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A consistent and conservative diffuse-domain lattice Boltzmann method for multiphase flows in complex geometries

Xi Liu School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, China    Chengjie Zhan School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, China    Ying Chen School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, China    Zhenhua Chai [email protected] School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, China Institute of Interdisciplinary Research for Mathematics and Applied Science, Huazhong University of Science and Technology, Wuhan, 430074, China Hubei Key Laboratory of Engineering Modeling and Scientific Computing, Huazhong University of Science and Technology, Wuhan, 430074, China    Baochang Shi School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, China Institute of Interdisciplinary Research for Mathematics and Applied Science, Huazhong University of Science and Technology, Wuhan, 430074, China Hubei Key Laboratory of Engineering Modeling and Scientific Computing, Huazhong University of Science and Technology, Wuhan, 430074, China
Abstract

Modeling and simulation of multiphase flows in complex geomerties are challenging due to the complexity in describing the interface topology changes among different phases and the difficulty in implementing the boundary conditions on the irregular solid surface. In this work, we first developed a diffuse-domain (DD) based phase-field model for multiphase flows in complex geometries. In this model, the irregular fluid region is embedded into a larger and regular domain by introducing a smooth characteristic function. Then, the reduction-consistent and conservative phase-field equation for the multiphase field and the consistent and conservative Navier-Stokes equations for the flow field are reformulated as the diffuse-domain based consistent and conservative (DD-CC) equations where some additional source terms are added to reflect the effects of boundary conditions. In this case, there is no need to directly treat the complex boundary conditions on the irregular solid surface, and additionally, based on a matched asymptotic analysis, it is also shown that the DD-CC equations can converge to the original governing equations as the interface width parameter tends to zero. Furthermore, to solve the DD-CC equations, we proposed a novel and simple lattice Boltzmann (LB) method with a Hermite-moment-based collision matrix which can not only keep consistent and conservation properties, but also improve the numerical stability with a flexible parameter. With the help of the direct Taylor expansion, the macroscopic DD-CC equations can be recovered correctly from the present LB method. Finally, to test the capacity of LB method, several benchmarks and complex problems are considered, and the numerical results show that the present LB method is accurate and efficient for the multiphase flows in complex geomerties.

I Introduction

Multiphase flows in complex geometries are ubiquitous in nature and numerous industrial applications, such as liquid drops splashing on the ground, enhanced oil recovery and double emulsion production in microfluidics CHEN2015 ; Gan2009 ; Li2005 . In these problems, the dynamics of the fluid-fluid interface and the moving contact lines (MCLs) on irregular solid surface have a significant influence on the behavior of multiphase flows confined in complex geometries. Thus, in the modeling and simulation of such complex problems, how to accurately capture the fluid-fluid interface and treat the boundary conditions on irregular solid surface, especially the wetting boundary condition, are two core issues needed to be considered.

To describe the multiple interfacial dynamics, the phase-field method Lowengrub1998 ; Shen2011Modeling where a diffusive interface with a small but finite width is adopted to replace the sharp interface between different phases, is commonly applied due to its capacity in capturing the topological changes implicitly. Based on the phase-field theory, the Cahn-Hilliard (CH) equation Boyer2014 ; Cahn1958 ; Dong2018 has been widely used in the study of the multiphase flows owing to its advantage in keeping the reduction-consistent property and thermodynamic consistency. However, the works on NN-phase (N>2N>2) flows in complex geometries are relatively rare, especially on how to deal with the MCLs on irregular solid surface efficiently.

The diffuse-domain (DD) method Aland2010TwophaseFI ; Guo2020ADD ; Li2009SOLVINGPI ; liu2022 ; Yang2023b ; Yang2023a ; yu2020Higher , as a diffuse interface approach, has received increasing attention in study of two-phase flows in complex geometries. As shown in Fig. 1, the basic idea of the DD method is that the complex fluid region is embedded into a larger and regular domain with a smooth characteristic function being used to enforce the boundary conditions at solid-fluid interface. Based on this idea, two main approaches have been developed to treat the boundary conditions on complex solid surface. The first one is based on a modified multi-component CH system, where one component is initially fixed as a solid phase, and the dynamics of fluid phases can be captured by solving the governing equations for remaining components Yang2023b ; Yang2023a . This approach has been used to capture two/ternary phase flows in arbitrary domains Yang2023b ; Yang2023a , but the CH system dose not satisfy the reduction-consistent property for multiphase flows Yang2023b . Besides, this approach also suffers from another problem, i.e., an obvious shrinkage of the droplet, and it needs to be improved with an interfacial correction technique xia2022 . The second one is to directly reformulate the original governing equations at a larger and regular domain, which are also called the DD equations Li2009SOLVINGPI ; yu2020Higher . This approach establishes the DD equations in both the original and extended domains by using a phase-field parameter ϕ\phi that varies continuously across the interface, and some additional source terms are added to enforce different boundary conditions. In addition, by using the matched asymptotic expansion, one can show that the DD equations would converge to the original governing equations and the corresponding boundary conditions on solid surface as the thickness of the DD interface ε0\varepsilon_{0} shrinks to zero. Actually, the second DD approach has been successfully utilized to investigate two-phase flows in complex geometries. For instance, Aland et al. Aland2010TwophaseFI first coupled the DD method with the standard diffuse-interface method to study the two-phase flows in complex geometries. Later, Guo et al. Guo2020ADD developed a thermodynamically consistent diffuse-interface model coupled with the DD method for the two-phase flows with large density ratio. Recently, Liu et al. liu2022 proposed a DD based consistent and conservative (DD-CC) phase-field model for two-phase flows in complex geometries, and investigated the effects of the wettability and viscosity ratio on the interfacial dynamics. To the best of our knowledge, however, there is no available DD model that can be used to treat NN-phase (N>2N>2) fluids in contact with complex solid surface, which is mainly caused by the difficulty in enforcing different boundary conditions of multiphase fluids.

To study NN-phase flows in complex geometries, in this work, we develop a DD based consistent and conservative phase-field model for the first time, which can inherit the advantages of the phase-field method in capturing multiple interfacial dynamics implicitly and keeping the reduction-consistent property and thermodynamic consistency, and the DD method in treating boundary conditions on the irregular solid surface. Furthermore, different from the traditional numerical methods for the DD equations Aland2010TwophaseFI ; Guo2020ADD , here we focus on the mesoscopic lattice Boltzmann (LB) method Chai2020Multiple ; Chai2023Multiple ; Chen1998LATTICEBM ; Krueger2016TheLB ; Succi2001TheLB for its potential advantage in parallel scalability when incorporating complex physics models, and develop a new LB method to solve the DD-CC equations. It is worth noting that compared to classic multiple-relaxation-time (MRT)-LB method Dd2002 , the current LB (hereafter DD-CCLB) method contains the Hermite-monent based collision matrix Chai2023Multiple ; Coreixas2019 ; Krueger2016TheLB with a flexible parameter d0d_{0} Chai2023Multiple , which can be used to improve the numerical stability. The rest of this paper is organized as follows. In section 2, the DD-CC equations for the NN-phase flows in complex geometries are first proposed, followed by the devloped DD-CCLB method in section 3. In section 4, we conduct some simulations to test the present DD-CCLB method, and finally, some conclusions are given in section 5.

Refer to caption
Figure 1: Schematic of the DD method.

II Mathematical equations

II.1 The reduction-consistent Cahn-Hilliard equation for multiphase flows

Based on the phase-field theory for NN-phase (N2N\geq 2) incompressible and immiscible fluids in an irregular domain Ω~\tilde{\Omega}, one can define the total mixture free energy (C,C)\mathcal{F}(\vec{C},\nabla\vec{C}) for NN-phase system Boyer2014 ; Dong2018 as

(C,C)=[0(C)+i,j=1Nκij2CiCj]𝑑Ω~,\mathcal{F}(\vec{C},\nabla\vec{C})=\int\left[\mathcal{F}_{0}(\vec{C})+\sum_{i,j=1}^{N}\frac{\kappa_{ij}}{2}\nabla C_{i}\cdot\nabla C_{j}\right]d\tilde{\Omega}, (1)

where CiC_{i} represents the volume fraction of iith fluid with the following constraint:

i=1NCi=1,0Ci1.\sum_{i=1}^{N}C_{i}=1,\quad 0\leq C_{i}\leq 1. (2)

In Eq. (1), the first term on the right-hand side 0(C)\mathcal{F}_{0}(\vec{C}) is the bulk free energy, and it can be given by 0(C)=i,j=1Nβij[g(Ci)+g(Cj)g(Ci+Cj)]\mathcal{F}_{0}(\vec{C})=\sum_{i,j=1}^{N}\beta_{ij}\left[g\left(C_{i}\right)+g\left(C_{j}\right)-g\left(C_{i}+C_{j}\right)\right] with C=(C1,C2,,CN)\vec{C}=\left(C_{1},C_{2},\ldots,C_{N}\right) and g(C)=C2(C1)2g(C)=C^{2}(C-1)^{2}. The second term is the excess free energy at the interfacial region. Here βij\beta_{ij} and κij\kappa_{ij} are two constant parameters related to the surface tension σij\sigma_{ij} and the interface width ε\varepsilon, and can be expressed as βij=3ε/σij\beta_{ij}=3{\varepsilon}/\sigma_{ij} and κij=3εσij/4\kappa_{ij}=-3\varepsilon\sigma_{ij}/4. In addition, the surface tension σij\sigma_{ij} has the symmetric property, i.e., σij=σji\sigma_{ij}=\sigma_{ji}, σji>0\sigma_{ji}>0 with iji\neq j, and σii=0\sigma_{ii}=0. By minimizing the total mixture free energy, we can derive the following expression of the chemical potential,

μCi=δδCi=Ci0j=1Nκij2Cj.\mu_{C_{i}}=\frac{\delta\mathcal{F}}{\delta C_{i}}=\partial_{C_{i}}\mathcal{F}_{0}-\sum_{j=1}^{N}\kappa_{ij}\nabla^{2}C_{j}. (3)

Then the CH equation for multiphase flows can be written as Dong2018

tCi+(Ciu)=j=1N(MijμCj),\partial_{t}C_{i}+\nabla\cdot(C_{i}\textbf{u})=\sum_{j=1}^{N}\nabla\cdot(M_{ij}\nabla\mu_{C_{j}}), (4)

where MijM_{ij} is the mobility. To guarantee the reduction-consistent property, which means when the iith fluid (or more fluids) is absent in NN-phase system, the CH equation for NN-phase flows should reduce to the one containing MM-phase flows (M<NM<N), the mobility MijM_{ij} and CiC_{i} are required to be zero when the iith fluid is absent. To this end, here we adopt the following expression of mobility MijM_{ij},

Mij={m0CiCj,ij,j,jiMij,i=j.M_{ij}=\begin{cases}-m_{0}C_{i}C_{j},&i\neq j,\\ -\sum_{j,j\neq i}M_{ij},&i=j.\end{cases} (5)

In addition, this type of MijM_{ij} could remedy a major defect of droplet shrinkage because the maximum principle property can be preserved in this reduction-consistent equation Acosta-Soba2023 ; Elliott1996 .

When the multiphase fluids are in contact with the solid surface, the wetting boundary condition should be used to account for the effect of the contact angles formed by fluid-fluid interface and solid wall on the interface dynamics. In this work, the following wetting boundary condition with a reduction-consistent property for NN-phase immiscible fluids is adopted Dong2017 ,

𝒏wCi=j=1NξijCiCj,1iN.\bm{n}_{w}\cdot\nabla C_{i}=\sum_{j=1}^{N}\xi_{ij}C_{i}C_{j},\quad 1\leq i\leq N. (6)

Here 𝒏w\bm{n}_{w} is the normal vector of solid wall, and the explicit expression of ξij\xi_{ij} can be given by

ξij={4εcosθij,1ijN,0,1i=jN,\xi_{ij}=\begin{cases}\frac{4}{\varepsilon}\cos\theta_{ij},&1\leq i\neq j\leq N,\\ 0,&1\leq i=j\leq N,\end{cases} (7)

where θij\theta_{ij} is the contact angle formed by fluid-fluid interface of i,ji,j phases and solid wall, and is measured on the side of the iith fluid. Additionally, we also introduce θiN\theta_{iN} (1iN11\leq i\leq N-1) to denote the contact angle between solid wall and fluid-fluid interface formed by the iith and NNth phases, and N1N-1 independent contact angles θiN\theta_{iN} can be used to calculate θij\theta_{ij} by Dong2017 ,

cosθij=(σiNσijcosθiNσjNσijcosθjN).\cos\theta_{ij}=\left(\frac{\sigma_{iN}}{\sigma_{ij}}\cos\theta_{iN}-\frac{\sigma_{jN}}{\sigma_{ij}}\cos\theta_{jN}\right). (8)

II.2 The conservative and consistent Navier-Stokes equations for flow field

For NN-phase immiscible and incompressible flows in the irregular domain Ω~{\tilde{\Omega}}, the Navier-Stokes (NS) equations can be written as Dong2018 ; Huang2020AConsistent

u=0,\nabla\cdot\textbf{u}=0, (9a)
t(ρu)+(mu)=P+[ρν(u+uT)]+Fs,\partial_{t}(\rho\textbf{u})+\nabla\cdot(\textbf{m}\textbf{u})=-\nabla P+\nabla\cdot[\rho\nu(\nabla\textbf{u}+\nabla\textbf{u}^{T})]+\textbf{F}_{s}, (9b)

where ρ\rho is the fluid density, m is the mass flux, ν\nu is the kinematic viscosity, PP is the pressure, Fs=iμCiCi\textbf{F}_{s}=\sum_{i}\mu_{C_{i}}\nabla C_{i} is the surface tension force. In the multiphase system, the density and viscosity are usually assumed to be a linear function of the phase-field variable CiC_{i},

ρ=iCiρi,ν=iCiνi,\rho=\sum_{i}C_{i}\rho_{i},\quad\nu=\sum_{i}C_{i}\nu_{i}, (10)

where ρi\rho_{i} and νi\nu_{i} are the density and viscosity of the iith-phase fluid, respectively. To guarantee the consistency of reduction, the consistency of mass and momentum transport, and the consistency of mass conservation Huang2020AConsistent , the mass flux m should be designed as

m=ρ𝐮+mC,\textbf{m}=\rho\mathbf{u}+\textbf{m}^{C}, (11)

with

mC=ijρiMijμCj.\textbf{m}^{C}=-\sum_{ij}\rho_{i}M_{ij}\nabla\mu_{C_{j}}. (12)

Here mC\textbf{m}^{C} denotes the mass diffusion between different phases. In addition, the no slip boundary condition is imposed on the solid surface.

II.3 The DD equations for multiphase flows in complex geometries

In this section, the DD method is applied to reformulate CC equations (4, 9b) coupled with the boundary conditions in a larger and regular domain Ω\Omega Aland2010TwophaseFI ; Guo2020ADD ; Li2009SOLVINGPI ; liu2022 ; yu2020Higher . Through introducing a smooth function ϕ\phi to label the diffuse-interface between the fluid and the solid surface, the following DD-CC equations can be obtained

t(ϕCi)+(ϕCiu)=j=1N(ϕMijμCj),\partial_{t}(\phi C_{i})+\nabla\cdot(\phi C_{i}\textbf{u})=\sum_{j=1}^{N}\nabla\cdot(\phi M_{ij}\nabla\mu_{C_{j}}), (13a)
(ϕu)=0,\nabla\cdot(\phi\textbf{u})=0, (13b)
t(ϕρu)+(ϕρuu+ϕmCu)=ϕP+[ϕρν(u+uT)]+i=1NϕμCiCi\displaystyle\partial_{t}(\phi\rho\textbf{u})+\nabla\cdot(\phi\rho\textbf{u}\textbf{u}+\phi\textbf{m}^{C}\textbf{u})=-\phi\nabla P+\nabla\cdot[\phi\rho\nu(\nabla\textbf{u}+\nabla\textbf{u}^{T})]+\sum_{i=1}^{N}\phi\mu_{C_{i}}\nabla C_{i} (13c)
(1ϕ)ε03u,\displaystyle-\frac{(1-\phi)}{\varepsilon_{0}^{3}}\textbf{u},

with

ϕμCi=j=1N2βijϕ[g(Ci)g(Ci+Cj)]+j=1N3ε4σij(ϕCj)\displaystyle\phi\mu_{C_{i}}=\sum_{j=1}^{N}2\beta_{ij}\phi\left[g^{\prime}\left(C_{i}\right)-g^{\prime}\left(C_{i}+C_{j}\right)\right]+\sum_{j=1}^{N}\frac{3\varepsilon}{4}\sigma_{ij}\nabla\cdot(\phi\nabla C_{j}) (14)
+j=1N3σijqjcosθjqCjCq|ϕ|,\displaystyle+\sum_{j=1}^{N}3\sigma_{ij}\sum_{q\neq j}\cos\theta_{jq}C_{j}C_{q}|\nabla\phi|,

where ϕ=1\phi=1 in the original complex domain Ω~\tilde{\Omega}, while ϕ=0\phi=0 in Ω/Ω~\Omega/\tilde{\Omega}, and ϕ=1/2\phi=1/2 is used to mark the solid boundary Ω~\partial\tilde{\Omega}. ε0\varepsilon_{0} is the thickness of the diffuse layer. In the larger and regular domain Ω\Omega, the boundary conditions, u=0\textbf{u}=0 , nCi=0\textbf{n}\cdot\nabla C_{i}=0, and nμCi=0\textbf{n}\cdot\nabla\mu_{C_{i}}=0, are imposed on Ω\partial{\Omega}. It is worth mentioning that there is no need to directly handle the complex boundary conditions on Ω~\partial\tilde{\Omega}. Additionally, with the help of the matched asymptotic analysis, the DD-CC equations can asymptotically converge to the original equations as ε00\varepsilon_{0}\rightarrow 0. Here we only take the DD-CH equation (13a) as an example, and show the details in Appendix B.

III The LB method for DD equations

In this section, we develop a novel and simple LB method for the DD-CC equations (13c). Due to the fact that the mobility MijM_{ij} (5) is related to CiC_{i}, the standard LB method would be unstable when it adopted to the DD-CH equation. To overcome this problem, the diffusion flux ϕMiiμCi\phi M_{ii}\nabla\mu_{C_{i}} is divided into two parts, ϕm0μCi\phi m_{0}\nabla\mu_{C_{i}} and (ϕMiiϕm0)μCi\left(\phi M_{ii}-\phi m_{0}\right)\nabla\mu_{C_{i}}, in which the first part containing a constant mobility m0m_{0} can be seen as a diffusion term, and the other part can be handled as a source term. Then we propose a new Hermite-moment-based LB method for the DD-CC equations (13c),

fpi(𝐱+𝐜pδt,t+δt)=fpi(𝐱,t)Λpqfi[fqi(𝐱,t)fqi,eq(𝐱,t)]\displaystyle f^{i}_{p}\left(\mathbf{x}+\mathbf{c}_{p}\delta t,t+\delta t\right)=f^{i}_{p}(\mathbf{x},t)-\Lambda^{f^{i}}_{pq}\left[f^{i}_{q}(\mathbf{x},t)-f_{q}^{i,eq}(\mathbf{x},t)\right] (15)
+δt(δpqΛpqfi2)Fqi(𝐱,t),\displaystyle+\delta t\left(\delta_{pq}-\frac{\Lambda^{f^{i}}_{pq}}{2}\right)F^{i}_{q}(\mathbf{x},t),
gp(𝐱+𝐜pδt,t+δt)=gp(𝐱,t)Λpqg[gq(𝐱,t)gqeq(𝐱,t)]\displaystyle g_{p}\left(\mathbf{x}+\mathbf{c}_{p}\delta t,t+\delta t\right)=g_{p}(\mathbf{x},t)-\Lambda^{g}_{pq}\left[g_{q}(\mathbf{x},t)-g_{q}^{eq}(\mathbf{x},t)\right] (16)
+δt(δpqΛpqg2)Gq(𝐱,t),\displaystyle+\delta t\left(\delta_{pq}-\frac{\Lambda^{g}_{pq}}{2}\right)G_{q}(\mathbf{x},t),

where fpif^{i}_{p} and gp(x,t)g_{p}(\textbf{x},{t}) (p=0,1,k1p=0,1...,k-1) are the distribution functions for the iith-phase field and flow field with kk being the number of the discrete velocities, fpi,eq(x,t)f_{p}^{i,eq}(\textbf{x},{t}) and gpeq(x,t)g_{p}^{eq}(\textbf{x},{t}) are the corresponding equilibrium distribution functions, Fpi(x,t){F}^{i}_{p}(\textbf{x},{t}) and Gp(x,t){G}_{p}(\textbf{x},{t}) are the distribution functions of the source and force terms. 𝚲fi\bm{\Lambda}^{f^{i}} and 𝚲g\bm{\Lambda}^{g} are the k×kk\times k invertible collision matrices with the following forms,

𝚲fi=H1SfiH,𝚲g=H1SgH,\bm{\Lambda}^{f^{i}}=\textbf{H}^{-1}\textbf{S}^{f^{i}}\textbf{H},\quad\bm{\Lambda}^{g}=\textbf{H}^{-1}\textbf{S}^{g}\textbf{H}, (17)

where H is the Hermite-moment-based transformation matrix Chai2023Multiple ; Coreixas2019 ; Krueger2016TheLB , Sfi\textbf{S}^{f^{i}} and Sg\textbf{S}^{g} are the relaxation matrices. To recover DD-CH equation (13a), the distribution functions fpi,eq(x,t)f_{p}^{i,eq}(\textbf{x},{t}) and Fpi(x,t){F}^{i}_{p}(\textbf{x},{t}) should be designed properly, and can be given by

fpi,eq(𝐱,t)={(ωp1)ηiϕμCi+ϕCi,p=0,ωpηiϕμCi+ωp𝐜pϕCi𝐮cs2,p0,f_{p}^{i,eq}(\mathbf{x},t)=\begin{cases}\left(\omega_{p}-1\right)\eta_{i}\phi\mu_{C_{i}}+\phi C_{i},&p=0,\\ \omega_{p}\eta_{i}\phi\mu_{C_{i}}+\omega_{p}\frac{\mathbf{c}_{p}\cdot\phi C_{i}\mathbf{u}}{c_{s}^{2}},&p\neq 0,\end{cases} (18)

and

Fpi(𝐱,t)=ωp𝐜p[t(ϕCi𝐮)+cs2ηi(μCiϕSi)]cs2,F^{i}_{p}(\mathbf{x},t)=\omega_{p}\frac{\mathbf{c}_{p}\cdot\left[\partial_{t}(\phi C_{i}\mathbf{u})+c_{s}^{2}\eta_{i}(\mu_{C_{i}}\nabla\phi-\textbf{S}_{i})\right]}{c_{s}^{2}}, (19)

where

Si=ϕMiiϕm0m0μCi+jiϕMijm0μCj.\textbf{S}_{i}=\frac{\phi M_{ii}-\phi m_{0}}{m_{0}}\nabla\mu_{C_{i}}+\sum_{j\neq i}\frac{\phi M_{ij}}{m_{0}}\nabla\mu_{C_{j}}. (20)

Here 𝐜p\mathbf{c}_{p} is the discrete velocity, csc_{s} is the lattice sound speed, ωp\omega_{p} is the weight coefficient satisfying ωp=1\sum\omega_{p}=1. Usually the weight coefficient ωp\omega_{p} is fixed in MRT-LB method, but in the present LB method, ωp\omega_{p} is related to a flexible parameter d0d_{0}, which can be adjusted to improve the numerical stability and accuracy Chai2023Multiple . To recover DD-NS equations (13b and 13c), the distribution functions gpeq(x,t)g_{p}^{eq}(\textbf{x},{t}) and Gp(x,t){G}_{p}(\textbf{x},{t}) are designed as

gpeq(𝐱,t)={(ωp1)ϕPcs2+ρ0+sp,p=0,ωpϕPcs2+sp,p0,g_{p}^{eq}(\mathbf{x},t)=\begin{cases}\left(\omega_{p}-1\right)\frac{\phi P}{c_{s}^{2}}+\rho_{0}+s_{p},&p=0,\\ \omega_{p}\frac{\phi P}{c_{s}^{2}}+s_{p},&p\neq 0,\end{cases} (21)

and

Gp(𝐱,t)=ωp[ϕ𝐮ρ+𝐜p𝐅cs2+Mαα2G(cpαcpαcs2)c2cs2cs4+Mαα¯2Gcpαcpα¯cs4],G_{p}(\mathbf{x},t)=\omega_{p}\left[\phi\mathbf{u}\cdot\nabla\rho+\frac{\mathbf{c}_{p}\cdot\mathbf{F}}{c_{s}^{2}}+\frac{M^{2G}_{\alpha{\alpha}}\left({c}_{p\alpha}{c}_{p\alpha}-c_{s}^{2}\right)}{c^{2}c_{s}^{2}-c_{s}^{4}}+\frac{M^{2G}_{\alpha\bar{\alpha}}{c}_{p\alpha}{c}_{p\bar{\alpha}}}{c_{s}^{4}}\right], (22)

where

sp=ωp[𝐜pϕρ𝐮cs2+(ϕρuαuα+ϕmαcuα)(cpαcpαcs2)c2cs2cs4\displaystyle s_{p}=\omega_{p}\left[\frac{\mathbf{c}_{p}\cdot\phi\rho\mathbf{u}}{c_{s}^{2}}+\frac{\left(\phi\rho u_{\alpha}u_{\alpha}+\phi{m}^{c}_{\alpha}u_{\alpha}\right)\left({c}_{p\alpha}{c}_{p\alpha}-c_{s}^{2}\right)}{c^{2}c_{s}^{2}-c_{s}^{4}}\right. (23)
+(ϕρuαuα¯+ϕmαcuα¯+ϕuαmα¯c2)cpαcpα¯cs4],\displaystyle\left.+\left(\phi\rho u_{\alpha}u_{\bar{\alpha}}+\frac{\phi{m}^{c}_{\alpha}u_{\bar{\alpha}}+\phi u_{\alpha}{m}^{c}_{\bar{\alpha}}}{2}\right)\frac{{c}_{p\alpha}{c}_{p\bar{\alpha}}}{c_{s}^{4}}\right],
𝐌2G=t(ϕ𝐦C𝐮+ϕ𝐮𝐦C2)+cs2[𝐮(ϕρ)+(ϕρ)𝐮]+(c23cs2)𝐮(ϕρ)𝐈,\mathbf{M}^{2G}=\partial_{t}\left(\frac{\phi\mathbf{m}^{C}\mathbf{u}+\phi\mathbf{um}^{C}}{2}\right)+c_{s}^{2}\left[\mathbf{u}\nabla(\phi\rho)+\nabla(\phi\rho)\mathbf{u}\right]+(c^{2}-3c_{s}^{2})\mathbf{u}\cdot\nabla(\phi\rho)\mathbf{I}, (24)

and

F=(ϕmcuϕumc2)+i=1NϕμCiCi+Pϕ(1ϕ)ε03u,\textbf{F}=-\nabla\cdot\left(\frac{\phi\textbf{m}^{c}\textbf{u}-\phi\textbf{u}\textbf{m}^{c}}{2}\right)+\sum_{i=1}^{N}\phi\mu_{C_{i}}\nabla C_{i}+P\nabla\phi-\frac{(1-\phi)}{\varepsilon_{0}^{3}}\textbf{u}, (25)

where α\alpha represents the dimension of space and α¯\bar{\alpha} denotes all subscripts except α\alpha. Through the direct Taylor analysis (see Appendix C for details), the DD-CC equations can be recovered correctly with the following relations,

m0=(1s1fi12)ηics2δt,m_{0}=\left(\frac{1}{s^{f^{i}}_{1}}-\frac{1}{2}\right)\eta_{i}c_{s}^{2}\delta{t}, (26)
ν=(1s21g12)c2cs22δt,ν=(1s22g12)cs2δt,\nu=\left(\frac{1}{s^{g}_{{21}}}-\frac{1}{2}\right)\frac{c^{2}-c_{s}^{2}}{2}\delta{t},\quad\nu=\left(\frac{1}{s^{g}_{{22}}}-\frac{1}{2}\right)c_{s}^{2}\delta{t}, (27)

where s1fis^{f^{i}}_{1}, s21gs^{g}_{21} and s22gs^{g}_{{22}} are the relaxation parameters appeared in Sfi\textbf{S}^{f^{i}} and Sg\textbf{S}^{g}, respectively. ηi\eta_{i} is an adjustable parameter which can be applied to improve the numerical stability for a specified m0m_{0} liu2022 . In addition, the macroscopic volume fraction parameter CiC_{i}, fluid velocity u, and pressure PP are calculated by

ϕCi=pfpi,\phi C_{i}=\sum_{p}f^{i}_{p}, (28)
ϕρu=pcpgp+12δtF,\phi\rho\textbf{u}=\sum_{p}{\textbf{c}_{p}g_{p}}+\frac{1}{2}\delta{t}\textbf{F}, (29)
ϕP=cs21ω0{p0gp+[12+K(1d0)(2s0g)2s0g]δtϕ𝐮ρ+δtK2c2t(ϕ𝐦ϕC𝐮)\displaystyle\phi P=\frac{c_{s}^{2}}{1-\omega_{0}}\left\{\sum_{p\neq 0}g_{p}+\left[\frac{1}{2}+\frac{K(1-d_{0})(2-s^{g}_{0})}{2s^{g}_{0}}\right]\delta t\phi\mathbf{u}\cdot\nabla\rho+\delta t\frac{K}{2c^{2}}\partial_{t}\left(\phi\mathbf{m}^{\phi C}\cdot\mathbf{u}\right)\right. (30)
+δtHs21g𝐮(ϕρ)+s0},\displaystyle\left.+\delta t\frac{H}{s^{g}_{21}}\mathbf{u}\cdot\nabla(\phi\rho)+s_{0}\right\},

where K=1d0K=1-d_{0} and H=K(12d0)(s21g2)H=K(1-2d_{0})(s^{g}_{21}-2) for two dimensional problems while K=12d0K=1-2d_{0} and H=K(37d0)(s21g2)/2H=K(3-7d_{0})(s^{g}_{21}-2)/2 for three-dimensional problems. In our simulations, the D2Q9 lattice model is adopted for both phase and flow fields in two-dimensional problems, while in three-dimensional problems, the D3Q7 and D3Q15 lattice models are used for phase and flow fields, respectively. In the following, the discrete velocity 𝐜p\mathbf{c}_{p}, the weight coefficient ωp\omega_{p}, and the relaxation matrix 𝐒\mathbf{S} in the Hermite-moment based lattice models are given by Chai2023Multiple

D2Q9:

𝐜p\displaystyle\mathbf{c}_{p} ={(0,0,0),p=0,(±c,0),(0,±c),p=14,(±c,±c),p=58,ωp={12d0+d02,p=0,(d0d02)/2,p=14,d02/4,p=58,\displaystyle=\begin{cases}(0,0,0),&p=0,\\ (\pm c,0),(0,\pm c),&p=1-4,\\ (\pm c,\pm c),&p=5-8,\\ \end{cases}\quad\omega_{p}=\begin{cases}1-2d_{0}+d_{0}^{2},&p=0,\\ (d_{0}-d_{0}^{2})/2,&p=1-4,\\ d_{0}^{2}/4,&p=5-8,\\ \end{cases} (31)
𝐒\displaystyle\mathbf{S} =diag(s0,s1,s1,s21,s21,s22,s3,s3,s4).\displaystyle=\operatorname{diag}\left(s_{0},s_{1},s_{1},s_{21},s_{21},s_{22},s_{3},s_{3},s_{4}\right).

D3Q7:

𝐜p\displaystyle\mathbf{c}_{p} ={(0,0,0),p=0,(±c,0,0),(0,±c,0),(0,0,±c),p=16,ωp={13d0,p=0,d0/2,p=16,\displaystyle=\begin{cases}(0,0,0),&p=0,\\ (\pm c,0,0),(0,\pm c,0),(0,0,\pm c),&p=1-6,\\ \end{cases}\quad\omega_{p}=\begin{cases}1-3d_{0},&p=0,\\ d_{0}/2,&p=1-6,\\ \end{cases} (32)
𝐒\displaystyle\mathbf{S} =diag(s0,s1,s1,s1,s21,s21,s21).\displaystyle=\operatorname{diag}\left(s_{0},s_{1},s_{1},s_{1},s_{21},s_{21},s_{21}\right).

D3Q15:

𝐜p\displaystyle\mathbf{c}_{p} ={(0,0,0),p=0,(±c,0,0),(0,±c,0),(0,0,±c),p=16,(±c,±c,±c),p=714,ωp={13d0+2d02,p=0,(d0d02)/2,p=16,d02/8,p=714,\displaystyle=\begin{cases}(0,0,0),&p=0,\\ (\pm c,0,0),(0,\pm c,0),(0,0,\pm c),&p=1-6,\\ (\pm c,\pm c,\pm c),&p=7-14,\\ \end{cases}\omega_{p}=\begin{cases}1-3d_{0}+2d_{0}^{2},&p=0,\\ (d_{0}-d_{0}^{2})/2,&p=1-6,\\ d_{0}^{2}/8,&p=7-14,\\ \end{cases} (33)
𝐒\displaystyle\mathbf{S} =diag(s0,s1,s1,s1,s21,s21,s21,s22,s22,s22,s3,s3,s3,s3,s4),\displaystyle=\operatorname{diag}\left(s_{0},s_{1},s_{1},s_{1},s_{21},s_{21},s_{21},s_{22},s_{22},s_{22},s_{3},s_{3},s_{3},s_{3},s_{4}\right),

where d0=cs2/c2d_{0}=c_{s}^{2}/c^{2} and c=δx/δtc=\delta x/\delta t.

IV Numerical results and discussion

In this section, four benchmark problems, i.e., the spreading of a single droplet, the spreading of a compound droplet in ternary system, the spreading of a compound droplet in quaternary system on an ideal wall in two-dimensional space, and a compound droplet spreading on a solid sphere in three-dimensional space, are first used to validate the present DD-CCLB method. Then a complex problem, a compound droplet passing through an irregular channel, is applied to demonstrate the capacity of the DD-CCLB method for multiphase flows in complex geometries.

IV.1 The spreading of a single droplet on an ideal wall

We first consider the spreading of a single droplet on an ideal wall, which can be used as a good benchmark to test the reduction-consistent property of the DD-CCLB method. In this numerical experiment, we focus on a ternary-phase system with two fluids (M=2M=2 and N=3N=3), and the volume fraction of the third phase (C3C_{3}) is set to be zero. Initially, a semicircular droplet with the radius R=50δxR=50\delta x is deposited on the ideal wall, and some parameters are fixed as ρ1=1\rho_{1}=1, ρ2=ρ3=0.01\rho_{2}=\rho_{3}=0.01, ν1=ν2=ν3=0.1\nu_{1}=\nu_{2}=\nu_{3}=0.1, σij=0.001\sigma_{ij}=0.001 where iji\neq j, m0=0.01m_{0}=0.01, ε0=0.16\varepsilon_{0}=0.16, ε=5δx\varepsilon=5\delta x, δx=0.04\delta x=0.04, c=20c=20, d0=0.4d_{0}=0.4, s0fi=1s^{fi}_{0}=1, s1fi=10/19s^{fi}_{1}=10/19, s21fi=s22fi=1.2s^{fi}_{21}=s^{fi}_{22}=1.2, s3fi=s4fi=1.2s^{fi}_{3}=s^{fi}_{4}=1.2, s0g=1s^{g}_{0}=1, s1g=s3g=s4g=1.2s^{g}_{1}=s^{g}_{3}=s^{g}_{4}=1.2, and the boundary conditions are the same as those in Ref. liu2022 . As seen from Fig. 2, the single droplet can form different steady patterns under different values of the contact angle θ\theta, and additionally, the present results are also in good agreement with those obtained by the two-phase method (M=N=2M=N=2) liu2022 . Moreover, we give a quantitative comparison of the contact angle in Table 1, and a good agreement between two different methods is observed, which indicates the present DD-CCLB method keeps the reduction-consistent property well.

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Figure 2: The predicted equilibrium shape of a single droplet [The solid and dashed lines (C=0.5C=0.5) are obtained by the present DD-CCLB method (M=2M=2 and N=3N=3) and two-phase method liu2022 (M=N=2M=N=2) under conditions of prescribed contact angles: (a) θ=60\theta=60^{\circ}, (b) θ=90\theta=90^{\circ}, (c) θ=120\theta=120^{\circ}].
Table 1: A comparison of the present DD-CCLB method (M=2M=2 and N=3N=3) and two-phase method liu2022 (M=N=2M=N=2) in predicting the contact angle of a single droplet.
Contact angles 6060^{\circ} 9090^{\circ} 120120^{\circ}
DD-CCLB 60.8160.81^{\circ} 90.2990.29^{\circ} 120.65120.65^{\circ}
Liu et al. liu2022 60.8560.85^{\circ} 89.7789.77^{\circ} 120.72120.72^{\circ}

IV.2 The spreading of a compound drop in ternary system on an ideal wall

Now we investigate the spreading of a compound droplet (M=N=3M=N=3) on an ideal wall to test the present DD-CCLB method for the ternary system. In our simulations, two immiscible fluids C1C_{1} and C2C_{2} with the same radius R=60δxR=60\delta x constitute a semicircular compound drop, which are surrounded by another fluid (C3C_{3}) and deposited on an ideal wall. The physical domain is divided into 300δx×170δx300\delta x\times 170\delta x, and some parameters are given by ρ1=100\rho_{1}=100, ρ2=50\rho_{2}=50, ρ3=1\rho_{3}=1, σij=0.005\sigma_{ij}=0.005 with iji\neq j, m0=0.01m_{0}=0.01, ε=8δx\varepsilon=8\delta x, ε0=0.6\varepsilon_{0}=0.6, δx=0.1\delta x=0.1, c=10c=10, and other parameters are the same as those adopted in the previous problem. We conduct some simulations, and present a comparison with the results in Ref. Liang2019wet , where the spreading of compound droplets on a substrate is studied by using the original governing equations combined the boundary condition (6) for ternary-phase flows. Figure 3 depicts the equilibrium shapes of a compound droplet at various contact angles with a fixed contact angle θ23=90\theta_{23}=90^{\circ}, and the present numerical results are close to those reported in the previous work Liang2019wet . In addition, to give a quantitative test on the accuracy of the present DD-CCLB method, we also measure the equilibrium spreading lengths of compound droplet, and list the corresponding analytical solutions and available numerical data in Table 2, from which a good agreement between them can be observed.

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Figure 3: The predicted equilibrium shape of a compound droplet in ternary system at a fixed contact angle θ23=90\theta_{23}=90^{\circ} [The solid line and circle (C=0.5C=0.5) are obtained by the present DD-CCLB method (M=N=3M=N=3) and ternary-phase method Liang2019wet under conditions of prescribed contact angles: (a) θ13=60\theta_{13}=60^{\circ}, (b) θ13=90\theta_{13}=90^{\circ}, (c) θ13=120\theta_{13}=120^{\circ}].
Table 2: The equilibrium spreading lengths L1L_{1} and L2L_{2} (normalized by the initial radius RR) in the spreading of a compound droplet in ternary system with θ23=90\theta_{23}=90^{\circ}.
Numerical Relative errors
Case Lengths Analytical DD-CCLB, Liang et al. Liang2019wet DD-CCLB, Liang et al. Liang2019wet
θ13=60\theta_{13}=60^{\circ} L1L_{1} 1.707 1.698 1.683 0.53% 1.41%
L2L_{2} 1.072 1.044 1.083 2.61% 1.03%
θ13=90\theta_{13}=90^{\circ} L1L_{1} 1.183 1.172 1.175 0.93% 0.68%
L2L_{2} 1.183 1.172 1.192 0.93% 0.76%
θ13=120\theta_{13}=120^{\circ} L1L_{1} 0.672 0.677 0.688 0.74% 2.38%
L2L_{2} 1.335 1.332 1.337 0.22% 0.15%

IV.3 The spreading of a compound droplet in quaternary system on an ideal wall

We continue to test the DD-CCLB method for multiphase flows through considering the spreading of a compound drop in quaternary system (M=N=4M=N=4) on an ideal wall. In the physical domain Ω\Omega with the lattice size 500δx×200δx500\delta x\times 200\delta x, three semicircular droplets with the same radius R=60δxR=60\delta x are contacted with each other, which are surrounded by the fourth phase and initially placed on an ideal wall. In the following simulations, the parameters are set as ρ1=1\rho_{1}=1, ρ2=0.8\rho_{2}=0.8, ρ3=0.5\rho_{3}=0.5, ρ4=0.1\rho_{4}=0.1, σij=0.005\sigma_{ij}=0.005 with iji\neq j, m0=0.002m_{0}=0.002, ε=10δx\varepsilon=10\delta x, ε0=0.8\varepsilon_{0}=0.8, d0=0.5d_{0}=0.5. We investigate the effect of the contact angle θ34\theta_{34} when θ14=θ24=90\theta_{14}=\theta_{24}=90^{\circ} are fixed, which leads to θ12=90\theta_{12}=90^{\circ} according to Eq. (8). From Fig. 4, one can find that the equilibrium shapes of the quaternary-phase compound droplet are different by changing θ34\theta_{34}. For example, when θ34=60\theta_{34}=60^{\circ}, the third phase tends to spread on the wall with a larger spreading length L3L_{3}. With the increase of θ34\theta_{34}, however, the third phase then begins to shrink on the substrate, and the length L3L_{3} decreases. In particular, the compound droplet forms a symmetrical structure in case of θ34=90\theta_{34}=90^{\circ}. We note that inspired by Zhang2016 , one can obtain the analytical solutions of the spreading lengths under the condition of θ12=90\theta_{12}=90^{\circ}, and the details can be found in Appendix D. We also list the spreading lengths of the compound droplet with different contact angles in Table 3, and give a comparison among the present numerical results, theoretical solutions, and those based on CCLB method which directly solves the original governing equations combined with the boundary condition (6). From Fig. 4 and Table 3, one can find that the results obtained by different methods agree well with each other, which indicates that the DD-CCLB method is accurate in predicting the contact angle and equilibrium shape of a compound droplet on the ideal wall.

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Figure 4: The predicted equilibrium shape of a compound droplet in quaternary system at the fixed contact angles θ14=θ24=90\theta_{14}=\theta_{24}=90^{\circ} [The solid and dashed lines (C=0.5C=0.5) are obtained by the present DD-CCLB method (M=N=4M=N=4) and CCLB method under conditions of prescribed contact angles: (a) θ34=60\theta_{34}=60^{\circ}, (b) θ34=90\theta_{34}=90^{\circ}, (c) θ34=120\theta_{34}=120^{\circ}].
Table 3: The equilibrium spreading lengths L1L_{1}, L2L_{2} and L3L_{3} (normalized by the initial radius RR) in the spreading of a compound droplet in quaternary system with θ14=θ24=90\theta_{14}=\theta_{24}=90^{\circ}.
Numerical Relative errors
Case Lengths Analytical DD-CCLB, CCLB DD-CCLB, CCLB
θ34=60\theta_{34}=60^{\circ} L1L_{1} 1.672 1.698 1.697 1.56% 1.50%
L2L_{2} 1.273 1.247 1.238 2.04% 2.75%
L3L_{3} 2.416 2.472 2.458 2.32% 1.74%
θ34=90\theta_{34}=90^{\circ} L1L_{1} 1.672 1.698 1.708 1.56% 2.15%
L2L_{2} 1.434 1.372 1.390 4.32% 3.07%
L3L_{3} 1.672 1.698 1.707 1.56% 2.09%
θ34=120\theta_{34}=120^{\circ} L1L_{1} 1.672 1.710 1.695 2.27% 1.38%
L2L_{2} 1.652 1.598 1.570 3.27% 4.96%
L3L_{3} 0.948 1.005 0.993 6.01% 4.75%

IV.4 A compound droplet spreading on a solid sphere

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Figure 5: (a) The initial setup for a hemispherical droplet on a solid sphere, (b) the profile in z=0z=0 direction for a perfect compound droplet when Vb<Vs/2V_{b}<{V_{s}}/{2}, (c) the profile in z=0z=0 direction for a perfect compound droplet when Vb>Vs/2V_{b}>{V_{s}}/{2}.

The last benchmark problem we consider is a compound droplet spreading on a solid sphere, which is more complicated and can also be used to test the present LB method in predicting the contact angle of multiphase flow in a complex geometry. The schematic of the problem is shown in Fig. 5, where a hemispherical compound droplet composed of blue (C1C_{1}) and green (C2C_{2}) fluids is initially placed on a solid sphere, and is immersed in another fluid (C3C_{3}). Under the assumption of two fluids (C1C_{1} and C2C_{2}) with the same size, density, viscosity and surface wettability, the compound droplet would eventually form a spherical shape under the action of interfacial tensions, which can be regarded as a single-phase droplet. In this case, we can obtain the asymptotic solution of the equilibrium shape. As seen from Figs. 5 and 5, when the droplet reaches a steady state, the contact angle θpre\theta_{pre} on spherical convex surface can be given by Extrand2012

θpre=2arctan{[48Vtπ(2a)3+(4+(48Vtπ(2a)3)2)13]23223213[48Vtπ(2a)3+(4+(48Vtπ(2a)3)2)12]13}arcsin(2a2Rs),\theta_{pre}=2\arctan\left\{\frac{\left[\frac{48V_{t}}{\pi(2a)^{3}}+\left(4+\left(\frac{48V_{t}}{\pi(2a)^{3}}\right)^{2}\right)^{\frac{1}{3}}\right]^{\frac{2}{3}}-2^{\frac{2}{3}}}{2^{\frac{1}{3}}\left[\frac{48V_{t}}{\pi(2a)^{3}}+\left(4+\left(\frac{48V_{t}}{\pi(2a)^{3}}\right)^{2}\right)^{\frac{1}{2}}\right]^{\frac{1}{3}}}\right\}-\arcsin\left(\frac{2a}{2R_{s}}\right), (34)

where Vt=V0+VbV_{t}=V_{0}+V_{b} with V0V_{0} and VbV_{b} being the volumes of the compound droplet and the spherical solid covered by the droplet. Actually, it is easy to obtain the initial volume V0V_{0} as

V0=2π3R032π3Rs3,V_{0}=\frac{2\pi}{3}R_{0}^{3}-\frac{2\pi}{3}R_{s}^{3}, (35)

where R0R_{0} is the initial radius of the hemispherical droplet and RsR_{s} is the radius of the solid sphere. If VbV_{b} is less than the half volume of the solid sphere VsV_{s}, see Fig. 5, one can derive its expression as

Vb=13πRs3{23[1(2a2Rs)2]12+[1(2a2Rs)2]32}.V_{b}=\frac{1}{3}\pi R_{s}^{3}\left\{2-3\left[1-\left(\frac{2a}{2R_{s}}\right)^{2}\right]^{\frac{1}{2}}+\left[1-\left(\frac{2a}{2R_{s}}\right)^{2}\right]^{\frac{3}{2}}\right\}. (36)

On the contrary, if VbV_{b} is larger than the half volume of the solid sphere VsV_{s}, see Fig. 5, it can be determined by

Vb=43πRs313πRs3{23[1(2a2Rs)2]12+[1(2a2Rs)2]32}.V_{b}=\frac{4}{3}\pi R_{s}^{3}-\frac{1}{3}\pi R_{s}^{3}\left\{2-3\left[1-\left(\frac{2a}{2R_{s}}\right)^{2}\right]^{\frac{1}{2}}+\left[1-\left(\frac{2a}{2R_{s}}\right)^{2}\right]^{\frac{3}{2}}\right\}. (37)

On the other hand, when the droplet is in equilibrium state with RlR_{l}, the volume of the droplet can also be given by

V0=43πRl3[π3(3Rsh1)h12+π3(3Rlh2)h22],V_{0}=\frac{4}{3}\pi R_{l}^{3}-\left[\frac{\pi}{3}\left(3R_{s}-h_{1}\right)h_{1}^{2}+\frac{\pi}{3}\left(3R_{l}-h_{2}\right)h_{2}^{2}\right], (38)

where h1=Rs(1cosα)h_{1}=R_{s}(1-\cos\alpha) and h2=Rl[1cos(πθpreα)]h_{2}=R_{l}[1-\cos(\pi-\theta_{pre}-\alpha)]. Then one can determine the center of the steady droplet through calculating the distance dOjOsd_{O_{j}O_{s}},

dOjOs=Rl2+Rs22RlRscosθ.d_{O_{j}O_{s}}=R_{l}^{2}+R_{s}^{2}-2R_{l}R_{s}\cos\theta. (39)

From above analysis, we can predict the equilibrium shape of the compound droplet with the asymptotic solution. However, for a ternary-phase flow, there exits a triple point where the interfacial angles are φ1\varphi_{1}, φ2\varphi_{2} and φ3\varphi_{3}, and satisfy the condition φ1+φ2+φ3=2π\varphi_{1}+\varphi_{2}+\varphi_{3}=2\pi. Based on the balance of interfacial angles at the equilibrium state, one can obtain

sinφ1σ23=sinφ2σ13=sinφ3σ12.\frac{\sin\varphi_{1}}{\sigma_{23}}=\frac{\sin\varphi_{2}}{\sigma_{13}}=\frac{\sin\varphi_{3}}{\sigma_{12}}. (40)

Owing to the fact that φ1=φ2π/2\varphi_{1}=\varphi_{2}\approx\pi/2 and φ3π\varphi_{3}\approx\pi, which can be seen from Figs. 5 and 5, in the following simulations, we choose σ12=0.0025\sigma_{12}=0.0025 and σ13=σ23=0.05\sigma_{13}=\sigma_{23}=0.05 to obtain φ1=φ2=88.6\varphi_{1}=\varphi_{2}=88.6^{\circ}. Some other parameters are set as ρ1=ρ2=10\rho_{1}=\rho_{2}=10, ρ3=1\rho_{3}=1, R0=50δxR_{0}=50\delta x, Rs=25δxR_{s}=25\delta x, m0=0.01m_{0}=0.01, ε0=0.5\varepsilon_{0}=0.5, ε=5δx\varepsilon=5\delta x, δx=0.1\delta x=0.1, c=10c=10, d0=0.4d_{0}=0.4, s0fi=s21fi=1.0s^{f_{i}}_{0}=s^{f_{i}}_{21}=1.0, s1fi=10/19s^{f_{i}}_{1}=10/19, s0g=1.0s^{g}_{0}=1.0 and s1g=s3g=s4g=1.2s^{g}_{1}=s^{g}_{3}=s^{g}_{4}=1.2. We perform some simulations, and present the numerical (solid curve) and asymptotic (dashed curve) solutions of the equilibrium droplet shape in Fig. 6 where the contact angles are θ1,2=30\theta_{1,2}=30^{\circ}, θ1,2=60\theta_{1,2}=60^{\circ}, θ1,2=90\theta_{1,2}=90^{\circ} and θ1,2=120\theta_{1,2}=120^{\circ}. It is obvious that the numerical results agree well with the asymptotic solutions except for the difference at the triple point. Furthermore, Fig. 7 shows a comparison between the predicted contact angle θpre\theta_{pre} based on Eq. (34) and the specified contact angle θ1,2\theta_{1,2}. From this figure, one can find that there is a good agreement between the numerical results and the asymptotic solutions, which illustrates that the DD-CCLB method has a good performance in the study of the multiphase flow in complex solid surface.

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Figure 6: The predicted equilibrium shape of a compound droplet spreading on a solid sphere [The solid and dashed lines (C=0.5C=0.5) in (e)-(h) are obtained by the present DD-CCLB method and the asymptotic solution under conditions of prescribed contact angles: (a) and (e) θ1,2=30\theta_{1,2}=30^{\circ}, (b) and (f) θ1,2=60\theta_{1,2}=60^{\circ}, (c) and (g) θ1,2=90\theta_{1,2}=90^{\circ}, (d) and (h) θ1,2=120\theta_{1,2}=120^{\circ}].
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Figure 7: A comparison of the predicted contact angle (θpre\theta_{pre}) and the specified contact angle (θ1,2\theta_{1,2}).

IV.5 A compound droplet passing through an irregular channel

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Figure 8: The schematic of a compound droplet passing through an irregular channel.

Unlike the static-state benchmark problems considered above, in this part, we investigate a compound droplet passing through the wavy channel, which is a typical irregular domain with a complex geometrical shape. The configuration of the problem is given in Fig. 8, where a concentric droplet composed of the red inner droplet with R1=L/5R_{1}=L/5 and the blue outer droplet with R2=L/3R_{2}=L/3 is located at (L/2,L/2)(L/2,L/2) of the computational domain. Besides, the top and bottom boundaries of the wavy channel are defined by U(x)=B(x)=0.05Lx/Lsin(3πx/L)U(x)=-B(x)=0.05L\sqrt{x/L}\sin(3\pi x/L). To reflect the effects of different wetting boundary conditions in the DD-CC equations, we introduce two characteristic functions,

ϕ1(x,y)=12+12tanh[2(yL/4B(x))ε0],\phi_{1}(x,y)=\frac{1}{2}+\frac{1}{2}\tanh\left[\frac{2\left(y-L/4-B(x)\right)}{\varepsilon_{0}}\right], (41)
ϕ2(x,y)=1212tanh[2(y3L/4U(x))ε0],\phi_{2}(x,y)=\frac{1}{2}-\frac{1}{2}\tanh\left[\frac{2\left(y-3L/4-U(x)\right)}{\varepsilon_{0}}\right], (42)

and then the characteristic function ϕ\phi and the source term ϕμCi\phi\mu_{C_{i}} appeared in the DD-CC equations can be rewritten as

ϕ(x,y)=ϕ1(x,y)ϕ2(x,y),\phi(x,y)=\phi_{1}(x,y)\phi_{2}(x,y), (43)

and

ϕμCi=j=1N2βijϕ[g(Ci)g(Ci+Cj)]+j=1N3ε4σij(ϕCj)\displaystyle\phi\mu_{C_{i}}=\sum_{j=1}^{N}2\beta_{ij}\phi\left[g^{\prime}\left(C_{i}\right)-g^{\prime}\left(C_{i}+C_{j}\right)\right]+\sum_{j=1}^{N}\frac{3\varepsilon}{4}\sigma_{ij}\nabla\cdot(\phi\nabla C_{j}) (44)
+j=1N3σijqjCjCq(cosθjq1|ϕ1|+cosθjq2|ϕ2|).\displaystyle+\sum_{j=1}^{N}3\sigma_{ij}\sum_{q\neq j}C_{j}C_{q}\left(\cos\theta^{1}_{jq}|\nabla\phi_{1}|+\cos\theta^{2}_{jq}|\nabla\phi_{2}|\right).

In our simulations, a parabolic velocity with the mean velocity uc=0.003u_{c}=0.003 is imposed on the inlet and outlet of the channel, and the other parameters are fixed as L=15L=15, ρ1=ρ2=1.0\rho_{1}=\rho_{2}=1.0, ρ3=0.1\rho_{3}=0.1, σij=0.004\sigma_{ij}=0.004 where iji\neq j, m0=0.01m_{0}=0.01, ε0=0.6\varepsilon_{0}=0.6, ε=8δx\varepsilon=8\delta x, δx=0.1\delta x=0.1, c=40c=40, d0=0.3d_{0}=0.3. We carry out some simulations, and plot the results in Fig. 9. From this figure, one can see that the compound droplet can be separated in different patterns under different wetting properties of the solid walls. For example, as shown in Fig. 9 where θ131,2=120\theta^{1,2}_{13}=120^{\circ} and θ231,2=60\theta^{1,2}_{23}=60^{\circ}, the concentric droplet splits into two blue subdroplets adhered to the solid walls and an unbroken red droplet passes through the channel. In contrast, if θ131,2=60\theta^{1,2}_{13}=60^{\circ} and θ231,2=120\theta^{1,2}_{23}=120^{\circ} [see Fig. 9], the red subdroplets are adhered to the solid walls and the blue droplet can pass through the channel. For the case of θ131=θ232=120\theta^{1}_{13}=\theta^{2}_{23}=120^{\circ} and θ231=θ132=60\theta^{1}_{23}=\theta^{2}_{13}=60^{\circ} shown in Fig. 9, the red and blue droplets can be split from the concentric droplet and then adhered to the top and bottom walls, respectively.

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Figure 9: The dynamics of a compound droplet passing through an irregular channel with (a) θ131,2=120\theta^{1,2}_{13}=120^{\circ} and θ231,2=60\theta^{1,2}_{23}=60^{\circ}, (b) θ131,2=60\theta^{1,2}_{13}=60^{\circ} and θ231,2=120\theta^{1,2}_{23}=120^{\circ}, (c) θ131=θ232=120\theta^{1}_{13}=\theta^{2}_{23}=120^{\circ} and θ231=θ132=60\theta^{1}_{23}=\theta^{2}_{13}=60^{\circ} ( tt^{*} is normalized by L/ucL/u_{c}).

V Conclusions

In this paper, we first developed a DD based conservative and consistent phase-field model for the multiphase flows in complex geometries, which can handle the topological changes of the fluid-fluid interface as well as the irregular fluid-solid interface with different wettability properties. Then we proposed a new LB method for the DD-CC equations and tested the method by four benchmark problems. It is found that the present results are in good agreement with analytical solutions and/or numerical results based on other numerical methods, which illustrates that the DD-CCLB method has a good ability in capturing the multiphase interfacial changes and treating the complex boundary on the irregular solid surface. Finally, the present LB method is also used to study a compound droplet passing through an irregular channel, and the results show that the compound droplet can be separated in different forms under different wetting properties of the solid walls. In a future work, we will consider the DD-CCLB method for the multiphase flows in porous media, which is a more complicated problem and also important in many different fields (e.g., enhanced oil recovery).

Acknowledgements

The computation is completed in the HPC Platform of Huazhong University of Science and Technology. This work is financially supported by the National Natural Science Foundation of China (Grants No. 12072127 and No. 51836003) and the Fundamental Research Funds for the Central Universities, HUST (No. 2021JYCXJJ010).

Appendix A Appendix: The Chapman-Enskog analysis of the LB model for the hybrid AC equation

Appendix B The matched asymptotic analysis on the DD-CH equations

Now we perform a matched asymptotic analysis to show that the DD-CH equation (13a) could converge to the CH equation (4) with the boundary conditions (6) as the interface width parameter ε\varepsilon tends to zero. First, the DD variable YY, which represents u, CiC_{i} or μCi{\mu}_{C_{i}}, can be expanded in the powers of ε\varepsilon in regions close to the boundary (inner expansion) and far from the boundary (outer expansion). On each side far from the domain boundary Ω~\partial\tilde{\Omega}, there exists an outer expansion for the variable Y¯i\bar{Y}_{i},

Y¯i(𝒙;ε)=Y¯i(0)(𝒙)+εY¯i(1)(𝒙)+,i=1,2,\bar{Y}_{i}(\bm{x};\varepsilon)=\bar{Y}_{i}^{(0)}(\bm{x})+\varepsilon\bar{Y}_{i}^{(1)}(\bm{x})+\cdots,\quad i=1,2, (A.1)

where i=1i=1 denotes the inside Ω~\tilde{\Omega} with ϕ=1\phi=1, and i=2i=2 represents the outside Ω~\tilde{\Omega} with ϕ=0\phi=0. Under the assumption of the boundary conditions on a larger and regular domain Ω\Omega, nu¯2=0\textbf{n}\cdot\nabla\bar{\textbf{u}}_{2}=0 and nC¯i2=nμ¯Ci2=0\textbf{n}\cdot\nabla\bar{C}_{i2}=\textbf{n}\cdot\nabla\bar{\mu}_{{C}_{i2}}=0, we can show that Y¯2\bar{Y}_{2} satisfies the original equations automatically. For the case of i=1i=1, inserting the expansion (A.1) into Eqs. (13a) and (14), one can get

tC¯i1(0)+(C¯i1(0)u¯1(0))=j=1N[M(C¯i1(0),C¯j1(0))μ¯Ci1(0)],\partial_{t}\bar{C}_{i1}^{(0)}+\nabla\cdot\left(\bar{C}_{i1}^{(0)}\bar{\textbf{u}}_{1}^{(0)}\right)=\sum_{j=1}^{N}\nabla\cdot\left[M\left(\bar{C}_{i1}^{(0)},\bar{C}_{j1}^{(0)}\right)\nabla\bar{\mu}_{C_{i1}}^{(0)}\right], (A.2a)
μ¯Ci1(0)=j=1N2βij[g(C¯i1(0))g(C¯i1(0)+C¯j1(0))]+j=1N3ε4σijC¯j1(0).\bar{\mu}_{C_{i1}}^{(0)}=\sum_{j=1}^{N}2\beta_{ij}\left[g^{\prime}\left(\bar{C}_{i1}^{(0)}\right)-g^{\prime}\left(\bar{C}_{i1}^{(0)}+\bar{C}_{j1}^{(0)}\right)\right]+\sum_{j=1}^{N}\frac{3\varepsilon}{4}\sigma_{ij}\nabla\cdot\nabla\bar{C}_{j1}^{(0)}. (A.2b)

If Y¯10\bar{Y}^{0}_{1} satisfies the corresponding boundary condition (6) on Ω~\partial\tilde{\Omega}, Y¯1\bar{Y}_{1} is the unique solution of CH equation, which means that the CH equation can be recovered by the DD-CH equation at the leading order 𝒪(ε)\mathcal{O}\left(\varepsilon\right).

Then, we conduct the inner expansion for Y^\hat{Y} associated with local coordinate variables zz and s as

Y^(z,s;ε)=Y^(0)(z,s)+εY^(1)(z,s)+,\hat{Y}(z,\textbf{s};\varepsilon)=\hat{Y}^{(0)}(z,\textbf{s})+\varepsilon\hat{Y}^{(1)}(z,\textbf{s})+\cdots, (A.3)

where ϕ=1\phi=1 as z{z\rightarrow-\infty}, and ϕ=0\phi=0 as z+{z\rightarrow+\infty}. In a overlapped region where both expansions are valid, the following asymptotic matching conditions at the first two leading orders can be derived,

limzY^(0)(z,s)=Y¯1(0)(s),limzY^(1)(z,s)=Y¯1(1)(s)+znY¯1(0),\displaystyle\lim_{z\rightarrow-\infty}\hat{Y}^{(0)}(z,\textbf{s})=\bar{Y}_{1}^{(0)}(\textbf{s}),\quad\lim_{z\rightarrow-\infty}\hat{Y}^{(1)}(z,\textbf{s})=\bar{Y}_{1}^{(1)}(\textbf{s})+z\textbf{n}\cdot\nabla\bar{Y}_{1}^{(0)}, (A.4)
limz+Y^(0)(z,s)=Y¯2(0)(s),limz+Y^(1)(z,s)=Y¯2(1)(s)+znY¯2(0).\displaystyle\lim_{z\rightarrow+\infty}\hat{Y}^{(0)}(z,\textbf{s})=\bar{Y}_{2}^{(0)}(\textbf{s}),\quad\lim_{z\rightarrow+\infty}\hat{Y}^{(1)}(z,\textbf{s})=\bar{Y}_{2}^{(1)}(\textbf{s})+z\textbf{n}\cdot\nabla\bar{Y}_{2}^{(0)}.

At the leading order 𝒪(ε2)\mathcal{O}\left(\varepsilon^{-2}\right), one can obtain

Eq. (13a)j=1N[ϕM(C^i(0),C^j(0))μ^Cjz(0)]z=0,\text{Eq. (\ref{eq:2.13a})}\rightarrow\sum_{j=1}^{N}\left[\phi M\left(\hat{C}_{i}^{(0)},\hat{C}_{j}^{(0)}\right)\hat{\mu}^{(0)}_{C_{jz}}\right]_{z}=0, (A.5)
Eq. (14)j=1N3ε4σij(ϕC^jz(0))z=0.\text{Eq. (\ref{eq:2.14})}\rightarrow\sum_{j=1}^{N}\frac{3\varepsilon}{4}\sigma_{ij}\left(\phi\hat{C}_{jz}^{(0)}\right)_{z}=0. (A.6)

At the next order 𝒪(ε1)\mathcal{O}\left(\varepsilon^{-1}\right), we have

Eq. (13a)j=1N[ϕM(C^i(0),C^j(0))μ^Cjz(1)]z=0,\text{Eq. (\ref{eq:2.13a})}\rightarrow\sum_{j=1}^{N}\left[\phi M\left(\hat{C}_{i}^{(0)},\hat{C}_{j}^{(0)}\right)\hat{\mu}^{(1)}_{C_{jz}}\right]_{z}=0, (A.7)
Eq. (14)j=1N3ε4σij(ϕC^jz(1))z=j=1N3σijϕzqjcosθjqC¯j(0)C¯q(0).\text{Eq. (\ref{eq:2.14})}\rightarrow\sum_{j=1}^{N}\frac{3\varepsilon}{4}\sigma_{ij}\left(\phi\hat{C}_{jz}^{(1)}\right)_{z}=-\sum_{j=1}^{N}3\sigma_{ij}\phi_{z}\sum_{q\neq j}\cos\theta_{jq}\bar{C}_{j}^{(0)}\bar{C}_{q}^{(0)}. (A.8)

Integrating above equations from -\infty to ++\infty with respect to zz, one can obtain

limzμ^Ciz(1)=0,limzC^iz(1)=ji4εcosθijC¯i(0)C¯j(0).\lim_{z\rightarrow-\infty}\hat{\mu}^{(1)}_{C_{iz}}=0,\quad\lim_{z\rightarrow-\infty}\hat{C}_{iz}^{(1)}=\sum_{j\neq i}\frac{4}{\varepsilon}\cos\theta_{ij}\bar{C}_{i}^{(0)}\bar{C}_{j}^{(0)}. (A.9)

Using the matching condition (A.4), we can derive

nμ¯Ci1(0)=0,nC¯i1(0)=ji4εcosθijC¯i(0)C¯j(0).\textbf{n}\cdot\nabla\bar{\mu}_{C_{i1}}^{(0)}=0,\quad\textbf{n}\cdot\nabla\bar{C}_{i1}^{(0)}=\sum_{j\neq i}\frac{4}{\varepsilon}\cos\theta_{ij}\bar{C}_{i}^{(0)}\bar{C}_{j}^{(0)}. (A.10)

The outer solutions μ¯Ci1(0)\bar{\mu}_{C_{i1}}^{(0)} and C¯i1(0)\bar{C}_{i1}^{(0)} satisfy the original boundary conditions (6), which indicates the DD-CH equation can recover the original CH equation at the leading order.

Appendix C The direct Taylor expansion of the DD-CCLB method for the DD-CC equations

We now carry out the direct Taylor expansion of Eqs. (15) and (16) to derive the DD-CC equations (13c). First, we apply the Taylor expansion to the left hand sides of Eqs. (15) and (16) Chai2020Multiple ; Chai2023Multiple ; Chen1998LATTICEBM ; Krueger2016TheLB ; Succi2001TheLB ,

l=1Nδtll!Dplfpi+O(δtN+1)=Λpqfi(fqifqi,eq)+δt(δpqΛpqfi2)Fqi,\sum_{l=1}^{N}\frac{\delta t^{l}}{l!}D_{p}^{l}f^{i}_{p}+O\left(\delta t^{N+1}\right)=-\Lambda_{pq}^{f^{i}}\left(f^{i}_{q}-f_{q}^{i,eq}\right)+\delta t\left(\delta_{pq}-\frac{\Lambda_{pq}^{f^{i}}}{2}\right)F^{i}_{q}, (B.1)
l=1Nδtll!Dplgp+O(δtN+1)=Λpqg(gqgqeq)+δt(δpqΛpqg2)Gq,\sum_{l=1}^{N}\frac{\delta t^{l}}{l!}D_{p}^{l}g_{p}+O\left(\delta t^{N+1}\right)=-\Lambda_{pq}^{g}\left(g_{q}-g_{q}^{eq}\right)+\delta t\left(\delta_{pq}-\frac{\Lambda_{pq}^{g}}{2}\right)G_{q}, (B.2)

where Dp=t+𝐜pD_{p}=\partial_{t}+\mathbf{c}_{p}\cdot\nabla. Based on above equations, fpi=fpi,eq+fpi,nef^{i}_{p}=f_{p}^{i,eq}+f_{p}^{i,ne} and gp=gpeq+gpneg_{p}=g_{p}^{eq}+g_{p}^{ne}, we can find fpi,ne=O(δt)f_{p}^{i,ne}=O(\delta t) and gpne=O(δt)g_{p}^{ne}=O(\delta t). According to Eqs. (B.1) and (B.2), the following equations at different orders of δt\delta t can be obtained,

Dpfpi,eq=Λpqfiδtfqi,ne+(δpqΛpqfi2)Fqi+O(δt),\displaystyle D_{p}f_{p}^{i,eq}=-\frac{\Lambda^{f^{i}}_{pq}}{\delta t}f_{q}^{i,ne}+\left(\delta_{pq}-\frac{\Lambda^{f^{i}}_{pq}}{2}\right)F^{i}_{q}+O(\delta t), (B.3)
Dpfpi,eq+Dp(δpqΛpqfi2)(fqi,ne+δt2Fqi)=Λpqfiδtfqi,ne+(δpqΛpqfi2)Fqi\displaystyle D_{p}f_{p}^{i,eq}+D_{p}\left(\delta_{pq}-\frac{\Lambda^{f^{i}}_{pq}}{2}\right)\left(f_{q}^{i,ne}+\frac{\delta t}{2}F^{i}_{q}\right)=-\frac{\Lambda^{f^{i}}_{pq}}{\delta t}f_{q}^{i,ne}+\left(\delta_{pq}-\frac{\Lambda^{f^{i}}_{pq}}{2}\right)F^{i}_{q}
+O(δt2),\displaystyle+O\left(\delta t^{2}\right),
Dpgpeq\displaystyle D_{p}g_{p}^{eq} =Λpqgδtgqne+(δpqΛpqg2)Gq+O(δt),\displaystyle=-\frac{\Lambda^{g}_{pq}}{\delta t}g_{q}^{ne}+\left(\delta_{pq}-\frac{\Lambda^{g}_{pq}}{2}\right)G_{q}+O(\delta t), (B.4)
Dpgpeq+Dp(δpqΛpqg2)(gqne+δt2Gq)\displaystyle D_{p}g_{p}^{eq}+D_{p}\left(\delta_{pq}-\frac{\Lambda^{g}_{pq}}{2}\right)\left(g_{q}^{ne}+\frac{\delta t}{2}G_{q}\right) =Λpqgδtgqne+(δpqΛpqg2)Gq+O(δt2).\displaystyle=-\frac{\Lambda^{g}_{pq}}{\delta t}g_{q}^{ne}+\left(\delta_{pq}-\frac{\Lambda^{g}_{pq}}{2}\right)G_{q}+O\left(\delta t^{2}\right).

From Eqs. (18), (19), (21) and (22), one can see that Λpq{\Lambda}_{pq}, fpi,eqf_{p}^{i,eq}, FpiF^{i}_{p}, gpeqg_{p}^{eq} and GpG_{p} satisfy the following conditions,

𝐞pΛpq=s0𝐞q,𝐜pΛpq=𝐒1𝐜q,𝐜p𝐜pΛpq=𝐒2(𝐜q𝐜q𝐜q𝐜qd𝐈)+cs2s0𝐞q𝐈,\sum\mathbf{e}_{p}{\Lambda}_{pq}=s_{0}\mathbf{e}_{q},\quad\sum\mathbf{c}_{p}{\Lambda}_{pq}=\mathbf{S}_{1}\mathbf{c}_{q},\quad\sum\mathbf{c}_{p}\mathbf{c}_{p}{\Lambda}_{pq}=\mathbf{S}_{2}(\mathbf{c}_{q}\mathbf{c}_{q}-\frac{\mathbf{c}_{q}\cdot\mathbf{c}_{q}}{d}\mathbf{I})+c_{s}^{2}s_{0}\mathbf{e}_{q}\mathbf{I}, (B.5a)
pfpi,eq=ϕCi,pcpfpi,eq=ϕCiu,pcpcpfpi,eq=cs2ηiϕμCiI,\sum_{p}f_{p}^{i,eq}=\phi C_{i},\quad\sum_{p}\textbf{c}_{p}f_{p}^{i,eq}=\phi C_{i}\textbf{u},\quad\sum_{p}\textbf{c}_{p}\textbf{c}_{p}f_{p}^{i,eq}=c_{s}^{2}\eta_{i}\phi\mu_{C_{i}}\textbf{I}, (B.5b)
pFpi=0,pcpFpi=t(ϕCiu)+cs2ηi(μCiϕSi),\sum_{p}F^{i}_{p}=0,\quad\sum_{p}\textbf{c}_{p}F^{i}_{p}=\partial_{t}(\phi C_{i}\textbf{u})+c_{s}^{2}\eta_{i}(\mu_{C_{i}}\nabla\phi-\textbf{S}_{i}), (B.5c)
pgpeq=ρ0,pcpgpeq=ϕρu,\displaystyle\sum_{p}g_{p}^{eq}=\rho_{0},\quad\sum_{p}\textbf{c}_{p}g_{p}^{eq}=\phi\rho\textbf{u}, (B.5d)
pcpcpgpeq=ϕρuu+ϕmCu+ϕumC2+ϕpI,\displaystyle\sum_{p}\textbf{c}_{p}\textbf{c}_{p}g_{p}^{eq}=\phi\rho\textbf{u}\textbf{u}+\frac{\phi\textbf{m}^{C}\textbf{u}+\phi\textbf{u}\textbf{m}^{C}}{2}+\phi p\textbf{I},
pcpcpcpgpeq=ϕρ(cs2𝚫+δ¯(4))u,\displaystyle\sum_{p}\textbf{c}_{p}\textbf{c}_{p}\textbf{c}_{p}g_{p}^{eq}=\phi\rho(c_{s}^{2}\mathbf{\Delta}+\bar{\delta}^{(4)})\cdot\textbf{u},
pGp=ϕuρ,pcpGp=F,pcpcpGp=cs2ϕ𝐮ρ𝐈+𝐌2G,\sum_{p}G_{p}=\phi\textbf{u}\cdot\nabla\rho,\quad\sum_{p}\textbf{c}_{p}G_{p}=\textbf{F},\quad\sum_{p}\textbf{c}_{p}\textbf{c}_{p}G_{p}=c_{s}^{2}\phi\mathbf{u}\cdot\nabla\rho\mathbf{I}+\mathbf{M}^{2G}, (B.5e)

where s0s_{0} is the relaxation parameter, 𝐒1\mathbf{S}_{1} and 𝐒2\mathbf{S}_{2} are two d×dd\times d and d2×d2d^{2}\times d^{2} invertible relaxation matrices, 𝐌2G\mathbf{M}^{2G} is a second-order tensor to be determined below. Δαβγη=δαβδγη+δαγδβη+δβγδαη\Delta_{\alpha\beta\gamma\eta}=\delta_{\alpha\beta}\delta_{\gamma\eta}+\delta_{\alpha\gamma}\delta_{\beta\eta}+\delta_{\beta\gamma}\delta_{\alpha\eta} and δ¯(4)\bar{\delta}^{(4)} is defined by δ¯(4)=c23cs2\bar{\delta}^{(4)}=c^{2}-3c_{s}^{2} with α=β=γ=η\alpha=\beta=\gamma=\eta, otherwise δ¯(4)=0\bar{\delta}^{(4)}=0. In addition, from Eqs. (B.4), (B.5d) and (B.5e), we have

pgpne=δt2pGp=δt2ϕuρ,pcpgpne=δt2pcpGp=δt2F.\sum_{p}g_{p}^{ne}=-\frac{\delta_{t}}{2}\sum_{p}G_{p}=-\frac{\delta_{t}}{2}\phi\textbf{u}\cdot\nabla\rho,\quad\sum_{p}\textbf{c}_{p}g_{p}^{ne}=-\frac{\delta_{t}}{2}\sum_{p}\textbf{c}_{p}G_{p}=-\frac{\delta_{t}}{2}\textbf{F}. (B.6)

Summing Eq. (B.3) over pp, one can obtain

t(ϕCi)+(ϕCiu)\displaystyle\partial_{t}(\phi C_{i})+\nabla\cdot(\phi C_{i}\textbf{u}) =O(δt),\displaystyle=O(\delta t), (B.7)
t(ϕCi)+(ϕCiu)+(IS1fi2)[pcpfpi,ne+δt2pcpFpi]\displaystyle\partial_{t}(\phi C_{i})+\nabla\cdot(\phi C_{i}\textbf{u})+\nabla\cdot\left(\textbf{I}-\frac{\textbf{S}^{{f}^{i}}_{1}}{2}\right)\left[\sum_{p}\textbf{c}_{p}f_{p}^{i,ne}+\frac{\delta_{t}}{2}\sum_{p}\textbf{c}_{p}F_{p}^{i}\right] =O(δt2).\displaystyle=O(\delta t^{2}).

With the aid of Eq. (B.3), we can determine pcpfpi,ne\sum_{p}\textbf{c}_{p}f_{p}^{i,ne} as

pcpfpi,ne=δt(S1fi)1[t(ϕCiu)+cs2ηiϕμCiI(IS1fi2)pcpFpi]+O(δt2).\sum_{p}\textbf{c}_{p}f_{p}^{i,ne}=-\delta_{t}(\textbf{S}^{{f}^{i}}_{1})^{-1}\left[\partial_{t}(\phi C_{i}\textbf{u})+c_{s}^{2}\nabla\eta_{i}\phi\mu_{C_{i}}\textbf{I}-\left(\textbf{I}-\frac{{\textbf{S}}_{1}^{{f}^{i}}}{2}\right)\sum_{p}\textbf{c}_{p}F_{p}^{i}\right]+O(\delta t^{2}). (B.8)

Combining Eq. (B.7) with m0=(1/s1fi1/2)cs2ηiδtm_{0}=(1/s^{{f}^{i}}_{1}-1/2)c_{s}^{2}\eta_{i}\delta t, yields Eq. (13a) at the order of O(δt2)O(\delta t^{2}). Following the same way, summing Eq. (B.4) and cp\textbf{c}_{p} ×\times Eq. (B.4), one can obtain

tϕρ0+(ϕρu)=ϕuρ+O(δt2),\partial_{t}\phi\rho_{0}+\nabla\cdot(\phi\rho\textbf{u})=\phi\textbf{u}\cdot\nabla\rho+O(\delta t^{2}),\\ (B.9)
t(ϕρu)\displaystyle\partial_{t}(\phi\rho\textbf{u}) +(ϕρuu+ϕmCu+ϕumC2+ϕpI)\displaystyle+\nabla\cdot\left(\phi\rho\textbf{u}\textbf{u}+\frac{\phi\textbf{m}^{C}\textbf{u}+\phi\textbf{u}\textbf{m}^{C}}{2}+\phi p\textbf{I}\right) (B.10)
+p𝐜p𝐜p(δpqΛpqg2)(gpne+δt2Gq)=F+O(δt2).\displaystyle+\nabla\cdot\sum_{p}\mathbf{c}_{p}\mathbf{c}_{p}\left(\delta_{pq}-\frac{\Lambda^{g}_{pq}}{2}\right)\left(g_{p}^{ne}+\frac{\delta t}{2}G_{q}\right)=\textbf{F}+O(\delta t^{2}).

With the help of Eq. (B.4), we can rewrite Eq. (B.10) as

t(ϕρu)\displaystyle\partial_{t}(\phi\rho\textbf{u}) +(ϕρuu+ϕmCu+ϕumC2+ϕpI)\displaystyle+\nabla\cdot\left(\phi\rho\textbf{u}\textbf{u}+\frac{\phi\textbf{m}^{C}\textbf{u}+\phi\textbf{u}\textbf{m}^{C}}{2}+\phi p\textbf{I}\right) (B.11)
δtp𝐜p𝐜p[(Λpqg)1δpq2](DqgqeqGq)=F+O(δt2).\displaystyle-\nabla\cdot\delta_{t}\sum_{p}\mathbf{c}_{p}\mathbf{c}_{p}\left[\left(\Lambda^{g}_{pq}\right)^{-1}-\frac{\delta_{pq}}{2}\right]\left(D_{q}g_{q}^{eq}-G_{q}\right)=\textbf{F}+O(\delta t^{2}).

In addition, from Eqs. (B.5a), (B.5d) and (B.5e), we get

p𝐜p𝐜p[(Λpqg)1δpq2](DqgqeqGq)\displaystyle\sum_{p}\mathbf{c}_{p}\mathbf{c}_{p}\left[\left(\Lambda^{g}_{pq}\right)^{-1}-\frac{\delta_{pq}}{2}\right]\left(D_{q}g_{q}^{eq}-G_{q}\right) (B.12)
=\displaystyle= [(𝑺2g)1𝐈2]q𝐜qα𝐜qβ(DqgqeqGq)(𝑺2g)1δαβq𝐜q𝐜q(DqgqeqGq)d\displaystyle\left[({\bm{S}^{g}_{2}})^{-1}-\frac{\mathbf{I}}{2}\right]\sum_{q}\mathbf{c}_{q\alpha}\mathbf{c}_{q\beta}(D_{q}g_{q}^{eq}-G_{q})-({\bm{S}^{g}_{2}})^{-1}\delta_{\alpha\beta}\frac{\sum_{q}\mathbf{c}_{q}\cdot\mathbf{c}_{q}(D_{q}g_{q}^{eq}-G_{q})}{d}
+(s0g)1cs2δαβq(DqgqeqGq),\displaystyle+({s^{g}_{0}})^{-1}c_{s}^{2}\delta_{\alpha\beta}\sum_{q}(D_{q}g_{q}^{eq}-G_{q}),

then we mark Παβ1=pcpαcpβ(DpgpeqGp)\Pi_{\alpha\beta}^{1}=\sum_{p}\textbf{c}_{p\alpha}\textbf{c}_{p\beta}(D_{p}g_{p}^{eq}-G_{p}), Π2=pcpcp(DpgpeqGp)\Pi^{2}=\sum_{p}\textbf{c}_{p}\cdot\textbf{c}_{p}(D_{p}g_{p}^{eq}-G_{p}), and Π3=p(DpgpeqGp)\Pi^{3}=\sum_{p}(D_{p}g_{p}^{eq}-G_{p}), and they can be calculated by

Παβ1=\displaystyle\Pi_{\alpha\beta}^{1}= t(ϕmαCuβ+ϕuαmβC2)+cs2[α(ϕρuβ)+β(ϕρuα)]+γ(ϕρδ¯αβγη(4)uη)\displaystyle\partial_{t}\left(\frac{\phi{m}_{\alpha}^{C}u_{\beta}+\phi u_{\alpha}m_{\beta}^{C}}{2}\right)+c_{s}^{2}\left[\nabla_{\alpha}(\phi\rho u_{\beta})+\nabla_{\beta}(\phi\rho u_{\alpha})\right]+\nabla_{\gamma}(\phi\rho\bar{\delta}_{\alpha\beta\gamma\eta}^{(4)}u_{\eta}) (B.13)
+cs2ϕuγγρδαβcs2ϕuγγρδαβMαβ2G,\displaystyle+c_{s}^{2}\phi u_{\gamma}\nabla_{\gamma}\rho\delta_{\alpha\beta}-c_{s}^{2}\phi u_{\gamma}\nabla_{\gamma}\rho\delta_{\alpha\beta}-{M}^{2G}_{\alpha\beta},
Π2=\displaystyle\Pi^{2}= t(ϕmαCuα)+2cs2α(ϕρuα)+γ(ϕρδ¯ααγη(4)uη)+dcs2ϕuααρ\displaystyle\partial_{t}\left(\phi{m}_{\alpha}^{C}u_{\alpha}\right)+2c_{s}^{2}\nabla_{\alpha}(\phi\rho{u}_{\alpha})+\nabla_{\gamma}(\phi\rho\bar{\delta}_{\alpha\alpha\gamma\eta}^{(4)}u_{\eta})+dc_{s}^{2}\phi{u}_{\alpha}\nabla_{\alpha}\rho
dcs2ϕuααρMαα2G,\displaystyle-dc_{s}^{2}\phi{u}_{\alpha}\nabla_{\alpha}\rho-{M}^{2G}_{\alpha\alpha},
Π3=\displaystyle\Pi^{3}= tϕρ0+(ϕρu)ϕuρ.\displaystyle\partial_{t}\phi\rho_{0}+\nabla\cdot(\phi\rho\textbf{u})-\phi\textbf{u}\cdot\nabla\rho.

By taking the following expression of 𝐌2G\mathbf{M}^{2G},

𝐌2G=t(ϕ𝐦C𝐮+ϕ𝐮𝐦C2)+cs2[𝐮(ϕρ)+(ϕρ)𝐮]+(c23cs2)𝐮(ϕρ)𝐈,\mathbf{M}^{2G}=\partial_{t}\left(\frac{\phi\mathbf{m}^{C}\mathbf{u}+\phi\mathbf{um}^{C}}{2}\right)+c_{s}^{2}\left[\mathbf{u}\nabla(\phi\rho)+\nabla(\phi\rho)\mathbf{u}\right]+(c^{2}-3c_{s}^{2})\mathbf{u}\cdot\nabla(\phi\rho)\mathbf{I}, (B.14)

and substituting Eq. (B.13) into Eq. (B.11), and this equation can be rewritten as

t(ϕρu)+(ϕρuu+ϕmCu+ϕumC2+ϕpI)=τ+F+O(δt2),\partial_{t}(\phi\rho\textbf{u})+\nabla\cdot\left(\phi\rho\textbf{u}\textbf{u}+\frac{\phi\textbf{m}^{C}\textbf{u}+\phi\textbf{u}\textbf{m}^{C}}{2}+\phi p\textbf{I}\right)=\nabla\cdot\tau+\textbf{F}+O(\delta t^{2}), (B.15)

where

τ=δtϕρ[(𝑺2g)1I2][cs2(u+(u)T)+(δ¯(4)u)].\tau=\delta_{t}\phi\rho\left[({\bm{S}^{g}_{2}})^{-1}-\frac{\textbf{I}}{2}\right]\left[c_{s}^{2}(\nabla\textbf{u}+(\nabla\textbf{u})^{T})+\nabla\cdot(\bar{\delta}^{(4)}\cdot\textbf{u})\right]. (B.16)

Thus the macroscopic incompressible DD-NS equations can be recovered at the order of O(δt2)O(\delta t^{2}) with

ν=(1s21g12)c2cs22δt,ν=(1s22g12)cs2δt.\nu=\left(\frac{1}{s^{g}_{21}}-\frac{1}{2}\right)\frac{c^{2}-c_{s}^{2}}{2}\delta t,\quad\nu=\left(\frac{1}{s^{g}_{22}}-\frac{1}{2}\right)c_{s}^{2}\delta t. (B.17)

Appendix D The computation of Pressure

Now let us focus on the computation of pressure PP. From Eq. (B.4), one can obtain the zeroth direction of gpneg_{p}^{ne} ,

g0ne=\displaystyle g_{0}^{ne}= δtt[(Λ0qg)1gqeq]+δt(Λ0q1GqG02)+O(δt2)\displaystyle-\delta t\partial_{t}\left[(\Lambda^{g}_{0q})^{-1}g_{q}^{eq}\right]+\delta t\left(\Lambda_{0q}^{-1}G_{q}-\frac{G_{0}}{2}\right)+O\left(\delta t^{2}\right) (C.1)
=\displaystyle= δtKc2s21gt(ϕ𝐦𝐮)+δt[K(s21g2)2c2s21gt(ϕ𝐦𝐮)+Hs21g𝐮(ϕρ)\displaystyle\delta t\frac{K}{c^{2}s^{g}_{21}}\partial_{t}(\phi\mathbf{m}\cdot\mathbf{u})+\delta t\left[\frac{K\left(s^{g}_{21}-2\right)}{2c^{2}s^{g}_{21}}\partial_{t}(\phi\mathbf{m}\cdot\mathbf{u})+\frac{H}{s^{g}_{21}}\mathbf{u}\cdot\nabla(\phi\rho)\right.
+K(1d0)(2s0g)2s0gϕ𝐮ρ].\displaystyle\left.+\frac{K(1-d_{0})(2-s^{g}_{0})}{2s^{g}_{0}}\phi\mathbf{u}\cdot\nabla\rho\right].

According to above equation and g0=g0eq+g0neg_{0}=g_{0}^{\mathrm{eq}}+g_{0}^{ne}, we have

1ω0cs2ϕP=\displaystyle\frac{1-\omega_{0}}{c_{s}^{2}}\phi P= ϕρ0(g0g0ne)+s0\displaystyle\phi\rho_{0}-\left(g_{0}-g_{0}^{ne}\right)+s_{0} (C.2)
=\displaystyle= p0gp+[12+K(1d0)(2s0g)2s0g]δtϕ𝐮ρ+δtK2c2t(ϕ𝐦ϕC𝐮)\displaystyle\sum_{p\neq 0}g_{p}+\left[\frac{1}{2}+\frac{K(1-d_{0})(2-s^{g}_{0})}{2s^{g}_{0}}\right]\delta t\phi\mathbf{u}\cdot\nabla\rho+\delta t\frac{K}{2c^{2}}\partial_{t}\left(\phi\mathbf{m}^{\phi C}\cdot\mathbf{u}\right)
+δtHs21g𝐮(ϕρ)+s0+O(δt2).\displaystyle+\delta t\frac{H}{s^{g}_{21}}\mathbf{u}\cdot\nabla(\phi\rho)+s_{0}+O\left(\delta t^{2}\right).

Neglecting the truncation error term O(δt2)O\left(\delta t^{2}\right), one can obtain the computational scheme (30) for pressure PP.

Appendix E Analytical solution of the equilibrium shape of a quaternary-phase compound drop

Refer to caption
Figure 10: The configuration for the equilibrium shape of a quaternary-phase compound drop.

The analytical solution for the shape of a compound drop on the idea wall can be derived based on the mass conservation and force balance. Now we give some details on how to derive the analytical solution. Under the assumption of θ12=90\theta_{12}=90^{\circ}, the equilibrium shape of the quaternary-phase compound drop is shown in Fig. 10, where some variables about the angles are denoted by x18x_{1-8}, and the lengths of FB¯\overline{FB} and FG¯\overline{FG} are set as x9,10x_{9,10}. According to the definition of the contact angle, we can easily obtain the following relations,

x1+x2=θ14,x5+x6=θ23,x7+x8=θ34,\displaystyle x_{1}+x_{2}=\theta_{14},\quad x_{5}+x_{6}=\theta_{23},\quad x_{7}+x_{8}=\theta_{34}, (D.1)
x1x2+π2=φ1,x3+x4+π2=φ2,\displaystyle x_{1}-x_{2}+\frac{\pi}{2}=\varphi_{1},\quad x_{3}+x_{4}+\frac{\pi}{2}=\varphi_{2},
x3+x5+πx4x6=φ3,x6+x7x5x8=φ4.\displaystyle x_{3}+x_{5}+\pi-x_{4}-x_{6}=\varphi_{3},\quad x_{6}+x_{7}-x_{5}-x_{8}=\varphi_{4}.

When the initial radius RR of a compound droplet is given, the initial areas of three droplets can be obtained by Sf1,2,3S_{f{1,2,3}}, then we can derive the expression of the areas of the circular segments:

S1=x1sinx1cosx14sin2x1cos2x1x92,\displaystyle S_{1}=\frac{x_{1}-\sin x_{1}\cos x_{1}}{4\sin^{2}x_{1}\cos^{2}x_{1}}x_{9}^{2}, (D.2)
S2=x3sinx3cosx34sin2x3x102,\displaystyle S_{2}=\frac{x_{3}-\sin x_{3}\cos x_{3}}{4\sin^{2}x_{3}}x_{10}^{2},
S3=x5sinx5cosx54sin2x5sin2(πx6)(x9+x10sinx4)2,\displaystyle S_{3}=\frac{x_{5}-\sin x_{5}\cos x_{5}}{4\sin^{2}x_{5}\sin^{2}\left(\pi-x_{6}\right)}\left(x_{9}+x_{10}\sin x_{4}\right)^{2},
S4=x7sinx7cosx74sin2x7sin2x8(x9+x10sinx4)2.\displaystyle S_{4}=\frac{x_{7}-\sin x_{7}\cos x_{7}}{4\sin^{2}x_{7}\sin^{2}x_{8}}\left(x_{9}+x_{10}\sin x_{4}\right)^{2}.

In addition, the areas of the triangles AFB\triangle AFB, CGE\triangle CGE, CGE\triangle CGE and the trapezoid BDGF\square BDGF can be determined by

SAFB=x922tanx2,\displaystyle S_{\triangle AFB}=\frac{x_{9}^{2}}{2\tan x_{2}}, (D.3)
SDGE=(x9+x10sinx4)22tanx8,\displaystyle S_{\triangle DGE}=\frac{\left(x_{9}+x_{10}\sin x_{4}\right)^{2}}{2\tan x_{8}},
SCGD=(x9+x10sinx4)22tan(πx6),\displaystyle S_{\triangle CGD}=\frac{\left(x_{9}+x_{10}\sin x_{4}\right)^{2}}{2\tan\left(\pi-x_{6}\right)},
SBDGF=2x9+x10sinx42x10cosx4.\displaystyle S_{\square BDGF}=\frac{2x_{9}+x_{10}\sin x_{4}}{2}x_{10}\cos x_{4}.

Therefore, the following equivalence relations of the areas of the compound droplet hold

Sf1=S1+SAFB,\displaystyle S_{f_{1}}=S_{1}+S_{\triangle AFB}, (D.4)
Sf2=S2+S3+SBDGFSCGD,\displaystyle S_{f_{2}}=S_{2}+S_{3}+S_{\square BDGF}-S_{\triangle CGD},
Sf3=S4S3+SCGD+SEGD.\displaystyle S_{f_{3}}=S_{4}-S_{3}+S_{\triangle CGD}+S_{\triangle EGD}.

If the physical quantities θ14\theta_{14}, θ23\theta_{23}, θ34\theta_{34}, φ1\varphi_{1}, φ2\varphi_{2}, φ3\varphi_{3} and φ4\varphi_{4} are fixed, Eqs. (D.1) and (D.4) constitute a closed system for the variables x110x_{1-10}, and their solutions can thus be uniquely determined. When these variables are given, the analytical shape of the compound drop at equilibrium can also be uniquely determined. Then the spreading lengths of phases 1, 2, 3 denoted by L1L_{1}, L2L_{2}, and L3L_{3} can be expressed as

L1=AB¯=x9tanx2,\displaystyle L_{1}=\overline{AB}=\frac{x_{9}}{\tan x_{2}}, (D.5)
L2=BC¯=x10cosx4x9+x10sinx4tan(πx6),\displaystyle L_{2}=\overline{BC}={x_{10}}\cos x_{4}-\frac{x_{9}+x_{10}\sin x_{4}}{\tan(\pi-x_{6})},
L3=CE¯=x10cosx4x9+x10sinx4tanx8+tan(πx6).\displaystyle L_{3}=\overline{CE}={x_{10}}\cos x_{4}-\frac{x_{9}+x_{10}\sin x_{4}}{\tan x_{8}+\tan(\pi-x_{6})}.

The solutions of these equations cannot be given explicitly, and we choose to numerically solve them by using the Newton iteration method and show some results in Table 3.

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