• Journal of the Korea Institute of Building Construction
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• v.19 no.1
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• pp.9-18
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• 2019

Concrete, which is the most widely used building material in modern times, has been improved not only in strength but also in structural performance such as increase in toughness and ductility, weight reduction, and improvement in quality of human life. Due to the surge in demand for the building, there is a tendency to be used variously from architectural panel and architecture to interior accessories. In Korea, a light-transmitting concrete, LEFC(Light Emotion Friendly Concrete), that insert plastic rods to stimulate emotional sensation through the combination of light and concrete has developed. In previous research, it was confirmed that the use of a synthetic foam agent rather than an animal foam agent did not cause a fogging phenomenon. In this study, lightweight by applying foaming agent to LEFC and two types of fiber (Nylon Fiber, Polyvinyl Alcohol) were compared to achieve to investigate the fiber to be applied in future. An equation that can predict the loss and adhesion reduction of the concrete section according to the diameter of the rod (5mm, 10mm) and the interval (10mm, 15mm, 20mm) was proposed.

• Journal of the Korea Concrete Institute
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• v.28 no.6
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• pp.665-672
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• 2016

This study is conducted to investigate the effect of phase change materials (PCM) on hydration heat and strength characteristics of cement mortar. Two types of Barium and Strontium-based PCMs were used in this study and the addition ratio of each PCM to the cement mortar ranged from 1% to 5% by cement weight. Flow test, semi-adiabatic temperature rise test, compressive strength and flexural strength test were carried out to examine the PCM effect on heat and mechanical properties of cement mortar. Test results indicated that PCMs used in this study were effective to control hydration heat of cement mortar, and Barium-based PCM slightly reduce flow value. The compressive and flexural strength of cement mortar with PCM decreased with increasing the adding mount of PCM. The prediction model for compressive strength of cement mortar with different addition levels of PCMs are suggested in this study.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.18-24
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• 2015

Non-destructive testing (NDT) methods are widely used in the construction industry to diagnose the defects/strength of the concrete structure. However, it has been reported that the results obtained from NDT are having low reliability. In order to resolve this issue, four kinds of NDT test (ultrasonic velocity measurements by P-wave and S-wave and the impact resonance methods by longitudinal vibration and deformation vibration) were carried out on 180 concrete cylinders made with two kinds of mix proportions. The reliability of the NDT results was analyzed and compared through the measurement of the actual compressive strength of the concrete cylinders. The statistical analysis of the results was revealed that the ultrasonic velocity method by S-wave is having lowest coefficient of variation and also most capable of stable observation. Analytical equations were established to estimate the compressive strength of the concrete from the obtained NDT results by relating the actual compressive strength. Moreover the equation established by the ultrasonic velocity method by S-wave had the highest coefficient of determination. Further studies on the stability of non-destructive testing depending on various mixing conditions will be necessary in the future.

• Steel and Composite Structures
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• v.17 no.5
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• pp.623-639
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• 2014

Due to recent advancements in the area of Artificial Intelligence (AI) and computational intelligence, the application of these technologies in the construction industry and structural analysis has been made feasible. With the use of the Adaptive-Network-based Fuzzy Inference System (ANFIS) as a modelling tool, this study aims at predicting the shear strength of channel shear connectors in steel concrete composite beam. A total of 1200 experimental data was collected, with the input data being achieved based on the results of the push-out test and the output data being the corresponding shear strength which were recorded at all loading stages. The results derived from the use of ANFIS and the classical linear regressions (LR) were then compared. The outcome shows that the use of ANFIS produces highly accurate, precise and satisfactory results as opposed to the LR.

• 한국도로학회:학술대회논문집
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• 2010.09a
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• pp.99-107
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• 2010

A permanent deformation model was developed in this study based on the shear properties of asphalt mixtures such as cohesion and friction angle. Triaxial compressive strength (TCS) and repeated load permanent deformation (RLPD) tests on the three types of asphalt mixtures are performed at various loading and temperature conditions to correlate shear properties of asphalt mixtures to rutting performance. It is observed from the tests results that the ratio of shear stress to strength accurately identifies the mixture rutting performance. It could take care of not only mixture types but also load and temperature conditions dependences. Three different versions of the permanent deformation model based on different input levels are proposed and verified using the tests data. The proposed model based on the ratio of shear stress to strength can successfully predict the permanent deformation of various asphalt mixtures all the way up to the 10% of permanent strain including all three stages of permanent deformation in a wide range of loading and temperature conditions without changing model coefficients.

• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.501-520
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• 2015

Presence of torsional loadings can significantly affect the flow of internal forces and deformation capacity of reinforced concrete (RC) columns. It increases the possibility of brittle shear failure leading to catastrophic collapse of structural members. This necessitates accurate prediction of the torsional behaviour of RC members for their safe design. However, a review of previously published studies indicates that the torsional behaviour of RC members has not been studied in as much depth as the behaviour under flexure and shear in spite of its frequent occurrence in bridge columns. Very few analytical models are available to predict the response of RC members under torsional loads. Softened truss model (STM) developed in the University of Houston is one of them, which is widely used for this purpose. The present study shows that STM prediction is not sufficiently accurate particularly in the post cracking region when compared to test results. An improved analytical model for RC square columns subjected to torsion with and without axial compression is developed. Since concrete is weak in tension, its contribution to torsional capacity of RC members was neglected in the original STM. The present investigation revealed that, disregard to tensile strength of concrete is the main reason behind the discrepancies in the STM predictions. The existing STM is extended in this paper to include the effect of tension stiffening for better prediction of behaviour of square RC columns under torsion. Three different tension stiffening models comprising a linear, a quadratic and an exponential relationship have been considered in this study. The predictions of these models are validated through comparison with test data on local and global behaviour. It was observed that tension stiffening has significant influence on torsional behaviour of square RC members. The exponential and parabolic tension stiffening models were found to yield the most accurate predictions.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05b
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• pp.51-52
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• 2010

In this study, it is confirmed that the use of equivalent age method can be applied to predict the early-age strength in case of using the new early strength concrete developed for the reduction of construction work period by our company, in apartment.

• Computers and Concrete
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• v.29 no.3
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• pp.187-199
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• 2022

The usability of waste materials as raw materials is necessary for sustainable production. This study investigates the effects of different powder materials used to replace cement (0%, 5% and 10%) and standard sand (0%, 20% and 30%) (basalt, limestone, and dolomite) on the compressive strength (f_c), flexural strength (f_r), and ultrasonic pulse velocity (UPV) of mortars exposed to freeze-thaw cycles (56, 86, 126, 186 and 226 cycles). Furthermore, the usability of artificial intelligence models is compared, and the prediction accuracy of the outputs is examined according to the inputs (powder type, replacement ratio, and the number of cycles). The results show that the variability of the outputs was significantly high under the freeze-thaw effect in mortars produced with waste powder instead of those produced with cement and with standard sand. The highest prediction accuracy for all outputs was obtained using the adaptive-network-based fuzzy inference system model. The significantly high prediction accuracy was obtained for the UPV, f_c, and f_r of mortars produced using waste powders instead of standard sand (R² of UPV, f_c and f_f is 0.931, 0.759 and 0.825 respectively), when under the freeze-thaw effect. However, for the mortars produced using waste powders instead of cement, the prediction accuracy of UPV was significantly high (R²=0.889) but the prediction accuracy of f_c and f_r was low (R²f_c=0.612 and R²f_f=0.334).

• Smart Structures and Systems
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• v.26 no.4
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• pp.403-418
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• 2020

In recent years, the use of Fiber Reinforced Polymers (FRPs) as one of the most common ways to increase the strength of concrete samples, has been introduced. Evaluation of the final strength of these specimens is performed with different experimental methods. In this research, due to the variety of models, the low accuracy and impact of different parameters, the use of new intelligence methods is considered. Therefore, using artificial intelligent-based models, a new solution for evaluating the bond strength of FRP is presented in this paper. 150 experimental samples were collected from previous studies, and then two new hybrid models of Imperialist Competitive Algorithm (ICA)-Artificial Neural Network (ANN) and Artificial Bee Colony (ABC)-ANN were developed. These models were evaluated using different performance indices and then, a comparison was made between the developed models. The results showed that the ICA-ANN model's ability to predict the bond strength of FRP is higher than the ABC-ANN model. Finally, to demonstrate the capabilities of this new model, a comparison was made between the five experimental models and the results were presented for all data. This comparison showed that the new model could offer better performance. It is concluded that the proposed hybrid models can be utilized in the field of this study as a suitable substitute for empirical models.

• Steel and Composite Structures
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• v.33 no.4
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• pp.583-594
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• 2019

In the areas highly exposed to earthquakes, concrete-filled steel tube columns (CFSTCs) are known to provide superior structural aspects such as (i) high strength for good seismic performance (ii) high ductility (iii) enhanced energy absorption (iv) confining pressure to concrete, (v) high section modulus, etc. Numerous studies were reported on behavior of CFSTCs under axial compression loadings. This paper presents an analytical model to predict ultimate load capacity of CFSTCs with circular sections under axial load by using multivariate adaptive regression splines (MARS). MARS is a nonlinear and non-parametric regression methodology. After careful study of literature, 150 comprehensive experimental data presented in the previous studies were examined to prepare a data set and the dependent variables such as geometrical and mechanical properties of circular CFST system have been identified. Basically, MARS model establishes a relation between predictors and dependent variables. Separate regression lines can be formed through the concept of divide and conquers strategy. About 70% of the consolidated data has been used for development of model and the rest of the data has been used for validation of the model. Proper care has been taken such that the input data consists of all ranges of variables. From the studies, it is noted that the predicted ultimate axial load capacity of CFSTCs is found to match with the corresponding experimental observations of literature.