• Computers and Concrete
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• v.25 no.1
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• pp.83-94
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• 2020

The use of fly ash in modern-day concrete technology aiming sustainable constructions is on rapid rise. Fly ash, a spinoff from coal calcined thermal power plants with pozzolanic properties is used for cement replacement in concrete. Fly ash concrete is cost effective, which modifies and improves the fresh and hardened properties of concrete and additionally addresses the disposal and storage issues of fly ash. Soft computing techniques have gained attention in the civil engineering field which addresses the drawbacks of classical experimental and computational methods of determining the concrete compressive strength with varying percentages of fly ash. In this study, models based on soft computing techniques employed for the prediction of the compressive strengths of fly ash concrete are collected from literature. They are classified in a categorical way of concrete strengths such as control concrete, high strength concrete, high performance concrete, self-compacting concrete, and other concretes pertaining to the soft computing techniques usage. The performance of models in terms of statistical measures such as mean square error, root mean square error, coefficient of correlation, etc. has shown that soft computing techniques have potential applications for predicting the fly ash concrete compressive strengths.

• Computers and Concrete
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• v.34 no.2
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• pp.137-149
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• 2024

In order to study the triaxial mechanical behavior of steel fiber reinforced high performance concrete (SFRHPC), the standard triaxial compression tests with four different confining pressures are performed on the cylindrical specimens. Three different steel fiber volumes (0, 1% and 2%) are added in the specimens with diameter of 50 mm and height of 100 mm. Test results show that the triaxial compressive strength and peak strain increase with the increasing of fiber content at the same confining pressure. At the same steel fiber content, the triaxial compressive strength and peak strain increases with the confining pressure. The compressive strength growth rate declines as the confining pressure and steel fiber content increases. Longitudinal cracks are dominant in specimens with or without steel fiber under uniaxial compression loading. While with the confining pressure increases, diagonal crack due to shear is obvious. The Mohr-Coulomb criterion is illustrated can be used to describe the failure behavior, and the cohesive force increases as steel fiber content increases. Finally, the numerical model is built by using the PFC3D software. In the numerical model a index is introduced to reflect the effect of steel fiber content on the triaxial compressive behavior. The simulating stress-strain curve and failure mode of SFRHPC are agree well with the experimental results.

• Journal of the Korea Institute of Building Construction
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• v.17 no.2
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• pp.167-174
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• 2017

This research investigated the mechanical performance of slurry infiltrated high performance fiber reinforced cementitious composite (SI-HPFRCC) with high volume blast furnace slag powder. Hooked-end steel fibers (volume fraction of 6.4%) were used for the fabrication of SI-HPFRCC. A series of mechanical performance test was conducted including strength and toughness of SI-HPFRCC in compressive and flexural mode at four different ages. Compressive and flexural strength tests of the slurry matrix at the same ages were also conducted in order to evaluate fiber reinforcing effect on the mechanical performance. The flexural response of SI-HPFRCC shows an increasing brittleness with age. The compressive response also shows an increasing brittleness with age but the degree of brittleness is much lower than the flexural case. In terms of strength, SI-HPFRCC shows about 140~190% of compressive strength improvement and 440~500% flexural strength improvement comparing to the slurry matrix.

• Journal of the Korea Concrete Institute
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• v.23 no.3
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• pp.365-376
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• 2011

The current Concrete Structural Design Code (2007) prescribe the equivalent rectangular stress block of the ACI 318 Building Code as concrete compressive stress distribution for design of concrete structures. The rectangular stress block may be enough for flexural strength calculation, but realistic stress-strain relationship is required for performance verification at selected limit state in performance-based design. Moreover, the ACI rectangular stress block provides non-conservative flexural strength for high strength concrete columns. Therefore a new stress distribution model is required for development of performance-based design code. This paper proposes a concrete compressive stress-strain distribution model for design and performance verification. The proposed model has a parabolic-rectangular shape, which is adopted by Eurocode 2 and Japanese Code (JSCE). It was developed by investigation of experimental test results conducted by the authors and other researchers. The test results cover high strength concrete as well as normal strength concrete. The stress distribution parameters of the proposed models are compared to those of the ACI 318 Building Code, Eurocode 2, Japanese Code (JSCE) and Canadian Code (CSA) as well as the test results.

• 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.

• Computers and Concrete
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• v.21 no.3
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• pp.345-353
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• 2018

This paper approaches to improve the mechanical and durability properties of low calcium fly ash geopolymer concrete with the addition of Alccofine as a mineral admixture. The mechanical and durability performance of GPC was assessed by means of compressive strength, flexural strength, permeability, water absorption and permeable voids tests. The correlation between compressive strength and flexural strength, depth of water penetration and percentage permeable voids are also reported. Test results show that addition of Alccofine significantly improves the mechanical as well as permeation properties of low calcium fly ash geopolymer concrete. Very good correlations were noted between the depth of water penetration and compressive strength, percentage permeable voids and compressive strength as well as between compressive strength and flexural strength.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.542-549
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• 2004

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. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.979-984
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• 2003

Quality control of ready-mixed concrete is most important in the production step because, the performance of hardened concrete is revealed due to ready-mixed concrete. Hardened concrete has several properties physically. Above all things compressive strength of concrete has a greate effect in the design of structures, analysis, and durability. Compressive strength is simple predicted by w/c up to date, but there are some limits because different compressive strengths can be revealed in the same w/c. Therefore this study contributes to the quality control of ready-mixed concrete through statistical analysis for the relation between mix factors in mix design and compressive strength, predictable equation for compressive strength.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.4
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• pp.174-181
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• 2021

Lightweight geopolymers were fabricated by using IGCC (integrated gasification combined cycle) slag and Si sludge which are classified as general wastes (recyclable resources). Three curing methods were tried to investigate the changes in compressive strength and density according to the curing method and immersion time. Immersion period was tried up to 21 days to observe long-term performance in water. Compressive strength of the specimens cured in oven decreased abruptly with an increase in immersion time. Compressive strength of the specimen cured in autoclave was low after 3 and 7 day immersion; however, increased rapidly after 21 day immersion. On the contrary, compressive strength of the specimen cured in autoclave and oven was high but substantially decreased after 21 day immersion. Conclusively, it was speculated that oven curing is effective for the compressive strength development at early age; however, autoclave curing is more desirable for the long-term performance in water.

• Advances in concrete construction
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• v.1 no.2
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• pp.151-162
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• 2013

The performance characteristics of high-strength and high-performance concrete are discussed in this review. Recent developments in the field of high-performance concrete marked a giant step forward in high-tech construction materials with enhanced durability, high compressive strength and high modulus of elasticity particularly for industrial applications. There is a growing awareness that specifications requiring high compressive strength make sense only when there are specific strength design advantages. HPC today employs blended cements that include silica fume, fly ash and ground granulated blast-furnace slag. In typical formulations, these cementitious materials can exceed 25% of the total cement by weight. Silica fume contributes to strength and durability; and fly ash and slag cement to better finish, decreased permeability, and increased resistance to chemical attack. The influences of various mineral admixtures such as fly ash, silica fume, micro silica, slag etc. on the performance of high-strength concrete are discussed.