Developing an artificial neural network model to evaluate chloride diffusivity in high performance concrete
المؤلفون المشاركون
المصدر
Housing and Building National Research Center Journal
العدد
المجلد 9، العدد 1 (30 إبريل/نيسان 2013)، ص ص. 15-21، 7ص.
الناشر
المركز القومي لبحوث الإسكان و البناء
تاريخ النشر
2013-04-30
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الموضوعات
الملخص EN
Chloride attack is one of the major causes of deterioration of reinforced concrete structures.
In order to evaluate chloride behavior in concrete, a reasonable prediction for the diffusion coefficient of chloride ion (Dc), which governs the mechanism of chloride diffusion inside concrete, is basically required.
However, it is difficult to obtain chloride diffusion coefficients from experiments due to time and cost limitations.
This study focuses on the artificial neural network (ANN) as an alternative approach to evaluate the chloride diffusivity of high performance concrete (HPC).
A total of 300 different data of fly ash (FA) and slag (GGBFS) concrete were collected from the literature.
Two separate ANN models were developed for two types of HPC.
The data used in the ANN model consisted of four input parameters which include W/B ratio, cement content, FA or GGBFS content and curing age.
Output parameter is determined as diffusion coefficient of chloride ion.
Back propagation (BP) algorithm was employed for the ANN training in which a Tansig function was used as the nonlinear transfer function.
Through the comparison of the estimated results from ANN models and experimental data, it was clear that ANN models give high prediction accuracy.
In addition, the research results demonstrate that using ANN models to predict chloride diffusion coefficient is practical and beneficial
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hudhud, O. A.& Ahmad, H. I.. 2013. Developing an artificial neural network model to evaluate chloride diffusivity in high performance concrete. Housing and Building National Research Center Journal،Vol. 9, no. 1, pp.15-21.
https://search.emarefa.net/detail/BIM-374920
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hudhud, O. A.& Ahmad, H. I.. Developing an artificial neural network model to evaluate chloride diffusivity in high performance concrete. Housing and Building National Research Center Journal Vol. 9, no. 1 (2013), pp.15-21.
https://search.emarefa.net/detail/BIM-374920
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hudhud, O. A.& Ahmad, H. I.. Developing an artificial neural network model to evaluate chloride diffusivity in high performance concrete. Housing and Building National Research Center Journal. 2013. Vol. 9, no. 1, pp.15-21.
https://search.emarefa.net/detail/BIM-374920
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 21
رقم السجل
BIM-374920
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر