• Journal of The Korean Society of Agricultural Engineers
• /
• v.46 no.1
• /
• pp.53-60
• /
• 2004

Roller-compacted concrete(RCC) dam have gained acceptance worldwide in a relatively short time due to their low cost, which is derived in part from their rapid method of construction. And RCC has recently emerged as an economically attractive material for dam construction, replacing the use of conventional concrete and even challenging the economics of earthfill and rockfill embankment dams. There are existing two major mix design methods. one used in USA and the other used in Japan. In this study, proper mix proportions of concrete for RCC dam is obtained using method of compound their merit.

• Proceedings of the Korea Concrete Institute Conference
• /
• 1997.04a
• /
• pp.177-185
• /
• 1997

The purpose of this study is to investigate the mechanical properties of super-workable concrete using O.P.C., blast-furnace slag, and fly ash respectively. For this purpose, after determining the optimum mix proportion of super-workable concrete according to unit weight of binder and percentage of fine aggregate respectively, mechanical properties of super-workable concrete such as compressive, tensile and flexural strength as well as elastic modules were tested and analyzed. Also, the mechanical performances of super-workable concrete were compared with those of high-strength concrete with equal mix proportion of concrete. As a result, super-workable concrete have an excellent mobility, placeability, and segregation-resistance, but the strength of super-workable concrete was shown to be somewhat lower than that of high-strength concrete with equal mix proportion of concrete.

• Advances in concrete construction
• /
• v.9 no.3
• /
• pp.267-278
• /
• 2020

This paper reports on the result of an experimental investigation carried out to study the compressive strength and sorptivity properties of blended cement concrete exposed to 5% and 10% MgSO₄ solution using fly ash (FA) and silpozz. Usually in sulphate environment the minimum grade of concrete is M30 and the mix design is done for target mean strength of 39 MPa. Silpozz is manufactured by burning of agro-waste rice husk in designed furnace in between 600° to 700℃ which is one of the main agricultural residues obtained from the outer covering of rice grains during the milling process. There are four mix series taken with control mix. The control mix made 0% replacement of FA and silpozz with Ordinary Portland Cement (OPC). The first mix series made 0% FA and 10-30% replacement of silpozz with OPC. The second mix series made with 10% FA and 10-40% replacement of silpozz with OPC. The third mix series made 20% FA and 10-30% replacement of silpozz with OPC and the fourth mix series made 30% FA and 10-20% silpozz replaced with OPC. The samples (cubes) are prepared and cured in normal water and 5% and 10% MgSO₄ solution for 7, 28 and 90 days. The studied parameters are compressive strength and strength deterioration factor (SDF) for 7, 28 and 90 days. The water absorption and sorptivity tests have been done after 28 days of normal water and magnesium sulphate solution curing. The investigation reflects that the blended cement concrete incorporating FA and silpozz showing better resistance against MgSO₄ solution when compared to normal water curing (NWC) samples.

• Journal of the Korean Society of Industry Convergence
• /
• v.4 no.4
• /
• pp.419-426
• /
• 2001

Concrete mix proportioning is a process of selecting the right combination of many materials such as cement, fine aggregates, coarse aggregates, water, and admixtures to make concrete satisfying for specification and cost. In determining proportioning of concrete mixes, code information, specification, and the experience of experts are needed. However, all factors regarding mix proportioning factor cannot be considered. Therefore, the final acceptance depends on concrete quality control test results. The proportioning of concrete mixes and the adjustments are somewhat complicated, time-consuming, and uncertain tasks. In this paper, as a tool to predict the factor of the proportioning of concrete mixes, an artificial neural network is used. To consider the varieties of material properties, the standard mixed table of two companies of ready mixed concrete are used. The results show that neural net works is successfully applied to the prediction of concrete mix proportioning factor.

• Magazine of the Korea Concrete Institute
• /
• v.9 no.1
• /
• pp.165-172
• /
• 1997

Lightweight foamed concrete is a concrete which is lighter than conventional concree by mixing ptetoamed foam in cement slurry. The objectives of this study are to develop optimal prefoarneti lightweight foamed concrete with high lightness. high flowability and enough strength fol special use of structural application by using the polymer foam agent. By mixing the admixtures such as silica-fume and fly-ash and the industrial by-product such as styrofoam for the purpose of practical use of industrial waste, lightweight foamed concrete shich has better lightness. flowability and strength than the conventional prefoamed lightweight foamed concrete is developed. This paper presents extensive data on characteristics of compressive strength and flowability of the concrete manufactured with the different factors in mix design and also presents optimum mix proportion.

• Journal of the Korea Institute of Building Construction
• /
• v.17 no.1
• /
• pp.39-46
• /
• 2017

In this research, considering the practical conditions at field, thermal cracking reducing method was suggested based on the comparative analysis between predicted value and actual value obtained from the actual structure member with optimum mix design. The optimum mix design was deduced from the various mix designs with various proportions of cementitious binder for upper and lower placement lifts of mat-foundation mass concrete. Therefore, before field applications, the mix designs were obtained from the theoretical analysis obtained by MIDAS GEN for upper lift was OPC to FA of 85 to 15, and for lower lift was OPC to FA to BS of 50 : 20 : 30. Based on this mix design, the actual concrete for field was determined and all concrete properties were reached within the predicted range. Especially, the temperature properties of mass concrete at core was approximately $39^{\circ}C$ of temperature difference for low-heat mix design, while approximately $54^{\circ}C$ was shown for normal mix design currently used. Additionally, in the case of cracking index, the low heat mix design showed about 1.4 of relatively high value while the normal mix design showed 1.0. Therefore, it can be stated that applying low heat mix design and different heating technique between upper and lower placement lifts for mass concrete are efficient to control the thermal cracking.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2012.11a
• /
• pp.253-254
• /
• 2012

The purpose of this study is to suggest and verify high-strength concrete mix design model applying neural network theory, in order to minimize effort and time wasted by using trial and error method utill now. There are 7 input and 2 output to predict mix design. 40 data of mix design were learned with back-propagation algorithm. Then they are repeatedly learned back-propagation in neural network theory. Also, to verify predicted model, we analyzed and compared value predicted from 60MPa mix design with value measured by actual compressive strength test.

• Computers and Concrete
• /
• v.6 no.3
• /
• pp.253-268
• /
• 2009

This study aims to develop a cost-based high-performance concrete (HPC) mix optimization system based on an integrated approach using artificial neural networks (ANNs) and genetic algorithms (GA). ANNs are used to predict the three main properties of HPC, namely workability, strength and durability, which are used to evaluate fitness and constraint violations in the GA process. Multilayer back-propagation neural networks are trained using the results obtained from experiments and previous research. The correlation between concrete components and its properties is established. GA is employed to arrive at an optimal mix proportion of HPC by minimizing its total cost. A system prototype, called High Performance Concrete Mix-Design System using Genetic Algorithm and Neural Networks (HPCGANN), was developed in MATLAB. The architecture of the proposed system consists of three main parts: 1) User interface; 2) ANNs prediction models software; and 3) GA engine software. The validation of the proposed system is carried out by comparing the results obtained from the system with the trial batches. The results indicate that the proposed system can be used to enable the design of HPC mix which corresponds to its required performance. Furthermore, the proposed system takes into account the influence of the fluctuating unit price of materials in order to achieve the lowest cost of concrete, which cannot be easily obtained by traditional methods or trial-and-error techniques.

• Proceedings of the Korea Concrete Institute Conference
• /
• 1997.10a
• /
• pp.103-110
• /
• 1997

The objective of this study is to provide the information on the small-scale model mix proportion when the behavior of prototype concrete pavement is studied through small-scale model experiments. However it is difficult to obtain a model material to simulate the prototype concrete by scaling the individual components according to the laws of similitude. In this paper, the stress-strain behavior in uniaxial compression is used as a means to correlate materials similitude between the prototype and the model concrete. Based on th results of experiments, We compared the stress-strain curves of prototype and model concrete mixes using a nondimensional basis. In order to simulate the stress-strain curves of prototype concrete, it is important that various mix as of model concrete selected properly which are varied from aggregate grading, cement-aggregate and sand-aggregate ratio.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.6 no.1
• /
• pp.69-78
• /
• 1986

The properties of ready mixed concrete are affected largely by quality of cement, grading and adhesive surface area water content of aggregate. The amount of variation must be found as soon as possible to minimize the variation of concrete properties. In this paper, a computer program is presented for fast and accurate calculation and modification of mix proportion according to property variation of concrete materials. The program calculates specified mix proportion, job mix proportion and batch weight of ready mixed concrete.