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CONTENTS
Volume 10, Number 2, August 2012
 

Abstract
This study uses recycled green building materials based on a Taiwan-made recycled mineral admixture (including fly ash, slag, glass sand and rubber powder) as replacements for fine aggregates in concrete and tests the properties of the resulting mixtures. Fine aggregate contents of 5% and 10% were replaced by waste LCD glass sand and waste tire rubber powder, respectively. According to ACI concretemixture design, the above materials were mixed into lightweight aggregate concrete at a constant water-tobinder ratio (W/B = 0.4). Hardening (mechanical), non-destructive and durability tests were then performed at curing ages of 7, 28, 56 and 91 days and the engineering properties were studied. The results of these experiments showed that, although they vary with the type of recycling green building material added, the slumps of these admixtures meet design requirements. Lightweight aggregate yields better hardened properties than normal-weight concrete, indicating that green building materials can be successfully applied in lightweight aggregate concrete, enabling an increase in the use of green building materials, the improved utilization of waste resources, and environmental protection. In addition to representing an important part of a

Key Words
recycled green building materials; waste LCD glass; waste tire rubber powder; lightweight aggregate concrete.

Address
Her-Yung Wang, Darn-Horng Hsiao and Shi-Yang Wang: Department of Civil Engineering, National Kaohsiung University of Applied Sciences, 807, Taiwan, R.O.C

Abstract
This paper presents the mix composition and production method that was applied to an extruded Ductile Fiber Reinforced Cement Composite (DFRCC) panel, as well as the flexural performance, represented by deformation hardening behavior with multiple cracking. The effect of fiber distribution characteristics on the flexural behavior of the panel is also addressed. In order to demonstrate the fiber distribution effect, a series of experiments and analyses, including a sectional image analysis and micromechanical analysis, was performed. From the experimental and analysis results, it was found that the flexural behavior of the panel was highly affected by a slight variation in the mix composition. In terms of the average fiber orientation, the fiber distribution was found to be similar to that derived under the assumption of a two-dimensional random distribution, irrespective of the mix composition. In contrast, the probability density function for the fiber orientation was measured to vary depending on the mix composition.

Key Words
extruded DFRCC panel; image analysis; fiber distribution; flexural behavior.

Address
Bang Yeon Lee: School of Architecture, Chonnam National University, Gwangju, Korea; Byung-Chan Han: Department of Remolding Architecture, Woosong Information College, Daejeon 300-715, Korea; Chang-Geun Cho: School of Architecture, Chosun University, Gwangju, Korea; Yun Yong Kim: Chungnam National University, Daejeon, Korea

Abstract
Structures suffer from damages in their lifetime due to time-dependant effects, such as fatigue, creep and shrinkage, which can be expressed by concrete strains. These processes could be seen in the context of strain estimation of pre-stressed structures in two phases by using numerical methods. Their aim is checking and validating existing code procedures in determination of deformations of pre-tensioned girders by solving a system of nonlinear equations with strains as unknown parameters. This paper presents an approach based on the Newton-Raphson method for obtaining the stresses and strains in middle span section of pre-stressed girders according the equilibrium state.

Key Words
pre-tensioning; strains; linear theory; Newton-Raphson method; nonlinear equations.

Address
Milan Gocic: University of Nis, Faculty of Civil Engineering and Architecture, Aleksandra Medvedeva 14, 18 000 Nis, Serbia; Enis Sadovic: Ambijent doo, Kej skopskih zrtava 18, 36300 Novi Pazar, Serbia

Abstract
At mesoscale, concrete is considered as a three-phase composite material consisting of the aggregate particles, the cement matrix and the interfacial transition zone (ITZ). The reconstruction of the internal structures for concrete composites requires the identification of the boundary of the aggregate particles and the cement matrix using digital imaging technology followed by post-processing through MATLAB. A parameter study covers the subsection transformation, median filter, and open and close operation of the digital image sample to obtain the optimal parameter for performing the image processing technology. The subsection transformation is performed using a grey histogram of the digital image samples with a threshold value of [120, 210] followed by median filtering with a 16

Key Words
digital image processing; concrete composites; mesoscale; experiment; numerical simulation.

Address
Chengbin Du, Shouyan Jiang, Hairong Xu and Dong Lei: Department of Engineering Mechanics, Hohai University, Nanjing 210098, China; Wu QIN: CCCC Third Harbor Consultants Co., Ltd, Shanghai 200032, China

Abstract
The problem of a concrete cross section under flexural and axial loading is indeterminate due to the existence of more unknowns than equations. Among the infinite solutions, it is possible to find the optimum, which is that of minimum reinforcement that satisfies certain design constraints (section ductility, minimum reinforcement area, etc.). This article proposes the automation of the optimum reinforcement calculation under any combination of flexural and axial loading. The procedure has been implemented in a program code that is attached in the Appendix. Conventional-strength or high-strength concrete may be chosen, minimum reinforcement area may be considered (it being possible to choose between the standards ACI 318 or Eurocode 2), and the neutral axis depth may be constrained in order to guarantee a certain sectional ductility. Some numerical examples are presented, drawing comparisons between the results obtained by ACI 318, EC 2 and the conventional method.

Key Words
cross section; flexural/axial loading; automated design; optimum reinforcement.

Address
Antonio Tomas: Department of Civil Engineering, Universidad Politecnica de Cartagena (UPCT), 30203 Cartagena, Spain; Antonio Alarcon: School of Mechanical Engineering, Universidad Politecnica de Cartagena (UPCT), 30202 Cartagena, Spain

Abstract
Experimental results of cyclic reversed lateral force test on a two-story reinforced concrete shear wall sub-assemblage are simulated analytically by using the PERFORM-3D program. A comparison of experimental and analytical results leads to the following conclusions: (1) "Shear Wall" and "General Wall" models with "Concrete shear" cannot simulate the pinching phenomena due to shear and show larger amounts of inelastic energy absorption than those in the experiment. (2) Modeling a story-height wall by using two or more "General Wall" elements with "Diagonal shear" in the vertical direction induces the phenomenon of swelling-out at the belly, leading to the erroneous simulation of shear behaviors. In application to tall building structures, it is recommended to use one element of "General Wall" with "Diagonal shear" for the full height of a story. (3) In the plastic hinge area, concrete deformations of analytical models overestimate elongation and underestimate shortening when compared with experimental results.

Key Words
reinforced concrete; nonlinear analysis; PERFORM-3D; wall sub-assemblage.

Address
Han Seon Lee, Da Hun Jeong and Kyung Ran Hwang: School of Civil, Environmental, and Architectural Engineering, Korea University, 74 Inchon-ro, Sungbuk-gu, Seoul, 136-713, Korea

Abstract
This research deals with the prediction of compressive strength of normal and high strength concrete using neural networks. The compressive strength was modeled as a function of eight variables: quantities of cement, fine aggregate, coarse aggregate, micro-silica, water and super-plasticizer, maximum size of coarse aggregate, fineness modulus of fine aggregate. Two networks, one using raw variables and another using grouped dimensionless variables were constructed, trained and tested using available experimental data, covering a large range of concrete compressive strengths. The neural network models were compared with regression models. The neural networks based model gave high prediction accuracy and the results demonstrated that the use of neural networks in assessing compressive strength of concrete is both practical and beneficial. The performance of model using the grouped dimensionless variables is better than the prediction using raw variables.

Key Words
compressive strength; concrete; neural network; regression models.

Address
Yousef A. Al-Salloum, Abid A. Shah, H. Abbas, Saleh H. Alsayed, Tarek H. Almusallam and M.S. Al-Haddad: Specialty Units for Safety and Preservation of Structures, Department of Civil Engineering, King Saud University, Riyadh 11421, Saudi Arabia


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