Numerical Particles Research Articles

Investigating the influence of sub-mesoscale current structures on Baltic Sea connectivity through a Lagrangian analysis

This study explores the impact of sub-mesoscale structures and vertical advection on the connectivity properties of the Baltic Sea using a Lagrangian approach. High-resolution flow fields from the General Estuarine Transport Model (GETM) were employed to compute Lagrangian trajectories, focusing on the influence of fine-scale structures on connectivity estimates. Six river mouths in the Baltic Sea served as initial positions for numerical particles, and trajectories were generated using flow fields with varying horizontal resolutions: 3D trajectories with 250m resolution as well as 2D trajectories with 250m and 1km resolutions. Several Lagrangian indices, such as mean transit time, arrival depths, and probability density functions of transit times, were analyzed to unravel the complex circulation of the Baltic Sea and highlight the substantial impact of sub-mesoscale structures on numerical trajectories. Results indicate that in 2D simulations, particles exhibit faster movement on the eastern side of the Gotland Basin in high-resolution compared to coarse-resolution simulations. This difference is attributed to the stronger coastal current in high-resolution compared to coarse-resolution simulations. Additionally, the study investigates the influence of vertical advection on numerical particle motion within the Baltic Sea, considering the difference between 3D and 2D trajectories. Findings reveal that denser water in the eastern and south-eastern areas significantly affects particle dispersion in 3D simulations, resulting in increased transit times. Conversely, regions in the North-western part of the basin accelerate particle movement in 3D compared to the 2D simulations. Finally, we calculated the average residence time of numerical particles exiting the Baltic Sea through the Danish strait. Results show an average surface layer residence time of approximately 790 days over an eight-year integration period, highlighting the relatively slow water circulation in the semi-enclosed Baltic Sea basin. This prolonged residence time emphasizes the potential for the accumulation of pollutants. Overall, the study underscores the pivotal role of fine-scale structures in shaping the connectivity of the Baltic Sea, with implications for understanding and managing environmental challenges in this unique marine ecosystem.

Inferring Tracer Diffusivity From Coherent Mesoscale Eddies

AbstractMixing along isopycnals plays an important role in the transport and uptake of oceanic tracers. Isopycnal mixing is commonly quantified by a tracer diffusivity. Previous studies have estimated the tracer diffusivity using the rate of dispersion of surface drifters, subsurface floats, or numerical particles advected by satellite‐derived velocity fields. This study shows that the diffusivity can be more efficiently estimated from the dispersion of coherent mesoscale eddies. Coherent eddies are identified and tracked as the persistent sea surface height extrema in both a two‐layer quasigeostrophic (QG) model and an idealized primitive equation (PE) model. The Lagrangian diffusivity is estimated using the tracks of these coherent eddies and compared to the diagnosed Eulerian diffusivity. It is found that the meridional coherent eddy diffusivity approaches a stable value within about 20–40 days in both models. In the QG model, the coherent eddy diffusivity is a good approximation to the upper‐layer tracer diffusivity in a broad range of flow regimes, except for small values of bottom friction or planetary vorticity gradient, where the motions of same‐sign eddies are correlated over long distances. In the PE model, the tracer diffusivity has a complicated vertical structure and the coherent eddy diffusivity is correlated with the tracer diffusivity at the e‐folding depth of the energy‐containing eddies where the intrinsic speed of the coherent eddies matches the rms eddy velocity. These results suggest that the oceanic tracer diffusivity at depth can be estimated from the movements of coherent mesoscale eddies, which are routinely tracked from satellite observations.

AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing

Abstract. Simulation tools are important to investigate and predict mobility and the destructive potential of gravitational mass flows (e.g., snow avalanches). AvaFrame – the open avalanche framework – offers well-established computational modeling approaches, tools for data handling and analysis, and ready-to-use modules for evaluation and testing. This paper presents the theoretical background, derivation, and model verification for one of AvaFrame's core modules, the thickness-integrated computational model for avalanches with flow or mixed form of movement, named com1DFA. Particular emphasis within the description of the utilized numerical particle–grid method is given to the computation of spatial gradients and the accurate implementation of driving and resisting forces. The implemented method allows us to provide a time–space criterion connecting the numerical particles, grid, and time discretization. The convergence and robustness of the numerical implementation is checked with respect to the spatiotemporal evolution of the flow variables using tests with a known analytical solution. In addition, we present a new test for verifying the accuracy of the numerical simulation in terms of runout (angle and distance). This test is derived from the total energy balance along the center-of-mass path of the avalanche. This article, particularly in combination with the code availability (open-source code repository) and detailed online documentation provides a description of an extendable framework for modeling and verification of avalanche simulation tools.

Sensitivity of gyre-scale marine connectivity estimates to fine-scale circulation

Abstract. We investigated the connectivity properties of an idealized western boundary current system separating two ocean gyres, where the flow is characterized by a well-defined mean circulation as well as energetic fine-scale features (i.e., mesoscale and submesoscale currents). We used a time-evolving 3D flow field from a high-resolution (HR-3D) ocean model of this system. In order to evaluate the role of the fine scales in connectivity estimates, we computed Lagrangian trajectories in three different ways: using the HR-3D flow, using the same flow but filtered on a coarse-resolution grid (CR-3D), and using the surface layer flow only (HR-SL). We examined connectivity between the two gyres along the western boundary current and across it by using and comparing different metrics, such as minimum and averaged values of transit time between 16 key sites, arrival depths, and probability density functions of transit times. We find that when the fine-scale flow is resolved, the numerical particles connect pairs of sites faster (between 100 to 300 d) than when it is absent. This is particularly true for sites that are along and near the jets separating the two gyres. Moreover, the connectivity is facilitated when 3D instead of surface currents are resolved. Finally, our results emphasize that ocean connectivity is 3D and not 2D and that assessing connectivity properties using climatologies or low-resolution velocity fields yields strongly biased estimates.

Assessing the risk of oil spill impacts and potential biodiversity loss for coastal marine environment at the turn of the COVID-19 pandemic event

The Tuscan Archipelago, with its great environmental and economic importance, is one of the highest oil spill density areas in the Western Mediterranean. In this study, an interdisciplinary approach, based on numerical applications and experimental methods, was implemented to quantify the risk of oil spill impact along the rocky shores of this archipelago in relation to the maritime activities. The risk, defined as a combination of the hazard and the damage, was quantified for the biennial 2019–2020 in order to account for the effects generated by the COVID-19 pandemic restrictions on the local maritime traffic. A high-resolution oceanographic and particle tracking model was applied to simulate the trajectories of possible oil spill events and to quantify the hazard of impacts on the coast of numerical particles, daily seeded in correspondence of those marine sectors that are characterised by relevant traffic of vessels. The damage, expressed as the product of exposure and vulnerability, was estimated following an extensive sampling approach aimed at quantifying the ecological status of the rocky shores in four selected islands of the Tuscan Archipelago. Results revealed and quantified the direct relationship between the temporary reduction of the maritime traffic due to the pandemic restrictions, and the probability of suffering damage from oil spill impact along the archipelago's rocky shores, which was highly context-dependent.

Event-driven sorting algorithm-based Monte Carlo method with neighbour merging method for solving aerosol dynamics

A new event-driven sorting algorithm-based merging Monte Carlo (SAMMC) method is proposed and developed for solving the general dynamic equation in aerosol dynamics. A neighbour merging method is proposed to maintain a constant-volume and constant-number scheme with minimal interference to the numerical particle population, where absolute volume difference (AVD) and relative volume difference (RVD) are used as the crucial merging criteria. The SAMMC method can be used for simulating all aerosol dynamic processes with very high computational accuracy, especially effective in those aerosol dynamic processes generating additional numerical particles. In the present study, comprehensive computational conditions are used to study their impacts on computational accuracy and efficiency by comparing the SAMMC method to previous MC methods and analytical solutions. Numerical results show that the SAMMC method has excellent agreement with analytical solutions for all specified cases of different aerosol dynamic processes and shows higher computational accuracy than equal-weight-based MC methods. In addition, the computational accuracy of the SAMMC method in the total particle number concentration is much higher than those of the weighted fraction Monte Carlo (WFMC) method and sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method in non-homogeneous coagulation. The SAMMC method can also achieve the same computational precision as the multi-Monte Carlo (MMC) method at only slightly higher computational cost in homogeneous coagulation. More importantly, the SAMMC method can deal with breakage-related processes and simultaneous coagulation and nucleation with very high computational accuracy and efficiency, while the numerical results of the MMC method may significantly deviate from analytical solutions due to the introduction of systematic errors. Furthermore, the RVD can achieve higher computational accuracy in multi-breakage modelling than AVD, but AVD and RVD have almost the same computational efficiency and accuracy in other aerosol dynamic processes.

Assessment of a Hybrid Eulerian–Lagrangian CFD Solver for Wind Turbine Applications and Comparison with the New MEXICO Experiment

In this paper, the hybrid Lagrangian–Eulerian solver HoPFlow is presented and evaluated against wind tunnel measurements from the New MEXICO experiment. In the paper, the distinct solvers that assemble the HoPFlow solver are presented, alongside with details on their mutual coupling and interaction. The Eulerian solver, MaPFlow, solves the compressible Navier–Stokes equations under a cell-centered finite-volume discretization scheme, while the Lagrangian solver uses numerical particles that carry mass, pressure, dilatation and vorticity as flow markers in order to represent the flow-field by following their trajectories. The velocity field is calculated with the use of the decomposition theorem introduced by Helmholtz. Computational performance is enhanced by utilizing the particle mesh (PM) methodology in order to solve the Poisson equations for the scalar potential ϕ and the stream function ψ→. The hybrid solver is tested in 3-D unsteady simulations concerning the axial flow around the wind turbine (WT) model rotor tested in the New MEXICO experimental campaign. Simulation results are presented as integrated rotor loads, radial distribution of aerodynamic forces and moments and pressure distributions at various span-wise positions along the rotor blades. Comparison is made against experimental data and computational results produced by the pure Eulerian solver. A total of 5 PM nodes per chord length of the blade section at 75% have been found to be sufficient to predict the loading at the tip region of the blade with great accuracy. Discrepancies with respect to measurements, observed at the root and middle sections of the blade, are attributed to the omission of the spinner geometry in the simulations.

Seasonal Surface Eddy Mixing in the Kuroshio Extension: Estimation and Machine Learning Prediction

AbstractResults of coarse‐resolution climate models are sensitive to the specification of ocean eddy mixing coefficients. Therefore, it is important to estimate, rationalize and predict eddy diffusivities. Here, we estimate the seasonal variability of surface eddy diffusivities in the Kuroshio Extension region using numerical particles advected by a submesoscale‐permitting model solution. We find that both the spatial structure and the domain‐averaged value of the particle‐based eddy diffusivities have a significant seasonal cycle. We also assess the predictability of cross‐stream mixing lengths in this region using the methods of machine learning, suppressed mixing length theory (SMLT), and multiple linear regression (LR). The predictors we choose are all variables from SMLT that represent eddy‐ and mean‐flow properties, and these predictors correlate well with the particle‐based cross‐stream mixing lengths. We demonstrate that, compared to SMLT and LR, machine learning methods, in particular the random forest (RF) and convolutional neural network (CNN), can better represent both the spatial structure and the domain‐averaged value of cross‐stream mixing lengths. The skill in predicting the mixing lengths with CNN has much less seasonal variability than that with RF. Our results indicate that the machine learning approach may be useful in future development of eddy parameterization schemes.

Lagrangian particle tracking with new weighted fraction Monte Carlo method for studying the soot particle size distributions in premixed flames

PurposeThe purpose of this paper is to study the soot formation and evolution by using this newly developed Lagrangian particle tracking with weighted fraction Monte Carlo (LPT-WFMC) method.Design/methodology/approachThe weighted soot particles are used in this MC framework and is tracked using Lagrangian approach. A detailed soot model based on the LPT-WFMC method is used to study the soot formation and evolution in ethylene laminar premixed flames.FindingsThe LPT-WFMC method is validated by both experimental and numerical results of the direct simulation Monte Carlo (DSMC) and Multi-Monte Carlo (MMC) methods. Compared with DSMC and MMC methods, the stochastic error analysis shows this new LPT-WFMC method could further extend the particle size distributions (PSDs) and improve the accuracy for predicting soot PSDs at larger particle size regime.Originality/valueCompared with conventional weighted particle schemes, the weight distributions in LPT-WFMC method are adjustable by adopting different fraction functions. As a result, the number of numerical soot particles in each size interval could be also adjustable. The stochastic error of PSDs in larger particle size regime can also be minimized by increasing the number of numerical soot particles at larger size interval.

Analysis of mixing structures in the Adriatic Sea using finite-size Lyapunov exponents

In this paper, we report on the mixing structures and transport properties of the Adriatic Sea surface, as a semi-enclosed basin of the Mediterranean Sea, from October 2006 until December 2011. Lagrangian transport models were used to simulate synthetic trajectories from the mean flow fields obtained by the Massachusetts Institute of Technology general circulation model implemented for the Adriatic. We examine the dispersion properties of numerical pair particles, through the calculation of time-averaged finite-size Lyapunov exponents (FSLEs) in the Adriatic Sea during selected months in each year. The results show the significant effects of river runoff and wind forcing, especially the Bora wind field, on the mixing activities of numerical pair particles by the generation of vortices, which appear as a tangle of filaments on the FSLE maps. The stretch/compression lines, which contain high values of the FSLEs, work as robust transport barriers, most having been detected along boundary currents on the eastern and western flanks of the Adriatic, particularly during winter. Numerical experiments have indicated that stable flows, with less mixing activity, occur in the northern part of the Adriatic in June and September of each year, while the Southern Adriatic Pit has flows with larger seasonal fluctuations and high values of eddy kinetic energy because of the influence of wind and energetic currents entering from the Ionian Sea.

Variable Nordic Seas inflow linked to shifts in North Atlantic circulation

AbstractThe inflow across the Iceland-Scotland Ridge determines the amount of heat supplied to the Nordic Seas from the subpolar North Atlantic (SPNA). Consequently, variable inflow properties and volume transport at the ridge influence marine ecosystems and sea ice extent further north. Here, we identify the upstream pathways of the Nordic Seas inflow, and assess the mechanisms responsible for interannual inflow variability. Using an eddy-permitting ocean model hindcast and a Lagrangian analysis tool, numerical particles are released at the ridge during 1986-2015 and tracked backward in time. We find an inflow that is well-mixed in terms of its properties, where 64% comes from the subtropics and 26% has a subpolar or Arctic origin. The local instantaneous response to the NAO is important for the overall transport of both subtropical and Arctic-origin waters at the ridge. In the years before reaching the ridge, the subtropical particles are influenced by atmospheric circulation anomalies in the gyre boundary region and over the SPNA, forcing shifts in the North Atlantic Current (NAC) and the subpolar front. An equatorward shifted NAC and westward shifted subpolar front correspond to a warmer, more saline inflow. Atmospheric circulation anomalies over the SPNA also affect the amount of Arctic-origin water re-routed from the Labrador Current toward the Nordic Seas. A high transport of Arctic-origin water is associated with a colder, fresher inflow across the Iceland-Scotland Ridge. The results thus demonstrate the importance of gyre dynamics and wind forcing in affecting the Nordic Seas inflow properties and volume transport.

Coupled CFD–DEM numerical modelling of perforation damage and sand production in weak sandstone formation

A coupled microscopic simulation method was implemented to investigate the bond breakage behaviour during perforation and sand production in a weak cemented sandstone. A new contact bond model was implemented in the open-source program CFDEM to simulate a large cylindrical sample of one hundred thousand numerical particles using a high-performance computer (HPC) system. The coupled simulation of the particle–fluid phases and the information exchange between them required intensive computational power and highly efficient parallelization algorithms, yet it provided the detailed information on the distribution of bond and bond breakage, new contact formation, particle migration and the associated change in the internal porosity across the sample. The perforation process was found to create a damage zone that contained a compacted core of unbonded particles. The compacted core expanded quickly under fluid flow condition and released its particles to migrate towards the perforation tunnel. Small particles were produced first from the perforation damage zone, while fewer particles of larger sizes were produced later in an overall transient sand production phenomenon.

A new weighted fraction Monte Carlo method for particle coagulation

PurposeThe purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method.Design/methodology/approachThe weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (α). Probabilistic removal is also introduced to maintain a constant number scheme.FindingsThree typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated.Originality ValueStochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

Evaluation of oxygen isotopes and trace elements in planktonic foraminifera from the Mediterranean Sea as recorders of seawater oxygen isotopes and salinity

Abstract. The Mediterranean Sea is characterized by a relatively strong west to east salinity gradient, which makes it an area suitable for testing the effect of salinity on foraminiferal shell geochemistry. We collected living specimens of the planktonic foraminifer Globigerinoides ruber albus to analyse the relation between element ∕ Ca ratios, stable oxygen isotopes of their shells, and surface seawater salinity, isotopic composition and temperature. The oxygen isotopes of sea surface water also correlate with salinity in the Mediterranean during winter, which is when sampling for this study took place. Seawater oxygen and hydrogen isotopes are positively correlated in both the eastern and western Mediterranean Sea, although the relationship differs from previously reported values, especially in the eastern region. The slope between salinity and seawater oxygen isotopes is lower than previously published results. Still, despite the rather modest slope, seawater and foraminiferal carbonate oxygen isotopes are correlated in our dataset, albeit with large residuals and high residual variability. This scatter could be due to either biological variability in vital effects or environmental variability. Numerical models backtracking particles show that ocean-current-driven mixing of particles of different origins might dampen sensitivity and could result in an offset caused by horizontal transport. Results show that Na ∕ Ca is positively correlated with salinity and independent of temperature. As expected, foraminiferal Mg ∕ Ca increases with temperature, which is in line with earlier calibrations, and in the high salinity environment. By using living foraminifera during winter, the previously established Mg ∕ Ca–temperature calibration is extended to temperatures below 18 ∘C, which is a fundamental prerequisite of using single foraminifera for reconstructing past seasonality.

Near-Surface Transport Properties and Lagrangian Statistics during Two Contrasting Years in the Adriatic Sea

This paper describes the near-surface transport properties and Lagrangian statistics in the Adriatic semi-enclosed basin using synthetic drifters. Lagrangian transport models were used to simulate synthetic trajectories from the mean flow fields obtained by the Massachusetts Institute of Technology general circulation model (MITgcm), implemented in the Adriatic from October 2006 until December 2008. In particular, the surface circulation properties in two contrasting years (2007 had a mild winter and cold fall, while 2008 had a normal winter and hot summer) are compared here. In addition, the Lagrangian statistics for the entire Adriatic Basin after removing the Eulerian mean circulation for numerical particles were calculated. The results indicate that the numerical particles were slower in this simulation when compared with the real drifters. This is because of the reduced energetic flow field generated by the MIT general circulation model during the selected years. The numerical results showed that the balanced effects of the wind-driven recirculation in the northernmost area(which would be a sea response to the Bora wind field) and the Po River discharge cause the residence times to be similar during the two selected years (182 and 185 days in 2007 and 2008, respectively). Furthermore, the mean angular momentum, diffusivity, and Lagrangian velocity covariance values are smaller than in the real drifter observations, while the maximum Lagrangian integral time scale is the same.

Pathways and Water Mass Transformation Along and Across the Mohn‐Knipovich Ridge in the Nordic Seas

AbstractAtlantic Water takes various pathways through the Nordic Seas, and its transformation to denser waters forms a crucial connection to the lower limb of the Atlantic Meridional Overturning Circulation. Circulation maps often schematize two distinct pathways of Atlantic Water: one following the Norwegian Atlantic Slope Current along the continental slope of Norway and one following the Norwegian Atlantic Front Current along the Mohn and Knipovich Ridges. In this paper, the connectivity between the northward flow along these ridges is investigated. Analyzing trajectories of surface drifters and ARGO floats, we find that only 8% of the floats that travel near the mid‐ocean ridges take the frontal pathway to the north. Indeed, by tracing numerical particles in a realistic numerical simulation, part of the water mass traveling along the Mohn Ridge follows the 2,500 m isobath eastward and joins the slope current, instead of flowing north along the Knipovich Ridge. Furthermore, north of 74°N, frequent exchange between the slope current and the front current is observed. Therefore, the slope current and front current are less isolated than often schematized. Additionally, the observational data set reveals substantial cross‐ridge exchange; 31% of the floats that travel within 60 km from the mid‐ocean ridges cross it. Results from numerical simulations indicate that the cross‐ridge exchange leads to cooling and freshening of the Atlantic Water along the front. Deployments of floats near the mid‐ocean ridges are needed to investigate the pathway of Atlantic Water and its exchange across the ridge in more detail.

Adaptive particle method based on moments for simulating the mass transport in natural flows

In this work, two modifications of an adaptive particle method based on the moments of the internal concentration of numerical particles are presented to introduce the effect of local shears on the mass transport in natural flows. This moment method uses a Taylor expansion of the flow velocity field to derive the transport equation of moments. The first modification is based on the introduction of a method of the local frame transport in order to perform an extension of the Taylor expansion of the flow velocity to a higher order. The second modification consists in applying a splitting or a merging to non-spherical numerical particles. When a non-spherical numerical particle becomes large compared to the scale of spatial variations of the velocity gradient, it is divided into two non-spherical numerical particles. On the contrary, when particles reach some other parts of the flow where they become small compared to spatial variations of the velocity gradient, then these particles should merge. The accuracy of both modifications is evaluated by simulating the mass transport in natural flows.

Dynamics control of an in-plane-switching liquid crystal cell using heterogeneous substrates.

The control of surface anchoring strength can be achieved by using heterogeneous substrates. In contrast to conventional substrates that control the anchoring strength by using temperature or chemical processes, heterogeneous substrates provide surface anchoring to liquid crystal molecules by using a mixed composition of (1) a zero anchoring surface and (2) planar-anchoring patches. To study the dynamics of in-plane-switching liquid crystal displays (IPS-LCDs) under external fields, a new particle-based numerical algorithm is developed to simulate both nematic liquid crystals and heterogeneous surfaces. This new method allows us to create different heterogeneous surfaces easily by adopting predefined distributions of numerical particles. The generated effective anchoring strength from the heterogeneous surface is thus calculated, and the dynamical response is found to be similar to that of conventional homogeneously processed substrates. The results suggest that the use of a heterogeneous LCD cell is a suitable alternative for creating desirable LCD substrates, for which chemical/temperature dependence can be transferred to a more controllable configurational dependence. Interestingly, we found master curves in the peak transmittance/recovery time phase space, and they appeared to be dependent solely on the cell thickness. This discovery clarifies the fundamental optical dynamics of IPS-LCD cells.

Large impact of Stokes drift on the fate of surface floating debris in the South Indian Basin.

In the open ocean, floating surface debris such as plastics concentrate in five main accumulation zones centered around 30° latitude, far from highly turbulent areas. Using Lagrangian advection of numerical particles by surface currents from ocean model reanalysis, previous studies have shown long-distance connection from the accumulation zones of the South Indian to the South Pacific oceans. An important physical process affecting surface particles but missing in such analyses is wave-induced Stokes drift. Taking into account surface Stokes drift from a wave model reanalysis radically changes the fate of South Indian particles. The convergence region moves from the east to the west of the basin, so particles leak to the South Atlantic rather than the South Pacific. Stokes drift changes the South Indian sensitive balance between Ekman convergence and turbulent diffusion processes, inducing either westward entrainment in the north of the accumulation zone, or eastward entrainment in the south.

A conservative finite volume-particle hybrid method for simulation of incompressible interfacial flow

Coupling the finite volume method (FVM) and the moving-particle semi-implicit (MPS) method, a conservative hybrid method is proposed for simulation of incompressible interfacial flow. In this hybrid method, bulk flow is resolved using the multi-moment constrained interpolation profile (CIP) FVM while the interface region is rendered using moving particles calculated by several enhanced MPS schemes. A new boundary condition is developed for particles located on the boundary of the interface. Numerical particles in the MPS method are used to determine the density of each mesh cell and the conservation of mass is guaranteed by a volume-fraction remedy procedure. The approach allows accurate interface tracking without diminishing numerical efficiency. Several benchmark simulations are conducted to demonstrate the accuracy and efficiency of the proposed hybrid method.