• Title/Summary/Keyword: estimation of compressive strength

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A Study on the Application of Non-Destructive Testing Equation for the Estimation of Compressive Strength of High Strength Concrete (고강도콘크리트의 압축강도 추정을 위한 비파괴시험식의 적용성에 관한 연구)

  • Kim, Moo-Han;Choi, Se-Jin;Kang, Suk-Pyo;Kim, Jae-Hwan;Jang, Jong-Ho
    • Journal of the Korea Institute of Building Construction
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    • v.2 no.3
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    • pp.123-130
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    • 2002
  • Recently, it is being studied on the high strength concrete in many laboratories and being applied to the construction field actually. But non-destruction testing equation that to be proposed about normal strength concrete in Japan has been using because the systematic study results for the estimation of compressive strength of high strength concrete do nit exist. So it is essential to suggest the non-destruction testing equation for the estimation of compressive strength of high strength concrete. This is an experimental study to analyze and investigate the non-destruction testing equation for the estimation of compressive strength of high strength concrete. The results are as follows; The relation between rebound number, pulse velocity and compressive strength of high strength concrete have lower coefficient than combined method of rebound number and pulse velocity. Also new non-destructive testing equation for the estimation on the compressive strength of high strength concrete was suggested in this study, and it is considered that these equations have possibility to be applied in domestic construction field.

Adaptive Probabilistic Neural Network for Prediction of Compressive Strength of Concrete (콘크리트 압축강도 추정을 위한 적응적 확률신경망 기법)

  • 김두기;이종재;장성규
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.10a
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    • pp.542-549
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    • 2004
  • The compressive strength of concrete is commonly used criterion in producing 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, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

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Estimation of Concrete Strength Using Improved Probabilistic Neural Network Method

  • Kim Doo-Kie;Lee Jong-Jae;Chang Seong-Kyu
    • Journal of the Korea Concrete Institute
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    • v.17 no.6 s.90
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    • pp.1075-1084
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    • 2005
  • The compressive strength of concrete is commonly used criterion in producing 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, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network(PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Improved probabilistic neural network was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment (DDA) algorithm. The conventional PNN and the PNN with DDA algorithm(IPNN) were applied to predict the compressive strength of concrete using actual test data of two concrete companies. IPNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

A Study Using Nondestructive Tests Based on Stress Waves for the Estimation of Concrete Compressive Strength (응력파 기반 비파괴 검사법에 의한 콘크리트 강도 추정에 관한 연구)

  • Joo, Hyun-Jee;Cho, Young-Sang
    • Proceedings of the Korea Concrete Institute Conference
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    • 2004.11a
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    • pp.675-678
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    • 2004
  • The importance of predicting concrete compressive strength of in concrete structures is gradually increasing in construction industry. The estimation of concrete compressive strength of is a critical factor of the construction schedule and quality control. This study was performed to examine the relationship between concrete compressive strength and stress wave velocity which was determined by the impact echo method and SASW method.

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Estimation for the Uniaxial Compressive Strength of Rocks in Korea using the Point Load Test (점하중시험을 이용한 국내 암석의 일축압축강도산정 연구)

  • Kim, Hak Joon
    • Tunnel and Underground Space
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    • v.28 no.1
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    • pp.72-96
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    • 2018
  • Accurate estimation of the uniaxial compressive strength of rock is very crucial for the safety of construction activities occurring in the rock mass. However, the uniaxial compressive strength test is expensive and time consuming. Moreover, the uniaxial compressive strength test cannot be performed in the field. In order to solve this kind of problem, many foreign researchers investigated the use of the point load strength test for the estimation of uniaxial compressive strength of rock. However, the result of research obtained for rocks from other countries may not be directly applicable for rocks in Korea. The correlation between the point load strength index and the uniaxial compressive strength for rocks in Korea is suggested in the form of table by using the results of the extensive literature reviews and laboratory tests. The suggested result is expected to be used for the simple and quick estimation of uniaxial compressive strength of rocks in Korea.

Strength Estimation Model for Early-Age Concrete Considering Microstructural Characteristics (미세구조 특성을 고려한 초기재령 콘크리트의 강도예측모델)

  • 황수덕;김의태;이광명
    • Proceedings of the Korea Concrete Institute Conference
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    • 2001.05a
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    • pp.397-402
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    • 2001
  • Microstructural characteristics such as hydrates and porosity greatly influence the development of concrete strength. In this study, a strength estimation model for early-age concrete considerig, the microstructural characteristics was proposed, which considers the effects of both an increment of degree of hydration and capillary porosity on a strength increment. Hydration modeling and compressive strength test with curing temperature and curing ages were carried out. By comparing test results with estimated strength, it is found that the strength estimation model can estimate compressive strength of early-age concrete with curing ages and curing temperature within a margin of error.

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Realistic Estimation Method of Compressive Strength in Concrete Structure (콘크리트 구조물의 합리적인 압축강도 추정기법 연구)

  • Oh, Byung-Hwan;Yang, In-Hwan
    • 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.

An Investigation on Estimation of the Compressive strength by P Type Schmidt Hammer (P형 슈미트햄머에 의한 압축강도 추정에 관한 검토)

  • 김기정;이용성;이백수;윤기원;최영화;한천구
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2002.11a
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    • pp.11-15
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    • 2002
  • This study is intended to analyze the relationship between the rebound value of P type schmidt hammer and the compressive strength for a quality control of concrete. According to the results, the compressive strength of standard curing specimen increases in proportion to age, but that of air curing specimen hardly increases after 28 days. The rebound value of P type schmidt hammer, however, increases due to carbonation of concrete in air curing specimen. The correlativity between the rebound value and the compressive strength is very favorable in the case of standard curing specimen, but drops remarkably in the case of air curing specimen. Thus, as application of age coefficient is required for exact estimation of the compressive strength, the age coefficient is derived from this study. The age coefficient of P type schmidt hammer is higher at the age of 3 and 7days, and drops significantly, compared with the age of 28days. And it is lower before 28days than that of N type schmidt hammer suggested in Japan, and shows the similar tendency after 28days.

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Strength Estimation of the High Strength Concrete by using Rock Test Hammer (암반용 테스트해머 사용에 의한 고강도콘크리트의 강도추정)

  • Seo, Yun-A;Nam, Kyung-Yong;Park, Soo-Hwa;Kim, Seong-Deok;Lim, Nam-Gi;Jung, Sang-Jin
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2012.11a
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    • pp.77-79
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    • 2012
  • This paper intends to review possible application in the high strength area through compressive strength estimation of the simulated high strength concrete member using Rock Test Hammer and suggest it as a reference data for the strength estimation technique of the ultra high strength concrete in the future. From the results of our test, in the low strength area less than 15MPa and normal strength area in 15~60MPa, as shown on the existing studies, it is indicated that P Type Schmidt Hammer in the low strength area and N Type Schmidt Hammer in the normal strength area have high correlation of rebound-compressive strength. As the Rock Test Hammer indicated more or less reduced accuracy in the low strength area and the normal strength area but high correlation on the high strength area (50~100MPa) defined on this test, it is determined that it would be possible to make the fastest and simplest compressive strength estimation on the site where the high strength concrete is applied.

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The Development of Compressive Strength Estimation Equation for LNG Storage Tank using Rebound Hardness Method (반발경도법을 이용한 LNG 저장탱크 콘크리트의 압축강도 추정식 개발)

  • Kim, Jung-Hoon;Kim, Young-Gu;Jo, Young-Do
    • Journal of the Korean Institute of Gas
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    • v.21 no.3
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    • pp.26-32
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    • 2017
  • Outer tank concretes of LNG storage tank are composed of prestressed concrete structures that act as a protective wall. The danger such as the collapse of structures will exist if concrete structures is not secured due to the deterioration. Concrete compressive strength directly related to the safety of structures can be predicted by using estimation equation of compressive strength through rebound hardness test and ultrasonic wave velocity method. But, there is no the estimation equation of LNG storage tank for a relation between NDT data and real strength. In this study, to obtain more accurate real strengths for LNG storage tank, core specimens were sampled from walls of pilot LNG storage tank. The rebound hardness test of general NDT for concrete structures was carried out at each 3 positions for the four areas. The compressive strength estimation equation of LNG storage tank was developed by using the data for rebound hardness test of pilot LNG storage tank and compressive strength test of sampled concrete cores.