• Structural Engineering and Mechanics
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• v.30 no.2
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• pp.211-223
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• 2008

A number of studies have suggested that the use of high ductile and high shear materials, such as Engineered Cementitious Composites (ECC) and High Performance Fiber Reinforced Cementitious Composites (HPFRCC), significantly enhances the shear capacity of structural elements, even with/without shear reinforcements. The present study emphasizes the development of a nonlinear model of shear behaviour of a HPFRCC panel for application to the seismic retrofit of reinforced concrete buildings. To model the shear behaviour of HPFRCC panels, the original Modified Compression Field Theory (MCFT) for conventional reinforced concrete panels has been newly revised for reinforced HPFRCC panels, and is referred to here as the HPFRCC-MCFT model. A series of experiments was conducted to assess the shear behaviour of HPFRCC panels subjected to pure shear, and the proposed shear model has been verified through an experiment involving panel elements under pure shear. The proposed shear model of a HPFRCC panel has been applied to the prediction of seismic retrofitted reinforced concrete buildings with in-filled HPFRCC panels. In retrofitted structures, the in-filled HPFRCC element is regarded as a shear spring element of a low-rise shear wall ignoring the flexural response, and reinforced concrete elements for beam or beam-column member are modelled by a finite plastic hinge zone model. An experimental study of reinforced concrete frames with in-filled HPFRCC panels was also carried out and the analysis model was verified with correlation studies of experimental results.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.320-324
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• 2000

Nonlinear stress analysis of nuclear containment building is carried out using microscopic concrete material model. The present study mainly focuses on the evaluation of the ultimate pressure capacity of idealized containment building in nuclear power plant. For this purpose, an eight-node degenerated shell element it adopted and an imaginary opening in the apex of containment building is allowed in FE model. From numerical analysis, the adopted concrete material model performs well and has a good agreement with the result obtained by using ABAQUS. Finally, we propose the present study as a benchmark test for nonlinear analysis of containment building.

• Computers and Concrete
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• v.17 no.3
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• pp.323-336
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• 2016

Although the self-compacting concrete (SCC) offers several practical and economic benefits and quality improvement in concrete constructions, in comparison with conventionally vibrated concretes confronts with autogenously chemical and drying shrinkage which causes the formation of different cracks and creates different problems in concrete structures. Using different fibers in the mix design and implementation of fibrous concrete, the problem can be solved by connecting cracks and micro cracks together and postponing the propagation of them. In this study an experimental investigation using response surface methodology (RSM) based on full factorial design has been undertaken in order to model and evaluate the polypropylene fiber effect on the fibrous self-compacting concrete and curing time, fiber percentage and fiber amount have been considered as input variables. Compressive strength has been measured and calculated as the output response to achieve a mathematical relationship between input variables. To evaluate the proposed model analysis of variance at a confidence level of 95% has been applied and finally optimum compressive strength predicted. After analyzing the data, it was found that the presented mathematical model is in very good agreement with experimental results. The overall results of the experiments confirm the validity of the proposed model and this model can be used to predict the compressive strength of fibrous self-compacting concrete.

• Computers and Concrete
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• v.12 no.5
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• pp.585-612
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• 2013

The paper presents quasi-static numerical simulations of the behaviour of short reinforced concrete beams without shear reinforcement under mixed shear-tension failure using the FEM and four various constitutive continuum models for concrete. First, an isotropic elasto-plastic model with a Drucker-Prager criterion defined in compression and with a Rankine criterion defined in tension was used. Next, an anisotropic smeared crack and isotropic damage model were applied. Finally, an elasto-plastic-damage model was used. To ensure mesh-independent FE results, to describe strain localization in concrete and to capture a deterministic size effect, all models were enhanced in a softening regime by a characteristic length of micro-structure by means of a non-local theory. Bond-slip between concrete and reinforcement was considered. The numerical results were directly compared with the corresponding laboratory tests performed by Walraven and Lehwalter (1994). The advantages and disadvantages of enhanced models to model the reinforced concrete behaviour were outlined.

• Proceedings of the Korea Concrete Institute Conference
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• 1993.04a
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• pp.148-153
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• 1993

The paper presents the results of shaking table test conducted on the 1/3.3 scaled large concrete panel model. The behaviors of large concrete panel structures subjected to seismic excitations are controlled by capacity of horizontal and vertical joints. To Study the seismic capacity of the large concrete panel structures, experimental researches for joints and structural assemblage are needed. Especially, since the magnitude of seismic loads are depended on the variation of time, period and accelerations, dynamic test is needed for estimating the seismic resistance of large concrete panel structures. The objective of this paper is to study the behaviors of large concrete panel structures on seismic excitations and to estimate the safety. Test results are as follows : 1) Test model was critically damaged in the first floor horizontal joint by rocking. 2) Elastic limit(0.12kg) of test model was 5times higher than that of korean seismic design code. 3) Maxium base shear of test model at the ground acceleration of 0.12g was 3.5 times higher than the result of equivalent static analysis. 4) Damping ratio of test model turned out 3.9~5.3% and the period at 0.12g was 0.065sec.

• Structural Engineering and Mechanics
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• v.5 no.4
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• pp.355-368
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• 1997

Fiber reinforced plastic (FRP) rods are used as reinforcement (prestressed or not) to concrete. FRP composites can also be combined with steel to form hybrid reinforcing rods that take advantage of the properties of both materials. In order to effectively utilize these rods, their bond behavior with concrete must be understood. The objective of this study is to characterize and model the bond behavior of hybrid FRP rods made with epoxy-impregnated aramid or poly-vinyl alcohol FRP skins directly braided onto a steel core. The model closely examines the split failure of the concrete by quantifying the relationship between slip of the rods resulting transverse stress field in concrete. The model is used to derive coefficients of friction for these rods and, from these, their development length requirements. More testing is needed to confirm this model, but in the interim, it may serve as a design aide, allowing intelligent decisions regarding concrete cover and development length. As such, this model has helped to explain and predict some experimental data from concentric pull-out tests of hybrid FRP rods.

• Computers and Concrete
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• v.14 no.3
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• pp.327-345
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• 2014

This paper presents the application of multi-gene genetic programming (MGP) technique for modeling the bond strength of ribbed steel bars in concrete. In this regard, the experimental data of 264 splice beam tests from different technical papers were used for training, validating and testing the model. Seven basic parameters affecting on the bond strength of steel bars were selected as input parameters. These parameters are diameter, relative rib area and yield strength of steel bar, minimum concrete cover to bar diameter ratio, splice length to bar diameter ratio, concrete compressive strength and transverse reinforcement index. The results show that the proposed MGP model can be alternative approach for predicting the bond strength of ribbed steel bars in concrete. Moreover, the performance of the developed model was compared with the building codes' empirical equations for a complete comparison. The study concludes that the proposed MGP model predicts the bond strength of ribbed steel bars better than the existing building codes' equations. Using the proposed MGP model and building codes' equations, a parametric study was also conducted to investigate the trend of the input variables on the bond strength of ribbed steel bars in concrete.

• Computers and Concrete
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• v.21 no.1
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• pp.47-54
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• 2018

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 ($20-900^{\circ}C$) 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 self-compacted 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.

• Smart Structures and Systems
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• v.26 no.1
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• pp.63-75
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• 2020

Substructure pseudo-dynamic hybrid simulation (SPDHS) combining the advantages of physical experiments and numerical simulation has become an important testing method for evaluating the dynamic responses of structures. Various parameter identification methods have been proposed for online model updating. However, if there is large model gap between the assumed numerical models and the real models, the parameter identification methods will cause large prediction errors. This study presents an ANN (artificial neural network) method based on forgetting factor. During the SPDHS of model updating, a dynamic sample window is formed in each loading step with forgetting factor to keep balance between the new samples and historical ones. The effectiveness and anti-noise ability of this method are evaluated by numerical analysis of a six-story frame structure with BRBs (Buckling Restrained Brace). One BRB is simulated in OpenFresco as the experimental substructure, while the rest is modeled in MATLAB. The results show that ANN is able to present more hysteresis behaviors that do not exist in the initial assumed numerical models. It is demonstrated that the proposed method has good adaptability and prediction accuracy of restoring force even under different loading histories.

• Structural Engineering and Mechanics
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• v.60 no.4
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• pp.655-665
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• 2016

This paper aims to develop models to accurately predict the behavior of fresh concrete exposed to vibration using artificial neural networks (ANNs) model and regression model (RM). For this purpose, behavior of a full scale precast concrete mold was investigated experimentally and numerically. Experiment was performed under vibration with the use of a computer-based data acquisition system. Transducers were used to measure time-dependent lateral displacements at some points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using both ANNs and RM. For the modeling of ANNs: Experimental data were divided randomly into two parts. One of them was used for training of the ANNs and the remaining part was used for testing the ANNs. For the modeling of RM: Sinusoidal regression model equation was determined and the predicted data was compared with measured data. Finally, both models were compared with each other. The comparisons of both models show that the measured and testing results are compatible. Regression analysis is a traditional method that can be used for modeling with simple methods. However, this study also showed that ANN modeling can be used as an alternative method for behavior of fresh concrete exposed to vibration in precast concrete structures.