• Steel and Composite Structures
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• v.29 no.1
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• pp.67-75
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• 2018

High performance concrete (HPC) depends on various parameters such as the type of cement, aggregate and water reducer amount. Generally, the ready concrete company in various regions according to the requirements and costs, mix design of concrete as well as type of cement, aggregates, and, amount of other components will vary as a result of moment decisions or dynamic optimization, though the ideal conditions will be more applicable for the design of mix proportion of concrete. This study aimed to apply dynamic optimization for mix design of HPC; consequently, the objective function, decision variables, input and output variables and constraints are defined and also the proposed dynamic optimization model is validated by experimental results. Results indicate that dynamic optimization objective function can be defined in such a way that the compressive strength or performance of all constraints is simultaneously examined, so changing any of the variables at each step of the process input and output data changes the dynamic of the process which makes concrete mix design formidable.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.10a
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• pp.48-49
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• 2004

• International Journal of Highway Engineering
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• v.19 no.1
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• pp.1-9
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• 2017

PURPOSES : The objective of this study is to develop an optimized method of mix design for rapid-set lightweight-formed mortar mix. To achieve this objective, the workability, setting time, and compressive strength of mixes under various conditions of mix design were evaluated. METHODS : The water-bonder ratio, fly-ash substitution ratio, and forming agent injection amount were selected as design variables in the study. The fluidity, setting time, density, and strength of the mortar mix were considered as major evaluation criteria of the mixture, and were subsequently utilized to evaluate the characteristics of the mortar mix under various conditions. RESULTS : The observations made from the mix design process are as follows: 1) the air content and fluidity increase as the forming agent ratio and forming agent ratio increase, respectively; 2) the maximum air content is approximately 20%; 3) the accelerating agent decreases the fluidity of the mortar mix by 15% on average; 4) the forming agent injection ratio and fly-ash substitution ratio yield significant effects on the initial and final set times of the mortar mix; 5) as the forming agent injection ratio and fly-ash substitution ratio increase, the compressive strength of the mortar mix decreases; and 6) the 28-day compressive strengths of the forming agent injection ratio and fly-ash substitution ratio yield the most significant effects. CONCLUSIONS : It is concluded that the governing design variables for the rapid-set lightweight-formed mortar mix are the forming agent injection ratio and fly-ash substitution ratio.

• Magazine of the Korea Concrete Institute
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• v.9 no.2
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• pp.145-151
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• 1997

In concrete mix design we need the informations of the codes, the specifications, and the experiences of experts. However we can't consider all factors regarding concrete mix design. The final acceptance depends on concrete quality control test results. In this process we meet the uncertainties of materials. temperature, site environmental situations, personal skillfulness. and errors in calculations and testing process. Then the mix design adjustments must be made. Concrete mix design and adjustments arc somewhat complicated, time-consuming. and uncertain tasks. In this paper, as a tool to minimize the uncertainties and errors the neural network is applied to the concrete mix design. Input data to train and test the neural network are obtained numerically from the results of design following the concrete standard specifications of Korea. The 28-days compressive strengths which are variate according to the uncertainties and errors are considered. The results show that neural networks have a strong potential as a tool for concrete mix design.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.457-462
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• 1999

The purpose of this study is to design the requirements for the materials of stabilizing slurry and to determine the optimum slruuy mix design used in the underground wall of Inchon LNG #213 and 214 tank. After the materials and mix conditions of stabilizing slurry investigated and tested, we propose materials and optimum mix design according to testing items including funnel viscosity, we propose materials and optimum mix design according to testing items including funnel viscosity, fluid loss, cake thickness and specific gravity. As this results, we select optimum mix design that the upper limit ratio of bentonite is 2.0%, polymer is 0.1% considering the funnel viscosity and dispersion agent is 0.05% considering the fluid loss. Also we select all materials which are composed of GTC4 as bentonite, KSTP as polymer and Bentocryl as dispersion agent. All test results are satisfied our specifications for stabilizing slurry.

• Proceedings of the Korea Concrete Institute Conference
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• 2010.05a
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• pp.329-330
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• 2010

For the computerization of structural lightweight concrete mix design, mix design theories of ACI211.2-98(Standard Practice for Selecting Proportions for Structural Lightweight Concrete) are investigated and the mix design process is mathematized by Table Curve 2D and 3D software of Jandel company.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.108-113
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• 1996

Concrete mix degign and adjustments are somewhat complicated and time-consuming tasks in which various uncertainties and errors are involved and depend on the quality control test results. In this paper, as a tool to minimize the uncertainties and errors the neural network is applied to the concrete mix design. Input data to train and test the neural network are obtained from the results of design and adjustments following the concrete standard specifications of Korea. The results show that neural networks have a strong potential as a tool for concrete mix design.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.209-214
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• 1999

Strength provisions in Korea Concrete Institute code are more conservative that those in ACI code by increasing load factors and decreasing capacity reduction factors. Cement content of mix design in construction field is usually higher than the modified for standard deviation because of rigorous inspection. Higher cement content increases not only strengths but also heat of hydration, shrinkage and brittleness which are not beneficial. To reduce and optimize the cement content in current mix design of Korean Highway Corporation, properties of fresh and hardened concrete for 16 different mix proportions have been investigated. It is found that the chemical admixture and cement of current mix proportions for highway construction are somewhat higher than the optimum amount. Therefore, the optimum mix design for 16 different purposes has been proposed.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.11a
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• pp.101-103
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• 2011

Various desired performances of concrete cannot be always obtained by current conventional mix proportion methods for recycled aggregate concrete (RAC). This paper suggests a new design method of mix proportion for RAC to reduce the number of trial mixes using genetic algorithm (GA) which has been an optimization technique to solve the multi-object problem. In mix design method by GA, several fitness functions for the required properties of concrete, i.e., slump, strength, price, and carbonation speed coefficient were considered based on conventional data or fitness function. As a result, various optimum mix proportions for RAC that meet required performances were obtained and the risk evaluation was also conducted for selected mixtures.

• Computers and Concrete
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• v.3 no.5
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• pp.357-373
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• 2006

The concepts of four parameters of nominal water-cement ratio, equivalent water-cement ratio, average paste thickness, fly ash-binder ratio were introduced. It was verified that the four parameters and the mix proportion of mortar can be transformed each other. The behaviors (strength, workability, et al.) of mortar primarily determined by the mix proportion of mortar now depend on the four parameters. The prediction models of strength and workability of mortar were built based on artificial neural networks (ANNs). The calculation models of average paste thickness and equivalent water-cement ratio of mortar can be obtained by the reversal deduction of the two prediction models, respectively. A mortar mix proportion design algorithm was proposed. The proposed mortar mix proportion design algorithm is expected to reduce the number of trial and error, save cost, laborers and time.