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RISS 인기검색어
- 검색키워드
- 저자 : Saleh H. Alsayed (검색결과 4 건)
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Investigations on the influence of radial confinement in the impact response of concrete
Yousef Al-Salloum,Saleh Alsayed,Tarek Almusallam,S.M. Ibrahim,H. Abbas 사단법인 한국계산역학회 2014 Computers and Concrete, An International Journal Vol.14 No.6
Annular and solid concrete specimens with different aspect ratios and static unconfined compressive strengths were studied for impact loading using SHPB test setup. Numerical simulations in LSDYNA were also carried out and results were validated. The stress-strain curves obtained under dynamic loading were also compared with static compressive tests. The mode of failure of concrete specimen was a typical ductile failure at high strain rates. In general, the dynamic increase factor (DIF) of thin solid specimens was higher than thick samples. In the numerical study, the variation of axial, hydrostatic and radial stresses for solid and annular samples was studied. The core phenomenon due to confinement was observed for solid samples wherein the applied loads were primarily borne by the innermost concrete zone rather than the outer peripheral zone. In the annular samples, especially with large diameter inside hole, the distribution of stresses was relatively uniform along the radial distance. Qualitatively, only a small change in the distribution of stresses for annular samples with different internal diameters studied was observed.
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Experimental and FE Study on RC One-Way Slabs Upgraded with FRP Composites
Hussein M. Elsanadedy,Tarek H. Almusallam,Saleh H. Alsayed,Yousef A. Al-Salloum 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.4
The use of externally bonded Fiber Reinforced Polymer (FRP) composites as a means of upgrading the flexural capacity of Reinforced Concrete (RC) one-way slabs is experimentally and numerically investigated in this study. A total of four groups of eight slabs were tested under four-point bending. The two slabs of the first group were left unstrengthened to be used as control specimens. The two slabs of the second group were externally strengthened with adhesively bonded pultruded, pre-cured CFRP plates. The four slabs of the last two groups were externally upgraded with unidirectional carbon (or E-glass) fiber fabric impregnated with an epoxy resin. In addition to the experimental program, a numerical investigation utilizing nonlinear Finite Element (FE) analysis was conducted using LS-DYNA software. Besides the eight slabs tested in this study, another eleven slabs were collected from the literature for the purpose of finite element validation. A comparison was made between the experimental and numerical results and good agreement was achieved. Based on FE validation, the numerical analysis was extended to include additional cases to study the effect of axial FRP stiffness and FRP-to-concrete width ratio on the flexural performance of upgraded slabs. As a result of the numerical study, new stiffness and reinforcement parameters were introduced in this research. These parameters were employed in the development of two new formulas for predicting the FRP debonding strain and percent gain in flexural capacity of FRPstrengthened slabs.
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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.
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Prediction of Punching Shear Strength of HSC Interior Slab-Column Connections
Hussein M. Elsanadedy,Yousef A. Al-Salloum,Saleh H. Alsayed 대한토목학회 2013 KSCE JOURNAL OF CIVIL ENGINEERING Vol.17 No.2
Flat plate systems are widely used in reinforced concrete structures. Using of high-strength concrete has been common recently. In the current international codes of practice for concrete structures, the design methods for assessment of punching shear capacity are based on experimental data of flat plates with Normal-Strength Concrete (NSC). The aim of this research is to come up with new formula for punching shear resistance, consistent with data of flat plates made from High-Strength Concrete (HSC). Test results of 61HSC interior slab-column connection specimens were collected from the literature. The available test results were not only compared with current code provisions but with equations proposed by other researchers as well. A new formula for predicting punching shear strength of HSC interior slab-column connections is proposed. An innovative design equation is also suggested.
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