Use a Model Reduction study node (

) to create a reduced-order model (ROM) based on a time-dependent or frequency-domain simulation (see 
Reduced-Order Modeling). Reduced-order models are usually thought of as computationally inexpensive mathematical representations that provide the ability to run faster simulations using a small model that captures the dynamic behavior of the original model.
 
    Click the Compute button (

) (or press F8) at the top of the 
Settings window to produce an instance of the reduced-order model under 
Global Definitions>Reduced-Order Modeling.
 
    The Settings window contains the following sections:
 
    From the Method list, choose one of the following model-reduction methods:
 
    From the Training study for eigenmodes list, choose an existing study for the eigenmode basis functions or choose 
None.
 
    From the Study step for eigenmodes list, choose 
Automatic (the default) to use the last applicable solution in the solver sequence, or select any of the applicable study steps (such as 
Eigenvalue).
 
    From the Training study for constraint modes list, choose an existing study for the constraint basis functions or choose 
None (the default).
 
    From the Study step for constraint modes list, choose 
Automatic (the default) to use the last applicable solution in the solver sequence, or select any of the applicable study steps (such as 
Stationary).
 
    From the Unreduced model study list, choose a study that contains at least one study step of a type that can be reduced using the selected model-reduction method, or the parent study of the current Model Reduction node. When another study is selected, select an applicable study step from the 
Defined by study step list.
 
    
    From the Reduced-order model list, choose 
New to create a new reduced-order model, or choose any existing and compatible reduced-order model (available under 
Global Definitions>Reduced-Order Modeling).
 
    If the model-reduction method is Modal, select the 
Ensure reconstruction capability check box to enable reconstruction of the unreduced solution vector also when there are only linear outputs defined. For the 
AWE method, reconstruction is always enabled. The reduced-order model can then also assign reconstructed values to some of the dependent variables not solved for. This is controlled by the table with 
Reconstruction and 
Reduced-order model columns in the 
Physics and Variables Selection section in the destination study. There is a row for each physics interface that is not solved whose dependent variables can be reconstructed by at least one reduced-order model. The 
Reconstruction column shows the physics interface name. The list in the 
Reduced-order model column determines which reduced-order model (if any) should be asked to reconstruct the fields for this physics interface.
 
    For the Modal method, select the 
Store reduced matrices check box to store the reduced matrices from the model reduction in the solution data for exporting state-space matrices, for example.
 
    The Use extra Compile Equations for Results check box is selected by default. This setting controls whether an extra, active 
Compile Equations node will be added last in the default solver sequence. The extra 
Compile Equations step is equivalent to an 
Update Solution call for the unreduced model study step. Most importantly, it includes the newly created reduced-order model feature in the final solution output by the study so that the reduced-order model’s outputs can be evaluated directly using this solution. The extra 
Compile Equation node is not necessary when the reduced-order model will only be called from some other study. In particular, when multiple reduced-order models are created in a sweep, it can be removed to save computation time.
 
    For the AWE method, enter a value for the 
Relative tolerance for adaptation (default: 0.01).
 
    In this section, you define the model control inputs when you use the Modal method. The 
Model Control Inputs table consists of three columns: 
Reduced-model input, 
Use, and 
Training expression. The 
Reduced-model input column shows all the variables defined in the 
Global Reduced-Model Inputs node under 
Global Definitions. When the variable is added to the 
Global Reduced-Model Inputs it is automatically added to the 
Model Control Inputs table. The 
Use column controls which of the defined variables that should be used. In the 
Training expression column, enter a training expression around which the model reduction will linearize the model. Note that the training expression value is not passed on to the training study steps: if their solution depends on reduced-order model input variables, they have to be recomputed manually when changing the training value.
 
    In the Outputs section, add outputs for the reduced-order model. You can add output variables by clicking the 
Add Expression (

) and 
Replace Expression (

) buttons to search through a list of predefined expressions. If you do not add a name in the 
Variable column, the output is assigned a default variable name in the created reduced-order model.