• Proceedings of the Korea Concrete Institute Conference
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• 2005.05b
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• pp.481-484
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• 2005

Recently, Since the advanced nano technology develops unique physical and chemical properties different from those of the conventional materials. Normal concretes mixed with nano size materials have been studied to improve the fire-resistance with high strength and lower heat conductivity. In this pilot study, the nano-particle contents in the specimens ($\Phi$10\times20 cm$) were 0, 2, 4, and 6$\%$ by weight of cement, and fire-temperatures 800$^{circ}C$ was considered. The results show that as the nano-particle contents increases, fire resistance of concrete are superior to those of the ordinary concrete. Also, the experimental results show that fire resistance of nano Aluminum hydroxide dispersed concrete are superior to those of the nano-SiO2 concrete.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.323-326
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• 2005

Uniaxial tension test of Glass Fiber Reinforced Polymer (GFRP) bar reinforced concrete prisms was performed. The objective was to investigate the adequate cover thickness of the GFRP rebars. The tension stiffening effect of GFRP bar reinforced concrete was also studied. The test variables included rebar types (conventional steel rebar and two different GFRP rebars) and cover thicknesses (five different cover thicknesses ranging between 1-3db). Normal strength concrete was used. Cracking patterns on concrete surface and cracking loads were careful1y observed during the direct tensile test. The test results indicated that the adequate cover thickness of the GFRP rebars may even be larger than that of the steel rebars and that the cover thickness of 2db commonly specified for the GFRP rebars may not be large enough. The tension stiffening effect of the GFRP rebars was also quantified and documented from the test results.

• Computers and Concrete
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• v.3 no.2_3
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• pp.177-195
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• 2006

Slipforming is a construction method in which the forms move continuously during the placement of concrete. This paper presents the development of a computer aided program designated as "CADSLIPFORM" for slipforming operations. The program incorporates maturity methods for the prediction of initial setting times of slipform concrete layers using laboratory data (time-temperature histories and setting times of concrete mixtures at different temperatures) and generates slipform mock-up times. The performance of CADSLIPFORM is validated by comparing simulated mock-up times with those estimated in the field through conventional hard front by rod (R) method. Moreover, the program versatility is demonstrated by illustrating mock-up simulations for different cases with variable slipform parameters such as: number and thickness of concrete layers, concrete temperature (simulating variable setting times) and slipform speed. The program also incorporates the choice of Freiesleben Hansen & Pederson (FHP) and Carino & Tank (CT) maturity functions. CADSLIPFORM can assist user to develop reliable schedule of slipforming operation suitable for a specific project by optimizing various slipform parameters.

• Computers and Concrete
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• v.24 no.4
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• pp.295-302
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• 2019

Evolutionary algorithms based on conventional statistical methods such as regression and classification have been widely used in data mining applications. This work involves application of gene expression programming (GEP) for predicting compressive strength of fly ash geopolymer concrete, which is gaining increasing interest as an environmentally friendly alternative of Portland cement concrete. Based on 56 test results from the existing literature, a model was obtained relating the compressive strength of fly ash geopolymer concrete with the significantly influencing mix design parameters. The predictions of the model in training and validation were evaluated. The coefficient of determination ($R^2$), mean (${\mu}$) and standard deviation (${\sigma}$) were 0.89, 1.0 and 0.12 respectively, for the training set, and 0.89, 0.99 and 0.13 respectively, for the validation set. The error of prediction by the model was also evaluated and found to be very low. This indicates that the predictions of GEP model are in close agreement with the experimental results suggesting this as a promising method for compressive strength prediction of fly ash geopolymer concrete.

• Steel and Composite Structures
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• v.30 no.4
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• pp.315-325
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• 2019

Double skin composite walls offer structural and economic merits over conventional reinforced concrete counterparts in terms of higher capacity, greater stiffness, and better ductility. This paper investigated the axial behavior of double skin composite walls with steel truss connectors. Full-scaled tests were conducted on three specimens with different height-to-thickness ratios. Test results were evaluated in terms of failure mode, load-axial displacement response, buckling loading, axial stiffness, ductility, strength index, load-lateral deflection, and strain distribution. The test data were compared with AISC 360 and Eurocode 4 and it was found that both codes provided conservative predictions on the safe side.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.43-54
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• 2019

Due to various numerical problems, crack analysis of reinforced concrete members using the finite element method is confronting with substantial difficulties, rendering the prediction of crack patterns and crack widths a formidable task. The root cause is that the conventional analysis methods are not capable of tracking the crack sequence and accounting for the stress relief and re-distribution during cracking. To address this deficiency, the crack queuing algorithm has been proposed. Basically, at each load increment, iterations are carried out and within each iteration step, only the most critical concrete element is allowed to crack and the stress re-distribution is captured in subsequent iteration by re-formulating the cracked concrete element and re-analysing the whole concrete structure. To demonstrate the effectiveness of the crack queuing algorithm, crack analysis of concrete members tested in the literature is performed with and without the crack queuing algorithm incorporated.

• Computers and Concrete
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• v.33 no.2
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• pp.147-162
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• 2024

This study presents a random-aggregate mesoscale model integrating the random distribution of the coarse aggerates and the damage mechanics of the mortar and interfacial transition zone (ITZ). This mesoscale model can generate the random distribution of the coarse aggregates according to the prescribed particle size distribution which enables the automation of the current methodology with different coarse aggregates' distribution. The main innovation of this work is to propose the "correction factor" to eliminate the dimensionally dependent mesh sensitivity of the concrete damaged plasticity (CDP) model. After implementing the correction factor through the user-defined subroutine in the randomly meshed mesoscale model, the predicted fracture resistance is in good agreement with the average experimental results of a series of geometrically similar single-edge-notched beams (SENB) concrete specimens. The simulated cracking pattern is also more realistic than the conventional concrete material models. The proposed random-aggregate mesoscale model hence demonstrates its validity in the application of concrete fracture failure and statistical size effect analysis.

• Journal of the Korea Concrete Institute
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• v.12 no.1
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• pp.13-22
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• 2000

This paper describes the results obtained from 11 direct tension tests to explore the influence of concrete strength on tension stiffening behavior in reinforced concrete axial members. Three different concrete compressive strengths, 250, 650, and 900kgf/$\textrm{cm}^2$, were included as a main variable, while the ratio of cover thickness-to-rebar diameter was kept constant to be 2.62 to prevent from splitting cracking. As the results, it was appeared that, as higher concrete strength was used, less tension stiffening effect was resulted, and the residual deformation upon unloading was larger. In addition, the spacing between adjacent transverse cracks became smaller with higher concrete strength. The major cause for those results may be attributed to the fact that nonuniform bond stress concentration at both loaded ends and crack sections becomes severer as higher concrete is used, thereby local bond failure becomes more susceptible. From these findings, it would be said the increase in flexural stiffness resulting from using high-strength concrete will be much smaller than that predicted by the conventional knowledge. Finally, a factor accunting for concrete strength was introduced to take account for the effect of HSC on tension stiffening. This proposed equation predicts well the tension stiffening for the effect of HSC on tension stiffening. This proposed equation predicts well the tension stiffening behavior of these tests.

• International Journal of Concrete Structures and Materials
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• v.10 no.3
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• pp.373-381
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• 2016

As part of this study, has been developed a numerical method which allows to establish abacuses connecting the normal force with bending moment for a circular section and therefore to predict the rupture of this type of section. This may be for reinforced concrete (traditional steel) or concrete reinforced with steel fibers. The numerical simulation was performed in nonlinear elasticity up to exhaustion of the bearing capacity of the section. The rupture modes considered occur by plasticization of the steel or rupture of the concrete (under compressive stresses or tensile stresses). Regarding the fiber-reinforced concrete, the rupture occurs, usually, by tearing of the fibers. The behavior laws of the different materials (concrete and steel) correspond to the real behavior. The influence of several parameters was investigated, namely; diameter of the section, concrete strength, type of steel, percentage of reinforcement and contribution of concrete in tension between two successive cracks of bending. A comparison was made with the behavior of a section considering the conventional diagrams of materials; provided by the BAEL rules. A second comparative study was performed for fibers reinforced section.

• Structural Engineering and Mechanics
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• v.84 no.1
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• pp.101-111
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• 2022

It is widely known that axially loaded fiber-reinforced polymer (FRP) confined concrete presents significant and enhanced mechanical properties with reference to the unconfined concrete. Therefore, to predict the mechanical behavior of FRP-confined concrete two quantities-peak strength and ultimate strain are required. Despite the significant advances, the determination of the ultimate strain of FRP-confined concrete is one of the most challenging problems to be resolved. This is often attributed to our persistence in desiring the conventional methods as the sole technique to examine this phenomenon and the complex nature of the ultimate strain of FRP-confined concrete. To bridge the research gap, this study adopted two machine learning (ML) techniques-artificial neural network (ANN) and Gaussian process regression (GPR)-to analyze observations obtained from 627 datasets of FRP-confined concrete circular and non-circular sections under axial loading test. Besides, the techniques are also used to predict the ultimate strain of FRP-confined concrete. Seven parameters namely width/diameter of the specimens, corner radius ratio, the strength of concrete, FRP elastic modulus, FRP thickness, FRP tensile rupture strain, and the axial strain of unconfined concrete-are the input parameters used to predict the ultimate strain of FRP-confined concrete. The results of the current study highlight the merit of using AI techniques in structural engineering applications given their extraordinary ability to comprehend multidimensional phenomena of FRP-confined concrete structures with ease, low computational cost, and high performance over the existing empirical models.