Getting Started with Multiphase CFD in OpenFOAM

In this lecture, we introduce twoLiquidMixingFoam, a multiphase solver in OpenFOAM specifically designed to simulate the mixing of two miscible incompressible liquids.

Unlike interFoam and interIsoFoam, where phases are immiscible and separated by a sharp interface, twoLiquidMixingFoam allows the two liquids to mix through diffusion. There is no explicit interface tracking and no surface tension modeling, making this solver suitable for problems such as concentration-driven mixing, molecular diffusion, and turbulent liquid–liquid blending.

This lecture covers:

• Physical meaning and use cases of miscible two-liquid flows

• Key differences between interface-tracking solvers and mixing solvers

• Role of the volume fraction (α) as a mixture fraction or concentration

• Governing equations solved by twoLiquidMixingFoam:

  • Continuity and momentum equations with mixture properties

  • Volume fraction transport equation with diffusion term

• Mixture laws for density and viscosity based on local concentration

• Why surface tension is absent in miscible flows

• Use of PIMPLE algorithm for time-dependent simulations

• Overview of the solver source code and alpha diffusion implementation

• Setting up a practical case with two miscible liquids (e.g., water and sludge)

• Defining transport properties, diffusion coefficient, and solver controls

• Stability considerations when mixing liquids with large density differences

• Practical limitations and numerical challenges of twoLiquidMixingFoam

Through a hands-on example, this lecture demonstrates how diffusion causes gradual phase mixing, how the volume fraction evolves toward a uniform value, and why solver stability becomes critical when property contrasts are large.

By the end of this lecture, you will understand when to use twoLiquidMixingFoam, how to configure it correctly, and how to distinguish between physical mixing behavior and numerical instability in miscible multiphase simulations.

In this lecture, we introduce interMixingFoam, a specialized OpenFOAM solver designed for three-phase flow problems where:

• Two phases are miscible with each other, and

• Both of those phases are immiscible with a third phase

This type of scenario commonly appears in practical applications, such as water–sludge mixing in the presence of air, where mixing and sharp interface tracking must occur simultaneously.

What this solver is (and is not)

• interMixingFoam can handle only three phases

• Two phases can diffuse and mix

• The third phase remains immiscible

• Interface tracking is performed using VOF with MULES

• This solver does not support arbitrary combinations of miscible and immiscible phases

Topics covered in this lecture

• Review of previously used solvers:

  • interFoam (two immiscible phases)

  • interIsoFoam (improved interface capturing)

  • Miscible two-phase solvers

• Physical motivation for partial miscibility problems

• Solver structure and similarity to interFoam

• Key difference in the alpha transport equations:

  • Separate equations for α₁ and α₂

  • α₃ computed as 1 − α₁ − α₂

• Why interMixingFoam is limited to three phases only

• Role of MULES in interface capturing

• How diffusion is enabled only between selected phase pairs

• Importance of phase ordering in transportProperties

• Defining:

  • Density and viscosity for each phase

  • Diffusion coefficients between miscible phases

  • Surface tension between immiscible phase pairs

• Correct setup of:

  • Alpha fields and boundary conditions

  • setFields for multi-region initialization

  • Gravity-driven mixing scenarios

• Common setup mistakes and how to fix them:

  • Incorrect solver selection for diffusive alphas

  • Inconsistent alpha initialization

  • Boundary condition conflicts

• Visualization of phase evolution and mixing behavior

Through a hands-on example, you will see how two fluids gradually mix, while the third phase maintains a sharp interface, capturing both diffusion-driven mixing and interface dynamics in a single simulation.

By the end of this lecture, you will clearly understand when interMixingFoam should be used, how to configure it correctly, and how it differs from both interFoam and multiphaseInterFoam.

In this lecture, we explore interPhaseChangeFoam, OpenFOAM’s simplest solver for modeling phase change in incompressible two-phase flows. Using cavitation as a motivating example, we learn how liquid–vapor phase change is introduced through volume-fraction transport and pressure-driven mass transfer.

We begin with the governing equations, highlighting how a single momentum equation is solved using mixture properties, where density and viscosity are weighted by phase volume fractions. Since the flow is incompressible and isothermal, no energy equation is solved, and phase change is driven purely by the difference between local pressure and saturation pressure.

Key topics covered in this lecture include:

• Physical meaning of cavitation in incompressible flows

• Volume of Fluid (VoF) formulation and phase identification using alpha

• How evaporation and condensation are modeled using pressure-based source terms

• Role of saturation pressure and phase-change coefficients

• Pressure–velocity coupling and phase-change contributions in the pressure equation

• Overview of cavitation models available in interPhaseChangeFoam

• Walkthrough of the solver source code and key implementation details

While interPhaseChangeFoam cannot capture pressure waves or shock-driven cavitation, it provides a strong foundation for understanding pressure-driven phase change mechanics in CFD.

In this lecture, we explore interCondensingEvaporatingFoam, an OpenFOAM multiphase solver used to model phase change between two immiscible incompressible fluids based on temperature-driven condensation and evaporation.

Unlike interPhaseChangeFoam, where phase change is governed by saturation pressure (commonly used for cavitation problems), this solver uses saturation temperature as the phase-change criterion and explicitly solves the energy equation.

Key differences from interPhaseChangeFoam

• Phase change driven by temperature difference instead of pressure difference

• Explicit solution of the energy (temperature) equation

• Suitable for condensation and evaporation problems

• Not intended for cavitation-type phenomena

Topics covered in this lecture

• Physical modeling assumptions:

  • Incompressible, immiscible liquid and vapor phases

  • Temperature-controlled phase change

• Overview of solver structure and governing equations

• Source terms in the pressure equation due to:

  • Condensation and evaporation mass transfer

• Role of the mixture model in:

  • Computing phase-change rates

  • Coupling momentum, pressure, and temperature fields

• Energy equation formulation and thermal source terms

• Required dictionaries and properties:

  • phaseChangeProperties

  • thermophysicalProperties

  • Transport and thermal properties (Cp, Cv, kappa, latent heat)

  • Prandtl number for heat transfer

• Setting up a condensation problem on a cold wall

• Mesh scaling considerations for phase-change simulations

• Boundary conditions for:

  • Phase fraction (liquid/vapor)

  • Pressure and velocity

  • Temperature and thermal gradients

• Importance of time-step control for stable condensation modeling

• Visualization of:

  • Condensate formation

  • Gravity-driven liquid accumulation

  • Temperature gradients and induced flow

Through practical simulations, this lecture demonstrates how vapor condenses on colder surfaces, forms liquid films or droplets, and accumulates under gravity—all captured using interCondensingEvaporatingFoam.

By the end of this lecture, you will understand when to use interCondensingEvaporatingFoam, how it differs from other phase-change solvers, and how to set up stable and physically meaningful condensation/evaporation simulations in OpenFOAM.

In this lecture, we explore icoReactingMultiphaseInterFoam, one of the most advanced multiphase solvers available in OpenFOAM. This solver goes far beyond simple evaporation or condensation and enables reactive, thermally coupled, volume-of-fluid–based multiphase simulations.

Unlike interCondensingEvaporatingFoam, where phase change is governed only by saturation temperature, icoReactingMultiphaseInterFoam allows multiple criteria for mass transfer, including reaction-driven phase change, species diffusion, and interfacial chemistry.

What makes this solver unique

• Volume of Fluid (VOF)–based interface tracking

• Thermally coupled: solves momentum, energy, and species equations

• Supports evaporation, condensation, oxidation, melting, and solidification

• Mixture-based single-formulation approach

• Fluid properties dynamically updated based on local volume fractions

• Applicable to gas–liquid–solid systems

Topics covered in this lecture

• Conceptual overview of icoReactingMultiphaseInterFoam

• Differences from interCondensingEvaporatingFoam

• Mixture-based formulation and single momentum equation

• Supported phase models:

  • Pure phase model

  • Static phase model (solid / immobile)

  • Moving phase model

  • Multicomponent phase model

• Overview of phaseSystem architecture in OpenFOAM

• Available mass-transfer models:

  • Lee model

  • Diffusion-controlled gas evaporation

  • Hertz–Knudsen–Schrage kinetic model

  • Interface oxide rate model

• Thermophysical modeling flexibility:

  • Constant or variable transport properties

  • Choice of equation of state

  • Enthalpy vs sensible energy formulation

  • Multi-species mixtures

• Surface tension and porous solidification models

• Boundary conditions for reactive interfaces

• Practical setup of a liquid–gas–oxide system

• Demonstration of oxide formation at the interface

• Visualization of:

  • Volume fraction evolution

  • Reactive phase conversion

  • Gravity-driven motion and accumulation

By the end of this lecture, you will understand when and why to use icoReactingMultiphaseInterFoam, how its phase models and mass-transfer mechanisms work, and how to set up reactive multiphase simulations involving gas, liquid, and solid phases in OpenFOAM.

n this lecture, we take a deep dive into cavitatingFoam, OpenFOAM’s transient compressible cavitation solver, and understand how it fundamentally differs from other cavitation and phase-change solvers such as phaseChangeFoam.

We begin by exploring the homogeneous equilibrium model (HEM) used in cavitatingFoam, where liquid and vapor phases are assumed to be in thermodynamic equilibrium, sharing velocity and temperature while accounting for different compressibilities. This key feature allows the solver to capture pressure wave propagation and shock-like cavitation dynamics, which are not possible in incompressible formulations.

Key topics covered in this lecture include:

• Why compressibility matters in cavitating flows

• Differences between cavitatingFoam and phaseChangeFoam

• Barotropic energy closure and why no energy equation is solved

• How density is used as the primary variable instead of volume fraction

• Overview of barotropic compressibility models (Linear, Chung, Wallis)

• Solver algorithm and the PIMPLE-based solution procedure

• Turbulence modeling options for cavitating flows

• Typical applications such as throttling devices, high-speed cavitation, and shock-induced bubble collapse

We also walk through:

• The OpenFOAM source code structure of cavitatingFoam

• Setup of thermophysical and transport properties

• Initialization of density and boundary conditions

• Running and visualizing a cavitation case

• Practical insights into mesh effects, inlet/outlet placement, and numerical stability

This lecture is ideal for learners who want to understand how cavitation is modeled in compressible flows, when to use cavitatingFoam, and how to correctly set up simulations for realistic cavitation dynamics.

In this lecture, we dive into compressibleInterFoam, OpenFOAM’s solver for two-phase, compressible, non-isothermal, immiscible flows. Unlike incompressible solvers such as interFoam, this solver accounts for density variations, compressibility, and heat transfer, making it suitable for problems where temperature and pressure changes strongly affect the flow.

We begin with the physical and mathematical foundations of the solver, explaining how:

• Two immiscible phases are tracked using the Volume of Fluid (VOF) method

• A single mixture momentum equation is solved using mixture properties

• Phase volume fractions (alpha1, alpha2) evolve with interface-compression to maintain sharp interfaces

• Energy (temperature) equation is solved in addition to momentum and pressure

• Phase-wise compressibility is handled through thermophysical models

Key topics covered in this lecture include:

• Differences between incompressible interFoam and compressibleInterFoam

• Mixture formulation vs Euler–Euler two-phase turbulence modeling

• Pressure formulation using p_rgh and its relation to absolute pressure

• Role of thermophysical properties and equations of state

• Handling strong density variation across gas–liquid interfaces

• Interface capturing using alpha-based VOF (and relation to compressibleInterIsoFoam)

• Turbulence modeling options for single-velocity, multi-phase flows

We then walk through a complete practical setup:

• Converting an incompressible dam-break-type case to compressibleInterFoam

• Defining pressure, velocity, temperature, and phase fraction boundary conditions

• Setting up thermophysicalProperties for air and water

• Choosing discretization schemes and solver settings

• Initializing fields using setFields

• Running the simulation and analyzing results

Finally, we compare results with incompressible simulations and observe:

• Temperature evolution during phase motion

• Density-driven flow behavior

• Additional physics captured due to compressibility and heat transfer

This solver is well-suited for:

• Gas–liquid flows with strong temperature gradients

• Compressible multi-phase flows with heat transfer

• High-speed or thermally driven interface problems

• Extending incompressible case setups to more realistic physics

If you want to move beyond isothermal assumptions and start modeling thermal effects in two-phase flows, compressibleInterFoam is the natural next step.

In this lecture, we explore the compressible multiphase solver family in OpenFOAM, focusing on how they extend the concepts you already know from incompressible solvers such as interFoam, interIsoFoam, and multiphaseFoam.

We begin by introducing the compressible counterparts:

• compressibleInterFoam

• compressibleInterIsoFoam

• compressibleMultiphaseFoam

Using a water column test case, we first demonstrate how to transition from compressibleInterFoam to compressibleInterIsoFoam, replacing the standard Volume of Fluid (VOF) interface capturing with the isoAdvector geometric interface tracking method. We walk through:

• Required solver changes

• Modifications to alpha transport

• Running and comparing simulations

• Visual comparison of interface sharpness between VOF and isoAdvector

• Discussion on mesh resolution effects and solver accuracy

Next, we move beyond two-phase flows and introduce compressibleMultiphaseFoam, which allows simulation of N-phase compressible flows with heat transfer. In this section, we:

• Extend a two-phase case to a three-phase system (air–water–mercury)

• Define additional phase fractions (alpha.water, alpha.air, alpha.mercury)

• Configure thermophysical properties for multiple phases

• Set up surface tension (sigma) between each phase pair

• Initialize complex phase distributions using setFields

• Address common setup errors related to boundary conditions, diffusivity, and discretization

You’ll also see how:

• A single mixture momentum equation is solved

• Density varies with pressure and temperature

• Interface tracking in compressibleMultiphaseFoam relies on VOF (MULES) rather than isoAdvector

• Phase density differences naturally drive realistic physical behavior (e.g., mercury sinking below water)

By the end of this lecture, you will understand:

• When to use compressibleInterFoam vs compressibleInterIsoFoam

• The advantages and limitations of geometric interface tracking

• How to scale from two-phase to N-phase compressible simulations

• Practical workflow for setting up complex multiphase cases in OpenFOAM

This lecture is ideal for learners who want to move from basic two-phase flows to realistic, multi-phase, compressible simulations involving strong density contrasts and thermal effects.

In this lecture, we introduce driftFluxFoam, a multiphase solver in OpenFOAM that sits conceptually between mixture models and full Euler–Euler approaches. This solver is especially useful for dispersed-phase flows where one phase moves relative to another without the high computational cost of solving separate momentum equations for each phase.

We begin by reviewing the three major multiphase modeling strategies in OpenFOAM:

• Mixture models, where a single momentum equation is solved and slip between phases is neglected

• Euler–Euler models, where each phase has its own momentum, pressure, and turbulence equations

• Drift-flux models, which retain a single mixture momentum equation while accounting for relative (slip) velocity between phases through constitutive models

You will learn when and why drift-flux modeling is appropriate, especially for applications such as:

• Sedimentation and settling of particles

• Dispersed solids or droplets in a carrier fluid

• Buoyancy-driven separation

• Pollutant transport and slurry flows

The lecture then dives into the theoretical foundation of driftFluxFoam, including:

• Volume-fraction transport using MULES

• Definition and role of drift velocity

• How slip velocity is modeled rather than solved

• Additional stress terms introduced in the momentum equation

• Comparison of accuracy, cost, and applicability versus mixture and Euler–Euler models

Next, we explore the driftFluxFoam source code, identifying:

• The role of the UdmModel in computing drift velocity

• Available drift models (simple and relative velocity)

• How additional stresses (tauDm) are introduced

• Supported viscosity and rheology models (including Bingham plastic and slurry-type behavior)

Finally, we work through a practical CFD example:

• Modification of a flow-past-cylinder case

• Introduction of a dispersed sludge phase

• Application of gravity-driven drift velocity

• Setup of boundary conditions, turbulence modeling, and transport properties

• Handling common numerical issues related to gradients and discretization

• Visualization of sedimentation, accumulation, and flow-induced separation

By the end of this lecture, you will be able to:

• Understand where driftFluxFoam fits in the multiphase modeling hierarchy

• Decide when drift-flux modeling is preferable to Euler–Euler methods

• Configure and run sedimentation and separation simulations

• Diagnose and correct common numerical and setup issues

• Interpret results for dispersed-phase transport in complex geometries

In this lecture, we move to the most advanced multiphase modeling approach in OpenFOAM—the Euler–Euler framework—and introduce the twoPhaseEulerFoam solver. Building on the previous discussion of mixture models and drift-flux models, this lecture explains when and why a full Euler–Euler formulation is required and how it is implemented in OpenFOAM.

The twoPhaseEulerFoam solver is designed for multiphase flows where interfacial interactions dominate the physics, such as:

• Bubble columns and boiling flows

• Droplet-laden or particle-laden flows

• Fluidized beds

• Slug, churn, annular, and mist flow regimes

Unlike mixture or drift-flux models, this solver treats both phases as interpenetrating continua and solves:

• Separate mass, momentum, and energy equations for each phase

• Distinct velocity fields for each phase

• A single shared pressure field coupled to both momentum equations

The lecture explains the governing equations in detail, highlighting:

• Volume-fraction-weighted conservation equations

• Phase-specific momentum equations and stress terms

• Interfacial momentum exchange and body forces

• Separate thermodynamics and interphase heat transfer

• Pressure coupling and the PIMPLE-based solution strategy

A major focus is placed on interfacial force modeling, including:

• Drag forces due to slip velocity

• Lift forces arising from velocity gradients

• Virtual mass effects from relative acceleration

• Turbulent dispersion forces

• Wall lubrication forces near solid boundaries

• Shape and aspect-ratio modeling for deforming bubbles

We also discuss the key numerical challenges of Euler–Euler methods, such as:

• Maintaining bounded volume fractions (α₁ + α₂ = 1)

• Handling regions where one phase disappears (α → 0)

• Stabilization using pseudo-mass, diagonal reinforcement, and artificial drag

• Managing multiple interacting time and length scales

The lecture concludes with a guided walkthrough of the OpenFOAM source code, showing:

• The structure of twoPhaseEulerFoam

• Phase-specific momentum and energy equations

• Pressure equation assembly

• Interfacial force evaluation

• The modular model hierarchy for drag, lift, heat transfer, turbulence, and wall effects

By the end of this lecture, you will be able to:

• Decide when Euler–Euler modeling is necessary

• Understand the physics and numerics behind twoPhaseEulerFoam

• Navigate and customize interfacial force models in OpenFOAM

• Prepare to convert existing cases to Euler–Euler formulations

This lecture lays the theoretical and practical foundation for solving high-fidelity, strongly coupled multiphase flow problems using OpenFOAM’s Euler–Euler framework.

In this lecture, we build a complete two-phase EulerFoam simulation in OpenFOAM using a classic air–water bubble rise problem. Starting from an interFoam-based setup, we transition to the Euler–Euler framework, highlighting the key conceptual and practical differences between the two approaches.

You’ll learn how to:

• Define both phases explicitly (air and water) in two-phase EulerFoam

• Configure separate velocity, temperature, and volume fraction fields for each phase

• Set up pressure and p_rgh correctly for compressible multiphase flows

• Apply appropriate boundary conditions for phase fractions, velocity, pressure, and temperature

• Configure phaseProperties, including drag models, aspect ratio models, blending functions, and interfacial forces

• Add phase-specific thermophysical properties using thermophysicalProperties.air and .water

• Initialize the domain using setFields for mixed-phase regions

• Debug common issues related to phase initialization and solver stability

We also explore how EulerFoam enables physics that cannot be captured by interFoam, such as:

• Non-sharp interfaces

• Phase mixing (e.g., 80% air / 20% water)

• Custom drag and interphase interaction models

• Different temperatures for each phase

The lecture concludes with a discussion on extending this approach to multiphase EulerFoam, where more than two interacting phases can be modeled.

This session wraps up the multiphase solver introduction series, laying a strong foundation for tackling real-world, industrial-scale multiphase CFD problems in OpenFOAM.