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Sensitivities

Which variable appears to be the most important?

The significance of a variable for a response can be illustrated with ANOVA (analysis of variance) or GSA/Sobol (global sensitivity ananlysis). Note that also GSA/Sobol illutstrates only the linear influence here, because we use a linear metamodel.

  1. Restart the LS-OPT Viewer either in the LS-OPTui by clicking on the Restart viewer button or click on  new plot icon on the menu bar .
  2. Select under Metamodel the item Sensitivity.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ANOVA
  1. Select  Linear ANOVA in the new window.
  2. From Response, e.g. for the load case US_NCAP, select mass.
    (The influence of different variables on response mass is shown in the Figure below.)
  3. Sort the variables according to their significance for mass.

→ For the response mass the variables rail_l and t_floor are the most important variables. (They are highlighted in red and blue in the figure below .)

In contrast the variables mat_rl and mat_rO are insignificant.

 

 

The influence of different variables on response max_intrusion_rail_l:

From Response select max_intrusion_rail_l  for the load case US_NCAP, to see therefor the belonging diagramm.

 → rail_l and mat_rl are the most important variables.

 

 

 

 

 

 

 

 

GSA/Sobol

  1. Select the GSA/Sobol.
  2. Select Multi. (This option allows to select multiple responses.)
  3. From Response select US_NCAP.
    (The influence of different variables on case US_NCAP is shown in the Figure.)
  4. Sort the variables according to their significance for US_NCAP.

 

 

 

 

 

Select now from Response IIHS to see the influence of variables on this load case.

 

 

 

 

 

 

 

 

 

Sobol - Diagram for load case Torsion: 

 

 

 

 

 

 

 

 

 

Sobol - Diagram for load case EVA:

 

 

 

 

 

 

 

 

 

 

This information may be used to reduce the set of variables for each load case and e.g. perform an optimization afterwards. Here, 8 most important variables are selected for each load case. The colors in the table below visualize the common variables of the load cases. Obviously the variable firewal is important for all four load cases.