Simcenter STAR-CCM+ 2406
User Guide
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 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.
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.
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.
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.
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.
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.
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 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 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 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.
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.
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.
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.
The interaction area density specifies the interfacial area available for momentum, heat, and mass transfer between each pair of phases in an interaction.
The momentum transfer between phases represents the sum of all the forces that the phases exert on one another.
The Single Component and Multicomponent Droplet Evaporation Mass Transfer Rate models calculate the mass transfer rate from single and multi-component droplets to a multi-component gas. The Multicomponent model assumes that the liquid drops are internally homogeneous and that the liquid behaves like an ideal mixture.
The bulk boiling model in Simcenter STAR-CCM+ is an essential part of subcooled boiling. It models boiling and condensation in the interior of the flow.
The wall boiling model is aimed at forced-flow, subcooled, boiling applications. In subcooled boiling, local boiling occurs on a heated surface despite the mean temperature of the liquid being less than the saturation temperature. The degree of liquid subcooling is expressed either as a temperature difference or an enthalpy difference below the saturation value.
The Dissolution Mass Transfer Rate model calculates the mass of a component that is transferred from one multi-component phase to another.
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(dp), which gives the number of particles (droplets or bubbles) whose diameters range from dp to dp+d(dp).
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 describe multiphase flow regimes that deal with gas-solid or liquid-solid flows.
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.
Simcenter STAR-CCM+ can model turbulence effects in a multiphase mixture, or individually in the continuous and the dispersed phases.
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.
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.
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.
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 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.
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.
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 is the discipline investigating relationships between electrical currents and chemical composition change in general.
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.
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.
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.
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.
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.
In transient simulations, mesh motion is a numerical technique that allows you to update the position of the computational domain while the solvers run.
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 usually occurs in rotating machinery such as pumps, propellers, fans, wind turbines, and so on.
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.
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 provides an automated approach within Simcenter STAR-CCM+ to run design exploration studies. Design exploration covers both performance assessment and optimization.
Most physical quantities in Simcenter STAR-CCM+ are either scalars, vectors, or 2nd-order tensors.
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.
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.
