Micro Structural Properties of Ternary Blended Concrete

The sum of CO2 that has been released into the atmosphere is roughly equal to the amount of cement produced. Cement manufacturing now consumes many natural resources and cement substitute materials in the analysis of Micro Structural Properties of Ternary Blended Concrete. The mixed proportion in this analysis is made of M30 Concrete. The cement is substituted with a mixture of two materials in amounts ranging from 10% to 50%. For the mix of materials, Fly Ash is kept constant. The specimen is a 150mmx150mmx150mm cube, and the concrete is cast in a 150mmx300mm cylinder. The cast specimens are held for 28 days to cure. Compressive and split tensile strength tests are used to achieve the results. The combination at 10%, at 20%, at 20%, and 20% produced better strength results in all proportions from 10% to 50%. Besides, scanning electron microscopy techniques were used to understand better phase changes and the formation of microstructures to maturing the combination of materials at various percentages. SEM was used to evaluate the microstructure of the concrete for five different varieties, which helps with solid growth. With the highest compressive strength gained among all the mixes from 10% to 50% with combinations for M30 grade of concrete at 28 days, significant innovative information on particle shape and microstructure was observed. Via SEM study, a good correlation of this Microscopical quantitative knowledge and material properties is also presented.

Micro Structural Properties of Ternary Blended Concrete

The sum of CO2 that has been released into the atmosphere is roughly equal to the amount of cement produced. Cement manufacturing now consumes many natural resources and cement substitute materials in the analysis of Micro Structural Properties of Ternary Blended Concrete. The mixed proportion in this analysis is made of M30 Concrete. The cement is substituted with a mixture of two materials in amounts ranging from 10% to 50%. For the mix of materials, Fly Ash is kept constant. The specimen is a 150mmx150mmx150mm cube, and the concrete is cast in a 150mmx300mm cylinder. The cast specimens are held for 28 days to cure. Compressive and split tensile strength tests are used to achieve the results. The combination at 10%, at 20%, at 20%, and 20% produced better strength results in all proportions from 10% to 50%. Besides, scanning electron microscopy techniques were used to understand better phase changes and the formation of microstructures to maturing the combination of materials at various percentages. SEM was used to evaluate the microstructure of the concrete for five different varieties, which helps with solid growth. With the highest compressive strength gained among all the mixes from 10% to 50% with combinations for M30 grade of concrete at 28 days, significant innovative information on particle shape and microstructure was observed. Via SEM study, a good correlation of this Microscopical quantitative knowledge and material properties is also presented.

Evaluation of Empirical Relation between Compressive and Flexural Strength of Concrete Partially Using Alccofine and Nano-Silica

In this paper, the flexural strength of concrete using alccofine and nano-silica was investigated experimentally and analytically. 15% alccofine and 3% nano-silica by weight of cement was used as a binary and ternary blend in three concrete grades M40, M50, and M60. Compressive strength and flexural strength were obtained experimentally by curing the specimens in water for 28 days. The empirical equation between compressive strength and flexural strength in the form of fr =bfc’n was obtained using regression analysis. The proposed empirical relation was compared with relations given by a code of practices and the relations reported by other researchers for predicting flexural strength using the compressive strength of concrete. The accuracy of the proposed empirical relation was validated using various statistical equations. From the experimental results, it was found that the cubic compressive strength and flexural strength of ternary blended concrete mixes using alccofine and nano-silica was 20 to 29% and 32 to 39 % higher compared to the control mixes. From the values of statistical equations, the proposed relation was found accurate. It showed less error compared to other relations and can be used to determine flexural strength results based on compressive strength data.

Freeze–Thaw Resistance of Ternary Blended Concrete Using Ferronickel Slag

The present study investigated the resistance of concrete blended with ground granulated blast furnace slag (GGBS) and ferronickel slag (FNS) to cycles of freeze and thaw. The replacement ratio of the binders was 0%, 50 wt% of GGBS and 30 wt% of GGBS + 20 wt% of FNS for O100, OG50 and OG30F20, respectively. Specimens consisted of cement paste and concrete kept at 0.45 water/binder ratio. After 28 days of curing, specimens were subjected to freeze and thaw cycles (300) for measuring the variation of strength, weight loss and fundamental transverse frequency. Simultaneously mercury intrusion porosimetry was performed to examine the pore structure modifications at 28 days. The hydration products for cement paste cured at each determined age were characterized by X-ray diffraction and the content of CH and CSH was obtained from thermogravimetric analysis (TGA). As a result, the ternary blended concrete specimens showed lower deterioration degree when subjected to the freeze and thaw cycles. This may be due to a latent hydraulic and/or pozzolanic reaction producing more CSH in the matrix, which in turn increases the volume of small pores. The increased content of C–S–H gel for OG30F20 was confirmed by TGA, accounting for 69.9%. However, the binder system consisting of ordinary Portland cement and GGBS did not exhibit higher resistance to the given deleterious environment, presumably due to a delayed hydration process.

Evaluation Compressive Strength of Cement-Limestone-Slag Ternary Blended Concrete Using Artificial Neural Networks (ANN) and Gene Expression Programming (GEP)

Limestone and slag blended concrete is an innovative concrete which belongs to the family of limestone calcined clay cement (LC3) concrete. Strength is an important property of structural concrete. This study shows artificial neural networks (ANN) and gene expression programming (GEP) models for predicting strength development of limestone and slag blended concrete. ANN model consists of an input layer, a hidden layer, and output layer. GEP model consists of the sum of three expression trees. The input parameters of ANN and GEP models are mixtures and ages. The output parameter is a strength. The correlation coefficients of ANN and GEP model are 0.99 and 0.98, respectively. Both ANN and GEP model can produce prediction results of the strength of ternary blended concrete reliably.