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Theory
Simcenter STAR-CCM+ simulations are built on numerical algorithms that solve relevant laws of physics according to the conditions that the simulation defines. So that you can identify the physical laws, and understand the methods by which they are solved, Simcenter STAR-CCM+ comes with a Theory Guide.
Multiphase—Eulerian Approach
Multiphase flows, where several fluids flow in the domain of interest, play an important role in variety of industrial applications. In general, we associate phases with gases, liquids or solids and as such some simple examples of multiphase flows are: air bubbles rising in a glass of water, sand particles carried by wind, rain drops in air. The definition of phase can be generalized and applied to other fluid characteristics such as size, shape, density, and temperature.
Eulerian Multiphase (EMP) Flow
The two-fluid model that is referred to as the Eulerian Multiphase (EMP) model in Simcenter STAR-CCM+, and whose initial development was driven largely by nuclear industry, is generally used for modeling dispersed flows.
Size Distribution
In order to account for a size distribution of the dispersed phase, the mass and momentum transport equations have to be combined with a population balance equation (PBE). The central object of a PBE is the particle number density $n (d_{p})$ , which gives the number of particles (droplets or bubbles) whose diameters range from $d_{p}$ to $d_{p} + d (d_{p})$ .

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Theory
Simcenter STAR-CCM+ simulations are built on numerical algorithms that solve relevant laws of physics according to the conditions that the simulation defines. So that you can identify the physical laws, and understand the methods by which they are solved, Simcenter STAR-CCM+ comes with a Theory Guide.
- Fundamental Equations
  Simcenter STAR-CCM+ models a range of physics phenomena including fluid mechanics, solid mechanics, heat transfer, electromagnetism, and chemical reactions. On a macroscopic scale, where the typical lengths are much greater than the inter-atomic distances, the discrete structure of matter can be neglected and materials can be modeled as continua. The mathematical models that describe the physics of continua are derived from fundamental laws that express conservation principles.
- Fluid Flow
  Simcenter STAR-CCM+ can simulate internal and external fluid flow across a wide range of flow regimes, and for a variety of fluid types. It solves the conservation equations for mass, momentum, and energy for general incompressible and compressible fluid flows.
- Numerical Flow Solution
  In the finite volume method, the solution domain is subdivided into a finite number of small control volumes, corresponding to the cells of a computational grid.
- Turbulence
- Transition
  The term transition refers to the phenomenon of laminar to turbulence transition in boundary layers. A transition model in combination with a turbulence model predicts the onset of transition in a turbulent boundary layer.
- Wall Treatment
  Walls are a source of vorticity in most flow problems of practical importance. Therefore, an accurate prediction of the flow across the wall boundary layer is essential.
- Wall Distance
  Wall distance is a parameter that represents the distance from a cell centroid to the nearest wall face with a non-slip boundary condition. Various physical models require this parameter to account for near-wall effects.
- Heat Transfer
  Heat transfer is the exchange of thermal energy between media at different temperatures. Heat transfers from locations of high temperature to locations of low temperature in order to reach an equilibrium state. The three main mechanisms of heat transfer are: conduction, convection, and radiation.
- Porous Media
  Porous media are continua that contain both fluid and fine-scale solid structures, for example: packed-bed chemical reactors, filters, radiators, honeycomb structures, or fibrous materials. The solid geometrical structures are too fine to be individually meshed and fully resolved by a computational grid.
- Species and Passive Scalars
  Simcenter STAR-CCM+ models the transport, the mixing, and the chemical reactions of multi-component liquids or multi-component gases by solving conservation equations for scalar variables that represent the mass fraction of each species in the mixture. This conservation equation allows for convection, diffusion, and optional source effects, and is solved in addition to the global mass continuity equation.
- Multiphase—Eulerian Approach
  Multiphase flows, where several fluids flow in the domain of interest, play an important role in variety of industrial applications. In general, we associate phases with gases, liquids or solids and as such some simple examples of multiphase flows are: air bubbles rising in a glass of water, sand particles carried by wind, rain drops in air. The definition of phase can be generalized and applied to other fluid characteristics such as size, shape, density, and temperature.
  - Eulerian Multiphase (EMP) Flow
    The two-fluid model that is referred to as the Eulerian Multiphase (EMP) model in Simcenter STAR-CCM+, and whose initial development was driven largely by nuclear industry, is generally used for modeling dispersed flows.
    - Phase Interaction Topology
      The two-fluid model provides a flexible framework where dispersed, stratified or mixed two-phase flow can be modeled by using appropriate closure relations. For a given pair of phases, the Eulerian Multiphase (EMP) model in Simcenter STAR-CCM+ can model different types of phase topology.
    - Interaction Length Scale
      For continuous-dispersed phase interactions, the interface length scale is taken to be an effective mean diameter of the dispersed phase particles. Where particles are not spherical, this is absorbed as a correction factor into interphase transfer models such as for bubble drag and lift force.
    - Interaction Area Density
      The interaction area density specifies the interfacial area available for momentum, heat, and mass transfer between each pair of phases in an interaction.
    - Momentum Transfer
      The momentum transfer between phases represents the sum of all the forces that the phases exert on one another.
    - Heat and Mass Transfer
    - Size Distribution
      In order to account for a size distribution of the dispersed phase, the mass and momentum transport equations have to be combined with a population balance equation (PBE). The central object of a PBE is the particle number density $n (d_{p})$ , which gives the number of particles (droplets or bubbles) whose diameters range from $d_{p}$ to $d_{p} + d (d_{p})$ .
      - S-Gamma
        The S-Gamma model is a method of moments that solves for the zeroth and the second moments of the number density $n (d_{p})$ . One transport equation is solved for each moment. Particles change size due to breakup and coalescence as they interact with each other.
      - Adaptive Multiple Size-Group (AMUSIG)
        The adaptive multiple size-group (AMUSIG) model predicts the size distribution of droplets or bubbles in a dispersed flow regime of a multiphase flow.
    - Large Scale Interfaces
      The large scale interface detection model is implemented within the multiple flow regime framework to enable the detection of a group of cells that contain a large interface.
    - Particulate Flows
      Particulate flows describe multiphase flow regimes that deal with gas-solid or liquid-solid flows.
    - Rheology of Emulsions and Suspensions
      A suspension is a heterogeneous mixture of dispersed solid particles in a liquid, for example, pastes and clays. An emulsion, on the other hand, is a mixture of two or more liquids where one liquid is dispersed in the other such as oil in water. The presence of particles suspended in a Newtonian liquid is known to lead to non-Newtonian behavior, as the mixture viscosity becomes increasingly dependent on the volume fraction of the dispersed phase.
    - Multiphase Turbulence
      Simcenter STAR-CCM+ can model turbulence effects in a multiphase mixture, or individually in the continuous and the dispersed phases.
    - Boundary Conditions
    - Eulerian Multiphase (EMP) Bibliography
  - Volume of Fluid Method
    The Volume of Fluid (VOF) multiphase model implementation in Simcenter STAR-CCM+ belongs to the family of interface-capturing methods that predict the distribution and the movement of the interface of immiscible phases. This modeling approach assumes that the mesh resolution is sufficient to resolve the position and the shape of the interface between the phases.
  - Fluid Film
    Simcenter STAR-CCM+ allows you to model the distribution and transport of a thin layer of liquid—a fluid film— on solid surfaces. Application areas include vehicle rainwater management, selective catalytic reduction (SCR), and lubrication.
  - Dispersed Multiphase
    The Dispersed Multiphase (DMP) model simulates the flow of dispersed particles in a continuous phase using a Eulerian approach. As such, for simulating these types of flow, the DMP model is an alternative to using the Lagrangian Multiphase (LMP) model, which uses a Lagrangian approach.
  - Mixture Multiphase (MMP)
    The Mixture Multiphase (MMP) model assumes that the phases are miscible. It is suitable for modeling dispersed multiphase flows such as bubbly and droplet flows. Typical applications include fuel cells, boilers, and steam turbines. When simulating liquid droplets dispersed in a gas, the Mixture Multiphase (MMP) model accounts for evaporation and condensation.
- Multiphase—Lagrangian Approach
  Multiphase flows are found in a wide variety of industrial processes, some examples of which are internal combustion engines, liquid, or solid fueled combustors, spray driers, cyclone dust separators, and chemical reactors. Multiphase in this context refers to one thermodynamic phase, be it a solid, a liquid, or a gas, interacting with another distinct phase.
- Reacting Flow
  In reacting flows, chemical species mix with each other and react when conditions allow. To model these flows, Simcenter STAR-CCM+ couples species and energy transport equations with the chemistry solvers that compute the source terms.
- Internal Combustion Engines
  Numerical modeling of internal combustion engines plays an increasingly important role in improving engine design. CFD simulation of such engines can give a comprehensive insight into the wide-ranging physics of the device, such as turbulent mixing between fuel and air, the ignition, and combustion chemistry.
- Electrochemistry
  Electrochemistry is the discipline investigating relationships between electrical currents and chemical composition change in general.
- Plasma
  Plasma is a state of matter similar to a gas that is composed partially or completely of charged particles such as ions and electrons which are not bound to each other.
- Electromagnetism
  Many engineering applications, such as electric motors, electric switches, and transformers, involve electromagnetic phenomena. Electromagnetic phenomena can be modeled based on the classical theory of Electromagnetism, which describes the interaction between electrically charged particles in terms of electric fields, magnetic fields, and their mutual interaction.
- Batteries
- Solid Mechanics
  Solid Mechanics describes the behavior of a solid continuum in response to applied loads. Applied loads include body forces, surface loads, point forces, or thermal loads that result from changes in the solid temperature. Applied loads induce a stress field in the structure and can cause displacement of the structure—from an initial undeformed configuration to a deformed configuration.
- Aeroacoustics
  Computational aeroacoustics (CAA) is a branch of multiphysics modeling and simulation that involves identifying noise sources that are induced by fluid flow and propagation of the sound waves then generated.
- Finite Element Method
  The Finite Element method is a powerful tool for finding approximate solutions to continuous problems. The methodology is similar to other numerical techniques that approximate continuous partial differential equations with discrete algebraic equations.
- Mesh Motion
  In transient simulations, mesh motion is a numerical technique that allows you to update the position of the computational domain while the solvers run.
- 6-DOF Rigid Body Motion
  Simcenter STAR-CCM+ allows you to model the motion of a rigid body in response to applied forces and moments. In a rigid body, the relative distance between internal points does not change. Therefore, it is sufficient to solve the equations of motion for the center of mass of the body.
- Rotating Flow
  Rotating flow usually occurs in rotating machinery such as pumps, propellers, fans, wind turbines, and so on.
- Harmonic Balance
  Harmonic Balance equations describe periodic unsteady flows where the unsteady frequencies are known beforehand. They are suited to modeling periodically repeating flow fields that typically occur in turbomachinery such as compressors, turbines, and fans.
- Adjoint
  The adjoint method is an efficient means to predict the influence of many input parameters on some engineering quantities of interest in a simulation.
- Design Manager
  Design Manager provides an automated approach within Simcenter STAR-CCM+ to run design exploration studies. Design exploration covers both performance assessment and optimization.
- Scalars, Vectors, and Tensors
  Most physical quantities in Simcenter STAR-CCM+ are either scalars, vectors, or 2nd-order tensors.
- Solution Data Interpolation
  Many operations require interpolation of solution data between different sets of mesh points. For example, remeshing operations require interpolation of existing solution data onto a new mesh. Data interpolation also occurs at the interface between regions, where contacting boundaries exchange data. Additionally, configurable data mappers allow you to interpolate field functions and tabular data to specified meshes.
- Idealizations
  In many simulations, it is common practice to reduce the size of the computational domain using planes of symmetry, axes of rotation, periodicity, or by reducing the 3D domain to a 2D domain. However, when you calculate physical quantities using reports you generally want to account for the whole domain. You can obtain report values for the full model using idealizations.

Size Distribution

In order to account for a size distribution of the dispersed phase, the mass and momentum transport equations have to be combined with a population balance equation (PBE). The central object of a PBE is the particle number density $n (d_{p})$ , which gives the number of particles (droplets or bubbles) whose diameters range from $d_{p}$ to $d_{p} + d (d_{p})$ .

In its general form, the PBE reads:

Figure 1. EQUATION_DISPLAY

\frac{\partial n (d_{p})}{\partial t} + \nabla\cdot (v n (d_{p})) = B - D

(2169)

where $B$ and $D$ are birth and death terms due to breakup, coalescence, nucleation, dissolution, and so on [531].

The two most popular numerical methods for solving the PBE are the method of moments and the method of classes. Instead of solving for the number density, the method of moments solves for a (usually small) number of its moments:

Figure 2. EQUATION_DISPLAY

S_{γ} = \int d_{p}^{γ} n (d_{p}) ⅆ (d_{p})

(2170)

In Simcenter STAR-CCM+, the method of moments based S-Gamma model is implemented. This model implementation relies on transporting one or two moments of the size distribution. The S-Gamma method is a computationally efficient tool suitable for engineering estimates.

The method of classes implies that the polydisperse phase is split into a number of size classes. Each class has its own mass and momentum balance. The standard method of classes, which is also known as multiple size-group (MUSIG) method [504], prescribes the sizes of the size-groups a priory. The sizes are constant throughout the computational domain, which makes the method time-consuming. In Simcenter STAR-CCM+, the partitioning of the particles ensemble into size classes is adaptive in space and time [565], therefore the name adaptive multiple size-group (AMUSIG) method. The AMUSIG method lets you work with a smaller number of size-groups than other class methods.