Hany Ibrahim Ahmed Awad <br/><br/>
Predicting the chloride ingress process inside blended concrete using artificial neural networks /  
 التنبؤ بعملة دخول الكلوردات داخل الخرسانة المخلوطة باستخدام الشبكات العصبة الاصطناعة 
Hany Ibrahim Ahmed Awad ; Supervised Osama A. Hodhod 
 - Cairo :   Hany Ibrahim Ahmed Awad ,   2014 
 - 126 P. :   plans ;   30cm 
<br/><br/>Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Civil Engineering 
<br/><br/> Three back-propagation neural networks (BPNN) were developed. One of them was developed to predict corrosion initiation time by simulating the error function solution to Fick`s second law of diffusion. The other two BPMMs were created to predict the chloride diffusivity in both FA and GGBFS concrete. Comparision between experimental data and ANN model predictions has proven that the developed ANN models have efficiently characterized both the chloride diffusivity of high performance concrete and the error function solution to Fick`s second law of diffustion 
<br/><br/>
<br/><br/><label>Subjects--Index Terms: </label>Chloride Diffusion Slag