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Getting Started

Get a first look at LS-OPTui and the basic procedure of an optimization process.

Info

Info

The info (main) panel has fields for entering problem description and author information.

 

info1.png

Solvers

Solvers

The Solver Panel allows the user to define:

  • Pre-Processor Package
    • Change of input files by a parametric Pre-Processor controlled by design variables from LS-OPT (ANSA, HyperMorph, DEP-Morpher, TrueGrid, User-Defined).
  • Solver Package
    • Solver Command: LS-DYNA or others (User-Defined)
    • Input File: Will be appended to the Command in the Command Line

solver2.png

 

  1. Push the category chooser to define a Pre-Processor Package Name.
  2. Define a solver with Solver Package Name.
  3. Define the solver Command, can be in the path ($path) or can be specified with the full path name.
  4. Type in the name of the Input File or browse the direction to the file.
  5. Enter a label for the Analysis Case.
  6. Push the Add button to create an analysis case.

 

Dist

Dist

The probabilistic component of a design variable is described using a probabilistic distribution. The distributions are created without referring to a variable. Many design variables can refer to a single distribution. As statistical distribution you can choose between these types:

Normal, Uniform, Lognormal, Weibull, Beta, User PDF (probability density function), User CDF (cumulative distribution function), Binomial

 

 Add a Distribution

add_dist1.png

 

  1. Select from the category chooser the statistical distribution Type, e.g. the type Normal, which will create a normal distribution that is symmetric and centered about the mean with a standard deviation.
  2. Type in the appropriate values to describe the distribution, e.g. here enter a Mean value and Standard Deviation value.
  3. Type in a Distribution Name or accept the default NORMAL3.
  4. Push the Add button to create the distribution.
  5. Select the generated distributions for a prewiew.

Var.

Var.

In the Variables Panel you can define or modify variables and choose between different types:

Variable, Constant, Dependent, Noise Variable, Discrete Variable

Add a Variable

Variable means a standard design variable which will be integrated in the optimization process.

variable1.png

 

  1. From the Type category chooser select Variable.
  2. Enter a variable Name (label), e.g. area_1.
  3. Enter a Starting value.
  4. Set the range: enter a Minimum (lower bound).
  5. Enter a Maximum (upper bound).

Add a Constant

Constants are used:

  • to define constant values in the input file as π, e or any other constant that may relate to the optimization problem, e.g. initial velocity, integration limits, etc.
  • to convert a variable to a constant. The number of optimization variables can be reduced without interfering with the template files.

constant1.png

 

  1.  To add a new variable  push the Add a Variable button.
  2. To create a constant switch the type of an existing variable from Variable to Constant.
If a variable is no longer needed you can delete it with the Delete a Variable button.

Sampling

Sampling

In the sampling panel you can choose between these metamodels:

Polynomial, Sensitivity, Feedforward Neural Network, Radial Basis Function Network

Furthermore several options and point selections can be selected.

sampling1.png

 

  1. Select a METAMODEL type, e.g. Radial Basis Function Network.
  2. Set the Options for the meta-model, e.g. the check in the check box Augment pts. Update surface will make LS-OPT build the meta-model by using all points from previous iterations.
  3. In the POINT SELECTION the default is Space Filling (usefull in conjunction with nonparametric models such as neural networks).

Histories

Histories

In the Histories panel you can specify time history curves to be extracted from the solver database.

histories1.png

  

  1. Select the LS-DYNA database for the history from the list.
  2. Choose further options for the selected history.
  3. Enter a name for the history or accept the default.
  4. To add a history push the button Add.

Responses

Responses

Create a response in the Responses Panel. A response can be a result of a mathematical operation applied to a time history curve, or can be directly extracted using the standard LS-DYNA interface or a user-defined interface.

response1.png

 

  1. Select the dataset for the response from the list.
  2. Specify the dataset response options.
  3. Enter a name for the response or accept the default.
  4. To add a response push the button Add.

Objective

Objective

Specification of the objective (function to minimize) for the optimization problem.

objective1.png

 

  1. Objectives can be specified in terms of composite functions and/or Response functions.
  2. More than one objective can be defined (multi objective). A Weight might be applied to each objective.

Constraints

Constraints

Soecitication of  constraints (functions to satisfy) of the optimization problem.

constraint1.png

  

  1. Select the response (defined in the Responses Panel) out of the list.
  2. Set the lower bound of the constraint.
  3. Set the upper bound of the constraint.

Run

Run

In the Run panel you can start the optimization, specify the number of concurrent jobs or adjust the convergence criteria. The state of completion is monitored.

run1.png

 

  1. Enter the Number of Iterations for the optimization problem.
  2. Start the optimization with the Run button.

View

View

The View panel starts the LS-OPT Viewer for the visualization of the optimization results. For example meta model plots, accuracy evaluation (computed vs predicted), optimization history, ANOVA results (variable screening)....

history_thood2.png

Fig.1 -  Progress of a variable during the optimization process

Stats

Stats

In the DYNA stats panel you can compute various statistics of the LS-DYNA d3plot results and LS-OPT history data for viewing in LS-PREPOST on the FE model. These statistics show:

  • The variation of the LS-DYNA results due to the variation of the design parameters.
  • The variation of the LS-DYNA results due to bifurcations and other stochastic process events.

dyna-stats_panel2.png

  

  1. Select the Data, e.g. D3Plot and z-displacement.
  2. Choose a Statistic value, e.g. Mean or Standard Deviation of the z-displacement.
  3. Select the analysis Case.
  4. Select the Iteration number and the Task, e.g. Monte Carlo of the fist iteration.
  5. Compute the data and display it in LS-PREPOST.

 

dyna_stats1.png

Fringe Plot of the z-displacement of a steel tube being crushed