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Analysis of the structural response of Beirut port concrete silos under blast loading

Ismail Sahar Ali, Raphael Wassim, Durand Emmanuel, Kaddah Fouad, Geara Fadi

Archives of Civil Engineering

2021

Vol. 67, nr 3

619--638

Several months after August 4, 2020, Lebanon is still recovering from the enormous explosion at the port of Beirut that killed more than 200 people and injured more than 7500. This explosion ripped the city to shreds and significantly damaged the Beirut port silos. Saint Joseph University of Beirut “the school of engineering ESIB” in collaboration with “Amann” Engineering performed a 3D scan of the Beirut port silos to assess the silos’ level of damage. The obtained data was then compared to the numerical modelling results, obtained from Abaqus explicit, in order to estimate the blast magnitude and to check if the pile foundation can be reused in building new silos at the same place due to the limited space available at the port of Beirut while considering the soil-foundation-structure interaction effect. In addition, the silos’ structural response against the filling of the silos at the time of explosion was investigated. The displacement of the silos and the amount of silos’ damage obtained from the fixed and flexible numerical models indicate that a blast magnitude of 0.44 kt TNT (approximately 1100 tons of Ammonium Nitrate) best estimates the 20 to 30 cm silos’ tilting in the direction of the blast. In addition, the soil and the foundation played a positive role by absorbing part while dissipating less amount of the blast energy. Also, the grains at the time of the event did not affect the silos’ deformation and damage amount. Noting that the displacement of the pile foundation exceeded all limits set by design codes, indicating that the pile foundation cannot be reused to build new silos at the same place.

Crash data reporting systems in Fourteen Arab countries: challenges and improvement

Abounoas Zahira, Raphael Wassim, Badr Yarob, Faddoul Rafic, Guillaume Anne

Archives of Transport

2020

Vol. 56, iss. 4

73--88

Traffic crash fatalities and serious injuries still represent a big burden for most Arab countries because the actual policies, strategies, and interventions are based on poorly collected data. Through this paper, we assessed the crash data reporting systems in Fourteen Arab countries via a survey conducted to identify the fundamental dysfunctions at the management and data collection levels. Then, to address some of the dataset problems, we had applied data mining technics to select a minimum of variables (crash, vehicle, and road user) that should be collected for a better understanding of crash circumstances. For this raison, three methods of selection (correlation, information gain, and gain ratio) and seven classifiers (naive Bayes, nearest neighbour, random forest, random tree, J48, reduced error pruning tree, and bagging) were tested and compared to identify the variables that affect significantly the crashes severity. Decision trees family of classifiers showed the best performance based on the analysis of the area under the curve. The explanatory variables obtained from the data mining process were combined with other descriptive variables to maintain traceability. As a result, we produced hybrid lists of variables for the crash, vehicle, and road user, each contains 25 variables. Finally, in order to propose a cost-effective solution to switch from manual to electronic data collection, we got inspired by a tool used to track animals to create and customize a unified e-form for handheld devices, in order to ensure easy entering of the harmonized data for the entire region based on our selected lists of variables. The tool verified the countries requirements especially by enabling data collection and transfer with and without the internet, and by allowing data analysis thought its built-in Geographic Information System (GIS) capabilities.