Prediction of mechanical properties of reactive powder concrete by using artificial neural network and regression technique after the exposure to fire flame
Author
Source
Jordan Journal of Civil Engineering
Issue
Vol. 9, Issue 3 (30 Sep. 2015), pp.381-399, 19 p.
Publisher
Jordan University of Science and Technology Deanship of Research
Publication Date
2015-09-30
Country of Publication
Jordan
No. of Pages
19
Main Subjects
Topics
Abstract EN
An experimental work was carried out to investigate some mechanical properties of Reactive Powder Concrete (RPC) which are particularly required as input data for structural design.
These properties include compressive strength, flexural strength, tensile strength and static modulus of elasticity.
A combined laboratory and modeling study was undertaken to develop a database of the estimation ability of the effects of exposure to real fire flame on the mechanical properties of reactive powder concrete using 2 different models: artificial neural network (ANN) and regression techniques.
Experimental results were used in the estimation models.
After being subjected to high temperatures from 200 to 500°C, the residual mechanical properties were determined, and RPC was considerably spalled under high temperature.
Exposing to high temperatures from 200 to 400°C, mechanical properties were enhanced more or less, which can be attributed to further hydration of cementitious materials activated by elevated temperature.
It was found that RPC can be used at elevated temperatures up to 300°C for heating times up to 1 hour, taking into consideration the loss of strength.
Finally, prediction performances of reactive powder concrete single and multiple variable regression equations were developed, and ANN was compared.
According to this comparison, best prediction performance which belongs to ANN was improved.
American Psychological Association (APA)
Kazim, Muhammad Jawad Hadi. 2015. Prediction of mechanical properties of reactive powder concrete by using artificial neural network and regression technique after the exposure to fire flame. Jordan Journal of Civil Engineering،Vol. 9, no. 3, pp.381-399.
https://search.emarefa.net/detail/BIM-587891
Modern Language Association (MLA)
Kazim, Muhammad Jawad Hadi. Prediction of mechanical properties of reactive powder concrete by using artificial neural network and regression technique after the exposure to fire flame. Jordan Journal of Civil Engineering Vol. 9, no. 3 (2015), pp.381-399.
https://search.emarefa.net/detail/BIM-587891
American Medical Association (AMA)
Kazim, Muhammad Jawad Hadi. Prediction of mechanical properties of reactive powder concrete by using artificial neural network and regression technique after the exposure to fire flame. Jordan Journal of Civil Engineering. 2015. Vol. 9, no. 3, pp.381-399.
https://search.emarefa.net/detail/BIM-587891
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 398-399
Record ID
BIM-587891