A model for predicting the effects of buoyancy driven convection on solidification of binary alloy with nanoparticles

Jegatheesan, M.; Bhattacharya, Anirban

doi:10.1016/j.ijheatmasstransfer.2021.121916

Cited by 6 publications

(5 citation statements)

References 65 publications

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“…3D dendrites grow faster than 2D, while secondary arms are more likely to form. Jegatheesan et al [158] studied the effects of distributing nanoparticles in a buoyancy driven convection solidification by using an enthalpy-based method. When considering methods for convection, a reduction in volume from solidification (shrinkage driven flow) was not considered as it was studied only in 2D.…”

Section: Features and Applicationsmentioning

confidence: 99%

“…In their proposed method, the cellular automaton method, enriched with a grain nucleation scheme, was used to predict columnar, equiaxed, and mixed grains, while the FV method was used to solve heat transfer and thermocapillary flow. L-PBF is the most popular process for manufacturing functional parts for different applications [138,[157][158][159]. The simulation of L-PBF requires considering localized L-PBF is the most popular process for manufacturing functional parts for different applications [138,[157][158][159].…”

Section: Additive Manufacturing Applicationsmentioning

confidence: 99%

“…L-PBF is the most popular process for manufacturing functional parts for different applications [138,[157][158][159]. The simulation of L-PBF requires considering localized L-PBF is the most popular process for manufacturing functional parts for different applications [138,[157][158][159]. The simulation of L-PBF requires considering localized phenomena that are highly transient, making the simulation very complex.…”

Section: Additive Manufacturing Applicationsmentioning

confidence: 99%

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A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

Cusato,

Nabavizadeh,

Eshraghi

2023

Metals

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During the past two decades, researchers have shown interest in large-scale simulations to analyze alloy solidification. Advances in in situ X-ray observations of the microstructural evolution of dendrites have shown defects that can be very costly for manufacturers. These simulations provide the basis for understanding applied meso-/macro-scale phenomena with microscale details using various numerical schemes to simulate the morphology and solve for transport phenomena. Methods for simulating methodologies include cellular automaton, phase field, direct interface tracking, level set, dendritic needle networks, and Monte Carlo while finite element, finite difference, finite volume, and lattice Boltzmann methods are commonly used to solve for transport phenomena. In this paper, these methodologies are explored in detail with respect to simulating the dendritic microstructure evolution and other solidification-related features. The current research, from innovations in algorithms for scaling to parallel processing details, is presented with a focus on understanding complex real-world phenomena. Topics include large-scale simulations of features with and without convection, columnar to equiaxed transition, dendrite interactions, competitive growth, microsegregation, permeability, and applications such as additive manufacturing. This review provides the framework and methodologies for achieving scalability while highlighting the areas of focus that need more attention.

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Section: Features and Applicationsmentioning

confidence: 99%

Section: Additive Manufacturing Applicationsmentioning

confidence: 99%

Section: Additive Manufacturing Applicationsmentioning

confidence: 99%

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A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

Cusato,

Nabavizadeh,

Eshraghi

2023

Metals

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“…21,22 Conventional viscoelastic models have been built on the combinations of spring and damper (dashpot) elements, including the Maxwell, Kelvin-Voigt, generalized Maxwell, Zener, Burgers, and fractional calculus-based models. 23,24 However, a material has to behave exactly as defined in a specific model to allow numerical fitting against experiments. 25 Only for very idealized materials, can t be defined theoretically through other properties.…”

Section: Introductionmentioning

confidence: 99%

Modeling the viscoelastic relaxation dynamics of soft particles via molecular dynamics simulation-informed multi-dimensional transition-state theory

et al. 2023

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“…El Hasadi and Khodadadi used the one fluid mixture model to investigate the freezing process of the NePCM [20][21][22][23], and El Hasadi for melting of NePCM [24]. There are a few other investigations that used a similar model developed by El Hasadi and Khodadadi [18] to model the freezing process of the NePCM [25][26][27] they showed the extreme importance of the redistribution of the particles in the overall performance of the NePCM.…”

Section: Introductionmentioning

confidence: 99%

A Computational Study of Particle Mass Transport during Melting of NePCM in a Square Cavity with a Single Adiabatic Side

Hasadi¹

2023

Coatings

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Nanostructured phase change materials (NePCM) are phase change materials that contain different types and sizes of colloidal I removed the word sizes particles. Many investigations in the literature assess those type of phase change materials to investigate their thermal performance. However, there is a discrepancy between the experimental observations and numerical results of the melting process of the NePCM because most numerical models do not count for the mass transfer of the particles. In the current work, we will investigate the melting process of NePCM that consists of copper nanoparticles suspended in water for the geometry of a square cavity, heated from the two sides, cooled from one side, and the remaining side is thermally insulated. Our numerical model will account for the mass transfer of the particles using a one-fluid mixture and the enthalpy porosity model for accounting for the phase change process. We found that adding the particles will lead to the deceleration of the melting process, as described by the experiments, because of the reduction of the convection intensity. We found that for NePCM suspension containing 10% of nanoparticles by mass, the deceleration of melting will be about 2.2% compared to pure water. Most of the particles are convected away by the flow cells toward the bottom side of the cavity, especially near the isolated right side of the cavity. Our findings indicate that incorporating mass transport of particles leads to a significantly improved prediction of the melting behavior of the NePCM.

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A model for predicting the effects of buoyancy driven convection on solidification of binary alloy with nanoparticles

Cited by 6 publications

References 65 publications

A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

Modeling the viscoelastic relaxation dynamics of soft particles via molecular dynamics simulation-informed multi-dimensional transition-state theory

A Computational Study of Particle Mass Transport during Melting of NePCM in a Square Cavity with a Single Adiabatic Side

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