• Journal of Industrial Technology
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• v.33 no.A
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• pp.109-116
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• 2013

In this study the compressive strength data were collected from ready­mix concrete plants, and the analysis result showed that when using A­D test the concrete of 24MPa is suitable than that of 21MPa for normal distribution. The prediction formula for average compressive strength were proposed to $f_{cu}=f_{ck}+4(MPa)$. When comparing the proposed equations and existing relationship, the estimation variations of elastic modulus and creep modulus were not significant. The proposed equation confirmed that there was no effect to the influence function for modulus of elasticity and creep. Therefore, it was concluded that the proposed equation could replace the exiting interaction formula.

• Proceedings of the Korea Concrete Institute Conference
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• 2010.05a
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• pp.221-222
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• 2010

In this study an expression is obtained the model equation for the prediction of carbonation based on the time and interaction velocity between $CO_2$ and $Ca(OH)_2$ diffusion coefficient.

• Journal of Korean Society of Steel Construction
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• v.14 no.4
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• pp.549-556
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• 2002

The natural frequency of a system is commonly used in evaluating the serviceability condition of a floor. However. the current equations recommended in many building codes do not consider the various material types of a slab system; thus. different results are observed. Likewise. the transformation of a slab section required to predict the natural frequency of a composite deck plate is complicated. due to the varying shapes of the deck plates. Therefore. a new and simplified method of transforming a composite slab into an equivalent concrete slab is proposed. he modified vibration prediction equation was proposed based on the current vibration prediction equation recommended by LRFD. Compared to other equations. it is the closest to those obtained from experiments. The modified equation provides about 14.3% more accurate results than that recommended by LRFD. Likewise. the applicability of the proposed equation to other types of composite deck plate floor system was validated.

• Journal of the Korea Concrete Institute
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• v.27 no.2
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• pp.169-176
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• 2015

Since the size effect law announced currently has been based on the normal weight concrete, for light weight concrete having different fracture characteristics, its application is questionable. Accordingly, in this study, a model equation to predict the effect of dried unit weight of the concrete on size effect of its compressive strength was developed and a database using existing research results was created. After determining the experimental constants of prediction models of Ba${\check{z}}$ant based on nonlinear fracture mechanics, Kim and Eo, and this study using the database, their results are mutually compared. Finally, it was found that the prediction model of this study considered dried unit weight of concrete predicted well the test results for light weight concrete than that of the models of Ba${\check{z}}$ant and Kim and Eo.

• Computers and Concrete
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• v.31 no.2
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• pp.111-121
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• 2023

The influence of material composition such as aggregate types, addition of supplementary cementitious materials as well as exposed temperature levels have significant impacts on concrete residual mechanical strength properties when exposed to elevated temperature. This study is based on data obtained from literature for fly ash blended concrete produced with natural and recycled concrete aggregates to efficiently develop prediction models for estimating its residual compressive strength after exposure to high temperatures. To achieve this, an extensive database that contains different mix proportions of fly ash blended concrete was gathered from published articles. The specific design variables considered were percentage replacement level of Recycled Concrete Aggregate (RCA) in the mix, fly ash content (FA), Water to Binder Ratio (W/B), and exposed Temperature level. Thereafter, a simplified mathematical equation for the prediction of concrete's residual compressive strength using Gene Expression Programming (GEP) was developed. The relative importance of each variable on the model outputs was also determined through global sensitivity analysis. The GEP model performance was validated using different statistical fitness formulas including R², MSE, RMSE, RAE, and MAE in which high R² values above 0.9 are obtained in both the training and validation phase. The low measured errors (e.g., mean square error and mean absolute error are in the range of 0.0160 - 0.0327 and 0.0912 - 0.1281 MPa, respectively) in the developed model also indicate high efficiency and accuracy of the model in predicting the residual compressive strength of fly ash blended concrete exposed to elevated temperatures.

• Journal of the Korea Concrete Institute
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• v.19 no.1
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• pp.75-81
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• 2007

Percentage that aggregate of materials that concrete composed about $70{\sim}80%$ of whole volume, therefore influence that quality of aggregate gets in concrete characteristics are very important. Schmidt hammer and ultra-sonic velocity method are commonly used for crushed sand concrete compressive strength test in a construction field. At present, various equations for prediction of strength are present, which have been used in a construction field. The purpose of this study is to evaluate the correlation between prediction strength by present equations and destructive strength to test specimen, and find out which is a suitable equation for the construction site, a strength test was carried out destructive test by means of core sampling and traditional test. The experimental parameters were concrete age, curing condition, and strength level. It is demonstrated that the correlation behavior of crushed sand concrete strength in this study good due to the perform analysis of correlation between core, destructive strength and non-destructive strength.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.83-95
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• 2017

PURPOSES : The purpose of this study is to develop a regression model to predict the International Roughness Index(IRI) and Surface Distress(SD) for the estimation of HPCI using Expressway Pavement Management System(PMS). METHODS : To develop an HPCI prediction model, prediction models of IRI and SD were developed in advance. The independent variables considered in the models were pavement age, Annual Average Daily Traffic Volume(AADT), the amount of deicing salt used, the severity of Alkali Silica Reaction(ASR), average temperature, annual temperature difference, number of days of precipitation, number of days of snowfall, number of days below zero temperature, and so on. RESULTS : The present IRI, age, AADT, annual temperature differential, number of days of precipitation and ASR severity were chosen as independent variables for the IRI prediction model. In addition, the present IRI, present SD, amount of deicing chemical used, and annual temperature differential were chosen as independent variables for the SD prediction model. CONCLUSIONS : The models for predicting IRI and SD were developed. The predicted HPCI can be calculated from the HPCI equation using the predicted IRI and SD.

• Computers and Concrete
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• v.23 no.4
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• pp.255-265
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• 2019

The potential of using genetic programming to predict engineering data has caught the attention of researchers in recent years. The present paper utilized weighted genetic programming (WGP), a derivative model of genetic programming (GP), to model the compressive strength of concrete. The calculation results of Abrams' laws, which are used as the design codes for calculating the compressive strength of concrete, were treated as the inputs for the genetic programming model. Therefore, knowledge of the Abrams' laws, which is not a factor of influence on common data-based learning approaches, was considered to be a potential factor affecting genetic programming models. Significant outcomes of this work include: 1) the employed design codes positively affected the prediction accuracy of modeling the compressive strength of concrete; 2) a new equation was suggested to replace the design code for predicting concrete strength; and 3) common data-based learning approaches were evolved into knowledge-based learning approaches using historical data and design codes.

• Steel and Composite Structures
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• v.47 no.6
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• pp.729-741
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• 2023

As the most popular shear connection in composite structures, mature concrete has been widely investigated by considering mechanical properties of stud connectors (SCs) embedded. To further enhance the fabrication efficiency of composite structures and solve the contradiction between construction progress and structural performance, it is required to analyze the shear performance of stud connections of composite structures with different concrete ages. 18 typical vertical push-out tests were carried out on stud shear connectors at concrete ages of 7 days, 14 days, and 28 days. Also, the effects of concrete age, stud spacing and stud diameter on the shear capacity, connection stiffness and failure mode of the connectors were studied. A new relationship expression of load-slip for SCs with various concrete ages was proposed. The existing design code for the SCs shear strength was evaluated according to the experimental data, and a more practical prediction equation for the shear capacity of SCs with different concrete ages was established. A great agreement was observed between the experimental and theoretical results, which can provide a reference for engineering practices.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.369-374
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• 1999

A practical approach of calculating the ultimate strength of composite beams with unreinforced web opening is proposed. In this method, the slab shear contribution at the opening is calculated as the smaller of the shear strength of the slab and the pullout capacity of the shear connectors at the high moment end. A simple interaction equation is used to predict the ultimate strength under simultaneous bending moment and shear force. Strength prediction by the proposed method is compared with previous test results and the predictions by other analytical method. The comparison shows that the proposed method predicts the ultimate capacity with resonable accuracy.