• Steel and Composite Structures
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• v.4 no.5
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• pp.385-402
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• 2004

Nearly 400 composite railway bridge decks of a new kind belonging to the trough type with U-shaped cross section have been constructed in Belgium over the last fifteen years. The construction of these bridge decks is rather complex with the preflexion of precambered steel girders, the prestressing of a concrete slab and the addition of a 2nd phase concrete. Until now, they have been designed with a classical computation method using a pseudo-elastic analysis with modular ratios. Globally, they perform according to the expectations but variability has been observed between the measured and the computed camber of these bridge decks just after the transfer of prestressing and also at long-term. A statistical analysis of the variability of the relative difference between the measured camber and the computed camber is made for a sample of 36 bridge decks using no less than 10 variables. The most significant variables to explain this variability at prestressing are the ratio between the maximum tensile stress reached in the steel girders during the preflexion and the yield strength and the type of steel girder. For the same sample, the long-term camber under permanent loading is computed by two methods and compared with measurements taken one or two years after the construction. The camber computed by the step-by-step method shows a better agreement with the measured camber than the camber computed by the classical method. The purpose of the paper is to report on the statistical analysis which was used to determine the most significant parameters to consider in the modeling in order to improve the prediction of the behaviour of these composite railway bridge decks.

• Computers and Concrete
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• v.11 no.2
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• pp.123-148
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• 2013

The nonlinear finite element method with eight noded isoparametric quadrilateral element for concrete and two noded element for reinforcement is used for the prediction of the behavior of reinforcement concrete structures. The disturbed state concept (DSC) including the hierarchical single surface (HISS) plasticity model with associated flow rule with modifications is used to characterize the constitutive behavior of concrete both in compression and in tension which is named DSC/HISS-CT. The HISS model is applied to shows the plastic behavior of concrete, and DSC for microcracking, fracture and softening simulations of concrete. It should be noted that the DSC expresses the behavior of a material element as a mixture of two interacting components and can include both softening and stiffening, while the classical damage approach assumes that cracks (damage) induced in a material treated acts as a void, with no strength. The DSC/HISS-CT is a unified model with different mechanism, which expresses the observed behavior in terms of interacting behavior of components; thus the mechanism in the DSC is much different than that of the damage model, which is based on physical cracks which has no strength and interaction with the undamaged part. This is the first time the DSC/HISS-CT model, with the capacity to account for both compression and tension yields, is applied for concrete materials. The DSC model allows also for the characterization of non-associative behavior through the use of disturbance. Elastic perfectly plastic behavior is assumed for modeling of steel reinforcement. The DSC model is validated at two levels: (1) specimen and (2) practical boundary value problem. For the specimen level, the predictions are obtained by the integration of the incremental constitutive relations. The FE procedure with DSC/HISS-CT model is used to obtain predictions for practical boundary value problems. Based on the comparisons between DSC/HISS-CT predictions, test data and ANSYS software predictions, it is found that the model provides highly satisfactory predictions. The model allows computation of microcracking during deformation leading to the fracture and failure; in the model, the critical disturbance, Dc, identifies fracture and failure.

• Computers and Concrete
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• v.13 no.6
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• pp.739-748
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• 2014

In this article, by using experimental studies and artificial neural network has been tried to investigate the use of nano-silica as concrete admixture to reduce alkali-silica reaction. If there are reactive aggregates and alkali of cement with enough moisture in concrete, a gel will be formed. Then with high reactivity between alkali of cement and existence of silica in aggregates, this gel will expand by absorption of water, and causes expansive pressure and cracks be formed. At the time passes, this gel will reduce both durability and strength of the concrete. By reducing the size of silicate to nano, specific surface area of particles and number of atoms on the surface will be increased, which causes more pozzolanic activity of them. Nano-silica can react with calcium hydroxide ($Ca(OH)_2$) and produces C-S-H gel. In this study, accelerated mortar bar specimens according to ASTM C 1260 and ASTM C 1567, with different mix proportions were prepared using aggregates of Kerman, such as: none admixture and plasticizer, different proportions of nano-silica separately. By opening the moulds after 24 hour and curing in water at $80^{\circ}C$ for 24 hour, then curing in (1N NaOH) at $80^{\circ}C$ for 14 days, length expansion of mortar bars were measured and compared. It was noted that, the lowest length expansion of a specimens shows the best proportion of admixture based on alkali-silica reactivity. Then, prediction of alkali-silica reaction of concrete has been investigated by using artificial neural network. In this study the backpropagation network has been used and compared with different algorithms to train network. Finally, the best amount of nano silica for adding to mix proportion, also the best algorithm and number of neurons in hidden layer of artificial neural network have been offered.

• Magazine of the Korea Concrete Institute
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• v.9 no.2
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• pp.121-132
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• 1997

The thermal behavior of' concrete can be ch;lracterized from a knowledge of concrete ternperatu1.e at early ages, environmental conditions, and cement hydration in the mixture. 'l'o account for thost. interactions, a computer model was developed for prwlicting the temperature pr.ol'ile in hnrdcning c o n c r c t ~ st.r~icture in terms of material and tmvironmcntal factors. The cerncnt hydration cha~.acteristics such as the activating energy, total heat 1ihei.atr.d. anti th\ulcorner degree of' hydration. can represent the internal heat gc,neration. In this study. th(> activating c1ncrgy and the tlcgree of' hydration curve were determined well fmm the rnortn~. compressive strength tests while total amount of heat liberated was determined by tht> isothermal calorimctcr method. The main purpose of' this study is to correlate measured tt>mperaturr distributions in a concrete st1,ucture during thc hardening process with the ~ c s u l t s computed f'ro~n theoretical considrl.ations. Using twodimensional heat transfer model, first. the importance of several parameters will be identified by a parametric analysis. Then, the tcmpcmture distribution of thc cylindrical concrete specimen in the laboratory was mensuwti and compared with that yielded by thc theoretical considel.ations.

• Journal of Korean Society of Steel Construction
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• v.24 no.4
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• pp.361-369
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• 2012

In this study, prefabricated composite columns using high-strength angles (PSRC composite column) was studied. Concentric axial loading tests were performed for 2/3 scale PSRC specimens and an conventional SRC specimen with H-steel at the center of the cross-section. The test parameters were the steel ratio of angles and the spacing of lateral re-bars. The test results showed that by placing the angles at the corners of the cross-section for confinement with provided for the core concrete, the PSRC column specimens exhibited greater load-carrying capacity and deformation capacity than those of the conventional SRC column. The axial load-carrying capacity of the PSRC columns was greater than the prediction by KBC 2009. Using existing stress-strain relationship of confined concrete, the axial load-deformation relationship of the specimens were predicted. The numerical predictions correlated well with the test results in terms of initial stiffness, load-carrying capacity, and post-peak strength- and stiffness-degradations.

• Computers and Concrete
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• v.21 no.5
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• pp.559-567
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• 2018

In this study alkali activation of Electric Arc Furnace Slag (EAFS) is studied with a comprehensive test program. Three different silicate moduli (1-1,5-2), three different sodium concentrations (4%-6%-8%) for each silicate module, two different curing conditions (45%-98% relative humidity) for each sodium concentration, two different curing temperatures ($400^{\circ}C-800^{\circ}C$) for each relative humidity condition and two different curing time (6h-12h) for each curing temperature variables are selected and their effects on compressive strength was evaluated then regression equations using multiple linear regressions methods are fitted. And then to select the best regression models confirm with using the variables, the regression models compared between itself. An Artificial Neural Network (ANN) models that use silicate moduli, sodium concentration, relative humidity, curing temperature and curing time variables, are formed. After the investigation of these ANN models' results, ANN and multiple linear regressions based models are compared with each other. After that, an explicit formula is developed with values of the ANN model. As a result of this study, the fluctuations of data set of the compressive strength were very well reflected using both of the methods, multiple linear regression with quadratic terms and ANN.

• Computers and Concrete
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• v.12 no.6
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• pp.785-802
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• 2013

Ready-mixed soil material, known as a kind of controlled low-strength material, is a new way of soil cement combination. It can be used as backfill materials. In this paper, artificial neural network and nonlinear regression approach were applied to predict the compressive strength of ready-mixed soil material containing Portland cement, slag, sand, and soil in mixture. The data used for analyzing were obtained from our testing program. In the experiment, we carried out a mix design with three proportions of sand to soil (e.g., 6:4, 5:5, and 4:6). In addition, blast furnace slag partially replaced cement to improve workability, whereas the water-to-binder ratio was fixed. Testing was conducted on samples to estimate its engineering properties as per ASTM such as flowability, strength, and pulse velocity. Based on testing data, the empirical pulse velocity-strength correlation was established by regression method. Next, three topologies of neural network were developed to predict the strength, namely ANN-I, ANN-II, and ANN-III. The first two models are back-propagation feed-forward networks, and the other one is radial basis neural network. The results show that the compressive strength of ready-mixed soil material can be well-predicted from neural networks. Among all currently proposed neural network models, the ANN-I gives the best prediction because it is closest to the actual strength. Moreover, considering combination of pulse velocity and other factors, viz. curing time, and material contents in mixture, the proposed neural networks offer better evaluation than interpolated from pulse velocity only.

• Journal of Korean Society of Steel Construction
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• v.22 no.4
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• pp.389-398
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• 2010

The flexural strength of composite HSB I-girders under a positive moment was investigated using the moment-curvature analysis method to evaluate the applicability of the current AASHTO LRFD design specifications to such girders. A total of 2,391 composite I-girder sections that satisfied the section proportion limits of the AASHTO LRFD specifications was generated by the random sampling technique to consider a wide range of section properties. The flexural capacities of the sections were calculated inthe nonlinear moment-curvature analysis in which the HSB600 and HSB800 steels were modeled as an elasto-plastic strain-hardening material, and the concrete, as a CEB-FIP model. The effects of the ductility ratio and the compressive strength of the concrete slab on the flexural strength of the composite girders made of HSB and SM520-TMC steels were analyzed. The numerical results indicated that the current AASHTO LRFD equation can be used to calculate the flexural strength of composite girders made of HSB600 steel. In contrast, the current AASHTO LRFD equation was found to be non-conservative in its prediction of the flexural strength of composite HSB800 girders. Based on the numerical results of this study for 2,391 girders, a new design equation for the flexural strength of composite HSB800 girders in a positive moment was proposed.

• Journal of the Korea Concrete Institute
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• v.20 no.4
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• pp.523-530
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• 2008

In structural design provision, maximum punching shear stress of slabs is prescribed as combined stress in direct shear occurred by gravity load and eccentric shear occurred by unbalanced moment. This means that the effect of unbalanced moment is considered to decide the punching shear stress. However, from the resistance capacity standpoint, the effect of unbalanced moment strength is not considered for deciding punching shear strength. In this paper, a model considering interrelation between unbalanced moment and punching shear was proposed. In the model, the relation between load effect and resistance capacity in unbalanced moment and punching shear was two-dimensionally expressed. Using the interrelation model, a method how unbalanced moment strength should be considered to decide the punching shear strength was proposed. Additionally, effective width enlargement factors for deciding the unbalanced moment strength of flat plates with shear reinforcements were proposed. The interrelation model proposed in this paper is very effective for the prediction of the behavior of slab-column connection because not only punching shear and unbalanced moment strengths but also failure modes of flat plates can be accurately predicted.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.5
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• pp.251-258
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• 2018

In construction site, conventional methods such as jackhammer or explosive methods(dynamite) have been often used for the demolition of structures. Use of those methods are more carefully treated in environmentally and historically sensitive area. For those reasons, use of Soundless Chemical Demolition Agent(SCDA) is getting the spotlight. The SCDA is a powder which has expansive strength when it is mixed with water. In these Characteristics, SCDA can destroy the concrete or rock as it is poured into boreholes of the concrete or rock structures. However, there is no industrial standard for the use of SCDA effectively yet. In this study, experimental study to measure the expansive pressure was conducted depending on various boundary conditions such as waterproof, length of the steel pipe, submerged of steel pipe. Furthermore, computational analysis using damage plasticity model to predict the minimum required pressure of the SCDA for the concrete demolition depending on spacing between holes(k-factor) and compressive strength of the concrete was conducted. Obtained results indicates that water heat dissipation with submerged steel pipe shows the stable pressure for measuring the SCDA and hole distance(k-factor) is the most important factor for crack initiation of concrete.