Impact strength and abrasion resistance of high strength concrete with rice husk ash and rubber tires

Barbosa, M. B.; Pereira, Adriana Maria; Akasaki, Jorge Luís; Fioriti, César Fabiano; Fazzan, João Victor; Tashima, Mauro M.; Bernabeu, J. J. P.; Melges, José Luiz Pinheiro

doi:10.1590/s1983-41952013000500007

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…La cascarilla de arroz proviene del molino arrocero de Sumber Jeruk, Jember, Java Oriental, Indonesia. Para obtener buenas características puzolánicas, la cascarilla de arroz debe quemarse en el rango de 600 0 C a 850 0 C (Barbosa et al, 2013). En este estudio se quemó a ± 650 0 C durante 24 horas.…”

Section: Ceniza De Cascarilla De Arroz (Cca)unclassified

“…La forma esférica de las partículas de CV incrementará la reacción aglutinante, reduciendo el consumo de agua, aglutinándose fácilmente y reduciendo el espacio entre los ingredientes mezclados (Manjunath and Ranganath, 2019). La forma de las partículas de CCA con orificios como esponja tendrá altos requerimientos de agua, por lo que su reacción es lenta (Barbosa et al, 2013). El contenido de sílice de la CT es menor que el de la CV, por lo que también en este caso la reacción es más lenta (Okoye et al, 2017).…”

Section: Tiempo De Fraguadounclassified

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Comparación de la adición de cenizas de cascarilla de arroz y cenizas de tejas a cemento de geopolímero en base a cenizas volantes con cemento Portland

et al. 2020

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The use of Portland cement is considered a very good material for making concrete. This is because many are found in building shops and it's high performance in making concrete. Research on alternative Portland cement is a worldwide priority for reducing CO emissions to the atmosphere. Alternative Portland cement is a material containing aluminosilicate which is dissolved with an alkaline solution to produce strong pozzolanic properties and replace the function of Portland cement. Natural aluminosilicates can be found in agricultural and industrial wastes. For example fly ash (FA), roof tile ash (RTA), rice husk ash (RHA), sugar cane bagasse ash (SCBA). This method estimates the development of mechanical properties of concrete with alternative portland cement with concrete with portland cement throughout the treatment process. The mechanical properties that will be seen are setting time and compressive strength. Alternative Portland cement uses the basic ingredients of fly ash aluminosilicate with an alkaline activator solution (NaOH, Na2SiO3) of 12 Molar. This study is based on experimental studies by replacing FA by 5% and 10% with RHA and RTA where the development of several mechanical properties will be investigated. The results show that several alternative portland cement mixes have similar mechanical properties to portland cement.

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Section: Ceniza De Cascarilla De Arroz (Cca)unclassified

Section: Tiempo De Fraguadounclassified

Comparación de la adición de cenizas de cascarilla de arroz y cenizas de tejas a cemento de geopolímero en base a cenizas volantes con cemento Portland

et al. 2020

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The Effect of Tire-Rubber Pretreatment on the Physical–Mechanical Properties and Durability of High-Performance Concrete

Silva¹,

Batista

Barbosa

et al. 2022

J. Mater. Civ. Eng.

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Prediction of Compressive Strengths for Rice Husks Ash incorporated concrete, Using Neural Network and Reviews

Ngandu¹

2021

ITECKNE

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Modelling of concrete that incorporates agricultural wastes such as rice husk ash (RHA) could potentially enhance utilization of green concrete and application of sustainable construction materials. This paper evaluations compressive strength prediction for rice husk ash (RHA) cementitious material incorporated concrete using artificial neural networks (ANNs) one of the various prediction methods. The research is based on various previous experimental studies.Literature reviews of 72 datasets for RHA incorporated concrete from 15 previous researches, were used and subjected to ANNs models, having learning rate of 0.06 with tanh activation functions. Four(4) input variables were considered, namely:- superplasticizer or water reducers variation from control (%), water to binder ratio, percentage of RHA and control compressive strengths. Output variable was compressive strength of RHA cementitious material incorporated concrete. The ANN with 15 neurons in the hidden layer was selected and indicated overall values of 5.10MPa, 0.99, 3.81MPa and 9.73% for the root mean square error (RMSE), absolute factor of variance (R2), mean absolute error (MAE) and mean absolute percentage error (MAPE) respectively and for individual training, validation/checking and testing datasets, the RMSE, R2, MAE and MAPE ranging between 3.98MPa-6.56MPa, 0.98-0.99, 3.44MPa-4.94MPa and 9.19%-12.41% respectively. Generally, both predicted and original dataset, indicated higher and lower strength values for 5-10% and 15-30% RHA incorporated cementitious material concrete respectively compared to the control strengths.Considering that the study utilized data from different sources and with a wide range of concrete strengths the selected ANN showed relatively good performance. The study provides an indicator that machine learning techniques could accurately predict green concrete strength. Based on model performance the percentage RHA cementitious materials in concrete and the other 3 input variable had a significant impact on concrete strengths. Future research should be conducted to predict green concrete focused on particular concrete class.

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Impact strength and abrasion resistance of high strength concrete with rice husk ash and rubber tires

Cited by 4 publications

References 3 publications

Comparación de la adición de cenizas de cascarilla de arroz y cenizas de tejas a cemento de geopolímero en base a cenizas volantes con cemento Portland

Comparación de la adición de cenizas de cascarilla de arroz y cenizas de tejas a cemento de geopolímero en base a cenizas volantes con cemento Portland

The Effect of Tire-Rubber Pretreatment on the Physical–Mechanical Properties and Durability of High-Performance Concrete

Prediction of Compressive Strengths for Rice Husks Ash incorporated concrete, Using Neural Network and Reviews

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