IV.2.4.3 Using predefined criteria

The example given in file “RUBY/EX05/calcHoneyAccel.rb” explains how a predfined criterion can be calculated. This is done for the “HoneycombAirbusSR” predefined criterion presented in detail in section X.D.1.2. The operations can be sorted in three steps:

• First the Cauchy Stress Tensor Result is extracted fro a Group of elements:

            targetGrp = db.getGroupCopy("pan_PZ_Honey_72")
            stress =  db.getResultCopy("ORBIT_ONE_MS2_Z","Statics","Stress Tensor",
                "ElemCorners",targetGrp,[])
  

• Then an Array of parameters is prepared:

            criterionData=[]
            criterionData << db
            criterionData << 1.5625
            criterionData << 2.41e6
            criterionData << 1.41e6
            criterionData << "XZ"
            criterionData << "YZ"
            criterionData << stress
  

  (The reader will easily check that these parameters correspond to those liste in section X.D.1.2.

• The criterion is calculated by a call to “Post.calcPredefinedCriterion” method:

            output=Post.calcPredefinedCriterion("HoneycombAirbusSR",criterionData)
  

• Finally, the “output” Array returned by the method is exploited:

            puts
            puts "Worst results in panel +Z honeycomb :"
            puts
            STDOUT.printf("   on element %d\n",output[0])
            STDOUT.printf("   on node %d\n",output[1])
            STDOUT.printf("   on layer %d\n",output[2])
            STDOUT.printf("   on sub-layer %d\n",output[3])
            STDOUT.printf("   SL = %g\n",output[4])
            STDOUT.printf("   SW = %g\n",output[5])
            STDOUT.printf("   SR max = %g\n",output[6])
            puts
            Util.printRes(STDOUT,"Honey SR",output[7])
  

  In this case, the “exploitation” consists simply in prints to standard output.

Note that the seventh element of the “output” Array above is the only Result object created and returned by the predefined criterion. The same object could be obtained by a few ruby statements like:

        shearL=@@stressTensor.deriveTensorToOneScal("Component XZ")
        shearW=@@stressTensor.deriveTensorToOneScal("Component YZ")
        tmp=sq(shearL/allL)+sq(shearW/allW)
        sr=fos*sqrt(tmp)

The computational cost of these few statement can be very important however. Indeed, several FeResPost Result objects are created by these few lines. One creates consecutively the following result objects:

1.

One “shearL” scalar Result by extraction of XZ component.

2.

One “shearW” scalar Result by extraction of YZ component.

3.

One “shearL/allL” scalar Result (division by real value).

4.

One “shearW/allW” scalar Result (division by real value).

5.

One “sq(shearL/allL)” scalar Result (scalar Result to the square).

6.

One “sq(shearW/allW)” scalar Result (scalar Result to the square).

7.

One “tmp” Result obtained by summation of two scalar Results.

8.

One “sqrt(tmp)” Result obtaiend by extracting the square root of a scalar Result.

9.

And finally, the “SR” Result, which is the only one that shall be kept.

This means that 8 intermediate Result objects have been created and are discared at the end. Each of the 8 intermediate Result creation involves a loop on all the key-value pairs of the operations argument(s), and insertion in the new Result. If the initial Cauchy Stress Tensor Result contains a large number of key-value pairs, the computation cost of this criterion can be very important.

In the same ruby file, a second computation is provided of the Airbus criterion using the “interaction” approach:

      lStress=stress.deriveTensorToOneScal("Component XZ")
      wStress=stress.deriveTensorToOneScal("Component YZ")
      criterionData=[]
      criterionData << Post.abs(lStress)*(1.5625/2.41e6)
      criterionData << 2.0
      criterionData << Post.abs(wStress)*(1.5625/1.41e6)
      criterionData << 2.0
      #~ output=Post.calcPredefinedCriterion("Interaction_2_SR",criterionData)
      output=Post.calcPredefinedCriterion("Interaction_N_SR",criterionData)
      srMax=output[1].extractResultMax()
      maxData=srMax.getData("int","int","int","int","int")[0];

Of couse, this calculation method is less efficient than the previous one. It illustrates however the calculation of Strength Ratios via interaction of failure criteria.