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CONTENTS
Volume 21, Number 1, January 2018
 

Abstract
Electrical resistivity is a property associated with both the physical and chemical characteristics of concrete. It allows the evaluation of the greater or lesser difficulty with which aggressive substances penetrate the concrete\'s core before the dissolution of the passive film process and the consequent reinforcement\'s corrosion begin. This work addresses the steel fiber addition to concrete with two types and various contents from 0% to 1.3%, correlating it with its electrical resistivity. To that effect, 9 different mixes of steel fiber reinforced concrete (SFRC) were produced. The electrical resistivity was evaluated on the on six years aged SFRC by direct measurement at different frequency from 0.1 kHz to 100 kHz. The results indicate that steel fiber content is strongly conditioned by the type and quantity of the additions used. It was also found that long type of fibers has more effect on decreasing the electrical resistivity of concrete than short fibers. Therefore, they increase the corrosion risk of concrete depending on fiber volume fraction and moisture percentage.

Key Words
steel fiber; old-concrete; electrical resistivity; carbonation

Address
Tayfun Uygunoglu: Engineering Faculty, Civil Engineering Department, Afyon Kocatepe University, 03200, Afyonkarahisar, Turkey
Ilker Bekir Topcu: Engineering-Architectural Faculty, Civil Engineering Department, Eskişehir Osmangazi University, 26480, Eskişehir, Turkey
Baris Simsek: Faculty of Engineering, Department of Chemical Engineering, Çank

Abstract
The possibilities of non-linear analysis of reinforced-concrete structures are under development. In particular, current research areas include structural analysis with the application of advanced computational and material models. The submitted article aims to evaluate the possibilities of the determination of material properties, involving the tensile strength of concrete, fracture energy and the modulus of elasticity. To evaluate the recommendations for concrete, volume computational models are employed on a comprehensive series of tests. The article particularly deals with the issue of the specific properties of fracture-plastic material models. This information is often unavailable. The determination of material properties is based on the recommendations of Model Code 1990, Model Code 2010 and specialized literature. For numerical modelling, the experiments with the so called \"classic\" concrete beams executed by Bresler and Scordelis were selected. It is also based on the series of experiments executed by Vecchio. The experiments involve a large number of reinforcement, cross-section and span variants, which subsequently enabled a wider verification and discussion of the usability of the non-linear analysis and constitutive concrete model selected.

Key Words
reinforced concrete; classic beams; material properties; three-point bending test; computational mechanics

Address
Oldrich Sucharda and Petr Konecny: Faculty of Civil Engineering, VŠB-Technical University of Ostrava, Ludvíka Podéště 1875/17, 708 33 Ostrava-Poruba, Czech Republic

Abstract
In this study, we analyze the behavior of concrete which contains zeolite and diatomite. In order to achieve the goal, we utilize expert system methods. The utilized methods are artificial neural network and adaptive network-based fuzzy inference systems. In this respect, we exploit seven different mixes of concrete. The concrete mixes contain zeolite, diatomite, mixture of zeolite and diatomite. All seven concrete mixes are exposed to 28, 56 and 90 days\' compressive strength experiments with 63 specimens. The results of the compressive strength experiments are used as input data during the training and testing of expert system methods. In terms of artificial neural network and adaptive network-based fuzzy models, data format comprises seven input parameters, which are; the age of samples (days), amount of Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer. On the other hand, the output parameter is defined as the compressive strength of concrete. In the models, training and testing results have concluded that both expert system model yield thrilling medium to predict the compressive strength of concrete containing zeolite and diatomite.

Key Words
expert systems; compressive strength; concrete; zeolite; diatomite

Address
Giyasettin Ozcan: Department of Computer Engineering, Faculty of Engineering, Uludag University, Bursa, Turkey
Yilmaz Kocak: Department of Construction, Kutahya Vocational School of Technical Sciences, Dumlupinar University, Kutahya, Turkey
Eyyup Gulbandilar: Department of Computer Engineering, Faculty of Engineering and Architecture, Eskisehir Osmangazi University, Eskisehir, Turkey

Abstract
This paper deals with the stability analysis of concrete pipes mixed with nanoparticles conveying fluid. Instead of cement, the Fe2O3 nanoparticles are used in construction of the concrete pipe. The Navier-Stokes equations are used for obtaining the radial force of the fluid.Mori-Tanaka model is used for calculating the effective material properties of the concrete pipe-Fe2O3 nanoparticles considering the agglomeration of the nanoparticles. The first order shear deformation theory (FSDT) is used for mathematical modeling of the structure. The motion equations are derived based on energy method and Hamilton\'s principal. An exact solution is used for stability analysis of the structure. The effects of fluid, volume percent and agglomeration of Fe2O3 nanoparticles, magnetic field and geometrical parameters of pipe are shown on the stability behaviour of system. Results show that considering the agglomeration of Fe2O3 nanoparticles, the critical fluid velocity of the concrete pipe is decreased.

Key Words
concrete pipe; Fe2O3 nanoparticles; conveying fluid; stability; agglomeration

Address
Alireza Zamani Nouri: Department of Civil Engineering, College of Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran

Abstract
With the increase in industrialization and urbanization, growing demand has enhanced rate of new constructions and old demolitions. To avoid serious environmental impacts and hazards recycled concrete aggregates (RCA) is being adopted in all over the world. This paper investigates successive recycled coarse aggregates (SRCA) in which old concrete made with RCA in form of concrete cubes was used. The cubes were crushed to prepare new concrete using aggregates from crushing of old concrete, used as SRCA. The mechanical behavior of concrete was determined containing SRCA; the properties of SRCA were evaluated and then compared with natural aggregates (NA). Replacement of NA with SRCA in ratio upto 100% by weight was studied for workability, mechanical properties and microstructural analysis. It was observed that with the increase in replacement ratio workability and compressive strength decreased but in acceptable limits so SRCA can be used in low strength concretes rather than high strength concrete structures.

Key Words
successive recycled coarse aggregate; waste; fly ash strength; scanning electron microscope; X-ray diffraction

Address
Deepankar K. Ashish: Department of Civil Engineering, Maharaja Agrasen University, Baddi 174103, India; Department of Civil Engineering, Punjab Engineering College (Deemed to be University), Chandigarh 160012, India
Preeti Saini: Department of Civil Engineering, Kurukshetra University, Kurukshetra 136119, India

Abstract
Artificial neural network models can be successfully used to simulate the complex behavior of many problems in civil engineering. As compared to conventional computational methods, this popular modeling technique is powerful when the relationship between system parameters is intrinsically nonlinear, or cannot be explicitly identified, as in the case of concrete behavior. In this investigation, an artificial neural network model was developed to assess the residual compressive strength of self-compacted concrete at elevated temperatures (20-900oC) and various relative humidity conditions (28-99%). A total of 332 experimental datasets, collected from available literature, were used for model calibration and verification. Data used in model development incorporated concrete ingredients, filler and fiber types, and environmental conditions. Based on the feed-forward back propagation algorithm, systematic analyses were performed to improve the accuracy of prediction and determine the most appropriate network topology. Training, testing, and validation results indicated that residual compressive strength of selfcompacted concrete, exposed to high temperatures and relative humidity levels, could be estimated precisely with the suggested model. As illustrated by statistical indices, the reliability between experimental and predicted results was excellent. With new ingredients and different environmental conditions, the proposed model is an efficient approach to estimate the residual compressive strength of self-compacted concrete as a substitute for sophisticated laboratory procedures.

Key Words
modeling; artificial neural network; residual compressive strength; self-compacted concrete; temperature; relative humidity

Address
Ahmed M. Ashteyat: Department of Civil Engineering, The University of Jordan, Amman 11942, Jordan
Muhannad Ismeik: Department of Civil Engineering, The University of Jordan, Amman 11942, Jordan; Department of Civil Engineering, Australian College of Kuwait, Safat 13015, Kuwait