• Advances in concrete construction
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• v.9 no.4
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• pp.345-354
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• 2020

Cement is the most significant component in concrete. Large scale manufacturing of cement consumes more energy and release harmful products (Carbon dioxide) into the atmosphere that adversely affect the environment and depletes the natural resources. A lot of research is going on in globally concentrating on the recycling and reuse of waste materials from many industries. A major share of research is focused on finding cementitious materials alternatives to ordinary Portland cement. Many industrial waste by-products such as quartz powder, metakaolin, ground granulated blast furnace slag, silica fume, and fly ash etc. are under investigations for replacement of cement in concrete to minimize greenhouse gases and improve the sustainable construction. In current research, the effects of a new generation, ultra-fine material i.e., alccofine which is obtained from ground granulated blast furnace slag are studied as partial replacement by 25% and with varying amounts of sulfonated naphthalene formaldehyde (i.e., 0.3%, 0.35% and 0.40%) on mechanical, water absorption, thermal and microstructural properties of concrete. The results showed moderate improvement in all concrete properties. Addition of SNF with combination of alccofine showed a significant enhancement in fresh, hardened properties and water absorption test as well as thermal and microstructural properties of concrete.

• Computers and Concrete
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• v.19 no.2
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• pp.133-142
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• 2017

Two-stage concrete (TSC), also known as pre-placed aggregate concrete, is characterized by its unique placement technique, whereby the coarse aggregate is first placed in the formwork, then injected with a special grout. Despite its superior sustainability and technical features, TSC has remained a basic concrete technology without much use of modern chemical admixtures, new binders, fiber reinforcement or other emerging additions. In the present study, an experimental database for TSC was built. Different types of cementitious binders (single, binary, and ternary) comprising ordinary portland cement, fly ash, silica fume, and metakaolin were used to produce the various TSC mixtures. Different dosages of steel fibres having different lengths were also incorporated to enhance the mechanical properties of TSC. The database thus created was used to develop fuzzy logic models as predictive tools for the grout flowability and mechanical properties of TSC mixtures. The performance of the developed models was evaluated using statistical parameters and error analyses. The results indicate that the fuzzy logic models thus developed can be powerful tools for predicting the TSC grout flowability and mechanical properties and a useful aid for the design of TSC mixtures.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.671-681
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• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

• Computers and Concrete
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• v.24 no.4
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• pp.329-345
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• 2019

Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method, available in the literature, which can reliably predict mortar strength based on its mix components. This limitation is due to the highly nonlinear relation between the mortar's compressive strength and the mixed components. In this paper, the application of artificial neural networks for predicting the compressive strength of mortars has been investigated. Specifically, surrogate models (such as artificial neural network models) have been used for the prediction of the compressive strength of mortars (based on experimental data available in the literature). Furthermore, compressive strength maps are presented for the first time, aiming to facilitate mortar mix design. The comparison of the derived results with the experimental findings demonstrates the ability of artificial neural networks to approximate the compressive strength of mortars in a reliable and robust manner.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3617-3627
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• 2023

This study presents a method to solidify spent ion-exchange resin (IER) in a metakaolin-based geopolymer and shows results of mechanical strength, immersion, leaching, irradiation, and thermal cycling tests for waste acceptance criteria (WAC) to repository. The geopolymer waste form with 20 wt% of simulated spent IER met the WAC in South Korea (ROK), and the leaching tests of various sized-waste forms up to 15.0 × 30.0 cm and waste loadings up to 20 wt% for 1-5 d and 1-90 d achieved a leachability index, L_i > 6. In a leaching test for 5 d, the cumulative fraction leached (CFL) for Cs, which leached the most, was linearly correlated with the square root of leaching time for all waste forms, and L_i increased as the size of the waste form increased. The CFL was also correlated with elapsed time in the 90 d leaching test. The correlations among CFL, time, and volume-to-surface area ratio of waste forms used to estimate the L_i of Cs of a 200-L sized geopolymer with 15 wt% IER showed the L_i values as 14.73 (5 d) and 17.71 (90 d), respectively, indicating that the large-sized geopolymer waste form met the WAC.

• Journal of the Korean Ceramic Society
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• v.52 no.4
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• pp.253-263
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• 2015

Ordinary Portland cement is a widely favored construction material because of its good strength and durability and its reasonable price; however, spalling behaviour during fire exposure can be a serious risk that can lead to strength degradation or collapse of a building. Geopolymers, which can be synthesized by mixing aluminosilicate source materials such as metakaolin and fly ash, and alkali activators, are resistant to fire. Because the chemical composition of geopolymers controls the properties of the geopolyers, geopolymers with various Si:Al ratios were synthesized and evaluated as fire resistant construction materials. Rejected fly ash generated from a power plant was quantitatively analyzed and mixed with alkali activators to produce geopolymers having Si:Al ratios of 1.5, 2.0, and 3.5. Compressive strength of the geopolymers was measured at 28 days before and after heating at $900^{\circ}C$. Geopolymers having an Si:Al ratio of 1.5 presented the best fire resistance, with a 44% increase of strength from 29 MPa to 41 MPa after heating. This material also showed the least expansion-shrinkage characteristics. Geopolymer mortar developed no spalling and presented more than a 2 h fire resistance rating at $1,050^{\circ}C$ during the fire testing, with a cold side temperature of $74^{\circ}C$. Geopolymers have high potential as a fire resistant construction material in terms of their increased strength after exposure to fire.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.4
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• pp.128-135
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• 2012

Autoclaved lightweight concrete, also known as autoclaved aerated concrete(AAC) or autoclaved cellular concrete (ACC), is made with fine silica powder, quik lime, cement, and an Al powder. ALC contains 70~80% air. The lightweight material offers excellent sound and thermal insulation, and like all cement-based materials, is strong and fire resistant. However, ALC have high water absorption, low compressive strength and popout the origin of the low surface strength in its properties. These properties make troubles under construction such as cracking and popout. Thus, this study is to improve the fundamental strength by controls of increasing of admixtures, gypsum and silica powder size. Admixtures make use of metakaolin and silica fume. From the test result, the ALC using admixture have a good fundamental properties compared with plain ALC. Compressive strength, specific strength and abrasion's ratio were improved depending on increasing admixtures ratio's, gypsum and silica powder size.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.2
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• pp.127-134
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• 2021

A hydrophobic emulsion consisting of PMHS and PVA was mixed into a cement mortar to observe changes in cement hydrate and microstructure, and to experimentally evaluate compressive strength and flexural strength. The hydrophobic emulsion was added with metakaolin and PVA fibers, and the stirring speed and sequence were adjusted to prepare a shell-concept hydrophobic emulsion. It was then mixed when mixing mortar to enhance filling of the internal pores and change of the hydrates. It was observed that the mortar mixed with a hydrophobic emulsion was filled with micropores and a coating film was formed on the surface of the hydrates by the emulsion. It was analyzed that the total pore area and porosity of the mortar mixed with the emulsion decreased from 30% to 60% compared to OPC, excluding the 50MK variable, which was extremely reduced and the median pore diameter decreased in some variables. It was also found that the compressive strength of the mortar mixed with emulsion 1% was increased up to 20%, but the strength of the mortar specimen mixed with 2% decreased to 50%.

• Advances in concrete construction
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• v.8 no.1
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• pp.65-76
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• 2019

This paper investigates the effect of recycled glass powder (RGP) on flowing properties of self-compacting mortars (SCMs) containing different ratios of fillers and superplasticizer dosages. Fly ash (FA), nano-silica (NS), micro-silica (MS), metakaolin (MK) and rice husk ash (RHA) are used as fillers and their synergistic effect with RFP is studied. The effects of fillers and high-range water reducer (HRWR) on flowing ability of mortars are primarily determined by slump flow and V-funnel flow time tests. The results showed that for composites with a higher RGP content, the mortar flowing ability increased but tended to decrease when the composites containing 10% MK or 5% RHA. However, the flowing ability of samples incorporating 5% RGP and 10% SF or 25% FA showed an opposite result that their slump flow spread decreased and then increased with increasing RGP content. For specimens with 3% NS, the influence of RGP content on flowing properties was not significant. Except RHA and MS, the fillers studied in this paper could reduce the dosage of HRWR required for achieving the same followability. Also, the mixture parameters were determined and indicated that the flowability of mixtures was also affected by the content of sand and specific surface area of cement materials. It is believed that excess fine particles provided ball-bearing effect, which could facilitate the movement of coarse particles and alleviate the interlocking action among particles. Also, it can be concluded that using fillers in conjunction with RGP as cementitious materials can reduce the material costs of SCM significantly.

• Computers and Concrete
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• v.27 no.4
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• pp.319-332
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• 2021

The performance of gene expression programming (GEP) in predicting the compressive strength of bacteria-incorporated geopolymer concrete (GPC) was examined in this study. Ground-granulated blast-furnace slag (GGBS), new bacterial strains, fly ash (FA), silica fume (SF), metakaolin (MK), and manufactured sand were used as ingredients in the concrete mixture. For the geopolymer preparation, an 8 M sodium hydroxide (NaOH) solution was used, and the ambient curing temperature (28℃) was maintained for all mixtures. The ratio of sodium silicate (Na2SiO3) to NaOH was 2.33, and the ratio of alkaline liquid to binder was 0.35. Based on experimental data collected from the literature, an evolutionary-based algorithm (GEP) was proposed to develop new predictive models for estimating the compressive strength of GPC containing bacteria. Data were classified into training and testing sets to obtain a closed-form solution using GEP. Independent variables for the model were the constituent materials of GPC, such as FA, MK, SF, and Bacillus bacteria. A total of six GEP formulations were developed for predicting the compressive strength of bacteria-incorporated GPC obtained at 1, 3, 7, 28, 56, and 90 days of curing. 80% and 20% of the data were used for training and testing the models, respectively. R2 values in the range of 0.9747 and 0.9950 (including train and test dataset) were obtained for the concrete samples, which showed that GEP can be used to predict the compressive strength of GPC containing bacteria with minimal error. Moreover, the GEP models were in good agreement with the experimental datasets and were robust and reliable. The models developed could serve as a tool for concrete constructors using geopolymers within the framework of this research.