Reliability Assessment of HFRC Slabs Against Projectile Impact

Nadeem A. Siddiqui,Yousef A. Al?Salloum,Tarek H. Almusallam,Aref A. Abadel,Husain Abbas 한국콘크리트학회 2018 International Journal of Concrete Structures and M Vol.12 No.6

In the present study, a probabilistic procedure is presented for estimating the reliability of hybrid fiber reinforced concrete (HFRC) slabs against the impact of hemispherical nose projectiles considering uncertainties involved in the material, geometric and impact parameters. The influence of hybrid fibers in improving the safety level of reinforced concrete slabs against impact loads has also been studied on a parametric basis. The failure of the HFRC slabs was assumed to occur when the impact velocity of the projectile exceeds the ballistic limit of the slab i.e. perforates the slab. To illustrate the procedure, a probabilistic analysis was carried out on the impact test results of HFRC slabs containing different proportions of hooked-end steel, polypropylene and Kevlar fibers, recently published by the authors. Reliability assessment was performed for a range of applied nominal impact loads by varying the impact velocity of the given projectile. Reliability analysis yields the safety level of all the HFRC slabs against the impact of the above projectile. Effect of fibers, especially steel fibers, and slab thickness on the reliability of HFRC slabs are also investigated on a parametric basis.

Prediction of compressive strength of concrete using neural networks

Yousef A. Al-Salloum,Abid A. Shah,Saleh H. Alsayed,Tarek H. Almusallam,M.S. Al-Haddad,H. Abbas 사단법인 한국계산역학회 2012 Computers and Concrete, An International Journal Vol.10 No.2

This research deals with the prediction of compressive strength of normal and high strength concrete using neural networks. The compressive strength was modeled as a function of eight variables: quantities of cement, fine aggregate, coarse aggregate, micro-silica, water and super-plasticizer, maximum size of coarse aggregate, fineness modulus of fine aggregate. Two networks, one using raw variables and another using grouped dimensionless variables were constructed, trained and tested using available experimental data, covering a large range of concrete compressive strengths. The neural network models were compared with regression models. The neural networks based model gave high prediction accuracy and the results demonstrated that the use of neural networks in assessing compressive strength of concrete is both practical and beneficial. The performance of model using the grouped dimensionless variables is better than the prediction using raw variables.

Effect of rebar spacing on the behavior of concrete slabs under projectile impact

Husain Abbas,Nadeem A. Siddiqui,Tarek H. Almusallam,Aref A. Abadel,Hussein Elsanadedy,Yousef A. Al-Salloum 국제구조공학회 2021 Structural Engineering and Mechanics, An Int'l Jou Vol.77 No.3

In this paper, the effect of different steel bar configurations on the quasi-static punching and impact response of concrete slabs was studied. A total of forty RC square slab specimens were cast in two groups of concrete strengths of 40 and 63 MPa. In each group of twenty specimens, ten specimens were reinforced at the back face (singly reinforced), and the remaining specimens were reinforced on both faces of the slab (doubly reinforced). Two rebar spacing of 25 and 100 mm, with constant reinforcement ratio and effective depth, were used in both singly and doubly reinforced slab specimens. The specimens were tested against the normal impact of cylindrical projectiles of hemispherical nose shape. Slabs were also quasi-statically tested in punching using the same projectile, which was employed for the impact testing. The experimental response illustrates that 25 mm spaced rebars are effective in (i) decreasing the local damage and overall penetration depth, (ii) increasing the absorption of impact energy, and (iii) enhancing the ballistic limit of RC slabs. The ballistic limit was predicted using the quasi-static punching test results of slab specimens showing a strong correlation between the dynamic perforation energy and the energy required for quasi-static perforation of slabs.

Evaluation of the parameters affecting the Schmidt rebound hammer reading using ANFIS method

Ali Toghroli,Ehsan Darvishmoghaddam,Yousef Zandi,Mahdi Parvan,Maryam Safa,Mu’azu Mohammed Abdullahi,Abbas Heydari,Karzan Wakil,Saad A.M. Gebreel,Majid Khorami 사단법인 한국계산역학회 2018 Computers and Concrete, An International Journal Vol.21 No.5

As a nondestructive testing method, the Schmidt rebound hammer is widely used for structural health monitoring. During application, a Schmidt hammer hits the surface of a concrete mass. According to the principle of rebound, concrete strength depends on the hardness of the concrete energy surface. Study aims to identify the main variables affecting the results of Schmidt rebound hammer reading and consequently the results of structural health monitoring of concrete structures using adaptive neuro-fuzzy inference system (ANFIS). The ANFIS process for variable selection was applied for this purpose. This procedure comprises some methods that determine a subsection of the entire set of detailed factors, which present analytical capability. ANFIS was applied to complete a flexible search. Afterward, this method was applied to conclude how the five main factors (namely, age, silica fume, fine aggregate, coarse aggregate, and water) used in designing concrete mixture influence the Schmidt rebound hammer reading and consequently the structural health monitoring accuracy. Results show that water is considered the most significant parameter of the Schmidt rebound hammer reading. The details of this study are discussed thoroughly.

Effect of molar ratios on strength, microstructure & embodied energy of metakaolin geopolymer

Abadel, Aref A.,Albidah, Abdulrahman S.,Altheeb, Ali H.,Alrshoudi, Fahed A.,Abbas, Husain,Al-Salloum, Yousef A. Techno-Press 2021 Advances in concrete construction Vol.11 No.2

In this study, twenty-five geopolymer (GP) mixes were prepared by varying the alkaline solids to Metakaolin (MK) and sodium silicate to NaOH ratios from 0.1 to 0.5 and 0.2 to 1.0, respectively, thus giving a wide range of molar ratios of silica to alumina, sodium oxide to alumina and water to sodium oxide. The compressive strength of these GP mixes was determined for four curing schemes involving oven curing at 100℃ for 24 h and three ambient curing with the curing ages of 3, 14, and 28 days. The test results revealed that for the manufacture of GP binder for structural applications of strength up to 90 MPa, the molar ratio of silica to alumina should be greater than 2.3, sodium oxide to alumina should be between 0.6 to 1.2, and water to sodium oxide should not exceed 12. The compressive strength of ambient cured GP mortar gets stabilized at 28 days of ambient curing. Experimental findings were also corroborated by GP microstructure analysis. The embodied energy of MK-based GP mortars, especially of high strength, is significantly less than the cement mortar of equivalent strength.

Seismic pounding effects on adjacent buildings in series with different alignment configurations

Shehata E. Abdel Raheem,Mohamed Y.M. Fooly,Aly G.A. Abdel Shafy,Yousef A. Abbas,Mohamed Omar,Mohamed M.S. Abdel Latif,Sayed Mahmoud 국제구조공학회 2018 Steel and Composite Structures, An International J Vol.28 No.3

Numerous urban seismic vulnerability studies have recognized pounding as one of the main risks due to the restricted separation distance between neighboring structures. The pounding effects on the adjacent buildings could extend from slight non-structural to serious structural damage that could even head to a total collapse of buildings. Therefore, an assessment of the seismic pounding hazard to the adjacent buildings is superficial in future building code calibrations. Thus, this study targets are to draw useful recommendations and set up guidelines for potential pounding damage evaluation for code calibration through a numerical simulation approach for the evaluation of the pounding risks on adjacent buildings. A numerical simulation is formulated to estimate the seismic pounding effects on the seismic response demands of adjacent buildings for different design parameters that include: number of stories, separation distances; alignment configurations, and then compared with nominal model without pounding. Based on the obtained results, it has been concluded that the severity of the pounding effects depends on the dynamic characteristics of the adjacent buildings and the input excitation characteristics, and whether the building is exposed to one or two-sided impacts. Seismic pounding among adjacent buildings produces greater acceleration and shear force response demands at different story levels compared to the no pounding case response demands.