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DYNA Stats

Fringe Plot

Fringe Plot

Display the Statistics in LS-PrePost (D3Plot)

  1. Select the DYNA Stats panel.
  2. Click on Create button.

 

 

 

 

 

 

 

 

 

 

  1. Select Fringe plot for the type of plot.

 

 

 

 

 

 

 

 

 

 

 

 

dyna_stats1.png

dyna_stats2_fringe.png

Display the Statistics in LS-PrePost (D3Plot) - Mean

  1. Select z_displacement from the list.
  2. Go to the next panel.

 

 

 

 

 

 

 

 

 

 

 

  1. For what to plot select Statistic of D3Plot data.
  2. Choose Mean as statistic.
  3. Build Quadratic Metamodel instead of using actual FEA results.
  4. Go to the next panel.

 

 

 

 

 

 

 

 

 

 

 

  1. Give a name to this plot, e.g. z_disp-mean-quad.
  2. Push the Finish button.

dyna_stats_panel1.png

metamodel_mean_panel2.png

metamodel_mean_panel3.png

Metamodels can be used to predict the statistics of the responses. These metamodels (approximations) are computed for all the results for all nodes for all time steps.

lspp_mean1.png

The figure shows the mean of the z-displacement at time 0.99963s.

→ The minimum occurs at node 259 (min=-64.1072) and the maximum at node 429 (max=0.0169754).

Display the Statistics in LS-PrePost (D3Plot) - Standard deviation

  • It follows the way above, except:
  1. By the second step, choose Std Dev (Standard deviation) as statistic.

 

 

 

 

 

 

 

 

 

 

 

  1. By the last step, give a name to this plot, e.g. z_disp-std_dev-quad.

metamodel_std_dev_panel2.png

metamodel_std_dev_panel3.png

lspp_std_dev3.png

The figure shows the standard deviation of the z-displacement at time 0.99978s.

→ The maximum occurs at node 694 (max = 1.32686) where the deformation is large.

 

History Plot

History Plot

Display the Statistics in LS-PrePost (History)

  1. Select the DYNA Stats panel.
  2. Click on Create button.

 

 

 

 

 

 

 

 

 

 

  1. Select History plot for the type of plot.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  1. Select TOP_DISP_HIST from the list.
  2. Go to the next panel.

 

 

 

 

 

 

 

 

 

 

 

 

 

  1. For what to plot select Statistic of histories.
  2. For analysis methed, choose Build quadratic metamodel from FEA results.
  3. Go to the next panel.

 

 

 

 

 

 

 

 

 

 

 

  1. Give a name to this plot, e.g. metamodel_history.
  2. Push the Finish button.

dyna_stats1.png

dyna_stats2_history.png

stats_history1.png

metamodel_history2.png

metamodel_history3.png

Statistics of the LS-OPT History

→ The figure shows the statistics of the TOP_DISP_HIST history (z-displacement at node 486).

metamodel_top_disp1.png

 

Single Variable Mode

Single Variable Mode

Single variable Mode (Contribution Analysis)

  • It follows the way of drawing a fringle plot, but:
  1. By the second step, select A single variable's contribution to the D3Plot data instead of Statistic of D3plot data.
  2. Select the variable SIGY.
  3. Build quadratic metamodel from FEA result.

 

 

 

 

 

 

 

  1. By the last step, give a name to this plot, e.g. single_variable.

single_fringle_panel2.png

single_fringle_panel3.png

Metamodels can be used to predict the statistics of the responses. In this case the statistics are computed due to one variable (SIGY).

z_displacement_single-variable1.png

→ The minimum occurs at node 1 (min=0) and the maximum at node 694 (max=1.10725).

Single Variable Mode (History)

  • It follows the way of drawing a history plot, but:
  1. By the second step, select How much each variable contributes to the history.
  2. Build quadratic metamodel from FEA result.

 

 

 

 

 

 

 

 

 

  1. By the last step, give a name to this plot, e.g. single_history.

single_history_panel2.png

single_history_panel3.png

The most important variable, or rather the variable responsible for the most variation of the response, can be plotted on the model.

→ In this case the variable T1 produces most of the variation.

top_disp_dueto_variables1.png