Modelling the Yield Stress of Fly-Ash Added Superplasticized Cement Paste at Different Temperatures Using Artificial Neural Network

2022 ◽  
Vol 1048 ◽  
pp. 366-375
Author(s):  
Pavan Chandrasekar ◽  
Anjala Nourin ◽  
Addepalli Sri Naga Bhushana Aravind Gupta ◽  
Bavineni Venkata Jyoshna ◽  
Dhanya Sathyan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fly Ash ◽  
Yield Stress ◽  
Cement Paste ◽  
Test Temperature ◽  
Fresh Concrete ◽  
Rheological Parameters ◽  
Different Temperatures ◽  
Artificial Neural

Abstract: Rheology is the science that concerns the flow of liquids, and the distortion of solids under an applied force. The study of the rheology of concrete determines the properties of fresh concrete. The rheological parameters are affected by temperature, stress conditions and several other factors. The main intention of this research is to model the rheological parameters of the fly ash incorporated cement with various types of superplasticizers exposed under different temperatures using an Artificial Neural Network. Test data were generated by performing rheological tests on cement paste at three distinct temperatures (15, 27, 35°C). Mixes were prepared using OPC, fly ash (15, 25, 35%) and superplasticizers of four different families. By conducting experiments, 252 data have been generated by modifying the combination of fly-ash, superplasticizer, and test temperature. Among the 252 data, 80% has been utilized for training and 20% is utilized for predicting the model’s accuracy. The input layer of the model consists of test temperature, the amount of fly ash replaced, cement and water content, and four different groups of superplasticizers. The cement paste’s yield stress was the output parameter of the model. The model generated data has been compared with the experimentally generated data to determine the accuracy of the model.Keywords: Rheology, Fly Ash, Superplasticizer, Temperature, ANN

Use of Artificial Neural Network for Modelling the Interaction between Fly Ash and Lime under Steam Curing

2007 ◽  
Vol 66 (4) ◽  
pp. 187-192
Author(s):  
S. Maitra ◽  
A. J. Pal ◽  
N. Bandyopadhyay ◽  
A. Basumajumdar ◽  
A. K. Das
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fly Ash ◽  
Steam Curing ◽  
Artificial Neural

scholarly journals Effects of Volume Fraction and Surface Area of Aggregates on the Static Yield Stress and Structural Build-Up of Fresh Concrete

2020 ◽  
Author(s):  
Irina Ivanova ◽  
Viktor Mechtcherine
Keyword(s):  
Rheological Properties ◽  
Yield Stress ◽  
Surface Area ◽  
Cement Paste ◽  
Volume Fraction ◽  
Fresh Concrete ◽  
Total Surface Area ◽  
Rheological Parameters ◽  
Static Yield ◽  
Static Yield Stress

With increasing interest in the use of additive manufacturing techniques in the construction industry, static rheological properties of fresh concrete have necessarily come into focus. In particular, the knowledge and control of static yield stress (SYS) and its development over time are crucial for mastering formwork-free construction, e.g. by means of layered extrusion. Furthermore, solid understanding of the influences of various concrete constituents on the initial SYS of the mixture and the structural build-up rate is required for purposeful material design. This contribution is concentrated on the effect of aggregates on these rheological parameters. The volume fraction of aggregates was varied in the range of 35 to 55 % by volume under condition of constant total surface area of the particles. The total surface area per unit volume of cement paste was equal to 5.00, 7.25 and 10.00 m²/l, conditioned on the constant volume fraction of aggregates. Both variations were enabled by changing the particle size distributions of the aggregates while holding the cement paste composition constant for all concrete mixtures. To characterise the SYS and the structural build-up, constant shear rate tests with a vane-geometry rotational rheometer were performed. It was found that in the ranges under investigation the variation in volume fraction had a more pronounced effect on the static rheological properties of concrete than did the variation in surface area. An accurate mathematical description of the relationship between the initial SYS of concrete and the relative volume fraction of aggregate based on the Chateau-Ovarlez-Trung model was proposed. Challenges in deriving a similar relationship for the structural build-up rate of concrete were highlighted.

scholarly journals Predicting shrinkage of alkali-activated blast furnace-fly ash mortars using artificial neural network (ANN)

2021 ◽  
Vol 124 ◽  
pp. 104265
Author(s):  
Elijah Adesanya ◽  
Adeyemi Aladejare ◽  
Adeolu Adediran ◽  
Abiodun Lawal ◽  
Mirja Illikainen
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Blast Furnace ◽  
Fly Ash ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Alkali Activated

scholarly journals Effects of Volume Fraction and Surface Area of Aggregates on the Static Yield Stress and Structural Build-Up of Fresh Concrete

Materials ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1551 ◽  
Author(s):  
Irina Ivanova ◽  
Viktor Mechtcherine
Keyword(s):  
Rheological Properties ◽  
Yield Stress ◽  
Surface Area ◽  
Cement Paste ◽  
Volume Fraction ◽  
Fresh Concrete ◽  
Total Surface Area ◽  
Rheological Parameters ◽  
Static Yield ◽  
Static Yield Stress

With increasing interest in the use of additive manufacturing techniques in the construction industry, static rheological properties of fresh concrete have necessarily come into focus. In particular, the knowledge and control of static yield stress (SYS) and its development over time are crucial for mastering formwork-free construction, e.g., by means of layered extrusion. Furthermore, solid understanding of the influences of various concrete constituents on the initial SYS of the mixture and the structural build-up rate is required for purposeful material design. This contribution is concentrated on the effect of aggregates on these rheological parameters. The volume fraction of aggregates was varied in the range of 35% to 55% by volume under condition of constant total surface area of the particles. The total surface area per unit volume of cement paste was equal to 5.00, 7.25 and 10.00 m²/L, conditioned on the constant volume fraction of aggregates. Both variations were enabled by changing the particle size distributions of the aggregates while holding the cement paste composition constant for all concrete mixtures. To characterise the SYS and the structural build-up, constant shear rate tests with a vane-geometry rotational rheometer were performed. It was found that in the ranges under investigation the variation in volume fraction had a more pronounced effect on the static rheological properties of concrete than did the variation in surface area. An accurate mathematical description of the relationship between the initial SYS of concrete and the relative volume fraction of aggregate based on the Chateau–Ovarlez–Trung model was proposed. Challenges in deriving a similar relationship for the structural build-up rate of concrete were highlighted.

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