Pr, ≡ ν/α (−−) volumetric compressibility: β, (1/K).
Abstract: Geometry: shape, size, aspect ratio and orientation Flow Type: forced, natural, laminar, turbulent, internal, external Boundary: isothermal (Tw = constant) or isoflux (q̇w = constant) Fluid Type: viscous oil, water, gases or liquid metals Properties: all properties determined at film temperature Tf = (Tw + T∞)/2 Note: ρ and ν ∝ 1/Patm ⇒ see Q12-40 density: ρ ((kg/m) specific heat: Cp (J/kg ·K) dynamic viscosity: μ, (N · s/m) kinematic viscosity: ν ≡ μ/ρ (m/s) thermal conductivity: k, (W/m ·K) thermal diffusivity: α, ≡ k/(ρ · Cp) (m/s) Prandtl number: Pr, ≡ ν/α (−−) volumetric compressibility: β, (1/K)
636 citations
Xi'an Jiaotong University1, Ferdowsi University of Mashhad2, King Mongkut's University of Technology Thonburi3, University of Monastir4, Shahid Beheshti University5, University of Rennes6, Clarkson University7, North Carolina State University8, University of Vermont9, University of New South Wales10, Khalifa University11, Royal Society12, King Abdulaziz University13, Quaid-i-Azam University14, University of Tehran15, Babeș-Bolyai University16
TL;DR: In this paper, the authors present a review of the main computational methods for solving the transport equations associated with nanofluid flow, including finite difference, finite volume, finite element, lattice Boltzmann methods, and Lagrangian methods.
Abstract: Modeling and simulation of nanofluid flows is crucial for applications ranging from the cooling of electronic devices to solar water heating systems, particularly when compared to the high expense of experimental studies. Accurate simulation of a thermal-fluid system requires a deep understanding of the underlying physical phenomena occurring in the system. In the case of a complex nanofluid-based system, suitable simplifying approximations must be chosen to strike a balance between the nano-scale and macro-scale phenomena. Based on these choices, the computational approach – or set of approaches – to solve the mathematical model can be identified, implemented and validated. In Part I of this review (Mahian et al., 2019), we presented the details of various approaches that are used for modeling nanofluid flows, which can be classified into single-phase and two-phase approaches. Now, in Part II, the main computational methods for solving the transport equations associated with nanofluid flow are briefly summarized, including the finite difference, finite volume, finite element, lattice Boltzmann methods, and Lagrangian methods (such as dissipative particle dynamics and molecular dynamics). Next, the latest studies on 3D simulation of nanofluid flow in various regimes and configurations are reviewed. The numerical studies in the literature mostly focus on various forms of heat exchangers, such as solar collectors (flat plate and parabolic solar collectors), microchannels, car radiators, and blast furnace stave coolers along with a few other important nanofluid flow applications. Attention is given to the difference between 2D and 3D simulations, the effect of using different computational approaches on the flow and thermal performance predictions, and the influence of the selected physical model on the computational results. Finally, the knowledge gaps in this field are discussed in detail, along with some suggestions for the next steps in this field. The present review, prepared in two parts, is intended to be a comprehensive reference for researchers and practitioners interested in nanofluids and in the many applications of nanofluid flows.
433 citations