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ALI NAZARI
Articles written in Bulletin of Materials Science
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Volume 35 Issue 6 November 2012 pp 1019-1029
In the present work, percentage of water absorption of geopolymers made from seeded fly ash and rice husk bark ash has been predicted by artificial neural networks. Different specimens, made from a mixture of fly ash and rice husk bark ash in fine and coarse form together with alkali activatormade of water glass and NaOH solution, were subjected to permeability tests at 7 and 28 days of curing. The curing regime was different: one set cured at room temperature until reaching to 7 and 28 days and the other sets were oven cured for 36 h at a range of 40–90 °C and then cured at room temperature for 7 and 28 days. To build the model, training and testing using experimental results from 120 specimens were conducted. According to these input parameters, in the neural networks model, the percentage of water absorption of each specimen was predicted. The training and testing results in the neural networks model have shown a strong potential for predicting the percentage of water absorption of the geopolymer specimens.
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Volume 45 All articles Published: 31 March 2022 Article ID 0064
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Bulletin of Materials Science
Volume 46, 2023
All articles
Continuous Article Publishing mode
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Bulletin of Materials Science | News
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Dr Shanti Swarup Bhatnagar for Science and Technology
Posted on October 12, 2020Prof. Subi Jacob George — Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bengaluru
Chemical Sciences 2020Prof. Surajit Dhara — School of Physics, University of Hyderabad, Hyderabad
Physical Sciences 2020 -
Editorial Note on Continuous Article Publication
Posted on July 25, 2019Click here for Editorial Note on CAP Mode
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