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Table 9 BTD models, 0/90/0, a/h = 10

From: On the use of neural networks to evaluate performances of shell models for composites

DOF \(\mathbf {u}_{\mathbf {x1}}\) \(\mathbf {u}_{\mathbf {y1}}\) \(\mathbf {u}_{\mathbf {z1}}\) \(\mathbf {u}_{\mathbf {x2}}\) \(\mathbf {u}_{\mathbf {y2}}\) \(\mathbf {u}_{\mathbf {z2}}\) \(\mathbf {u}_{\mathbf {x3}}\) \(\mathbf {u}_{\mathbf {y3}}\) \(\mathbf {u}_{\mathbf {z3}}\) \(\mathbf {u}_{\mathbf {x4}}\) \(\mathbf {u}_{\mathbf {y4}}\) \(\mathbf {u}_{\mathbf {z4}}\) \(\mathbf {u}_{\mathbf {x5}}\) \(\mathbf {u}_{\mathbf {y5}}\) \(\mathbf {u}_{\mathbf {z5}}\)
15 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \)
14 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \)
13 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \)
12 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \)
11 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\blacktriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \)
10 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \)
9 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \)
8 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \)
7 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \)
6 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \)
5 \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\blacktriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \) \(\vartriangle \)
  \({\hbox {RF}}_0 = 1.00\) \({\hbox {RF}}_1 = 0.70\) \({\hbox {RF}}_2 = 0.55\) \({\hbox {RF}}_3 = 0.61\) \({\hbox {RF}}_4 = 0.49\)