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Post-Processing
Simcenter STAR-CCM+ allows you to post-process the solution after each iteration or time-step, (while the simulation is running), as well as when the simulation completes. For this reason, you generally create post-processing objects before running the simulation. Post-processing objects are also known as analysis objects.
Monitoring the Solution
Monitors sample, save, and plot solution data.
Customizing Monitors
The way in which monitors sample data and send data to an XY plot can be customized to suit the particular quantity being monitored.
Normalizing the Monitor Data
The data in a monitor can be normalized one of two ways: manually or automatically.

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Post-Processing
Simcenter STAR-CCM+ allows you to post-process the solution after each iteration or time-step, (while the simulation is running), as well as when the simulation completes. For this reason, you generally create post-processing objects before running the simulation. Post-processing objects are also known as analysis objects.
- Analysis Workflow
  The key steps in successfully analyzing simulation results are to: (1) be clear on what quantities you want to extract; (2) locate or define surfaces on which to obtain the data; and, (3) present the data in visual scenes or numeric output.
- Data Interpolation
  Most visualization objects such as plots, reports, and scalar displayers allow for smooth and non-smooth values. For example, the contour style for scalar displayers provides a Smooth Filled option (smooth) and a Filled option (non-smooth). The way these values are calculated depends on the discretization method.
- Field Function Interpolation and Interfaces (FV)
  For finite volume meshes, understanding how Simcenter STAR-CCM+ deals with field function data is important for avoiding non-physical results in post-processing at an interface, and to appreciate the difference that smoothing makes when it is applied.
- Accessing Solution Data through Derived Parts
  Although Simcenter STAR-CCM+ can display, analyze, and report simulation data on regions, boundaries, and parts, there are many cases when you want to access data in other entities of the solution space. Derived parts provide a mechanism for defining additional entities on which you can access solution data.
- Visualizing the Solution
  The visualization tools in Simcenter STAR-CCM+ are integrated with the analysis, allowing for the interactive extraction and viewing of solution data from either a running or converged simulation.
- Transient Solution Data
  For transient solutions, Simcenter STAR-CCM+ provides the simulation history file (.simh) to which you can save selected data while a simulation is running. After the simulation completes, you can load this file and query its states for post-processing.
- Sampling Data Values Using Reports and Monitors
  This workflow incorporates the roles of both reports and monitors.
- Accessing Field Data from Previous Time-Steps or Iterations
  A field history is a type of field monitor that stores a finite number of past values (or samples) of a field function, captured at moments defined by its update policy, for a given set of input regions or boundaries (or both).
- Reporting Results
  Reports provide summaries of solution data.
- Monitoring the Solution
  Monitors sample, save, and plot solution data.
  - What Is a Monitor?
    Monitors enable summary information from the simulation to be sampled and saved during the solution.
  - Customizing Monitors
    The way in which monitors sample data and send data to an XY plot can be customized to suit the particular quantity being monitored.
    - Changing the Trigger Event and Sampling Frequency
      Trigger events control how often the monitor samples data.
    - Setting Maximum Plot Samples
      The Maximum Plot Samples property sets an upper limit on the number of points that will be displayed in the monitor plot.
    - Normalizing the Monitor Data
      The data in a monitor can be normalized one of two ways: manually or automatically.
  - Using Report-Based Monitors
    This section explains:
  - Field Function Monitors
    There are seven varieties of field function monitor. During a simulation run, they collect data samples for a selected part at a frequency that you specify.
  - Field Histories
    A field history is a type of field monitor that lets you access field data from previous time-steps or iterations.
  - Properties of the Monitors Manager
    These properties allow you to control how the monitor data appears in the output.
  - Pop-Up Menu of the Monitors Manager
    These are the pop-up menu items available when you right-click the Monitors manager node.
- Plots
  The plotting features in Simcenter STAR-CCM+ allow you to create three kinds of two-dimensional plots.
- Exploring Solutions with Data Focus
  This interactive tool lets you extract knowledge of merit -- information that facilitates a correct engineering decision -- from a large volume of data.
- Parametric Positioning for Analysis Surfaces in Turbomachine Domains
  In studies of cases of revolving volumes, such as turbomachinery, a typical requirement for post-processing is to render and plot data on surfaces or profiles that are positioned parametrically in relation to the domain bounding surfaces. For example, you may wish to view the total pressure on a surface located exactly half-way between the hub and shroud, or you may wish to plot pressure across both blade surfaces on a given slice.
- Triggers and Update Events
  Several features of Simcenter STAR-CCM+ require that you define a trigger for when an action takes place. Simcenter STAR-CCM+ provides three built-in trigger types, and one custom trigger type (defined by an update event).
- Signal Processing
  Signal processing applies data set functions to sets of wave data.

Normalizing the Monitor Data

The data in a monitor can be normalized one of two ways: manually or automatically.

Normalizing Manually

To normalize the data using a specified value, click the monitor node and select Manual from the pull-down menu under the Normalization Option property in the Properties window.

The Manual Normalization node, with its own properties, will be added as a sub-node of the monitor node.

The normalization factor can be specified by expanding the monitor node, clicking on the Manual Normalization child node, and then modifying the value in the Normalization Factor property in the Properties window.

Manual Normalization Properties


Normalization Factor	The normalization factor for the monitored quantity.

Normalizing Automatically

To normalize the data automatically, click the monitor node and select Auto from the pull-down menu under the Normalization Option property in the Properties window.

The Automatic Normalization node, with its own properties, will be added as a sub-node of the monitor node.

You must enter the number of samples from the start from which the monitor will search for a maximum normalization factor. Expand the monitor node, click the Automatic Normalizationchild node and modify the Normalization Number property in the Properties window. The normalization factor found is displayed under the read-only Normalization Factor property.

Automatic Normalization Properties


Normalization Factor	The normalization factor for the monitored quantity. Computed as the maximum monitor value over the first N iterations or time-step events of the monitor, where N is the Normalization Number (read-only).
Normalization Number	The number of iterations or time-step events, from the start of the solution, used to compute the Normalization Factor.

Copying Properties of a Normalization Node

When properties are copied from one normalization node to another, all of the properties are applied so that the destination normalization node matches the source one. However, it is not possible to copy properties between different types of normalization nodes.