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CONTENTS
Volume 15, Number 2, February 2015
 

Abstract
In the present study, a Finite Element Model has been developed and used to study the effect of diameter to wall thickness ratio (D/t) of steel tube filled with concrete under axial loading on its behavior and load carrying capacity. The model is verified by comparing its findings with available experimental results. Influence of thickness and area of steel tube on strength, ductility, confinement and failure mode shapes has been studied. Strength enhancement factors, load factor, confinement contribution, percentage of steel and ductility index are defined and introduced for the assessment. A parametric study by varying length and thickness of tube has been carried out. Diameter of tube kept constant and equals to 140 mm while thickness has been varied between 1 mm and 6 mm. Equations were developed to find out the ultimate load and confined concrete strength of concrete. Variation of lateral confining pressure along the length of concrete cylinder was obtained and found that it varies along the length. The increase in length of tubes has a minimal effect on strength of tube but it affects the failure mode shapes. The findings indicate that optimum use of materials can be achieved by deciding the thickness of steel tube. A better ductility index can be obtained with the use of higher thickness of tube.

Key Words
concrete filled steel tube (CFST); ductility; confinement; strength; finite element method

Address
P.K. Gupta, V.K. Verma, Ziyad A. Khaudhair and Heaven Singh: Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India

Abstract
\"Mortar or concrete pneumatically projected at high velocity onto a surface\" is called Shotcrete. Models that predict shotcrete design parameters (e.g. compressive strength, slump etc) from any mixing proportions of admixtures could save considerable experimentation time consumed during trial and error based procedures. Artificial Neural Network (ANN) has been widely used for similar purposes; however, such models have been rarely applied on shotcrete design. In this study 19 samples of shotcrete test panels with varying quantities of water, steel fibers and silica fume were used to determine their slump, cost and compressive strength at different ages. A number of 3-layer Back propagation Neural Network (BPNN) models of different network architectures were used to train the network using 15 samples, while 4 samples were randomly chosen to validate the model. The predicted compressive strength from linear regression lacked accuracy with R2 value of 0.36. Whereas, outputs from 3-5-3 ANN architecture gave higher correlations of R2 = 0.99, 0.95 and 0.98 for compressive strength, cost and slump parameters of the training data and corresponding R2 values of 0.99, 0.99 and 0.90 for the validation dataset. Sensitivity analysis of output variables using ANN can unfold the nonlinear cause and effect relationship for otherwise obscure ANN model.

Key Words
ANN; shotcrete design; admixtures; sensitivity analysis

Address
Khan Muhammad, Noor Mohammad and Fazal Rehman: Department of Mining Engineering,University of Engineering & Technology, Peshawar, KP, Pakistan

Abstract
Chloride ingress implies a complex interaction between physical and chemical process, in which heat, moisture and chloride ions transport through concrete cover. Meanwhile, reinforced concrete structure itself undergoes evolution due to variation in temperature, relative humidity and creep effects, which can potentially change the deformation and trigger some micro-cracks in concrete. In addition, all of these process show time-dependent performance with complex interaction between structures and environments. In the present work, a time-dependent behavior of chloride transport in reinforced concrete beam subjected to flexural load is proposed based on the well-known section fiber model. The strain state varies because of stress redistribution caused by the interaction between environment and structure, mainly dominated by thermal stresses and shrinkage stress and creep. Finally, in order to clear the influence of strain state on the chloride diffusivity, experiment test were carried out and a power function used to describe this influence is proposed.

Key Words
concrete structure; chloride ingress; section fiber model; strain state; external loadings

Address
Hailong Ye Chuanqing Fu, Nanguo Jin and Xianyu Jin: Department of Civil Engineering, Zhejiang University, 388 Yuhangtang Road, Hangzhou 310058, China

Nanguo Jin: College of Civil Engineering and Architecture, Zhejiang University of Technology, Hangzhou, 310014, China

Xianyu Jin: Department of Civil Engineering, Zhejiang University, 388 Yuhangtang Road, Hangzhou 310058, China

Abstract
The residual fracture toughness of post-fire normal-strength concrete subjected up to 600oCis considered by the wedge splitting test. The initial fracture toughness KIini and the critical fracture toughness KIun could be calculated experimentally. Their difference is donated as the cohesive fracture toughness KIc which is caused by the distribution of cohesive stress on the fracture process zone. A comparative study on determining the residual fracture toughness associated with three bi-linear functions of the cohesive stress distribution, i.e. Peterson\'s softening curve, CEB-FIP Model 1990 softening curve and Xu\'s softening curve, using an analytical method is presented. It shows that different softening curves have no significant influence on the fracture toughness. Meanwhile, comparisons between the experimental and the analytical calculated critical fracture toughness values further prove the validation of the double-K fracture model to the post-fire concrete specimens.

Key Words
post-fire; fracture toughness; bi-linear; softening curve; double-K fracture model

Address
Kequan YU and Zhoudao LU: College of civil engineering, Tongji University, No.1239 SiPing Road, Shanghai, China

Abstract
The emerging technology of self compacting concrete, fiber reinforcement together reduces vibration and substitute conventional reinforcement which help in improving the economic efficiency of the construction. The objective of this work is to find the regression model to determine the response surface of mix proportioning Steel Fiber Reinforced Self Compacting Concrete (SFSCC) using statistical investigation. A total of 30 mixtures were designed and analyzed based on Design of Experiment (DOE). The fresh properties of SCC and mechanical properties of concrete were studied using Response Surface Methodology (RSM). The results were analyzed by limited proportion of fly ash, fiber, volume combination ratio of two steel fibers with aspect ratio of 50/35: 60/30 and super plasticizer (SP) dosage. The center composite designs (CCD) have selected to produce the response in quadratic equation. The model responses included in the primary stage were flowing ability, filling ability , passing ability and segregation index whereas in harden stage of concrete, compressive strength, split tensile strength and flexural strength at 28 days were tested. In this paper, the regression model and the response surface plots have been discussed, and optimal results were found for all the responses.

Key Words
steel fiber reinforced self compacting concrete, hybrid fiber; fly ash; statistical experimental design; response surface methodology

Address
Akila. P: Department of Civil Engineering, University College of Engineering, Panruti 607106, Tamil nadu, India

Kandasamy. S: Department of Civil Engg. (Structural), Govt. College of Tech., Coimbatore 641013, Tamil nadu, India

Abstract
This paper discusses the spatial variability of the carbonation depth caused by the mesoscopic structure of the concrete and the influence of the spatial variability on the thickness of the concrete cover. To conduct the research, a method to generate the random aggregate structure (RAS) based on polygonal particles and a simplified numerical model of the concrete carbonation at meso-scale are firstly developed. Based on the method and model, the effect of the aggregate properties including shape, content and gradation on the spatial variability of the carbonation depth is comprehensively studied. The results show that a larger degree of the spatial variability will be obtained by using (1) the aggregates with a larger aspect ratio; (2) a larger aggregate content; (3) the gradation which has more large particles. The proper sample size and model size used in the analysis are also studied. Finally, a case study is conducted to demonstrate the influence of the spatial variability of the carbonation depth on the proper thickness of the concrete cover. The research in this paper not only provides suggestions on how to decrease the spatial variability, but also proposes the method to consider the effect of the spatial variability in designing the thickness of the concrete cover.

Key Words
concrete structures; carbonation; spatial variability; meso-scale

Address
Zichao Pan, Xin Ruan and Airong Chen: Department of Bridge Engineering, Tongji University, Shanghai, 200092, China



Abstract
The lack of experimental studies on the mechanical behavior of reinforced concrete (RC) haunched beams leads to difficulties in statistical and reliability analyses. This study performs stochastic and reliability analyses of the ultimate shear capacity of RC haunched beams based on nonlinear finite element analysis. The main aim of this study is to investigate the influence of uncertainty in material properties and geometry parameters on the mechanical performance and shear capacity of RC haunched beams. Firstly, 65 experimentally tested RC haunched beams and prismatic beams are analyzed via deterministic nonlinear finite element method by a special program (ATENA) to verify the efficiency of utilized numerical models, the shear capacity and the crack pattern. The accuracy of nonlinear finite element analyses is verified by comparing the results of nonlinear finite element and experiments and both results are found to be in a good agreement. Afterwards, stochastic analyses are performed for each beam where the RC material properties and geometry parameters are assigned to take probabilistic values using an advanced simulating procedure. As a result of stochastic analysis, statistical parameters are determined. The statistical parameters are obtained for resistance bias factor and the coefficient of variation which were found to be equal to 1.053 and 0.137 respectively. Finally, reliability analyses are accomplished using the limit state functions of ACI-318 and ASCE-7 depending on the calculated statistical parameters. The results show that the RC haunched beams have higher sensitivity and riskiness than the RC prismatic beams.

Key Words
haunched beams; reinforced concrete; nonlinear finite element analysis; stochastic analysis; reliability analysis

Address
Hasan M. Albegmprli,AbdulkadirÇevik and M. ErenGülşan: Department of Civil Engineering, Gaziantep University, University Avenue, 27310 Gaziantep, Turkey

Hasan M. Albegmprli: Technical College of Mosul, Foundation of Technical Education, Iraq

AhmetEminKurtoglu: Department of Civil Engineering, Zirve UniversityKizilhisar Campus, Gaziantep, Turkey

Abstract
In this study, reliability analyses of steel fiber reinforced concrete (SFRC) corbels based on stochastic finite element were performed for the first time in literature. Prior to stochastic finite element analysis, an experimental database of 84 sfrc corbels was gathered from literature. These sfrc corbels were modeled by a special finite element program. Results of experimental studies and finite element analysis were compared and found to be very close to each other. Furthermore experimental crack patterns of corbel were compared with finite element crack patterns and were observed to be quite similar. After verification of the finite element models, stochastic finite element analyses were implemented by a specialized finite element module. As a result of stochastic finite element analysis, appropriate probability distribution functions (PDF\'s) were proposed. Finally, coefficient of variation, bias and strength reduction (resistance) factors were proposed for sfrc corbels as a consequence of stochastic based reliability analysis.

Key Words
steel fiber reinforced concrete corbel; nonlinear finite element analysis; stochastic analysis; reliability analysis; statistical parameters

Address
Mehmet Eren Gulsan and Abdulkadir Cevik: Department of Civil Engineering, Gaziantep University, University Avenue, 27310, Gaziantep, Turkey

Ahmet Emin Kurtoglu: Department of Civil Engineering, Zirve University, K

Abstract
On mesoscopic level, concrete can be treated as a three-phase composite material consisting of mortar, aggregates and interfacial transition zone (ITZ) between mortar and aggregate. A lot of research has confirmed that ITZ plays a crucial role in the mechanical fracture process of concrete. The aim of the present study is to propose a numerical method on mesoscale to analyze the failure mechanism of reinforced concrete (RC) structures under mechanical loading, and then it will help precisely predict the damage or the cracking initiation and propagation of concrete. Concrete is meshed by means of the Rigid Body Spring Model (RBSM) concept, while the reinforcing steel bars are modeled as beam-type elements. Two kinds of RC members, i.e. subjected to uniaxial tension and beams under bending, the fracture process of concrete and the distribution of cracks, as well as the load-deflection relationships are investigated and compared with the available test results. It is found that the numerical results are in good agreement with the experimental observations, indicating that the model can successfully simulate the failure process of the RC members.

Key Words
mesoscale simulation; Rigid Body Spring Model (RBSM); reinforced concrete (RC) member; crack distribution; deflection

Address
Licheng Wang: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China

Licheng Wangand Jiuwen Bao: State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China

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