1. Introduction
Gravity current is a flow event driven by horizontal pressure gradient. This pressure gradient can originate from horizontal density differences caused by variations in temperature, salinity, etc. or from the settlement of suspended particles (Meiburg, Radhakrishnan & Nasr-Azadani Reference Meiburg, Radhakrishnan and Nasr-Azadani2015). The corresponding flows are known as compositional gravity current, of which salinity-driven (SD) gravity current is taken as an example in this work, as well as particle-driven (PD) gravity current. Such flow occurs widely in natural environments, such as turbidity currents on deep-sea continental slopes, saltwater mazes at estuaries, sandstorms in the atmosphere, etc. A thorough investigation of gravity current is of great significance for understanding material transport and deposition processes in the environment, as well as exposing dynamic processes in ocean and estuarine areas (Parker, Fukushima & Pantin Reference Parker, Fukushima and Pantin1986; Böttner et al. Reference Böttner, Stevenson, Englert, Schönke, Pandolpho, Geersen, Feldens and Krastel2024).
Numerous researchers (Bonnecaze, Huppert & Lister Reference Bonnecaze, Huppert and Lister1993; Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2005; He et al. Reference He, Zhao, Hu, Yu and Lin2018) have long been interested in the similarities and differences in the dynamic processes between PD and SD gravity current. The main dynamic processes of both are controlled by gravity, and both include core features such as stratification, mixing and convection. However, PD gravity current is distinct from SD gravity current due to the complex settling behaviour of the particles and the intricate fluid–particle interactions.
The front velocity of the gravity current in the early stages is approximately independent of the particle settling velocity (Nasr-Azadani & Meiburg Reference Nasr-Azadani and Meiburg2014; He et al. Reference He, Zhao, Hu, Yu and Lin2018). The longitudinal length of the current increases linearly in proportion to time
$t$
when invading shallow ambient fluids (Bonnecaze et al. Reference Bonnecaze, Huppert and Lister1993), corresponding to the constant-velocity slumping stage. After that, the increase in particle settling velocity leads to the acceleration of particle deposition, which reduces the driving force and ultimately the forward velocity of the current (Bonnecaze et al. Reference Bonnecaze, Huppert and Lister1993; Huang, Imran & Pirmez Reference Huang, Imran and Pirmez2008; Nasr-Azadani & Meiburg Reference Nasr-Azadani and Meiburg2014; Nasr-Azadani, Meiburg & Kneller Reference Nasr-Azadani, Meiburg and Kneller2018) – it will reduce the flow height near the head (Nasr-Azadani & Meiburg Reference Nasr-Azadani and Meiburg2014) and weaken the backflow formed by the lock-exchange current (Huang et al. Reference Huang, Imran and Pirmez2008). As the particle settling velocity increases from zero, the density stratification close to the interface weakens, increasing the generation of turbulent kinetic energy and resulting in a decreasing velocity gradient (Kneller et al. Reference Kneller, Nasr-Azadani, Radhakrishnan and Meiburg2016). Thus, the gradient Richardson number decreases, making the current interface more unstable (Kneller et al. Reference Kneller, Nasr-Azadani, Radhakrishnan and Meiburg2016; Nasr-Azadani et al. Reference Nasr-Azadani, Meiburg and Kneller2018). According to He et al. (Reference He, Zhao, Hu, Yu and Lin2018), the particle settling velocity has no bearing on the current entrainment. They attributed it to the balance between the entrainment enhancement induced by the weakening of stratification and the entrainment weakening caused by the decrease in current velocity, which is consistent with the conclusion of Nasr-Azadani et al. (Reference Nasr-Azadani, Meiburg and Kneller2018). Generally, the evolution characteristics of PD current and SD current during the acceleration phase do not differ significantly. The distinction between these two becomes more noticeable after they reach the slumping stage with a constant forward velocity, which is typically ascribed to the particle sedimentation effect. However, the specific mechanism of particle settling on current is not yet clear.
In addition, this begs the question: How are PD gravity current and SD gravity current associated with one another? Clarifying this transition regime is essential to comprehending the dynamics of gravity current. In real environments like estuaries and marine sedimentary areas, particles and salinity often influence the evolution of gravity current simultaneously, creating a complex phenomenon known as salinity–particle dual-driven (SPDD) gravity current. The two factors may coexist and interact to produce more intricate flow phenomena. Some researchers have become intrigued by this phenomenon since the late 20th century (Gladstone & Woods Reference Gladstone and Woods2000; Huang et al. Reference Huang, Imran and Pirmez2008) and theoretically and experimentally investigated its mechanism. Previous research has shown that the PD current has a stronger turbulent wake region on the current interface and reaches higher elevation than the SPDD current, despite moving more slowly. They ascribed the discrepancy to the varying densities of interstitial fluid. Currently, more research is required to fully comprehend how the interstitial fluid influences the current evolution.
In the manner of mathematical modelling of gravity current, it is possible to degenerate the convection–diffusion equation of PD current to the case of SD current by assuming that the particle phase is regarded as a continuous medium and the particle settling velocity is considered to be zero (Kneller et al. Reference Kneller, Nasr-Azadani, Radhakrishnan and Meiburg2016). Alternatively, the discrete element method (DEM) has emerged as a new tool for studying particle motion in PD current (Jing et al. Reference Jing, Yang, Kwok and Sobral2019; Xie et al. 2023a,b; Lu et al. Reference Lu, Liu, Xie, Sun, Yang and Guo2024) in recent years. Accurately describing the forces acting on each particle and tracking particles’ trajectory are two benefits of this method that can aid in a thorough analysis of the fluid–particle interaction during the current, especially that between varying interstitial fluids and particles. Based on this, this work develops a direct numerical simulation (DNS)-DEM coupled model to analyse the coupling between miscible fluid systems and discrete particles, specifically focusing on SPDD gravity currents. Previous studies have developed numerical models for SP coupled gravity currents (Shringarpure, Cantero & Balachandar Reference Shringarpure, Cantero and Balachandar2015; He et al. Reference He, Zhao, Zhu and Hu2019). Unlike the Eulerian–Eulerian model used in prior research, our simulation of the fluid phase does not rely on the Boussinesq assumption. We employ the concentration transport equation to describe salinity convection–diffusion behaviour, consistent with the approach adopted by He et al. (Reference He, Zhao, Zhu and Hu2019), rather than treating salinity as constant as Shringarpure et al. (Reference Shringarpure, Cantero and Balachandar2015) did. Furthermore, we utilize DEM to simulate the behaviour of discrete particles, whereas earlier studies typically employed the concentration transport equation to describe sediment transport under the assumption of negligible sediment response time. In § 2, the numerical model is introduced. The transition regimes between PD and SD gravity currents are revealed in § 3. Lastly, § 4 provides the conclusions.
2. Description of numerical method
2.1. Governing equations
A DNS-DEM coupled model is developed to simulate the SPDD gravity current. Direct numerical simulation is responsible for modelling the miscible fluid, and DEM is for the particle motion. The Navier–Stokes equations without the Boussinesq approximation are employed in DNS as follows:
where
$\alpha _{\!f}$
is the volume fraction of the fluid phase, in which
$\alpha _{\!f} = 1 - \alpha _p$
with
$\alpha _p$
being the particle volume fraction;
$\rho _{\!f} = \alpha _s \rho _{s} + \alpha _w \rho _{w}$
is the fluid density with
$\alpha _s$
and
$\alpha _w$
denoting the relative volume fractions of saline fluid and water, respectively, which represent the proportion of saline fluid and water in the fluid (
$\alpha _s + \alpha _w = 1$
) and
$\rho _s$
and
$\rho _w$
being the densities of saline fluid and water, respectively;
$\boldsymbol{u}_{\!f} = (u_{\!f},v_{\!f},w_{\!f})$
is the fluid velocity;
$p$
is the pressure;
$\boldsymbol{g} = (0,0,-9.81)$
m s
$^{-2}$
is the gravitational acceleration;
$\boldsymbol{\tau }$
is the fluid stress tensor;
$\boldsymbol{R}_{pf}$
is the momentum exchange between fluids and particles.
The salinity transport equation has the following form:
where
$D_s$
is the salt diffusion coefficient.
The translational and rotational motion of individual particles are tracked by the DEM method (Cundall & Strack Reference Cundall and Strack1979). Within the DEM framework, the contact force
$\boldsymbol{F}^{c}$
between particles and between particles and wall is solved by the Hertz–Mindlin model which is a linear spring–dashpot model (Cundall & Strack Reference Cundall and Strack1979). Parameter values involved in the collision model can be found in our previous paper (Xie et al. Reference Xie, Hu, Zhu, Yu and Pähtz2023b
). The point-force approximation is adopted to determine the fluid–particle interaction forces as
$d_p/\eta \ll O(1)$
with
$d_p$
the particle diameter and
$\eta$
the Kolmogorov length. Herein, the interaction force
$\boldsymbol{F}^f$
encompasses drag force
$\boldsymbol{F}^d\!$
, pressure gradient force
$\boldsymbol{F}^{\boldsymbol{\nabla} p}\!$
, viscous force
$\boldsymbol{F}^{\boldsymbol{\nabla \cdot} \boldsymbol{\tau }}\!$
, lift force
$\boldsymbol{F}^l$
and added mass force
$\boldsymbol{F}^{\textit{add}}$
. The modelling of the above forces is applicable in this study to cases where the particle Reynolds number
$Re_ p = |\boldsymbol{u}_{\!f} - \boldsymbol{u}_p|d_p / \nu _f$
is of the order of
$O(10^{-1})$
, where
$\boldsymbol{u}_p$
is the particle velocity and
$\nu _f$
is the kinematic viscosity. With the exception of the pressure gradient force and viscous force, the modelling formulae for the other forces agree with our earlier research (Xie et al. 2023a,b). The pressure gradient force and viscous force are formulated by (Zhou et al. Reference Zhou, Kuang, Chu and Yu2010)
The total force acting on a particle can be expressed by
$\boldsymbol{F}^T = \boldsymbol{F}^d + \boldsymbol{F}^{\boldsymbol{\nabla} p} + \boldsymbol{F}^{\boldsymbol{\nabla \cdot} \boldsymbol{\tau }} + \boldsymbol{F}^l + \boldsymbol{F}^{\textit{add}} + \boldsymbol{F}^c$
. During the coupling process, the force exerted by a particle on a given fluid grid depends on the actual volume of the particle within that grid. In addition, as the pressure gradient term and viscous term in (2.2) already include the particle contribution, the momentum exchange
$\boldsymbol{R}_{pf}$
only includes drag, lift and added mass forces (see Zhou et al. Reference Zhou, Kuang, Chu and Yu2010). In the model, fluid properties, such as density and velocity, are interpolated to discrete particle positions using Gaussian interpolation. The point-force model has been validated as an effective method for simulating particle motion in density-stratified fluids (Blanchette Reference Blanchette2013). To further illustrate the model’s ability to capture particle behaviour in density-varying fluids, we simulate particle settling in a linearly stratified fluid. The results indicate that the model effectively describes the fluid mixing phenomenon induced by particle settling. Additional details are provided in Appendix A.
2.2. Numerical configurations
We employ a lock-exchange approach to generate gravity currents, consistent with the methodology used in previous studies (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002; Cantero, Balachandar & Garcia Reference Cantero, Balachandar and García2008; Espath et al. Reference Espath, Pinto, Laizet and Silvestrini2015; He et al. Reference He, Zhao, Zhu and Hu2019; Pelmard, Norris & Friedrich Reference Pelmard, Norris and Friedrich2020). Unlike Shringarpure et al. (Reference Shringarpure, Cantero and Balachandar2012, Reference Shringarpure, Cantero and Balachandar2015, Reference Shringarpure, Cantero and Balachandar2019), who used streamwise periodic boundaries to study steady-state currents, our simulation captures the acceleration, slumping and deceleration phases of gravity currents. The simulation of the lock-exchange gravity current is conducted in a cuboid domain with dimensions
$L_x = 0.5$
m (length),
$L_y = 0.01$
m (width) and
$L_z = 0.1$
m (height), as shown in figure 1. The streamwise direction of the domain is set as a no-slip boundary, the spanwise direction as a periodic boundary, the top surface as a slip boundary and the bottom surface a no-slip boundary. For the particle phase simulation, the spanwise direction also uses periodic boundaries, aligning with the fluid simulation, and the other surfaces are treated as wall boundaries. The left-hand side of the domain is a lock with a streamwise length of
$L_g = 0.05$
m. Initially, the lock is filled with saline or fresh water, with a density of
$\rho _{s}$
and a kinematic viscosity of
$\nu _f = 10^{-6}$
m
$^2$
s
$^{-1}$
. Additionally, a number of
$N_p$
particles, with a density of
$\rho _p = 1500$
kg m
$^{-3}$
and a diameter of
$d_p = 100$
$\unicode{x03BC}$
m, are randomly distributed in the lock, corresponding to an initial particle volume fraction of
$\alpha _{p0}$
. Accordingly, the overall initial density of the fluid–particle mixture in the lock is given by
$\rho _{m0}=\alpha _{p0}\rho _p + \alpha _{\!f0}\rho _s$
. The region outside the lock is filled with fresh fluid, with a density of
$\rho _w = 1000$
kg m
$^{-3}$
and a kinematic viscosity of
$\nu _f = 10^{-6}$
m
$^2$
s
$^{-1}$
. The initial density difference between the gravity current and the ambient fluid is expressed as
$\Delta \rho = \rho _{m0} - \rho _w = \alpha _{p0} (\rho _p - \rho _w) + \alpha _{\!f0} (\rho _s - \rho _w) = 3.5$
kg m
$^{-3}$
, where
$\alpha _{p0} (\rho _p - \rho _w)$
represents the particle contribution and
$\alpha _{\!f0} (\rho _s - \rho _w)$
is the salinity contribution. Thus, the ratio of the salinity contribution to
$\rho _{m0}$
to the particle contribution
$\xi _{sp}$
is determined by
As the simulation starts, the gate is lifted up and the gravity current is formed and propagates downstream. The local density of fluid–particle mixture is determined by
$\rho _m = \alpha _p\rho _p + \alpha _{\!f} (\alpha _s\rho _s + \alpha _w \rho _w)$
. The front position,
$x_{\textit{front}}$
, is an important parameter describing the gravity current propagation ability. The front of the particle flow is captured by the position of the most downstream particle, and the front of the salinity is identified by the relative volume fraction of saline fluid
$\alpha _s=10^{-4}$
.
Schematic diagram of the lock-exchange dual-driven gravity current.

For dimensionalization, we adopt the buoyancy velocity
$u_b =\sqrt { g^{\prime} {L_z}/2}$
as the characteristic velocity (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2005; Pelmard et al. Reference Pelmard, Norris and Friedrich2020), where the effective gravity acceleration
$g^{\prime} = |\boldsymbol{g}| (\rho _{m0}-\rho _w) / \rho _w$
. The characteristic length is taken as half the initial mixture height
$L_z/2$
, and the characteristic time is given by
$L_z/(2u_b)$
. The particle mass
$m_p$
and the gravity of a particle,
$m_{p}|\boldsymbol{g}|$
, are used as the characteristic mass and characteristic force. The density
$\rho$
is non-dimensionalized by
$\tilde \rho = ( \rho - \rho _w)/ (\rho _{m0} - \rho _w)$
. All the dimensionless variables are denoted by a tilde
$ ( \tilde {\cdot })$
. Thus, the dimensionless domain sizes are
$\tilde L_x \times \tilde L_y \times \tilde L_z = 10 \times 0.2 \times 2$
, and the lock length is
$\tilde L_g = 1$
.
This study is carried out with
$\xi _{sp}$
as a variable, and the set-ups for cases are shown in table 1. A decrease in
$\xi _{sp}$
implies a higher contribution from particles to the gravity current’s density difference
$\Delta \rho$
. There are some dimensionless parameters describing the flow characteristics, including the flow Reynolds number (
$Re$
), the Schmidt number (
$Sc$
) reflecting the salinity diffusion, the particle Stokes number (
$St$
), the Galileo number (
$Ga$
), the particle settling Reynolds number (
$Re_{\!p,t}$
), the dimensionless particle settling velocity (
$\tilde \gamma _t$
), the dimensionless characteristic settling time (
$\tilde t_s$
), the ratio of time scales (
$\tilde S$
) and the density ratio of particle to fluid (
$\tilde s_p$
), which are given by
\begin{align} \begin{split} Re = \frac {u_b L_z}{2 \nu _f}, \;\; Sc = \frac {\nu _f}{D_s}, \;\; St = \frac {\rho _p |\boldsymbol{u}_{\!f} - \boldsymbol{u}_{\!p}|d_p}{(9\rho _s \nu _f)}, \;\; Ga = \frac {\sqrt {\rho _p/\rho _{\!f} g^{\prime} d_p^3}}{\nu _f}, \\ Re_{\!p,t} = \frac { u_t d_p }{\nu _f}, \;\; \tilde \gamma _t = \frac {u_t}{u_b}, \;\; \tilde t_s = \frac {L_z}{u_t} \frac {u_b}{L_z/2} \;\;, \tilde S = \frac {L_g}{u_b} \frac {u_t}{L_z}, \;\; \tilde s_p = \frac {\rho _p}{\rho _{\!f}}, \end{split} \end{align}
where
$D_s$
is the salt diffusivity, and
$u_t = (\rho _p-\rho _s)|\boldsymbol{g}|d_p^2/(18\rho _s \nu _f)$
is the particle settling velocity which is negatively related to
$\xi _{sp}$
. In this work,
$Re = 2071$
,
$Sc = 1$
,
$St$
is of the order of
$O(10^{-2})$
,
$Ga$
is of the order of
$O(10^{-1})$
,
$Re_{\!p,t}$
is of the order of
$O(10^{-1})$
,
$\tilde \gamma _t$
is approximately 0.07,
$\tilde t_s$
is approximately 30,
$\tilde S$
is approximately 0.03 within the range of Gadal et al. (Reference Gadal, Mercier, Rastello and Lacaze2023) and
$\tilde s_p$
is approximately 1.5. The reason for selecting the particle density of 1500 kg m
$^{-3}$
is to maximize the dimensionless characteristic settling time
$\tilde t_s$
, though
$\tilde t_s \approx 30$
is approximately one order less than that in the previous studies (Cantero et al. Reference Cantero, Balachandar and García2008; Kneller et al. Reference Kneller, Nasr-Azadani, Radhakrishnan and Meiburg2016; Nasr-Azadani et al. Reference Nasr-Azadani, Meiburg and Kneller2018).
List of simulations: initial particle volume fraction
$\alpha _{p0}$
; particle number
$N_p$
; saline fluid density
$\tilde \rho _s$
; dimensionless particle settling velocity
$\tilde \gamma _t$
; dimensionless characteristic settling time
$\tilde t_s$
; ratio of time scales
$\tilde S$
; salinity–particle contribution ratio
$\xi _{sp}$
.

The characteristic length used in studies influences buoyancy velocity (
$u_b$
) and, consequently, the flow Reynolds number (
$Re$
). This study adopts half the initial height (
$L_z/2$
) as the characteristic length (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002; Tsai & Chou Reference Tsai and Chou2025), whereas some previous studies use the full initial height (
$L_z$
) (Cantero et al. Reference Cantero, Lee, Balachandar and Garcia2007; Marshall et al. Reference Marshall, Dorrell, Dutta, Keevil, Peakall and Tobias2021). In this case, the flow Reynolds number is defined as
$Re_{L} = \sqrt { g^{\prime} {L_z}} L_z / \nu _f = 2\sqrt {2}Re$
. The flow Reynolds numbers in this study (
$Re = 2071$
and
$Re_L = 5858$
) fall within the ranges reported in previous three-dimensional DNS studies, such as
$Re = 316{-}3164$
in Cantero et al. (Reference Cantero, Lee, Balachandar and Garcia2007),
$Re = 2236{-}10\,000$
in Necker et al. (Reference Necker, Härtel, Kleiser and Meiburg2002),
$Re = 2000{-}5000$
in Nasr-Azadani & Meiburg (Reference Nasr-Azadani and Meiburg2014),
$Re = 35\!-\!3536$
in Bonometti & Balachandar (Reference Bonometti and Balachandar2008) and
$Re = 1125{-}2249$
in a computational fluid dynamics (CFD)-DEM simulation (Tsai & Chou Reference Tsai and Chou2025). Provided the dimensionless settling time (
$\tilde t_s$
) remains sufficient, higher Reynolds numbers increase the number of fluid cells and particles in CFD-DEM simulations. Although increasing Reynolds number fragments the turbulent structures (Espath et al. 2014, 2015), it does not alter the qualitative understanding. Future research should explore gravity current dynamics in high-
$Re$
CFD-DEM simulations in greater depth.
We employ a uniform grid system with a grid resolution of
$N_x \times N_y \times N_z = 800\times 16 \times 160$
. The ratio of grid size to particle size
$d_{x(yz)}/d_p$
is accordingly 6.25. The ratio of particle size to Kolmogorov length
$d_p / \eta$
is of the order of
$O(10^{-4}\! \sim\! 10^{-1})$
, validating using the point-force approximation (Balachandar Reference Balachandar2009), and the ratio of grid size to Kolmogorov length
$d_{x(yz)} / \eta$
is of the order of
$O(10^{-3} \!\sim\! 10^{0})$
with the maximum being the 1.3, demonstrating that the grid resolution is fine enough to capture the turbulence structures (Arthur & Fringer Reference Arthur and Fringer2014).
For the main two-dimensional characteristics of turbidity currents, spanwise averaging is the main research method. The spanwise-averaged quantities of fluid and particle phases (
$\langle \mathcal{Q}^f \rangle$
and
$\langle \mathcal{Q}^p \rangle$
) are calculated as follows:
\begin{equation} \begin{gathered} \langle \mathcal{Q}^p\left (x,z\right) \rangle = \frac {1}{N_{p,y}} \sum \limits _{i = 1}^{N_{p,y}} \mathcal{Q}^p_i \left (x,y,z\right),\\ x_{p,i} \in \left(x-\frac {L_x}{2N_x},x+\frac {L_x}{2N_x}\right]\quad \mathrm{and}\quad z_{p,i} \in \left(z-\frac {L_z}{2N_z},z+\frac {L_z}{2N_z}\right], \end{gathered} \end{equation}
in which
$\mathcal{Q}^f$
and
$\mathcal{Q}^p_i$
are the fluid variables and the variables of particle
$i$
before spanwise averaging, respectively. Here
$N_{p,y}$
is the particle number within the selected area.
2.3. Discussion on the effect of numerical parameters
The Schmidt number
$Sc = 1$
adopted here is lower than
$Sc = 700$
corresponding to the salinity diffusion in the oceanic applications (Meiburg et al. Reference Meiburg, Radhakrishnan and Nasr-Azadani2015). Generally, as long as
$Sc$
is not less than unity, the current evolution is independent of
$Sc$
(Härtel et al. 2000; Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2005; Cantero et al. Reference Cantero, Lee, Balachandar and Garcia2007), especially at high Reynolds numbers (Bonometti & Balachandar Reference Bonometti and Balachandar2008; Ooi, Constantinescu & Weber Reference Ooi, Constantinescu and Weber2009). This justifies the use of
$Sc=1$
in many studies for simplicity (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002, Reference Necker, Härtel, Kleiser and Meiburg2005; Nasr-Azadani & Meiburg Reference Nasr-Azadani and Meiburg2014; He et al. Reference He, Zhao, Hu, Yu and Lin2018; Pelmard et al. Reference Pelmard, Norris and Friedrich2020). A recent work by Marshall et al. (Reference Marshall, Dorrell, Dutta, Keevil, Peakall and Tobias2021) demonstrated the impact of
$Sc$
at low Reynolds numbers of
$Re \leqslant 1061$
, which is related to structures in the mixed layer between the ambient fluid and the current. The Reynolds number (
$Re$
) in this work is 2071, which is higher than the maximum Reynolds number in Marshall et al. (Reference Marshall, Dorrell, Dutta, Keevil, Peakall and Tobias2021) but lower than the Reynolds number of 3536, above which Bonometti & Balachandar (Reference Bonometti and Balachandar2008) pointed out that
$Sc$
has no significant effect. Therefore, there may be uncertainty regarding the effect of
$Sc$
at the Reynolds number in this study. In view of this, we investigate the effect of
$Sc$
on the gravity current evolution. Figure 2 illustrates the three-dimensional profiles and coherent vortex structures of the current under varying Schmidt numbers. Figure 3 shows the spanwise-averaged profiles at different
$Sc$
values, including the fluid streamwise velocity
$\langle \tilde u_{\!f\!} \rangle$
, fluid density
$\langle \tilde \rho _{\!f\!} \rangle$
, relative particle volume fraction
$\langle \alpha _p \rangle / \alpha _{p0}$
, mixture density
$\langle \tilde \rho _m \rangle$
and gradient Richardson number
$\langle Ri_g \rangle$
, which is defined as (Kneller et al. Reference Kneller, Nasr-Azadani, Radhakrishnan and Meiburg2016)
\begin{equation} \langle Ri_g \rangle = -\frac {|\boldsymbol{g}| \frac {\partial \langle \rho _m \rangle }{\partial z}} { \langle \rho _{\!f\!} \rangle \frac {\partial \langle u_{\!f\!} \rangle }{\partial z}}. \end{equation}
The figures reveal that, under the Reynolds number considered in the present study, an increase in
$Sc$
from 1 to 700 has no significant effect on the flow structures.
Evolution of
$\xi _{sp} = 1.0$
dual-driven current for different Schmidt numbers: (
$a$
,
$b$
)
$Sc = 1$
and (
$c$
,
$d$
)
$Sc = 700$
; (
$a$
,
$c$
)
$\tilde t = 4$
and (
$b$
,
$d$
)
$\tilde t = 6$
. The grey translucent vortex structures are captured using the
$Q$
-criterion (
$\tilde Q = 5$
). The saline flow profile is captured with
$\alpha _s = 0.5$
and is coloured with the streamwise fluid velocity
$\tilde u_{\!f}$
.

Spanwise-averaged profiles under varying Schmidt numbers (
$Sc = 1$
and
$Sc = 700$
) at different times (
$\tilde t = 4$
and
$\tilde t = 6$
). Profiles at
$\tilde t = 4$
are obtained by averaging over
$\tilde x = 2{\sim}2.4$
and those at
$\tilde t = 6$
are obtained by averaging over
$\tilde x = 3.2{\sim}3.6$
. (
$a$
) Fluid streamwise velocity
$\langle \tilde u_{\!f\!} \rangle$
, (
$b$
) fluid density
$\langle \tilde \rho _{\!f\!} \rangle$
, (
$c$
) relative particle volume fraction
$\langle \alpha _p \rangle / \alpha _{p0}$
, (
$d$
) mixture density
$\langle \tilde \rho _m \rangle$
and (
$e$
) gradient Richardson number
$\langle Ri_g \rangle$
. The inset in panel (
$a$
) presents a magnified view of the velocity profile to highlight the impact of
$Sc$
.

Previous studies have shown that two- and three-dimensional configurations yield quantitatively different but qualitatively consistent simulation results (Cantero et al. Reference Cantero, Lee, Balachandar and Garcia2007; Ooi et al. Reference Ooi, Constantinescu and Weber2009; Francisco, Espath & Silvestrini Reference Francisco, Espath and Silvestrini2017; He et al. Reference He, Zhao, Hu, Yu and Lin2018), and some studies typically employed density distributions with random perturbations as initial conditions (Härtel et al. Reference Härtel, Kleiser, Michaud and Stein1997; Cantero et al. Reference Cantero, Lee, Balachandar and Garcia2007). The influence of computational domain width (
$\tilde L_y$
) and initial disturbance configuration on flow evolution is examined here. Figure 4(
$a$
,
$b$
) shows the three-dimensional structures of the SPDD gravity current at
$\xi _{sp} = 1.0$
under different computational domain widths (
$\tilde L_y =$
0.2, 0.8) and initial density distributions, including coherent vortex structures identified by using the
$Q$
-criterion and current profiles captured by salinity. Spanwise-averaged profiles for various
$\tilde L_y$
values (
$\tilde L_y =$
0.2, 0.4, 0.8) are shown in figure 4(
$c$
). As the spanwise computational domain expands, the number of grids in the spanwise direction increases proportionally to maintain consistent grid resolution. Comparisons between figures 4(
$a$
) and 4(
$b$
) reveal that initial density perturbations have minimal impact on flow structure evolution in this study. The figure also demonstrates that, during the slumping stage, the width of the computational domain exerts negligible influence on the flow dynamics. Three-dimensional simulations across different domain widths consistently exhibit Kelvin–Helmholtz (KH) instabilities at the interface and complex structures at the current head. These flow features are consistent with previous understandings (Cantero et al. Reference Cantero, Lee, Balachandar and Garcia2007; Espath et al. Reference Espath, Pinto, Laizet and Silvestrini2015; Nasr-Azadani et al. Reference Nasr-Azadani, Meiburg and Kneller2018; Tsai & Chou Reference Tsai and Chou2025). As the domain width increases, spanwise variations of these structures, especially the lobes and clefts reflected on the bottom side of the head, become more observable, though qualitative differences remain absent.
Comparison of current structures at
$\xi _{sp}=1.0$
with different computational domain widths (
$\tilde L_y$
) and initial density distribution conditions. Three-dimensional structures (
$a$
) without initial disturbance and (
$b$
) with initial disturbance. Panels (
$a$
i), (
$a$
iii), (
$b$
i) and (
$b$
iii) correspond to
$\tilde t = 4$
, while panels (
$a$
ii), (
$a$
iv), (
$b$
ii) and (
$b$
iv) correspond to
$\tilde t = 6$
. Here (
$a$
i,
$a$
ii,
$b$
i,
$b$
ii)
$\tilde L_y = 0.2$
and (
$a$
iii,
$a$
iv,
$b$
iii,
$b$
iv)
$\tilde L_y = 0.8$
. The grey translucent vortex structures are captured using the
$Q$
-criterion (
$\tilde Q = 5$
). The saline flow profile is captured with
$\alpha _s = 0.5$
and is coloured with the streamwise fluid velocity
$\tilde u_{\!f}$
. (
$c$
i) Spanwise-averaged current profiles identified by
$\langle \alpha _s \rangle = 10^{-4}$
, (
$c$
ii) spanwise-averaged fluid streamwise velocity profiles (
$\langle \tilde u_{\!f\!} \rangle$
) and (
$c$
iii) spanwise-averaged salinity profiles (
$\langle \alpha _s \rangle$
) for various
$\tilde L_y$
values at
$\tilde x = 0.85 \tilde x_{\textit{front}}$
and at
$\tilde t =$
2, 4, 6 and 8.

3. Results
3.1. Current front and morphological patterns
Figure 5 presents the time evolution of the current front position
$\tilde x_{\textit{front}} - \tilde L_g$
and front velocity
$\tilde u_{\textit{front}}$
, calculated as
$\tilde u_{\textit{front}} = \mathrm{d} \tilde x_{\textit{front}} / \mathrm{d} \tilde t$
, of the particle and salinity flow. In order to access the duration of the slumping (constant-velocity) phase,
$\tilde t_{sp}$
, the maximum front velocity is considered the beginning of the slumping stage, and a 10 % decay from the maximum velocity marks its end. The inset of figure 5(
$b$
) shows the relationship between the duration of the slumping stage and the time scale ratio
$\tilde S$
. Initially, the front velocity of the current undergoes a brief acceleration, followed by a slight decrease or near-constant phase (
$\tilde u_{\textit{front}} \approx 0.6$
), and finally decelerates. It is consistent with the typical comprehension of the lock-exchange gravity current (Huppert & Simpson Reference Huppert and Simpson1980; Cantero et al. Reference Cantero, Lee, Balachandar and Garcia2007; Huang et al. Reference Huang, Imran and Pirmez2008). Before
$\tilde t=12$
, the simulated results of gravity current are quantitatively consistent with the experimental results and numerical results reported in previous studies (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002; Dai Reference Dai2014; Gadal et al. Reference Gadal, Mercier, Rastello and Lacaze2023). For the saline flow front, the simulated results at
$\tilde t\lt 15$
are quite consistent with the previous results (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002; Dai Reference Dai2014). At
$\tilde t\gt 15$
, the difference in simulation comes from the limitation of the streamwise length of the computational domain. For particle flow, the decrease of
$\xi _{sp}$
corresponds to the enhancement of the particle settling effect, indicated by an increase in
$\tilde S$
. This results in the front leaving the constant-velocity slumping stage earlier, which is consistent with previous observations (Gladstone & Woods Reference Gladstone and Woods2000; Gadal et al. Reference Gadal, Mercier, Rastello and Lacaze2023). The front position for
$\tilde S=0.033$
simulated in this work is basically enveloped by the front curves of
$\tilde S=0.076$
and
$\tilde S=0.026$
from Gadal et al. (Reference Gadal, Mercier, Rastello and Lacaze2023). All of the above show that our simulation results have good credibility.
Temporal evolution of (
$a$
) front position
$\tilde x_{\textit{front}} - \tilde L_g$
and (
$b$
) front velocity
$\tilde u_{\textit{front}}$
. The lines indicate the front position and velocity given by the salinity contour, and the data marked in symbols is obtained from the most downstream particle’s position. The inset in panel (
$b$
) shows the duration of slumping stage
$\tilde t_{sp}$
at different
$\tilde S$
s.

The salinity distribution and the particle dataset yield similar front position and velocity values in the dual-driven current, showing minimal differences. This suggests a high degree of coordination between salinity and particle diffusion and propagation under strong fluid–particle interactions. During the acceleration stage, the front velocity in figure 5(
$b$
) is independent of
$\xi _{sp}$
, consistent with the findings in Gladstone & Woods (Reference Gladstone and Woods2000). The duration of the slumping stage (
$\tilde t_{sp}$
) is gradually shortened as
$\tilde S$
increases corresponding to a decrease in
$\xi _{sp}$
. The reason for the short slumping stage at large
$\xi _{sp}$
is that the low particle settling velocity enhances the backflow’s propagation (Huang et al. Reference Huang, Imran and Pirmez2008), enabling the reflected wave to catch up with the front more quickly and alter the front dynamics. When
$\xi _{sp}$
is small, the stronger particle settling effect is primarily responsible for the earlier end time of the slumping stage.
Spatial distribution of spanwise-averaged relative volume fraction of saline fluid
$\langle \alpha _s \rangle$
and particle flow profile. The heat map shows the relative volume fraction of the saline fluid, and the black line indicates the outer contour of the particle flow. Here (
$a$
,
$d$
,
$g$
,
$j$
)
$\xi _{sp} = 6.0$
, (
$b$
,
$e$
,
$h$
,
$k$
)
$\xi _{sp} = 1.0$
and (
$c$
,
$f$
,
$i$
,
$l$
)
$\xi _{sp} = 0.17$
; (
$a$
–
$c$
)
$\tilde t = 3$
, (
$d$
–
$\!f$
)
$\tilde t = 6$
, (
$g$
–
$i$
)
$\tilde t = 9$
and (
$j$
–
$l$
)
$\tilde t = 12$
.

The salinity and particle distribution of the dual-driven current at various
$\xi _{sp}$
s are depicted in figure 6. It can be seen that the salinity propagation is closely connected to the particle movement in the dual-driven current. A reduction in
$\xi _{sp}$
, which decreases the interstitial fluid density and thereby increases particle settling, results in a slower advancement velocity, reduced ability to maintain head shape (Huang et al. Reference Huang, Imran and Pirmez2008) and a lower relative saline fluid fraction
$\alpha _s$
near the head. Compared with the salinity-dominated current (figure 6
$a$
), the particle-dominated current (figure 6
$c$
) is more prone to interfacial instability at early stages, leading to the formation of KH billows. The interfacial instability structures in the salinity-dominated current (figure 6
$a$
,
$d$
,
$g$
,
$j$
) are generally confined to the region where
$\tilde z\lt 1$
. The excited interfacial vortex propagates downstream with the current, rapidly expands in size, and then slowly dissipates as salinity diffuses. In contrast, the interfacial vortex in particle-dominated current essentially does not move streamwise (figure 6
$\!f\!$
,
$i$
,
$l$
). The vortex continues to grow spatially throughout the evolution. Such pronounced vortices have also been reported in previous studies on PD gravity currents (Nasr-Azadani & Meiburg Reference Nasr-Azadani and Meiburg2014; Lu et al. Reference Lu, Liu, Xie, Sun, Yang and Guo2024). These vortices form due to the interaction between wall-reflected bores and vortices induced by the settling of particle groups. As the strength of vortex structure progressively weakens, the reduced fluid forces are insufficient to retain the particles within the vortex, especially at small
$\xi _{sp}$
. Thus, particles are displaced by centrifugal force, leading to an expansion in the vortex’s spatial range.
From the above analysis, the key phenomena and transition regimes from SD to PD current can be summarized as follows.
-
(i) Material transport: analysing the variations in transport capacity for salinity and particles is crucial for comprehending SPDD current behaviour.
-
(ii) Interfacial instability: this phenomenon is linked to the entrainment regime and thus the density dilution of interstitial fluid, significantly altering current dynamics.
3.2. Salinity convection–diffusion and particle transport
The material transport capacity can be reflected by the equivalent material height
$\tilde h$
and current height
$\tilde h_t$
which includes the transporting material covering transported particle part
$\tilde h_{p,t}$
and saline fluid part
$\tilde h_{s}$
. The difference between the two is that the latter isolates the contribution of the deposited particles
$\tilde h_{p,d}$
, yielding
$\tilde h = \tilde h_t + \tilde h_{p,d} = ( \tilde h_{p,t} +\tilde h_{s}) + \tilde h_{p,d}$
. The equivalent material height
$\tilde h$
can be given by referring to Cantero et al. (Reference Cantero, Lee, Balachandar and Garcia2007, Reference Cantero, Balachandar and García2008), Shin, Dalziel & Linden (Reference Shin, Dalziel and Linden2004) and Birman, Martin & Meiburg (Reference Birman, Martin and Meiburg2005) as
The first and second terms on the right-hand side represent the height contributed from particles and salinity denoted as
$\tilde h_p =\tilde h_{p,t} + \tilde h_{p,d}$
and
$\tilde h_s$
, respectively. The deposited particle height
$\tilde h_{p,d}$
is calculated by
where
$\langle \alpha _{p,d} \rangle$
denotes the spanwise-averaged volume fraction of deposited particles, which is given by
in which
$N_{p,d}^l(x)$
is the deposited particle number in the region
$\mathcal{R} = (x-({L_x}/{2N_x}),x+({L_x}/{2N_x}))$
. The deposited particles here refer to the particles that are in contact with the bottom wall and have a velocity
$|\boldsymbol{\tilde u}_p|$
less than
$10^{-2}$
. It is important to note that both the equivalent material height
$\tilde h$
and current height
$\tilde h_t$
account for the material transported by large-sized vortices in the flow field, aligning with the approach in previous studies (Cantero et al. 2007, 2008). This is primarily because these vortices are a significant feature generated by the current and exert a non-negligible influence on its dynamics.
Spatiotemporal evolution of material heights for various cases: (
$a$
–
$c$
)
$\xi _{sp} = 6.0$
, (
$d$
–
$f$
)
$\xi _{sp} = 1.0$
and (
$g$
–
$i$
)
$\xi _{sp} = 0.17$
; (
$a$
,
$d$
,
$g$
) relative salinity height
$\tilde h_s / \tilde h$
, (
$b$
,
$e$
,
$h$
) relative particle height
$\tilde h_p / \tilde h$
and (
$c$
,
$f$
,
$i$
) equivalent material height
$\tilde h$
.

Figure 7 illustrates the spatiotemporal evolution of three material heights (
$\tilde h_s / \tilde h$
,
$\tilde h_p / \tilde h$
and
$\tilde h$
) at varying
$\xi _{sp}$
s. Regions with locally large salinity height
$\tilde h_s$
often corresponds to regions with locally large
$\tilde h$
, indicating that the interstitial fluid is essential to the material transport. The relative salinity/particle height (
$\tilde h_s / \tilde h$
,
$\tilde h_p / \tilde h$
) in the head essentially stays constant in the slumping stage. It suggests that the composition ratio of salinity to particle in the head region remains in equilibrium. This balance is crucial for maintaining the constant front velocity regime of the slumping stage. During the slumping stage, the equivalent material height
$\tilde h$
near the head is approximately unity, which corresponds to half the initial height of the fluid–particle column. This observation aligns with previous studies (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002; Cantero et al. Reference Cantero, Lee, Balachandar and Garcia2007; Bonometti & Balachandar Reference Bonometti and Balachandar2008; Meiburg et al. Reference Meiburg, Radhakrishnan and Nasr-Azadani2015). The position of the maximum
$\tilde h$
progressively shifts away from the head as
$\xi _{sp}$
decreases after entering the deceleration period (approximately
$\tilde t\gt 10$
) in figure 7(
$c$
,
$f\!$
,
$i$
). When
$\xi _{sp}$
is small, the inherent sedimentation properties of the particles cause the density difference between the gravity current and the ambient fluid to decay more. It corresponds to a faster decay of the forward ability (also see in figure 5), making it increasingly difficult for the particles to be transported downstream by the current.
Spatial distribution of the ratio of transporting particle height to particle height
$\tilde h_{p,t} / \tilde h_p$
: (
$a$
)
$\tilde t = 3$
, (
$b$
)
$\tilde t = 6$
, (
$c$
)
$\tilde t = 9$
, (
$d$
)
$\tilde t = 12$
, (
$e$
)
$\tilde t = 15$
and (
$f$
)
$\tilde t = 18$
.

We then discuss the ratio of transporting particles to deposited particles at different locations. Figure 8 illustrates the ratio of transporting particle height relative to total particle height,
$\tilde h_{p,t} / \tilde h_p$
, at different times and varying values of
$\xi _{sp}$
. During the slumping stage,
$\xi _{sp}$
has minimal influence on the ratio of transporting particle height, indicating that particle transport capacity and sedimentation are largely independent of
$\xi _{sp}$
. In this phase, the maximum
$\tilde h_{p,t} / \tilde h_p$
near the front remains at unity, meaning the particles here are primarily transported in suspension. Particles in the upstream gradually settle, leading to a decrease in
$\tilde h_{p,t} / \tilde h_p$
. In the deceleration stage, gravity currents with larger
$\xi _{sp}$
exhibit higher
$\tilde h_{p,t} / \tilde h_p$
values, particularly in terms of maximum
$\tilde h_{p,t} / \tilde h_p$
near the front. This implies a great capacity of particle suspension at larger
$\xi _{sp}$
, corresponding to the greater forward velocity observed in figure 5. Upstream, after the current passes,
$\tilde h_{p,t} / \tilde h_p$
stabilizes at approximately 0.3, indicating that most particles are deposited. This low
$\tilde h_{p,t} / \tilde h_p$
results from the movement of particles within the near-wall region under the influence of residual flow.
Spatiotemporal evolution of current heights for various cases: (
$a$
–
$c$
)
$\xi _{sp} = 6.0$
, (
$d$
–
$f$
)
$\xi _{sp} = 1.0$
and (
$g$
–
$i$
)
$\xi _{sp} = 0.17$
; (
$a$
,
$d$
,
$g$
) relative salinity height
$\tilde h_s / \tilde h_t$
, (
$b$
,
$e$
,
$h$
) relative transporting particle height
$\tilde h_{p,t} / \tilde h_t$
and (
$c$
,
$f$
,
$i$
) current height
$\tilde h_t$
.

Figure 9 depicts the spatiotemporal evolution of the proportions of transporting particle height (
$\tilde h_{p,t}$
) and salinity height (
$\tilde h_s$
) in the current height (
$\tilde h_t$
), and the evolution of the current height (
$\tilde h_t$
). The distribution patterns are qualitatively similar to those in figure 7. At larger
$\xi _{sp}$
, the particle effect on the current is weak, resulting in heights in figure 9(
$a$
–
$c$
) comparable to the heights observed in figure 7(
$a$
–
$c$
). Conversely, when
$\xi _{sp}$
is small, particle deposition reduces transporting material heights by
$\tilde h_{p,d}$
, causing the values in figure 9(
$h$
–
$i$
) to be lower than those in figure 7(
$h$
–
$i$
).
Time evolution of (
$a$
) transporting particle quantity
$N_{p,t}$
and (
$b$
) particle deposition rate
$\mathrm{d} N_{p,d} / \mathrm{d} \tilde t$
, both of which are normalized by the total particle quantity
$N_p$
. The inset in panel (
$a$
) shows the transporting particle quantity at varying
$\xi _{sp}$
s at
$\tilde t = 12$
.

A statistical analysis of the number of deposited particles is crucial for understanding the deposition process in gravity current. Figure 10 illustrates the time evolution of normalized transporting particle number
$N_{p,t}/N_p$
and the corresponding deposition rate
$\mathrm{d} (N_{p,d}/N_p) / \mathrm{d} \tilde t$
under different values of
$\xi _{sp}$
. During the early stage of the current (
$\tilde t\lt 10$
), the deposition process is independent of
$\xi _{sp}$
, and the deposition rate scales with
$\tilde t^{\;0.5}$
, which is consistent with previous findings (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002; Espath et al. Reference Espath, Pinto, Laizet and Silvestrini2014; Francisco et al. Reference Francisco, Espath and Silvestrini2017). As the current experiences a short stage (
$8\lt \tilde t\lt 10$
) developing from the slumping stage to the deceleration stage, the deposition rate decreases following a scaling law of
$\tilde t^{-2.25}$
. For
$\tilde t\gt 10$
, a decrease in
$\xi _{sp}$
leads to a lower deposition rate. It is attributed to the large-sized vortex structures in the flow field (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002) as seen in figure 6, which trap some particles and hinder sedimentation. This phenomenon is evident from the higher number of transporting particles at very small
$\xi _{sp}$
, as shown in the inset of figure 10(
$a$
). At this stage, the deposition rate scales approximately with
$\tilde t^{-6}$
, slightly higher than the earlier decay rate (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2002; Espath et al. Reference Espath, Pinto, Laizet and Silvestrini2015). This difference is attributed to the higher particle settling velocity
$\tilde \gamma _t$
in this study (Necker et al. Reference Necker, Härtel, Kleiser and Meiburg2005; Espath et al. Reference Espath, Pinto, Laizet and Silvestrini2015; Francisco et al. Reference Francisco, Espath and Silvestrini2017).
We compute the average vertical predominant forces (
$\boldsymbol{\tilde {F}}^{\boldsymbol{\nabla} p}_z$
,
$\boldsymbol{\tilde {F}}^{d}_z$
, and
$\boldsymbol{\tilde {F}}^{c}_z$
) acting on the transported particles (Xie et al. 2023a) to elucidate the effect of salinity–particle interaction on particle suspension, as illustrated in figure 11. Changes in
$\xi _{sp}$
have a minimal effect on the dominant drag force (figure 11
$a$
) and pressure gradient forces (figure 11
$b$
) before the slumping stage. At this stage, the primary pressure gradient force initially rises and then falls, while the secondary drag force mostly stays constant. After that, both (
$\boldsymbol{\tilde {F}}^{\boldsymbol{\nabla} p}_z$
and
$\boldsymbol{\tilde {F}}^{d}_z$
) gradually diminish. As the particle concentration increases, the contact force takes on greater significance in maintaining particle suspension (figure 11
$c$
). With
$\xi _{sp}$
decreasing, and given that the dimensionless deposition rates are comparable (figure 10), a larger number of particles are deposited, further reducing the mixture density of the gravity current. This reduction in density weakens the flow dynamics, significantly decreasing the pressure gradient force and drag force, as shown in figure 11(
$a$
,
$b$
). Consequently, the particle suspension ability declines and the particle settling is enhanced, as illustrated in figure 8. Additionally, with particles gradually settling, the increased particle concentration near the wall leads to a corresponding rise in the contact force, as depicted in figure 11(
$c$
).
Average vertical forces acting on transported particles over time. (
$a$
) Pressure gradient force
$\boldsymbol{\tilde {F}}^{\boldsymbol{\nabla} p}_z$
, (
$b$
) drag force
$\boldsymbol{\tilde {F}}^{d}_z$
and (
$c$
) contact force
$\boldsymbol{\tilde {F}}^{c}_z$
.

3.3. Entrainment and detrainment
One of the key mechanisms to entrainment is the formation of a series of billows resulting from interfacial shear instability, which alters the density difference with the ambient fluid by affecting the material concentration of the current (Wells & Dorrell Reference Wells and Dorrell2021). Here we focus on current entrainment during the slumping phase characterized by a constant velocity. Figure 12(
$a$
–
$\!f\!$
) displays the spanwise-averaged flow profiles averaged over
$\tilde x = 1.4 \!\sim\! 1.8$
at
$\tilde t =2.5$
(in the slumping stage), including fluid streamwise velocity
$\langle \tilde u_{\!f\!} \rangle$
, fluid vertical velocity
$\langle \tilde w_{\!f\!} \rangle$
, fluid density
$\langle \tilde \rho _{\!f\!} \rangle$
, relative particle volume fraction
$\langle \alpha _p \rangle /\alpha _{p0}$
, mixture density
$\langle \tilde \rho _m \rangle$
and gradient Richardson number
$\langle Ri_g \rangle$
. The spatial distribution of the vertical total force
$\boldsymbol{F}^T_z$
on the particles in the slumping stage for various cases is shown in figure 12(
$g$
–
$i$
).
Spanwise-averaged current profiles at
$\tilde t =2.5$
averaged over
$\tilde x = 1.4{\sim}1.8$
: (
$a$
) fluid streamwise velocity
$\langle \tilde u_{\!f\!} \rangle$
; (
$b$
) fluid vertical velocity
$\langle \tilde w_{\!f\!} \rangle$
; (
$c$
) fluid density
$\langle \tilde \rho _{\!f\!} \rangle$
; (
$d$
) relative particle volume fraction
$\langle \alpha _p \rangle / \alpha _{p0}$
; (
$e$
) mixture density
$\langle \tilde \rho _m \rangle$
; (
$f$
) gradient Richardson number
$\langle Ri_g \rangle$
. The insets in panels (
$a$
) and (
$f\!$
) plot
$\langle \tilde u_{\!f\!} \rangle$
and
$\langle Ri_g \rangle$
, respectively, at current height
$\tilde h_t$
which is given in table 2 at different
$\xi _{sp}$
. The inset in panel (
$b$
) shows the relationship between mean fluid vertical velocity
$\langle \tilde w_{\!f\!} \rangle$
near the wall (
$\tilde z = 0 {\sim} 0.05$
) and
$\xi _{sp}$
. Spatial distribution of vertical total force
$\boldsymbol{\tilde F}^T_z$
acting on particles at
$\tilde t = 2.5$
for (
$g$
)
$\xi _{sp} = 6.0$
, (
$h$
)
$\xi _{sp} = 1.0$
and (
$i$
)
$\xi _{sp} = 0.17$
. The higher density of the granular medium arises from the projection of three-dimensional Lagrangian particle points onto a two-dimensional plane.

Average current interface elevations over
$\tilde {x} = 1.4\!-\!1.8$
at
$\tilde{t} =2.5$
.

For the sake of interface definition, the current height
$\tilde h_t$
is considered as the interface elevation. The average interface elevations over
$\tilde x = 1.4{\sim}1.8$
at
$\tilde t =2.5$
are presented in table 2. The downward sedimentation of particles inevitably causes the current interface to descend, and the degree of descent increases with the decrease of
$\xi _{sp}$
. With regard to
$\langle \tilde u_{\!f\!} \rangle$
profiles (figure 12
$a$
), the decrease of
$\xi _{sp}$
reduces
$\langle \tilde u_{\!f\!} \rangle$
at the interface but increases
$\partial \langle \tilde u_{\!f\!} \rangle / \partial \tilde z$
here. It increases
$\langle \tilde u_{\!f\!} \rangle$
below the interface, which is consistent with the results of Shringarpure et al. (Reference Shringarpure, Cantero and Balachandar2015). Figure 12(
$b$
) illustrates that, in most regions (excluding the range
$\tilde z = 0.4 \!\sim\! 0.7$
), a decrease in
$\xi _{sp}$
results in a leftward shift of the
$\langle \tilde w_{\!f\!} \rangle$
profile. This shift indicates a reduction in upward vertical velocity (at
$\tilde z \gtrapprox 0.7$
and the very near the wall as shown in the inset) and an increase in downward vertical velocity (at
$\tilde z \lessapprox 0.4$
). This phenomenon is closely associated with particle sedimentation. Conversely, within the range
$\tilde z = 0.4 \!\sim\! 0.7$
, smaller
$\xi _{sp}$
values cause the profile to shift to the right, a behaviour attributed to enhanced interface instability. Simultaneously, the interface fluid stratification is reduced with
$\xi _{sp}$
decreasing, as evidenced by the decrease in
$\partial \langle \tilde \rho _{\!f\!} \rangle / \partial \tilde z$
in figure 12(
$c$
), and the fluid–particle mixture stratification also diminishes (figure 12
$e$
) under the impact of the particle spatial distribution. Additionally, as shown in figure 12(
$f$
),
$Ri_g$
near the interface is positively correlated with
$\xi _{sp}$
and clearly falls below the classical shear instability threshold of 1/4 (Nasr-Azadani et al. Reference Nasr-Azadani, Meiburg and Kneller2018; Caulfield Reference Caulfield2021). This explains why, during the slumping stage, currents with low
$\xi _{sp}$
are more prone to become unstable and form interfacial billows. Correspondingly, the particles in the low-
$\xi _{sp}$
regime are more easily rolled up by the stronger fluid forces provided by the vortices as shown in figure 12(
$g$
–
$i$
).
Time evolution of entrainment coefficients for (
$a$
) saline flow
$\mathcal{\tilde E}_{s}$
and (
$b$
) particle flow
$\mathcal{\tilde E}_{p}$
.

By setting thresholds on the volume fraction to capture the envelope (
$\langle \alpha _s \rangle = 10^{-3}$
and
$\langle \alpha _p \rangle / \alpha _{p0} = 10^{-2}$
) which is similar to He et al. (Reference He, Zhao, Hu, Yu and Lin2018), we determine the corresponding current volumes per unit width,
$\tilde V_{F,s}$
and
$\tilde V_{F,p}$
. Then, we can get the current volume change rate per unit width by
$\tilde Q_{F,s(p)} = \mathrm{d} \tilde V_{F,s(p)} / \mathrm{d} \tilde t$
. The entrainment velocity (
$\tilde W_{s(p)}$
) and entrainment coefficient (
$\mathcal{\tilde E}_{s(p)}$
) can be given by (Ottolenghi et al. Reference Ottolenghi, Adduce, Inghilesi, Roman and Armenio2016)
\begin{equation} \tilde W_{s(p)} = \frac {\tilde Q_{F,s(p)}}{\tilde L_{F,s(p)}}, \;\;\;\; \mathcal{\tilde E}_{s(p)} = \frac {\tilde W_{s(p)}}{\tilde u_{front,s(p)}}, \end{equation}
where
$\tilde L_{F,s(p)}$
denotes the length of the upper interface. Given that the deposited particles form only a very thin layer and often coexist in thin layers with near-wall moving particles, their inclusion in the interface identification using volume fraction has a negligible effect on the captured volume and can therefore be ignored. Figure 13 depicts the time evolution of entrainment coefficients (
$\mathcal{\tilde E}_{s(p)}$
). The entrainment coefficients for particle flow and saline flow are distinct:
$\mathcal{\tilde E}_{s}\gt 0$
in figure 13(
$a$
) and
$\mathcal{\tilde E}_{p}\lt 0$
in figure 13(
$b$
), respectively. This indicates that the saline flow is always entraining the fluid, while the particle flow is always detraining the fluid due to particle gravity. Here
$\mathcal{\tilde E}_{s}\gt |\mathcal{\tilde E}_{p} |$
, meaning that in the dual-driven current, the entrainment from salinity convection–diffusion is always greater than the detrainment from particle flow sedimentation. Both
$\mathcal{\tilde E}_{s}$
and
$\mathcal{\tilde E}_{p}$
undergo the initial fast decay, governed by complex vertical and horizontal dynamics. After that (in the slumping stage),
$\mathcal{\tilde E}_{s(p)}$
decreases slightly or stabilizes, aligning with He et al. (Reference He, Zhao, Hu, Yu and Lin2018). Finally,
$\mathcal{\tilde E}_{s(p)}$
at large
$\xi _{sp}$
exhibits a significant rise as a result of impact on the downstream wall. The entrainment/detrainment of saline/particle flow is independent of
$\xi _{sp}$
in the early stage (
$\tilde t\lt 1$
), with
$\mathcal{\tilde E}_{s}$
decaying faster (
${\sim}\tilde t ^{-1.25}$
) than
$\mathcal{\tilde E}_{p}$
(
${\sim}\tilde t ^{-0.75}$
). Then, the particle sedimentation effect impacts both entrainment and detrainment. The entrainment coefficient of saline flow is approximately 0.1 as close to the previous reports (Van den Bremer & Hunt Reference van den Bremer and Hunt2014; He et al. Reference He, Zhao, Hu, Yu and Lin2018; Parker et al. Reference Parker, Burridge, Partridge and Linden2020; Richardson & Hunt Reference Richardson and Hunt2022; Salizzoni et al. Reference Salizzoni, Vaux, Creyssels, Craske and van Reeuwijk2024), and is facilitated by the decrease in
$\xi _{sp}$
, particularly during the deceleration phase. This is because the presence of particles promotes interface instability in figure 6. This explains also why, as
$\xi _{sp}$
decreases, the particle flow detrainment weakens. In the slumping stage, when
$\xi _{sp} = 0$
,
$\mathcal{\tilde E}_{p}$
decays at a rate of
$\tilde t^{-0.05}$
, whereas
$\mathcal{\tilde E}_{p}$
is essentially constant when
$\xi _{sp} = 6.0$
. The high-
$\xi _{sp}$
flow exhibits a weaker detrainment during the deceleration period (figure 13
$b$
), primarily because the interfacial vortices are continuously excited (figure 6).
Time evolution of entrainment coefficients for (
$a$
,
$c$
,
$e$
) saline flow
$\mathcal{\tilde E}_{s}$
and (
$b$
,
$d$
,
$f$
) particle flow
$\mathcal{\tilde E}_{p}$
with different interface definition thresholds: (
$a$
,
$b$
)
$\xi _{sp} = 6.0$
, (
$c$
,
$d$
)
$\xi _{sp} = 1.0$
and (
$e$
,
$f$
)
$\xi _{sp} = 0.17$
.

Figure 14 illustrates the time evolution of the entrainment and detrainment coefficients (
$\mathcal{\tilde E}_{s}$
and
$\mathcal{\tilde E}_{p}$
) under different current interface definition thresholds (
$\langle \alpha _s \rangle$
for saline flow and
$\langle \alpha _{p} \rangle / \alpha _{p0}$
for particle flow). Within the range of
$\langle \alpha _s \rangle$
and
$\langle \alpha _{p} \rangle / \alpha _{p0}$
values shown in the figure, changes in the threshold values do not qualitatively alter the temporal trends of
$\mathcal{\tilde E}_{s}$
and
$\mathcal{\tilde E}_{p}$
. Specifically, increasing the
$\langle \alpha _s \rangle$
threshold slightly reduces the entrainment coefficient, while increasing the
$\langle \alpha _{p} \rangle / \alpha _{p0}$
threshold slightly enhances the detrainment coefficient. This behaviour arises because larger threshold values encompass smaller captured current volumes. Considering that interface vortices can contain substantial amounts of matter and influence current dynamics below, we here treat vortices near the interface as part of the gravity current. Accordingly, adopting a relatively small threshold value captures most of the saline and particle flow contours, thereby providing a more comprehensive depiction of material entrainment and detrainment.
4. Conclusions and discussion
This work studies the lock-exchange SPDD gravity current using a DNS DEM numerical method. The flow Reynolds number is maintained at 2071. The transition regime of gravity current from SD to PD is investigated by introducing the variable
$\xi _{sp}$
, which represents the ratio of the salinity contribution and the particle contribution to the density difference.
The results indicate that the transition regime from SD gravity current to PD gravity current is related to interface dynamics and material transport behaviour. The interfacial stability during this transition is affected by a positive feedback loop between interstitial fluid entrainment and particle settling. As
$\xi _{sp}$
decreases, associated with the enhanced particle contributions, the intensity of interfacial fluid stratification and the gradient Richardson number decrease. This reduction increases the likelihood of the interfacial instability and KH billow formation. As a result, the formation of interfacial vortices accelerates fluid entrainment, leading to further dilution of the interstitial fluid, which, in turn, amplifies the particle settlement effect over time. During the slumping stage, stronger KH billows at large
$\xi _{sp}$
enhance the streamwise transport of particles (Xie, Hu & Pan Reference Xie, Hu and Pan2025), while the sedimentation of more particles supplies more abundant energy to drive the current downstream. The synergistic effect of these processes enables the front velocity of the particle-dominated current to remain comparable to that of the salinity-dominated current, despite greater material loss and a corresponding reduction in density difference with the ambient fluid. In the later stage, the pursuit of wall-reflected bore and the deposition of more particles at large
$\xi _{sp}$
cause the front velocity to decay faster, making the current enter the deceleration stage.
Additionally, salinity and particles possess distinct diffusion and transport properties, with saline flow characterized by entrainment and particle flow by detrainment. This highlights that the spatial distribution of materials is significantly affected by
$\xi _{sp}$
, and the current ability of transporting particles gradually decreases with increasing particle contribution. As
$\xi _{sp}$
decreases, the reduction in particle flow detrainment is attributed to larger interfacial vortices. Over time, the wall-reflected bore combines with vortices generated by particle settling dynamics, forming a larger vortex structure. As the current weakens, the diminishing vortex strength causes particles to migrate away from the vortex centre due to centrifugal forces, resulting in the continuous spatial expansion of the vortex.
Future research can explore dual-driven gravity currents with higher
$Re$
, varying
$St$
and different particle settling velocities to gain a deeper comprehension of the entrainment–detrainment mechanism in the current.
Funding
The work was supported by the Postdoctoral Fellowship Program of CPSF (grant no. GZB20240656 for J.X.), the China Postdoctoral Science Foundation (grant no. 2024M752777 for J.X.) and the National Natural Science Foundation of China (grant no. 12222211 for D.P.).
Declaration of interests
The authors report no conflict of interest.
Data availability
The authors declare that all data supporting the findings of this study are available within the paper.
Appendix A. Validation of particles settling in linearly stratified environment
We examine the settling behaviour of a suspension of particles in a linearly stratified fluid environment to evaluate the model’s capability in simulating the effects of particle sedimentation on fluid density mixing. The computational domain is a cubic region with dimensions of 0.02 m
$\times$
0.02 m
$\times$
0.02 m in length (
$L_x$
), width (
$L_y$
) and height (
$L_z$
). Periodic boundary conditions are applied in the streamwise (
$x$
) and spanwise (
$y$
) directions, and a no-slip wall boundary condition is enforced in the vertical (
$z$
) direction. The grid resolution is
$N_x \times N_y \times N_z = 50 \times 50 \times 50$
. The fluid kinematic viscosity is
$\nu _f = 10^{-6}$
m
$^2$
s
$^{-1}$
. By adjusting the volume ratio of fresh water to saline water, the fluid density
$\rho _{\!f}$
decreases linearly from the bottom to the top of the domain at the initial moment, following the relation
where
$\Delta \rho _{\!f} = 20$
kg m
$^{-3}$
is the density difference between the top and bottom interfaces, and
$\rho _a = 1000$
kg m
$^{-3}$
is the fluid density at the top interface which is marked as the background fluid density. The natural frequency of oscillation in the stratified fluid, known as the Brunt–Väisälä frequency
$N = \sqrt {|\boldsymbol{g}| \Delta \rho _{\!f} / (\rho _a L_z)}$
, is 3.13 s
$^{-1}$
. Initially, particles with zero velocity, a diameter of
$d_p$
and a density of
$\rho _p = 2650$
kg m
$^{-3}$
are uniformly distributed throughout the computational domain. The bulk particle volume fraction is
$\alpha _{p0}$
. The particle diameters
$d_p$
are 0.1 and 0.2 mm, with corresponding particle settling Reynolds numbers
$Re_{\!p,t}$
, as defined by (2.6), of approximately 0.9 and 7.2, respectively. The particle settling Froude number,
$Fr = u_t / \sqrt {|\boldsymbol{g}| L_z \Delta \rho _{\!f} / \rho _a}$
, representing the ratio of inertial to buoyancy time scales, is approximately 0.14 and 0.57, respectively. The bulk particle volume fraction
$\alpha _{p0}$
is set to 0.5 %, 1 %, 5 %, and Schmidt number
$Sc$
is set to 0.1, 0.5, 1 and 700. After the simulation begins, the particles settle in the linearly stratified fluid due to gravity.
Snapshots of particles settling in the linearly stratified fluid at (
$a$
)
$(\alpha _{p0},Sc,d_p) = (0.5\,\%, 1, 0.2 \,\mathrm{mm})$
, (
$b$
)
$(\alpha _{p0},Sc,d_p) = (1\,\%, 1, 0.2 \,\mathrm{mm})$
, (
$c$
)
$(\alpha _{p0},Sc,d_p) = (5\,\%, 1, 0.2 \,\mathrm{mm})$
, (
$d$
)
$(\alpha _{p0},Sc,d_p) = (1\,\%, 1, 0.1 \,\mathrm{mm})$
, (
$e$
)
$(\alpha _{p0},Sc,d_p) = (1\,\%, 700, 0.2 \,\mathrm{mm})$
and (
$f$
)
$(\alpha _{p0},Sc,d_p) = (1\,\%, 0.1, 0.2 \,\mathrm{mm})$
. In each panel, the three images from (i) to (iii) correspond to
$t = 1/2N$
,
$t = 3/2N$
and
$t = 2/N$
. Each surface of the computational domain is coloured by the fluid density
$\rho _{\!f}$
. The isosurfaces within the flow field, defined by
$\rho _{\!f}=1010$
kg m
$^{-3}$
, are coloured according to the fluid vertical velocity
$w_{\!f}$
. The spheres in the figure represent particles.

Comparison of mixing under (
$a$
,
$d$
) varying bulk particle volume fractions (
$\alpha _{p0}$
), (
$b$
,
$e$
) varying Schmidt numbers (
$Sc$
) and (
$c$
,
$f$
) varying particle diameters (
$d_p$
). (
$a$
,
$b$
,
$c$
) Time evolution of the variance (Var
$(\bar z /L_z)$
) of the elevation of the
$\rho _{\!f}=1010$
kg m
$^{-3}$
isosurface. (
$d$
,
$e$
,
$f$
) Average fluid density exceeding the background fluid density (
$\rho _{\!f} - \rho _a$
) at various elevations at
$t = 4/N$
.

Figure 15 depicts the settling process of particles in a linearly stratified fluid under different conditions. Figure 16 illustrates the time evolution of the isosurface elevation variance (Var
$(z/L_z)$
) for a fluid density of
$\rho _{\!f}=1010$
kg m
$^{-3}$
, alongside the fluid density profiles at
$t = 4/N$
across varying conditions. As shown in figure 15, particle sedimentation induces the downward movement of the lower-density fluid with the density isopycnals distorted downward (Doostmohammadi & Ardekani Reference Doostmohammadi and Ardekani2015; Deepwell & Sutherland Reference Deepwell and Sutherland2022), leading to fluctuations at the density interface and promoting the mixing of fluids with different densities. Once sedimentation is nearly complete, the interface stabilizes under the influence of buoyancy. Such evolution aligns with previous understandings (Magnaudet & Mercier Reference Magnaudet and Mercier2020; More & Ardekani Reference More and Ardekani2023). Thus, the variance in figure 16(
$a$
–
$c$
) initially increases and then decreases. Notably, the density is not fully mixed during particle setting, as the parameter
$2\alpha _{p0}u_t/d_pN$
is less than 10, far below the mixing threshold of 60 proposed by Blanchette (Reference Blanchette2013).
As shown in figures 15(
$a$
–
$c$
) and 16(
$a$
), increasing particle volume fraction intensifies density interface instability. Higher
$\alpha _{p0}$
correlates with lower density near the bottom (figure 16
$d$
), indicating enhanced fluid mixing. As the Schmidt number increases (the density diffusivity is weakened), although the fluid density isosurface perturbations intensify (figure 16
$b$
), the higher bottom fluid density (figure 16
$e$
) suggests reduced mixing. This is because low diffusivity (high
$Sc$
) reduces the ability to blur sharp interfaces while suppressing mixing, which increases variance. Notably, the impact of
$Sc$
increasing from 1 to 700 on the flow process is negligible. Larger particle sizes increase settling velocity, amplifying interface perturbations at
$t \lt 3/2N$
as shown in figure 16(
$c$
) and enhancing fluid mixing as shown in figure 16(
$f$
). These insights into the effects of particle concentration, Schmidt number and particle size on the mixing process are consistent with Blanchette (Reference Blanchette2013). This demonstrates the model’s ability to simulate the particle motion-induced fluid density mixing.



























































































































































































































































































