Carbon fiber reinforced polymers (CFRP) were widely used in strengthening reinforced concrete members
in the last few years, these fibers consist mainly of high strength fibers which increase the member capacity in addition to changing the mode of failure of the reinforced concrete beams. Experimental and theoretical investigations were carried to find the behavior of reinforced concrete beams strengthened by CFRP in shear and bending. The experimental work included testing of 12 beams divided into 4 groups; each group contains 3 beams. The following parameters were taken into consideration: - Concrete crushing strength. - CFRP strengthening location (shear strengthening and both shear and flexure strengthening). Reinforced beams were simply supported subjected to two point loads. Each group consists of three beams; the first beam without CFRP, the second one, is strengthened with CFRP in shear and the third is strengthened with CFRP in both flexure and shear. Four groups with different crushing strength of (12, 20, 30 and 39 MPa). The CFRP sheets are attached externally.
It was found that in beam with low crushing strength loads transfer to the CFRP at early stages while in
those of high crushing strength, CFRP contribution only starts when full strength of the beam is fulfilled. A
full bond between CFRP sheets and the concrete is assumed in the theoretical analysis. Comparison between the theoretical and the experimental results revealed the validity of the numerical analysis and the developed methods such that there was a difference of 13% in the ultimate strength for the tested and analyzed beams.
Abstract: -
The concept of joint integration of important concepts in macroeconomic application, the idea of cointegration is due to the Granger (1981), and he explained it in detail in Granger and Engle in Econometrica (1987). The introduction of the joint analysis of integration in econometrics in the mid-eighties of the last century, is one of the most important developments in the experimental method for modeling, and the advantage is simply the account and use it only needs to familiarize them selves with ordinary least squares.
Cointegration seen relations equilibrium time series in the long run, even if it contained all the sequences on t
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a
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