A Predictive Model for Damage Assessment and Deformation in Blast Walls Resulted by Hydrocarbon Explosions

Majid Aleyaasin* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
6 Downloads (Pure)

Abstract

In this paper, a new method is developed to find the ductility ratio in blast walls, resulted by hydrocarbon explosions. In this method, only the explosion energy and distance from the centre of explosion are required to find the damage by using simple predictive models in terms of empirical-type formulas. The explosion model herein is a TNO multiphysic method. This provides the maximum overpressure and pulse duration in terms of the explosion length and distance from explosion centre. Thereafter, the obtained results are combined with the SDOF model of the blast wall to determine the ductility ratio and the damage. By using advanced optimisation techniques, two types of predictive models are found. In the first model, the formula is found in terms of 2 parameters of explosion length and distance from explosion centre. However, the 2nd model has 3 parameters of explosion length, distance, and also the natural period of the blast wall. These predictive models are then used to find explosion damages and ductility ratio. The results are compared with FEM analysis and pressure-impulse (P-I) method. It is shown that both types of models fit well with the outputs of the simulation. Moreover, results of both models are close to FEM analysis. The comparison tables provided in this paper show that, in the asymptotic region of P-I diagrams, results are not accurate. Therefore, this new method is superior to classical pressure-impulse (P-I) diagrams in the literature. Advantage of the new method is the easy damage assessment by using simple empirical-type formulas. Therefore, the researchers can use the method in this paper, for damage assessment in other types of blast resistive structures.
Original languageEnglish
Article number5129274
Number of pages13
JournalAdvances in Civil Engineering
Volume2019
DOIs
Publication statusPublished - 4 Jul 2019

Bibliographical note

The data used to support the findings of this study are available from the corresponding author upon request.

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