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Mahian, Omid; Kolsi, Lioua; Amani, Mohammad; Estellé, Patrice; Ahmadi, Goodarz; Kleinstreuer, Clement; Marshall, Jeffrey S.; Taylor, Robert A.; Abu-Nada, Eiyad; Rashidi, Saman; Niazmand, Hamid; Wongwises, Somchai; Hayat, Tasawar; Kasaeian, Alibakhsh; Pop, Ioan
Physics reports, 02/2019, Volume: 791Journal Article
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.
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