• Journal of the Korea Concrete Institute
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• v.14 no.1
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• pp.1-7
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• 2002

The purpose of this research is to obtain a practical expression for the estimation of compressive strength of concrete using non-destructive testing method such as rebound Schmidt hammer and ultrasonic pulse

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.655-661
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• 2020

In this study, the correlation between concrete core compressive strength and rebound hardness of urban railway underground structures was analyzed. The equations for the range of rebound hardness were derived and compared with the measured concrete core strengths for each range of rebound hardness to confirm the adequacy of the estimated compressive strength. As the result, the linear regression analysis results of the average compressive strength by the Gaussian probability density function (representative compressive strength estimation formula) and the estimation formula by the rebound hardness range were founded to match well within 3% of the experimental concrete core compressive strength test results. Therefore, the stochastic statistical analysis using the rebound hardness measurement results suggested in this study could be help to secure the confidence level of the correlation between the rebound hardness and the concrete compressive strength which are relatively large deviation according to the estimation equations.

• Magazine of the Korea Concrete Institute
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• v.10 no.1
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• pp.119-124
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• 1998

콘크리트는 시멘트, 잔골재 및 굵은 골재, 물 및 첨가제의 양이나 투입순서 ,혼합방법등 여러 가지 요인에 따라 성질이 바뀌게 되는 복합재료이다. 따라서 넓은 의미에서 품질 판정의 한 수단이 되는 콘크리트의 설계기준강도 또는 압축강도 fc'(=28일 압축강도)는 물론 기타의 성질도 정확한 예측이 불가능하다. 즉 소요강도를 목표로 배합된 공시체의 시험결과는 예외없이 통계적 가변성을 나타낸다. 여기에서는 공시체의 7일 강도의 평균치 및 표준 편차와 공시체의 28일 강도 측정치로부터 콘크리트의 압축강도를 추정하는식을 제안하였다. 이를 위하여 7,320개의 강도시험자료를 수집한 후 이들을 선형 회귀 분석법으로 처리하였다. 제안된 식에 의한 콘크리트의 압축강도는 타 추정식에 의한 값보다 실측치에 좀 더 근접함을 보여주었다. 또한 제안식의 검정을 위해 서울지역 자료 5,200개를 수집하여 제안식과 JIS, Slater식과의 오차를 비교한 결과에 따르면 제안식이 더 안전측임을 알 수 있었다. 그리고 슈미트 햄머에 의한 현장 실측 강도와 제안식과의 콘크리트 강도 오차는 대체로 2.3%이었다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.2
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• pp.159-167
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• 2004

The compressive strength of concrete is a criterion to produce concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, strength prediction before the placement of concrete is highly desirable. This study presents the probabilistic technique for predicting the compressive strength of concrete on the basis of concrete mix proportions. The estimation of the strength is based on the probabilistic neural network which is an effective tool for pattern classification problem and gives a probabilistic result, not a deterministic value. In this study, verifications for the applicability of the probabilistic neural networks were performed using the test results of concrete compressive strength. The estimated strengths are also compared with the results of the actual compression tests. It has been found that the present methods are very efficient and reasonable in predicting the compressive strength of concrete probabilistically.

• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.313-322
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• 2005

Recently, as the remodeling market gradually substitute for new construction market and safety diagnosis for reconstruction apartment become a matter of principal Interest, it is demanded that scientific diagnosis and evaluation for existing concrete structure state. And it is increasing that the significance for reliability of data which is used for estimating the concrete compressive strength by nondestructive test. As a result, it is found that different proposal to material age and hitting angle is good to improving the reliability of presumption of concrete compressive strength in the linear hitting rebound test hammer. And for the reason that mutual relation between the compressive strength and rebound degree is highest in linear hitting rebound test hammer 25mm in all portion according to early md middle material age and hitting angle except the early material age $-45^{\circ}$, analysis showed that linear hitting rebound test hammer is more reliable than existing schmidt hammer in presumption of concrete compressive strength.

• Magazine of the Korea Concrete Institute
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• v.11 no.2
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• pp.241-249
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• 1999

To estimate the compressive strength of concrete more realistically, relative large number of data are necessary. However, it is very common in practice that only limited data are available. The purpose of the present paper is therefore to propose a realistic method to estimate the compressive strength of concrete with limited data in actual site. The Bayesian method of statistical analysis has been applied to the problem of the estimation of compressive strength of concrete. The mean compressive strength is considered as the random parameter and a prior distribution is selected to enable updating of the Bayesian distribution of compressive strength of concrete reflecting both existing data and sampling observations. The updating of the Bayesian distribution with increasing data is illustrated in numerical application. It is shown that by combining prior estimation with information from site observation, more precise estimation is possible with relatively small sampling. It is also seen that the contribution of the prior in determining the posterior distribution depends on its sharpness or flatness in relation to the sharpness or flatness of the likelihood function. The present paper allows more realistic determination of concrete strength in site with limited data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.25-34
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• 2015

Proposed equation is used many time in calculation of concrete compressive strength using the non-destructive testing at precision safety diagnosis. Most of proposed equation is suggested in abroad and have an error to estimate concrete compressive strength in the domestic. Therefor, proposed equation is low reliability to estimate concrete compressive and it has a significant effect in reliability of precision safety diagnosis. Nevertheless, It is possible to increase the reliability through a number of experiments from this problem that occurs in some localized part. This paper is proposed assessment formula of reliability related core compressive strength to increase the reliability. It is verified that reliability of proposed assessment formula is useful by probabilistic techniques. It is compared with each graphs of concrete compressive strength of proposed equation. It has been found that the present methods are very efficient.

• Journal of the Korea Institute of Building Construction
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• v.16 no.3
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• pp.229-235
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• 2016

In construction field, it used various technique for concrete formwork. Part of them, non-destructive test has been conducted to estimate a compressive strength of concrete easily such as rebound method and ultrasonic pulse velocity method etc. Former research has recommend proposed equation based on experimental data to investigate strength of concrete but it was sometimes deferent actual value of that from in field because of the few of data in case of early strength concrete. In this study, an experiment was conducted to analyze strength properties for early strength concrete using cylinder mold and $1,000mm{\times}1,000mm{\times}200mm$ rectangular specimen. And compressive strength of concrete was tested by non-destructive test, and calculated by the equation proposed former research. As a result, the non-destructive test results showed approximately 70 percent of the failure test value for all conditions, and worse reliability was obtained for high strength concrete samples when the ultrasonic pulse velocity method was used. Based on the scope of this study, the experimental equation for estimating compressive strength of early strength concrete from 24MPa to 60MPa was proposed.

• Journal of the Korean Geotechnical Society
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• v.38 no.10
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• pp.5-15
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• 2022

In this study, to propose simplified methods for estimating the cohesion and internal friction angle of volcanic rocks in Jeju Island using uniaxial compressive strength and/or Brazilian tensile strength, the estimated values of cohesion and internal friction angle from triaxial and uniaxial compression tests and Brazilian tests were compared in terms of estimation accuracy. This study proposed simplified methods for estimating the cohesion and internal friction angle using the uniaxial compressive strength and/or Brazilian tensile strength of volcanic rocks in Jeju Island. According to the findings, among the proposed simplified methods, the method using uniaxil compressive strength was most desirable to accurately estimate the cohesion and internal friction angle of volcanic intact rocks in Jeju Island.

• Journal of the Korea Concrete Institute
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• v.27 no.4
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• pp.331-341
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• 2015

The main purpose of this study is reducing the cost and effort for characterization of tensile strength of fiber reinforced concrete, in order to use in structural design. For this purpose, in this study, test for fiber reinforced concrete was carried out. Because fiber reinforced concrete is consisted of diverse material, it is hard to define the correlation between mix proportions and strength. Therefore, compressive strength test and tensile strength test were carried out for the range of smaller than 100 MPa of compressive strength and 0.25~1% of steel fiber volume fraction. as a results of test, two types of tensile strength were highly affected by compressive strength of concrete. However, increase rate of tensile strength was decreased with increase of compressive strength. Increase rate of tensile strength was decreased with increase of fiber volume fraction. Database was constructed using previous research data. Because estimation equations for tensile strength of fiber reinforced concrete should be multiple variable function, linear regression is hard to apply. Therefore, in this study, we decided to use the ANN(Artificial Neural Network). ANN was constructed using multiple layer perceptron architecture. Sigmoid function was used as transfer function and back propagation training method was used. As a results of prediction using artificial neural network, predicted values of test data and previous research which was randomly selected were well agreed with each other. And the main effective parameters are water-cement ratio and fiber volume fraction.