PSI - Issue 35

Jarmil Vlach et al. / Procedia Structural Integrity 35 (2022) 132–140 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

139

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7. Conclusion The results of the calibration (Table 10) show a high correlation of the experiment with the calculation. All required quantities were found in the required error interval. While the stiffness optimization convergence is shown in Fig. 8a, convergence of strength optimization process shows Fig. 8b. The Regula-Falsi method is fast and efficient, but it can only be used for optimizations that depend on only 1 parameter.

b

a

Fig. 8. Convergence of optimization, (a) Laminate stiffness; (b) Laminate strength

The magnitude and direction of the impact analysis violation are correct. The real dimensions of the unglued zones in the analysed sections are comparable with the results of the impact analysis. The performed calculations showed a significant influence of the speed of the impactor at the same energy on the quality of the result. At a speed of 100 m/s a higher frequency response mode is excited. This results in less deflection and more damage. The biggest problem is that the direction of the violation is 90° rotated against reality. The result of the decrease in stiffness is misleading because the results are comparable for both speeds. Therefore, a significant acceleration of the calculation is not possible. The relationship of the impactor speed to the calculation time is shown in Table 9. The acceptable results can be obtained from impact simulation with speed of impactor up to 10 m/s as shown on Fig. 5.

Table 10. Deviation of calibration results. Sample stiffness

Poisson’s ratio

Sample strength

Deflection under Impactor

Deviation (%)

-0.14

-0.80

+2.03

-4.25

From the results it can be concluded that the demonstrated procedure gives good results especially in terms of stiffness and strength. The procedure can thus be applied in overview analyses and in the introduction to construction work. However, in order to increase the certainty of the forecast, it is essential to thoroughly check all parameters of the model experimentally. Acknowledgements This project has received funding from the European Union’s Horizon 2020 research and innovation programme MODIFLAW under grant agreement No 886703.

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