• Advances in concrete construction
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• v.6 no.1
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• pp.87-102
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• 2018

Utilization of waste tires may be considered as one of the solution to the problems faced by the local authorities in disposing them. Reclaimed rubber (RR) is being used in concrete for replacing conventional aggregates. This research work is focused on the strength prediction of reclaimed rubber concrete using a Genetic Algorithm (GA) for M40 grade of concrete and comparing it with experimental results. 1000 sets were taken and 100 iterations were run during training of GA models. A base study has been carried out in this research work partially replacing cement with three types of fillers such as Plaster of Paris (POP), Fly Ash (FA) and Silica Fume (SF). A total of 243 cubes were cast and tested for compression using a Universal Testing Machine. It was found that SF produced maximum strength in concrete and was used in the main study with reclaimed rubber. Tests were conducted on 81 cube samples with a combination of optimum SF percent and various proportions of RR replacing coarse aggregates in concrete mix. Compressive strength tests of concrete at 7, 14 and 28 days reveal that the maximum strength is obtained at 12 percent replacement of cement and 9 percent replacement of coarse aggregates respectively. Moreover the GA results were found to be in line with the experimental results obtained.

• Computers and Concrete
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• v.20 no.1
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• pp.31-38
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• 2017

In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

• Computers and Concrete
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• v.3 no.4
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• pp.249-260
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• 2006

Self-consolidating concrete (SCC) in the fresh state is known for its excellent deformability, high resistance to segregation, and use, without applying vibration, in congested reinforced concrete structures characterized by difficult casting conditions. Such a concrete can be obtained by incorporating either mineral or chemical admixtures. This paper presents the results of an investigation to asses the applicability of Abram's law in predicting the compressive strength of SCC to any given age. Abram's law is based on the assumption that the strength of concrete with a specific type of aggregate at given age cured at a prescribed temperature depends primarily on the water-to-cement ratio (W/C). It is doubtful that such W/C law is applicable to concrete mixes with mineral or chemical admixtures as is the case for SCC where water to binder ratio (W/B) is used instead of W/C as the basis for mix design. Strength data of various types of SCC mixtures is collected from different sources to check the performance of Abram's law. An attempt has been made to generalize Abram's law by using various optimization methodologies on collected strength data of various SCC mixtures. A set of generalized equations is developed for the prediction of SCC strength at various ages. The performance of generalized equations is found better than original Abram's equations.

• Computers and Concrete
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• v.16 no.3
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• pp.343-356
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• 2015

1078 sets of mixtures in total that include fly ash, slag, and/or silica fume have been collected for prediction on concrete properties. A new database platform (Compos) has been developed, by which the stepwise multiple linear regression (SMLR) and BP artificial neural networks (BP ANNs) programs have been applied respectively to identify correlations between the concrete properties (strength, workability, and durability) and the dosage and/or quality of raw materials'. The results showed obvious nonlinear relations so that forecasting by using nonlinear method has clearly higher accuracy than using linear method. The forecasting accuracy rises along with the increasing of age and the prediction on cubic compressive strength have the best results, because the minimum average relative error (MARE) for 60-day cubic compressive strength was less than 8%. The precision for forecasting of concrete workability takes the second place in which the MARE is less than 15%. Forecasting on concrete durability has the lowest accuracy as its MARE has even reached 30%. These conclusions have been certified in a ready-mixed concrete plant that the synthesized MARE of 7-day/28-day strength and initial slump is less than 8%. The parameters of BP ANNs and its conformation have been discussed as well in this study.

• Magazine of the Korea Concrete Institute
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• v.8 no.2
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• pp.109-117
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• 1996

Recently, High-Workable Concrete has been developed and began to be used to a great extent in foreign countries, but it is not familiar with and fully Introduced in Korea yet. Therefore the aim of this paper is to suggest a reference data. for the development of High-Workable Concrete according to the comparative analysis which were done on the effects of mix proportion(water-binder ratio, sand-aggregate ratio, unit water, a kind of superplasticizer) on the flowing characteristics. And also this paper aims to examine the compactability and segregation resistance of High-Workable Concrete in a mock-up test and in a field test. From the result, we concluded that it is possible to produce and to use the High-Workable Concrete at the construction site.

• Structural Engineering and Mechanics
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• v.86 no.4
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• pp.431-441
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• 2023

The aim of this paper is to present a new sustainable ternary and quaternary binder by partially replacing ordinary Portland cement (OPC) with different percentages of supplementary cementitious materials. The motivation is to reduce our dependency on OPC to reduce CO₂ emission and carbon foot print. As the main substitute for the OPC, siliceous fly ash was used. Moreover, silica fume and nanosilica were also used. During examinations the main mechanical parameters of concrete composites, i.e., compressive strength (f_cm) and splitting tensile strength (f_ctm) were assed. The microstructure of these materials was also analysed. It was found that the concrete incorporating pozzolanic materials is characterized by a well-developed structure and has high values of mechanical parameters. The quaternary concrete containing: 80% OPC, 5% FA, 10% SF, and 5% nS have shown the best results in terms of good strength parameters as well as the most favourable microstructure, whereas the worst mechanical parameters with microstructure containing microcracks at phase interfaces were characterized by concrete with more content of FA additive in the concrete mix, i.e., 15%. Nevertheless, all concretes made on quaternary binders had better parameters than the reference one. It can be stated that sustainable concrete incorporating pozzolanic materials could be good substitute of ordinary concretes.

• Computers and Concrete
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• v.32 no.2
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• pp.185-206
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• 2023

This article aimed to explore the optimization of mineral admixtures and retarding admixture for high-performance concrete. In essence, fresh concrete can be regarded as a mixture in which both coarse and fine aggregates are suspended in a cement-based matrix paste. Based on this view, the test procedure was divided into three progressive stages of binder paste, mortar, and concrete to explore their rheological behavior and mechanical properties respectively. At each stage, there were four experimental control factors, and each factor had three levels. In order to reduce the workload of the experiment, the Taguchi method with an L9(3⁴) orthogonal array and four controllable three-level factors was adopted. The test results show that the use of the Taguchi method effectively optimized the composition of high-performance concrete. The slump of the prepared concrete was above 18 cm, and the slump flow was above 50 cm, indicating that it had good workability. On the other hand, the 28-day compressive strength of the hardened concretes was between 31.3-59.8 MPa. Furthermore, the analysis of variance (ANOVA) results showed that the most significant factor affecting the initial setting time of the fresh concretes was the retarder dosage, and its contribution percentage was 62.66%. On the other hand, the ANOVA results show that the most significant factor affecting the 28-day compressive strength of the hardened concretes was the water to binder ratio, and its contribution percentage was 79.05%.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.57-58
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• 2022

Concrete mix design is used as essential data for the quality of concrete, analysis of structures, and stable use of sustainable structures. However, since most of the formulation design is established based on the experience of experts, there is a lack of data to base it on. are suffering Accordingly, in this study, the purpose of this study is to build a predictive model to use the concrete mixing factor as basic data for calculation using the DNN technique. As for the data set for DNN model learning, OPC and ternary concrete data were collected according to the presence or absence of admixture, respectively, and the model was separated for OPC and ternary concrete, and training was carried out. In addition, by varying the number of hidden layers of the DNN model, the prediction performance was evaluated according to the model structure. The higher the number of hidden layers in the model, the higher the predictive performance for the prediction of the mixing elements except for the compressive strength factor set as the output value, and the ternary concrete model showed higher performance than the OPC. This is expected because the data set used when training the model also affected the training.

• Advances in materials Research
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• v.12 no.4
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• pp.331-349
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• 2023

Foam concrete can be considered as environmental friendly material due to its low weight, its minimal cost and a possibility to add waste materials in its production. This paper investigates the possibility of producing foam concrete with waste glass as powder and aggregate. Then, the effect of using waste glass on strength and drying shrinkage of foam concrete was examined. Also, the effect of incorporating polypropylene fibers (12 mm length and proportion of 0.5% of a mix volume) on distribution of waste glass as coarse particles within 1200 kg/m³ foam concrete mixes was evaluated. Waste glass was used as powder (20% of cement weight), as coarse particles (25%, 50% and 100% instead of sand volume) and as fine particles (25% instead of sand volume). From the results, the problem of non-uniform distribution of coarse glass particles was successfully solved by adding polypropylene fibers. It was found that using of waste glass as coarse aggregate led to reduce the strength of foam concrete mixes. However, using it with polypropylene fibers in combination helped in increasing the strength by about 29- 50% for compressive and 55- 71% for splitting tensile and reducing the drying shrinkage by about (31- 40%). In general, not only the fibers role but also the uniformly distributed coarse glass particles helped in improving and enhancing the strength and shrinkage of the investigated foam concrete mixes.

• Journal of the Korea Concrete Institute
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• v.19 no.6
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• pp.701-706
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• 2007

This study evaluated the durability of high-performance shotcrete mixed in the proper proportions using alkali-free and cement mineral accelerators as a permanent support that maintains its strength for the long term. Durability tests were performed the chloride permeability, repeated freezing and thawing, accelerated carbonation, and the effects of salt environments. Test results showed that all the shotcrete mixes included silica fume had low permeability. In addition, after 300 freeze/thaw cycles, the shotcrete mix had excellent freeze/thaw resistance more than the 85% relative dynamic modulus of elasticity. The accelerated carbonation test results were no effect of accelerator type but, the depth of carbonation was greater in the shotcrete mix containing silica fume. No damage was seen in a salt environments. Therefore, the high performance shotcrete mix proportions used in this study showed excellent durability.