18.6.4 Configuring a sizing optimization task

A sizing optimization is a flexible, sensitivity-based optimization that allows you to apply a range of constraints and objective functions to your model. You use the optimization task editor to customize various aspects of a sizing optimization. To locate the editor, select TaskEditoptimization task name from the main menu bar.

The following topics are covered:

Configuring basic settings

To configure basic settings:

  1. In the optimization task editor, click the Basic tab.

  2. Choose whether to freeze load or boundary condition regions.

    It is recommended that you freeze regions to which prescribed conditions are applied because you do not want these regions to be removed during the optimization. Freezing these regions stabilizes the optimization and often leads to a significantly lower number of iterations.

Configuring the thickness settings

To configure thickness settings:

  1. In the optimization task editor, click the Thickness tab.

  2. Select the Thickness update strategy.

    This setting controls the rate at which the Optimization module updates the shell thickness of design elements during the optimization using the method of moving asymptotes. In most cases you should accept the default setting (Normal). However, if the design responses are very sensitive and you have problems fulfilling the constraints, you may need a more conservative rate that requires more optimization iterations. Selecting an aggressive rate may lead to unstable optimization or prevent the optimization from converging on a solution.

  3. Enter the Maximum change per design cycle.

    This setting controls the limit on the change in shell element thickness during each design cycle.

Configuring the perturbation settings

To configure the perturbation settings:

  1. In the optimization task editor, click the Perturbation tab.

  2. Enter the number of eigenmodes to track. The default value is five, which means that the Optimization module tracks the five lowest eigenfrequencies.

    In some cases many local low frequency eigenmodes appear during the optimization iterations, which leads to a high number of modes to track and degrades performance. You can avoid tracking a high number of modes by choosing the lower bound of the eigenfrequencies to be 25% of the eigenfrequency of interest in the first optimization iteration.

    Mode tracking is not required if your design response will use the Kreisselmaier-Steinhauser formulation to evaluate the eigenfrequencies. Your Abaqus model must include an output request for at least the number of eigenfrequencies you are tracking.

  3. Select the region over which the Optimization module should track the eigenmodes.

Configuring convergence options

To configure convergence options:

  1. In the optimization task editor, click the Convergence tab.

  2. Specify the Convergence Criteria. The following options allow you to specify the convergence criteria for a sizing optimization:

    Specifying when to start checking for convergence

    You can specify the iteration during which the Optimization module will begin to check the two convergence criteria. The optimization will always continue at least until this value has been reached. The default value is 4.

    Specifying which convergence criterion to check

    You can specify whether the optimization should end when either of the convergence criterion has been fulfilled or both of the criteria have been fulfilled. The default value is that both criteria must be fulfilled.

    Convergence based on the change in optimization function

    You can specify that the optimization will end based on the change in the objective function from one iteration to the next. The default value is 0.001.

    Convergence based on the change in element thickness

    Element thickness is the design variable for a sizing optimization. You can specify that the optimization will end based on the average change in the element thickness from one iteration to the next. The default value is 0.005.