• 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.

• Computers and Concrete
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• v.14 no.3
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• pp.247-262
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• 2014

Partial replacement of Portland cement by slag can reduce the energy consumption and $CO_2$ emission therefore is beneficial to circular economy and sustainable development. Compressive strength is the most important engineering property of concrete. This paper presents a numerical procedure to predict the development of compressive strength of slag blended concrete. This numerical procedure starts with a kinetic hydration model for cement-slag blends by considering the production of calcium hydroxide in cement hydration and its consumption in slag reactions. Reaction degrees of cement slag are obtained as accompanied results from the hydration model. Gel-space ratio of hardening slag blended concrete is determined using reaction degrees of cement and slag, mixing proportions of concrete, and volume stoichiometries of cement hydration and slag reaction. Furthermore, the development of compressive strength is evaluated through Powers' gel-space ratio theory considering the contributions of cement hydration and slag reaction. The proposed model is verified through experimental data on concrete with different water-to-binder ratios and slag substitution ratios.

• Computers and Concrete
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• v.21 no.5
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• pp.505-511
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• 2018

This paper investigates the potential of a hybrid model which combines the least squares support vector machine (LSSVM) and an improved particle swarm optimization (IMPSO) techniques for prediction of concrete compressive strength. A modified PSO algorithm is employed in determining the optimal values of LSSVM parameters to improve the forecasting accuracy. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed IMPSO-LSSVM model. Further, predictions from five models (the IMPSO-LSSVM, PSO-LSSVM, genetic algorithm (GA) based LSSVM, back propagation (BP) neural network, and a statistical model) were compared with the experimental data. The results show that the proposed IMPSO-LSSVM model is a feasible and efficient tool for predicting the concrete compressive strength with high accuracy.

• Computers and Concrete
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• v.19 no.3
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• pp.233-241
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• 2017

During the last two decades, CFRP have been extensively used for repair and rehabilitation of existing structures as well as in new construction applications. For rehabilitation purposes CFRP are currently used to increase the load and the energy absorption capacities and also the shear strength of concrete columns. Thus, the effect of CFRP confinement on the strength and deformation capacity of concrete columns has been extensively studied. However, the majority of such studies consider empirical relationships based on correlation analysis due to the fact that until today there is no general law describing such a hugely complex phenomenon. Moreover, these studies have been focused on the performance of circular cross section columns and the data available for square or rectangular cross sections are still scarce. Therefore, the existing relationships may not be sufficiently accurate to provide satisfactory results. That is why intelligent models with the ability to learn from examples can and must be tested, trying to evaluate their accuracy for composite compressive strength prediction. In this study the forecasting of wrapped CFRP confined concrete strength was carried out using different Data Mining techniques to predict CFRP confined concrete compressive strength taking into account the specimens' cross section: circular or rectangular. Based on the results obtained, CFRP confined concrete compressive strength can be accurately predicted for circular cross sections using SVM with five and six input parameters without spending too much time. The results for rectangular sections were not as good as those obtained for circular sections. It seems that the prediction can only be obtained with reasonable accuracy for certain values of the lateral confinement coefficient due to less efficiency of lateral confinement for rectangular cross sections.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.325-330
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• 1999

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

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.10a
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• pp.129-132
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• 2001

Fiber waviness is one of manufacturing defects encountered frequently in thick composite structures. It affects significantly on the behavior as well as strength of thick composites. The effects of fiber waviness on tensile/compressive nonlinear elastic behavior and strength of thick composite with fiber waviness are studied theoretically and experimentally. FEA(Finite Element Analysis) models are proposed to predict tensile/compressive nonlinear behavior and strength of thick composites. In the FEA models, both material and geometric nonlinearities were incorporated into the model using energy density, iterative mapping and incremental method. Also Tsai-Wu criteria was adopted to predict the strength of thick composites with fiber waviness. Tensile and compressive tests were conducted on the specimens with uniform fiber waviness. It was observed that the degree of fiber waviness in composites significantly affected the nonlinear behavior and strength of the composites

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.225-231
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• 1996

Prediction of the early-stage strength of concrete is useful for modernized concrete construction. An experiment was attempted on the high-strength of concrete produced by ordinary portland cement under the curing temperatures of 30, 20, $10^{\cire}C$ and the various mixing proportions such as water-binder ratio of 0.30, 0.35 and silica fume content of 10% by weight of cement. It is the aim of this study to investigare and compare the development of concrete strength with maturity and analyze the application of Maturity as a parameter to correlation estimate test results of concrete. They are statistically analyzed to infer the correlation coefficient between the Maturity and the compressive strength of high-strength concrete.

• Computers and Concrete
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• v.30 no.6
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• pp.377-391
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• 2022

The use of carbon fiber-reinforced polymers (CFRP) has widely increased due to its enhancement in the ultimate strength and ductility of the reinforced concrete (RC) structures. This study presents a prediction model for the axial compressive strength and strain of normal-strength concrete cylinders confined with CFRP. Besides, soft computing approaches have been extensively used to model in many areas of civil engineering applications. Therefore, the genetic expression programming (GEP) models to predict axial compressive strength and strain of CFRP-confined concrete specimens were used in this study. For this purpose, the parameters of 283 CFRP-confined concrete specimens collected from 38 experimental studies in the literature were taken into account as input variables to predict GEP based models. Then, the results of GEP models were statistically compared with those of models proposed by various researchers. The values of R² for strength and strain of CFRP-confined concrete were obtained as 0.897 and 0.713, respectively. The results of the comparison reveal that the proposed GEP-based models for CFRP-confined concrete have the best efficiency among the existing models and provide the best performance.

• International Journal of Concrete Structures and Materials
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• v.10 no.2
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• pp.205-219
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• 2016

High-early-strength-concrete (HESC) made of Type III cement reaches approximately 50-70 % of its design compressive strength in a day in ambient conditions. Experimental investigations were made in this study to observe the effects of temperature, curing time and concrete strength on the accelerated development of compressive strength in HESC. A total of 210 HESC cylinders of $100{\times}200mm$ were tested for different compressive strengths (30, 40 and 50 MPa) and different curing regimes (with maximum temperatures of 20, 30, 40, 50 and $60^{\circ}C$) at different equivalent ages (9, 12, 18, 24, 36, 100 and 168 h) From a series of regression analyses, a generalized rate-constant model was presented for the prediction of the compressive strength of HESC at an early age for its future application in precast prestressed units with savings in steam supply. The average and standard deviation of the ratios of the predictions to the test results were 0.97 and 0.22, respectively.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05b
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• pp.105-108
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• 2005

This study investigated fundamental properties of the recycled aggregate which was produced through recent hi-techniques of recycling. In addition, the mechanical properties of the concrete that used the recycled aggregate were compared to the concrete used the natural aggregate. From the results of the mechanical property tests, as the recycled aggregate replacement ratio increased, the compressive strength and elastic modulus decreased. When the recycled aggregate completely replaced the natural aggregate, the compressive strength and elastic modulus was about 15$\%$ and 35$\%$ lower than the natural aggregate concrete, respectively. Based on the test results, equations for prediction of compressive strength and elastic modulus were suggested in the consideration of the amount of the replaced recycled aggregate. Based on the test results and study, the equation predicting the required development length of the recycled aggregate concrete is proposed.