Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

(181.63KB)
This is an Open Access publication published under CSC-OpenAccess Policy.
Publications from CSC-OpenAccess Library are being accessed from over 74 countries worldwide.
Experimental Investigation and Numerical Modeling of the Effect of Natural and Steel Fibers on the Performance of Concrete
Hossam Hodhod, Mostafa Abdeen
Pages - 321 - 337     |    Revised - 30-11-2010     |    Published - 20-12-2010
Volume - 4   Issue - 5    |    Publication Date - December 2010  Table of Contents
MORE INFORMATION
KEYWORDS
Concrete, Fibers, Ultrasonic Pulse Velocity, Modeling, Artificial Neural Network
ABSTRACT
The application of fibers to concrete industry is growing due to the demanding needs of concrete with better structural performance. Environmental considerations urge this application since many of the fiber types (especially natural ones) results as by products from different industrial and agricultural processes. In this study, the application of metallic steel fibers and natural (Linen) fibers in concrete industry is investigated. Twenty one mixes are made with different mix proportions and with different types of fibers. The mixes were designed first to give strengths in the range from 150 to 450 Kg/cm2, without fiber inclusion. The two types of fibers are added to each of the basic control mixes. Standard specimens in forms of cubes and cylinders were cast from each mix. The specimens were tested in compression, tension and impact. Measurements were also made using two NDT techniques. The specimens were tested at ages of 7 and 28 days and after exposure to elevated temperatures of 400 and 450„aC . The results were compared and showed the enhancement level obtained by including steel and natural fibers. Following this experimental effort, the Artificial Neural Network (ANN) technique was applied for predicting the performance of concrete with different mix proportions. The current paper introduced the (ANN) technique to investigate the effect of natural and steel fibers on the performance of concrete. The results of this study showed that the ANN method with less effort was very efficiently capable of simulating and predicting the performance of concrete with different mix proportions and different types of fibers.
CITED BY (1)  
1 Sakthivel, P. B., & Jagannathan, A. (2012). Fibrous Ferrocement Composite with PVC-coated weld mesh and bar-chip polyolefin fibers. International Journal of EOMATE, 3(2), 381-388.
1 Google Scholar 
2 CiteSeerX 
3 Socol@r  
4 ResearchGATE 
5 Libsearch 
6 Scribd 
7 SlideShare 
8 PdfSR 
9 PDFCAST 
1 Abdeen, M. A. M. “Neural Network Model for predicting Flow Characteristics in Irregular Open Channel”. Scientific Journal, Faculty of Engineering-Alexandria University, Alexandria,Egypt, 40(4):539-546, 2001
2 Abdeen, M. A. M. “Development of Artificial Neural Network Model for Simulating the Flow Behavior in Open Channel Infested by Submerged Aquatic Weeds”. Journal of Mechanical Science and technology, KSME Int. J., Soul, Korea, 20(10): 2006
3 ACI 228.1 R89. “In-Place Methods for Determination of Strength of Concrete”. American Concrete Institute, 1989
4 ACI 437 R91. “Strength Evaluation of Existing Concrete Buildings”. American Concrete Institute, 1991
5 [ACI 544.1 R82-96. “State of the Art Report on Fiber Reinforced Concrete”. American Concrete Institute, 1996
6 ACI 544.2R-99. “Measurement of Properties of Fiber Reinforced Concrete”. American Concrete Institute, 199
7 ALLAM, B. S. M. “Artificial Intelligence Based Predictions of Precautionary Measures for building adjacent to Tunnel Rout during Tunneling Process”. Ph.D. Thesis, Faculty of Engineering, Cairo University, Giza, Egypt, 200
8 ASTM C0469-02E01. “Test Method for Static Modulus of Elasticity and Poisson's Ratio of Concrete in Compression”, 200
9 Azmathullah, H. Md., Deo, M. C., Deolalikar, P. B. “Neural Networks for Estimation of Scour Downstream of a Ski-Jump Bucket”. Journal of Hydrologic Engineering, ASCE, 131(10), 898- 908, 2005
10 Gorillo, P., Shimizu, G. “Study of the Properties of Coir Fiber Mortar and Concrete”. Proc. of the Annual Meeting of Japan Concrete Institute JCI, 14(1):1143-1148, 1992
11 Kheireldin, K. A. “Neural Network Application for Modeling Hydraulic Characteristics of Severe Contraction”. Proc. of the 3rd Int. Conference, Hydroinformatics, Copenhagen - Denmark August 24-26, 1998
12 Malhotra, V.M. “Testing Hardened Concrete: Nondestructive Methods”. ACI Monograph, No. 9, 1986
13 Mohamed, M. A. M. “Selection of Optimum Lateral Load-Resisting System Using Artificial Neural Networks”. M. Sc. Thesis, Faculty of Engineering, Cairo University, Giza, Egypt, 2006
14 Minns. “Extended Rainfall-Runoff Modeling Using Artificial Neural Networks”. Proc. of the 2nd Int. Conference on Hydroinformatics, Zurich, Switzerland, 1996
15 Parrett, N. J.. “Fiber Reinforced Materials Technology”. Van Nostrand Reinhold Company, London, 197
16 Ramachandran, V.,J. et al. “Concrete Science”. Heyden & Sons Ltd., London, (1981
17 Shin, Y. “Neuralyst TM User’s Guide”. “Neural Network Technology for Microsoft Excel”. Cheshire Engineering Corporation Publisher, (1994
18 Silva, R. V., Aquino, E. M. F.,”Curaua Fiber: A New Alternative to Polymeric Composites”. Journal of Reinforced Plastics and Composites, 27(1):2008
19 Tahk, K. Mo, K. H. Shin. “A study on the Fault Diagnosis of Roller-Shape Using Frequency Analysis of Tension Signals and Artificial Neural Networks Based Approach in a Web Transport System”. Journal of Mechanical Science and technology, KSME Int. J., Soul, Korea, 16(12):2002
Mr. Hossam Hodhod
- Egypt
Associate Professor Mostafa Abdeen
- Egypt
mostafa_a_m_abdeen@hotmail.com