• 한국농공학회지
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• 제42권2호
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• pp.99-107
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• 2000

The objective of this study are to compare the development of compressive strength of epoxy mortars used as repairing materials with respect to maturity , and to propose a model predicting strength development of epoxy mortars. A series of tests are carried out for the hardener contents of 30, 40 and 50 percentage of epoxy resin and compressive strengths are measured at the age of 6, 12, 24, 72, 120 and 168 hours respectively under the cure temperature of 0, 10, 20 and 3$0^{\circ}C$. The datum temperature is estimated by measured strengths, and the maturity is calculated with the estimated datum temperature. The compressive strength of epoxy mortars can be predicted by regression analysis from the maturity-compressive strength relationship.

• 한국구조물진단유지관리공학회 논문집
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• 제3권2호
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• pp.177-183
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• 1999

The major object of this study is to investigate experimentally the experimental equation by the non-destructive testing methods of ultrasonic pulse velocity, rebound number, combined method of ultrasonic pulse velocity and rebound number, maturity which are applicable to the evaluation of compressive strength of concrete at early ages. Also test result of mix are statistically analyzed to infer the correlation coefficient between the maturity and the compressive strength of concrete. The results show good application of Logistic curve for estimating strength development under various curing temperature. The relation between ultrasonic pulse velocity, rebound number, combined method of ultrasonic pulse velocity and rebound number and compressive strength of concrete have low correlation coefficient, but maturity method show good correlation coefficient.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.61-62
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• 2021

Because of the problem of increasing self-weight due to the enlargement and high-rise of buildings using normal aggregate concrete, the need for structural lightweight aggregate concrete increases. However, early strength prediction is required when placing structural lightweight aggregate concrete, but research is insufficient. In this study, the ultrasonic pulse velocity of normal aggregate concrete and lightweight aggregate concrete was measured at early age. As a result, the ultrasonic pulse velocity of lightweight aggregate concrete was lower than normal aggregate concrete according to elapsed time at early age.

• Computers and Concrete
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• 제21권6호
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• pp.697-703
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• 2018

Compressive strength is one of the most important engineering properties of concrete, and testing of the compressive strength of concrete specimens is often costly and time consuming. In order to provide the time for concrete form removal, re-shoring to slab, project scheduling and quality control, it is necessary to predict the concrete strength based upon the early strength data. However, concrete compressive strength is affected by many factors, such as quality of raw materials, water cement ratio, ratio of fine aggregate to coarse aggregate, age of concrete, compaction of concrete, temperature, relative humidity and curing of concrete. The concrete compressive strength is a quite nonlinear function that changes depend on the materials used in the concrete and the time. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of concrete compressive strength. The training of fuzzy system was performed by a hybrid method of gradient descent method and least squares algorithm, and the subtractive clustering algorithm (SCA) was utilized for optimizing the number of fuzzy rules. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the back propagation neural network model, the statistics model, and the ANFIS model) were compared with the experimental data. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the concrete compressive strength.

• Smart Structures and Systems
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• 제30권2호
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• pp.195-207
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• 2022

Computational drawbacks associated with regular predictive models have motivated engineers to use hybrid techniques in dealing with complex engineering tasks like simulating the compressive strength of concrete (CSC). This study evaluates the efficiency of tree potential metaheuristic schemes, namely shuffled complex evolution (SCE), multi-verse optimizer (MVO), and beetle antennae search (BAS) for optimizing the performance of a multi-layer perceptron (MLP) system. The models are fed by the information of 1030 concrete specimens (where the amount of cement, blast furnace slag (BFS), fly ash (FA1), water, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA2) are taken as independent factors). The results of the ensembles are compared to unreinforced MLP to examine improvements resulted from the incorporation of the SCE, MVO, and BAS. It was shown that these algorithms can considerably enhance the training and prediction accuracy of the MLP. Overall, the proposed models are capable of presenting an early, inexpensive, and reliable prediction of the CSC. Due to the higher accuracy of the BAS-based model, a predictive formula is extracted from this algorithm.

• Steel and Composite Structures
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• 제39권1호
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• pp.81-93
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• 2021

Splitting tensile strength (STS) is an important mechanical parameter of concrete. This study offers novel methodologies for the early prediction of this parameter. Artificial neural network (ANN), which is a leading predictive method, is synthesized with two metaheuristic algorithms, namely atom search optimization (ASO) and equilibrium optimizer (EO) to achieve an optimal tuning of the weights and biases. The models are applied to data collected from the published literature. The sensitivity of the ASO and EO to the population size is first investigated, and then, proper configurations of the ASO-NN and EO-NN are compared to the conventional ANN. Evaluating the prediction results revealed the excellent efficiency of EO in optimizing the ANN. Accuracy improvements attained by this algorithm were 13.26 and 11.41% in terms of root mean square error and mean absolute error, respectively. Moreover, it raised the correlation from 0.89958 to 0.92722. This is while the results of the conventional ANN were slightly better than ASO-NN. The EO was also a faster optimizer than ASO. Based on these findings, the combination of the ANN and EO can be an efficient non-destructive tool for predicting the STS.

• 한국농공학회논문집
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• 제59권6호
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• pp.19-27
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• 2017

This study investigated to predict the compressive strength of unsaturated polyester resin based polymer concrete using the maturity method. The test results show that the development of the compressive strength increased exponentially until an age of 24 hours. After 24 hours, the development of the compressive strength just increased gradually. This test result shows that the strength of unsaturated polyester resin based polymer concrete was developed mainly at the early age. Estimated datum temperature of unsaturated polyester resin based polymer concrete was $-20.67^{\circ}C$ which was much lower than of datum temperature ($-10^{\circ}C$) of Portland cement concrete. Also, this study result shows that the existing maturity index associated with Portland cement concrete was not applicable for polymer concrete because curing time of Portland cement concrete is different clearly with curing time of polymer concrete. The cause of different curing time was that there were different curing mechanisms between Portland cement concrete and polymer concrete. In order to best apply the experimental data to a model, CurveExpert Professional, the commercial software, was used to determine the predictive model regarding the compressive strength of unsaturated polyester resin based polymer concrete. As a result, Gompertz Relation or Weibull Model was an appropriate model as a predictive model. The proposed model can be used to predict the compressive strength, especially, it is more useful when the maturity is in the range between $40^{\circ}C{\cdot}h^{0.4}$ and $900^{\circ}C{\cdot}h^{0.4}$.

• 대한토목학회논문집
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• 제32권5A호
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• pp.307-315
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• 2012

최근 국내에서도 압축강도 180 MPa, 인장강도 10 MPa 이상의 초고성능 섬유보강 콘크리트(Ultra High Performance Fiber Reinforced Concrete, UHPFRC)가 개발되었다. 그러나 UHPFRC는 물-결합재비가 낮고 다량의 고분말 혼화재료를 혼입하며, 굵은 골재를 사용하지 않기 때문에 초기 재령에서의 자기수축이 크고, 표면이 급격히 건조하는 등 기존의 일반 콘크리트(Normal Concrete, NC) 및 고성능 콘크리트(High Performance Concrete, HPC)와는 다른 재료적 특성을 보인다. 그러므로 본 연구에서는 UHPFRC에 적합한 재료 실험 방법과 규정을 제안하고 극 초기 재령에서의 강도 특성을 평가하기 위하여 응결 및 수축, 인장 실험을 수행하였다. 응결 실험 결과 파라핀 오일을 UHPFRC의 모르타르 표면에 적용할 경우 표면에서의 급격한 건조현상을 효율적으로 억제할 수 있는 것으로 나타났으며, 시멘트와 배합수의 수화반응을 지연 또는 촉진 시키지 않는 것으로 나타나 응결 실험 시 표면건조 방지제로 적합한 것으로 판단되었다. 또한, 링-테스트를 수행하여 내부 강재 링의 온도와 변형률의 경향이 달라지는 시점을 수축 응력 발현 시점으로 정의하였으며, 이를 응결 실험과 비교하여 본 결과 응결침에 걸리는 관입 저항력이 약 1.5 MPa일 때 수축 응력이 발현되는 것으로 나타났다. 이는 초결 및 종결보다 약 0.6시간, 2.1시간 빠른 것이며, 상기 시점을 UHPFRC의 자기수축 측정 시점(time-zero)으로 규정하였다. 마지막으로, 본 연구에서는 극 초기 재령 인장강도 측정 장비를 제작하여 초결시점에서부터 UHPFRC의 인장강도와 탄성계수를 측정하였으며, 이를 고려한 UHPFRC의 인장강도 및 탄성계수 예측식을 제안하였다.

• 한국구조물진단유지관리공학회 논문집
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• 제16권6호
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• pp.124-133
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• 2012

콘크리트의 강도는 시간에 따라 증가하며, 많은 연구에서 시간에 대한 회귀 분석식을 사용하고 있다. 본 연구는 수화물량을 수화도 및 공극률의 함수로 가정하였으며, 재령의 증가에 따라 감소하는 공극률을 이용하여 고성능 콘크리트의 압축강도 모델링을 수행하였다. 본 연구에서는 기존의 시간에 대한 회귀분석없이 공극률의 감소만을 이용하여 압축강도를 예측하였다. 총 21개의 고성능 콘크리트 배합에 대해 초기재령 콘크리트의 거동 해석프로그램인 DUCOM을 이용하여 각각의 공극률을 도출하였으며, 강도 모델링을 수행하였다. OPC 콘크리트에 대해서 수화도, 단위시멘트량, 공극률의 함수로 강도 예측식을 제안하였으며, GGBFS 및 FA를 혼입한 콘크리트에 대해서는 장기강도 영향을 구현하기 위해 공극률을 고려한 장기강도변수를 도입하였다. 기존의 실험결과와의 비교를 통하여 제안된 강도예측식의 타당성을 입증하였다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1996년도 가을 학술발표회 논문집
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• pp.114-121
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• 1996

This study presented a simple test method of early decision on the quality of concrete by the way of refrigeration curing. It is a method of early decision for the quality of hardened concrete, after 28days, through the using refrigeration curing, at -18$\pm$$3^{\cire}C$ for five hours. I could find that there were fixed connections between the solidities after 28days and 48days, by the test of compression on the Re-Mi-Con through the test of standard curing and refergeration curing. (F = 1.02X + 13, $r^2$ = 0.964, S = 10.6kg/$\textrm{cm}^2$) I except that we can reduce the mistakes of construction work by forecasting the quality through the refrigeration curing.