• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.494-497
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• 2004

This paper presents the analysis results predicted by the upper bound approach in the limit analysis of concrete incorporating the original plastic and crack sliding solutions for short high-strength concrete beams that varied the compressive strength of concrete, and the shear span-to-depth and vertical shear reinforcement ratios. The significance of the distance away from the support to define the location where the yield line starts and the properties of cracked concrete, particularly related to high-strength concrete, is identified.

• Earthquakes and Structures
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• v.8 no.5
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• pp.1171-1190
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• 2015

Enhancement of strength and ductility is the main reason for the extensive use of FRP jackets to provide external confinement to reinforced concrete columns especially in seismic areas. Therefore, numerous researches have been carried out in order to provide a better description of the behavior of FRP-confined concrete for practical design purposes. This study presents a new approach to obtain strength enhancement of CFRP (carbon fiber reinforced polymer) confined concrete cylinders by applying artificial neural networks (ANNs). The proposed ANN model is based on experimental results collected from literature. It represents the ultimate strength of concrete cylinders after CFRP confinement which is also given in explicit form in terms of geometrical and mechanical parameters. The accuracy of the proposed ANN model is quite satisfactory when compared to experimental results. Moreover, the results of the proposed ANN model are compared with five important theoretical models proposed by researchers so far and considered to be in good agreement.

• KCI Concrete Journal
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• v.14 no.2
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• pp.81-85
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• 2002

The strength development of concrete is influenced by temperature and cement type which greatly affect hydration degree of cement. There is not pertinent concrete strength management method in korea. There are several methods for estimating the in-place strength of concrete. One such method is the maturity concept. The maturity concept is based on the fact that concrete gains strength gradually as a result of chemical reactions between cement and water; and for a specific concrete mixture, strength at any age and at normal conditions is related to the degree of hydration. The rate of hydration and, therefore, strength development of a given concrete will be a function of its temperature. Thus, strength of concrete depends on its time-temperature history. The goals of the present study are to investigate a relationship between strength of high-strength concrete and maturity that is expressed as a function of an integral of the curing period and temperature and predict strength of concrete.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2005.05a
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• pp.119-124
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• 2005

It is necessary for prediction of recycled aggregate concrete(RAC) strength at the early stage that facilitate concrete form removal and scheduling for construction. However, to predict RAC strength is difficult because of being influenced by complicated many factors. Therefore, this research suggest optimized estimation method that can reflect many factors. One way is Case-Based Reasoning(CBR) that solved new problems by adapting solutions to similar problems solved in the past, which are solved in the case library. Other way is Artificial Neural Networks(ANN) that solved new problems by training using a set of data, which is representative of problem domain. This study is to propose comparing accuracy of the estimating the compressive strength of recycled aggregate concrete using Case-Based Reasoning(CBR) and Artificial Neural Networks(ANN).

• Computers and Concrete
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• v.5 no.5
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• pp.461-473
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• 2008

The paper explores the potential of Support Vector Machines (SVM) approach in predicting 28-day compressive strength and slump flow of self-compacting concrete. Total of 80 data collected from the exiting literature were used in present work. To compare the performance of the technique, prediction was also done using a back propagation neural network model. For this data-set, RBF kernel worked well in comparison to polynomial kernel based support vector machines and provide a root mean square error of 4.688 (MPa) (correlation coefficient=0.942) for 28-day compressive strength prediction and a root mean square error of 7.825 cm (correlation coefficient=0.931) for slump flow. Results obtained for RMSE and correlation coefficient suggested a comparable performance by Support Vector Machine approach to neural network approach for both 28-day compressive strength and slump flow prediction.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.23-24
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• 2020

In this study, the concrete compressive strength estimation system Concrete IoT Management System (hereinafter referred to as CIMS) was developed, and CIMS was applied to domestic field structure slabs and wall concrete to check whether CIMS is practically available and to estimate the accuracy of the initial strength estimation of concrete. As a result, it shows a very high correlation when the compressive strength of the specimen for structural management is compared with the estimated strength of CIMS in terms of integrated temperature, and it is expected to be gradually applied to domestic construction sites in the future.

• Journal of the Korea Institute of Building Construction
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• v.8 no.5
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• pp.119-125
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• 2008

In this paper, the estimation of super retarding concrete incorporating mineral admixtures at the same time including fly ash(FA), blast furnace slag(BS) are studied based on maturity method. The setting time was retarded, as super retarding agent contents increase and curing temperature decreases. In addition, apparent activation energy by Arrhenius function was ranged from $24\sim35$ KJ/mol with slightly difference along with mixture proportion. This value is smaller than existing value $30\sim50$ KJ/mol. Based on strength development estimation. it exhibited comparable relativity between prediction value and measurement value. Therefore, this study provided effective strength development prediction value with super retarding agent contents and mineral admixture combination. Strength development prediction equation provided herein is possibly valid for estimating accurate strength development of the super retarding concrete at the job site.

• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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• pp.177-182
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• 2002

The purpose of this study is to develope the strength prediction model by Maturity Method. A maturity function is a mathematical expression to account for the combined effects of time and temperature on the strength development of a cementious mixture. The method of equivalent ages is to use Arrhenius equation which indicates the influence of curing temperature on the initial hydration ratio of cement. For the experimental factors of this study, we selected the concrete mixing of W/C ratio 45, 50, 55 and 60% and curing temperature 5, 10, 20 and $30^{\circ}C$. And we compare and evaluate with logistic model that is existing strength prediction model, because we have to verify adaption possibility of new strength prediction model which is proposed by maturity method. As the results, it is found that investigation of the activation energy that are used to calculate equivalent age is necessary, and new strength prediction model was proved to be more accurate in the strength prediction than logistic model in the early age. Moreover, the use of new model was more reasonable because it has low SSE and high decisive factor.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.2
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• pp.137-146
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• 2001

The non-destructive tests are widely used to predict the strength of existing structures. The purpose of the present study is to propose the prediction equations for strength evaluation of concrete structures. The present study focuses on the rebound method and ultrasonic pulse velocity method for quartzite aggregate concrete. The major test variables include the water-cement ratio and curing methods. The water-cement ratio are 0.4, 0.5, 0.6, 0.7, respectively and the curing method covers ail-dry condition and standard curing condition. The prediction equations for strength of concrete are proposed from the present test data.

• Advances in concrete construction
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• v.16 no.6
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• pp.317-325
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• 2023

Strength prediction and correlation of concrete is done using experimental and analytical methods. Main objective is to correlate the experimental and simulated values of compressive strength of concrete mix using Fly Ash (FA) and Silica Fume (SF) by partial replacement of cement in concrete. Mix proportion was determined using IS method for M40grade concrete. Hundred and forty-seven cubes were cast and tested using Universal Testing Machine (UTM). Genetic Algorithm (GA) model was developed using C++ program to simulate the compressive strength of concrete for various proportions of FA and SF replacements individually at 3% increments. Experiments reveal that 12 percent silica fume replacement produced maximum compressive strength of 35.5 N/mm², 44.5 N/mm² and 54.8 N/mm² moreover 9 percent fly ash replacement produced a maximum strength of 31.9 N/mm², 37.6 N/mm² and 51.8 N/mm² during individual material replacement of concrete mix. Correlation coefficient for each curing period of fly ash and silica fume replaced mix were acquired using trend lines. The correlation coefficient is found to be approximately 0.9 in FA and SF replaced mix irrespective of the mix proportion and age of concrete. A higher and positive correlation was found between the experimental and simulated values irrespective of the curing period in all the replacements.