• Magazine of the Korean Society of Agricultural Engineers
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• v.42 no.2
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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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.2
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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.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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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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• v.21 no.6
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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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• v.30 no.2
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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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• v.39 no.1
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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.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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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 $900^{\circ}C{\cdot}h^{0.4}$.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5A
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• pp.307-315
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• 2012

Recently, ultra high performance fiber reinforced concrete (UHPFRC) having over 180 MPa compressive strength and 10 MPa tensile strength has been developed in Korea. However, UHPFRC represents different material properties with normal concrete (NC) and conventional high performance concrete (HPC) such as a high early age autogenous shrinkage and a rapid dry on the surface, because it has a low water-binder ratio and high fineness admixtures without coarse aggregate. In this study, therefore, to propose suitable experimental methods and regulations, and to evaluate mechanical properties at a very early age for UHPFRC, setting, shrinkage and tensile tests were performed. From the setting test results, paraffin oil was an appropriate material to prevent drying effect on the surface, because if paraffin oil is applied on the surface, it can efficiently prevent the drying effect and does not disturb or catalyze the hydration of cement. From the ring-test results, it was defined that the shrinkage stress is generated at the time when the graph tendency of temperature and strain of inner steel ring is changed. By comparing with setting test result, the shrinkage stress was firstly occurred as the penetration resistance of 1.5 MPa was obtained, and it was about 0.6 and 2.1 hour faster than those of initial and final sets. So, the starting time of autogenous shrinkage measurement (time-zero) of UHPFRC was determined when the penetration resistance of 1.5 MPa was obtained. Finally, the tensile strength and elastic modulus of UHPFRC were measured from near initial setting time by using a very early age tensile test apparatus, and the prediction models for tensile strength and elastic modulus were proposed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.6
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• pp.124-133
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• 2012

Compressive strength in concrete increases with time. Regression analysis with time is conventionally performed for strength evaluation and prediction. In this study, hydrate amount is assumed as a function of hydration rate and porosity, and modeling on compressive strength is carried out considering decreasing porosity with time, which does not need the regression analysis with time. For twenty one mix proportions of HPC (High Performance Concrete), DUCOM (FE program) which can simulate the behavior in early aged concrete is utilized, and porosity from each mix proportions is obtained with time. For HPC with OPC (Ordinary Portland Cement) concrete, modeling on compressive strength is performed considering hydration rate, unit content of cement, and porosity with time. For HPC with mineral admixtures, a long-term parameter which can handle long-term strength development is additionally considered. From the comparison with the previous test results, the applicability of the proposed model is verified.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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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.