Three-dimensional simulation of microdroplet formation in a co-flowing immiscible fluid system using front tracking method

Shahin, Heidari; Mortazavi, Saeed

doi:10.1016/j.molliq.2017.08.082

Cited by 18 publications

(5 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3 and 4, we present convergence results for mDDM1-3 for case 1 (see also Tabs. [13][14][15][16][17][18] in Appendix B for other cases). Consistent with our analysis, we observe that mDDM1 and mDDM3 are approximately 2nd order accurate in the L 2 norm but approximately 1.5 order accurate in the L ∞ norm.…”

Section: Numerical Results For Mddm1-3mentioning

confidence: 99%

“…In this second approach, the complex domain is embedded into a larger, regular domain and the boundary conditions are approximated by a variety of different techniques. Examples include the adaptive fast multipole accelerated Poisson solver (e.g., [4]), which combines boundary and volume integral methods in the larger domain, fictitious domain methods (e.g., [5,6,7,8]) where Lagrange multipliers are applied in order to enforce the boundary conditions, immersed boundary (e.g., [9,10,11,12]), front-tracking (e.g., [13,14,15]) and arbitrary Lagrangian-Eulerian methods (e.g., [16,17,18,19]) utilize separate surface and volume meshes where force distributions are interpolated from the surface to the volume meshes, in a neighborhood of the domain boundary, to approximate the boundary conditions. In addition, a number of specialized methods have been designed to achieve better than first order accuracy in the L ∞ norm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Higher-order accurate diffuse-domain methods for partial differential equations with Dirichlet boundary conditions in complex, evolving geometries

Guo

Lowengrub

2020

Journal of Computational Physics

View full text Add to dashboard Cite

The diffuse-domain, or smoothed boundary, method is an attractive approach for solving partial differential equations in complex geometries because of its simplicity and flexibility. In this method the complex geometry is embedded into a larger, regular domain. The original PDE is reformulated using a smoothed characteristic function of the complex domain and source terms are introduced to approximate the boundary conditions. The reformulated equation, which is independent of the dimension and domain geometry, can be solved by standard numerical methods and the same solver can be used for any domain geometry. A challenge is making the method higher-order accurate. For Dirichlet boundary conditions, which we focus on here, current implementations demonstrate a wide range in their accuracy but generally the methods yield at best first order accuracy in , the parameter that characterizes the width of the region over which the characteristic function is smoothed. Typically, ∝ h, the grid size. Here, we analyze the diffuse-domain PDEs using matched asymptotic expansions and explain the observed behaviors. Our analysis also identifies simple modifications to the diffuse-domain PDEs that yield higher-order accuracy in , e.g., O( 2 ) in the L 2 norm and O( p ) with 1.5 ≤ p ≤ 2 in the L ∞ norm. Our analytic results are confirmed numerically in stationary and moving domains where the level set method is used to capture the dynamics of the domain boundary and to construct the smoothed characteristic function.

show abstract

Section: Numerical Results For Mddm1-3mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Higher-order accurate diffuse-domain methods for partial differential equations with Dirichlet boundary conditions in complex, evolving geometries

Guo

Lowengrub

2020

Journal of Computational Physics

View full text Add to dashboard Cite

show abstract

“…The formation regime of a droplet or bubble in microchannels has been widely investigated [55][56][57][58][59][60], and the formation patterns have been classified into three categories based on the droplet shape [14,53]. (1) The dripping-squeezing regime occurs at a low capillary number; the droplet breakup is mainly caused by pressure difference, and the breakup occurs at the T-junction corner.…”

Section: Formation Regime and Critical Capillary Numbermentioning

confidence: 99%

“…Liquid-liquid multicomponent flows in microchannels exist widely in many fields, including chemical synthesis, oil recovery [1][2][3][4][5], lab-on-chip microfluidic applications [6][7][8][9][10], and microchemical reactions [11][12][13][14]. Many conventional computational fluid dynamics (CFD) approaches have been used to simulate multicomponent flows in microchannels by solving the macroscopic Navier-Stokes equations [15].…”

Section: Introductionmentioning

confidence: 99%

Pseudopotential Lattice Boltzmann Model for Immiscible Multicomponent Flows in Microchannels

Liu

2023

Processes

View full text Add to dashboard Cite

To investigate droplet formation in a microchannel with different walls, simulations were conducted based on a pseudopotential model using the exact difference method force scheme. The variable surface tension was obtained using Laplace’s law, and the static contact angle was estimated using a first-order linear equation of the corresponding control parameter of the model. The droplet motion in microchannels was simulated using our model, and the effects of surface wettability and the Bond number on the droplet motion were investigated. The droplet motion for the intermediate microchannel wall took a significantly shorter time than that for the hydrophilic wall, and the wet length also depended on the contact angle. As the Bond number increased, the wet length of the droplet decreased on the hydrophilic surface. The droplet formation in a T-junction device was also simulated using the proposed model, and the effects of the capillary number and viscosity ratio on droplet formation were discussed in detail, and some empirical correlations between the capillary number and dimensionless droplet length are presented according to different viscosity ratios. The three flow patterns of droplet formation were categorized by the different capillary numbers as the dripping–squeezing, jetting–shearing, and threading regimes. In the dripping–squeezing regime, the droplet volume was nearly independent of the viscosity ratio, but the viscous effect was more prone to occur in the jetting–shearing regime. In the jetting–shearing regime, as the capillary number increased, the effect of the viscosity ratio on droplet formation became more significant.

show abstract

“…The droplet formation process is discussed by varying the viscosity of the dispersed phase and the velocity of the continuous phase [19]. There are two types of droplets generated by the co-ow device, dripping and jetting, and factors such as capillary number, Weber number, viscosity ratio, and density ratio also have an effect on the droplet diameter [20].…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of droplet formation in a Co-flow microchannel capillary device

Zhang,

Ma,

Song

et al. 2024

Preprint

View full text Add to dashboard Cite

In this article, a numerical simulation of the droplet formation in a Co-flow microchannel capillary device, and the influencing factors of the formation of droplets are studied. The level set method is used to track the two-phase interface and droplet formation. In the Co-flow focusing device, we explored the influencing factors of the size of the generated droplets. The results show that as the ratio of the dispersed phase velocity to the continuous phase velocity increases, the volume of the generated droplets decreases significantly, the droplet generation frequency increases significantly, and the pressure of the droplets at the centerline decreases significantly. As the viscosity of continuous phase increases, the volume of generated droplets decreases significantly, the frequency of droplet generation increases significantly, and the pressure of droplets at the centerline decreases significantly. As the contact angle between the continuous phase and the wall increases, the volume of the generated droplets increases, but the volume increase is not obvious enough, the droplet generation frequency becomes smaller, and the droplet pressure at the centerline decreases. As the increase of interfacial tension, the volume of droplet generation increases significantly, the frequency of droplet generation decreases significantly, and the pressure of droplet at the centerline increases significantly.

show abstract

Three-dimensional simulation of microdroplet formation in a co-flowing immiscible fluid system using front tracking method

Cited by 18 publications

References 34 publications

Higher-order accurate diffuse-domain methods for partial differential equations with Dirichlet boundary conditions in complex, evolving geometries

Higher-order accurate diffuse-domain methods for partial differential equations with Dirichlet boundary conditions in complex, evolving geometries

Pseudopotential Lattice Boltzmann Model for Immiscible Multicomponent Flows in Microchannels

Numerical simulation of droplet formation in a Co-flow microchannel capillary device

Contact Info

Product

Resources

About