Evaluation of strength of mortar using different saw waste with sand and model development

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• 作者：H. M. A. Mahzuz ; M. Ahmed ; M. M. Hossain ; M. M. Islam…
• 关键词：ANN ; biomaterial ; density ; mortar ; mathematical model ; strength
• 刊名：KSCE Journal of Civil Engineering
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：20
• 期：7
• 页码：2822-2831
• 全文大小：1,831 KB
• 刊物类别：Engineering
• 刊物主题：Civil Engineering
  Industrial Pollution Prevention
  Automotive and Aerospace Engineering and Traffic
  Geotechnical Engineering
  
• 出版者：Korean Society of Civil Engineers
• ISSN：1976-3808
• 卷排序：20

文摘

In this study saw wastes of wood, rattan and bamboo were used in mortar as a partial replacement of fine aggregate at different proportion. The variation of strength with time, density and water absorption, modulus of elasticity, and poisons ratio were identified. The test result was verified with the standard of mortar strength. Comparing to sand, being lighter in weight the above mentioned saw wastes decreased the weight of mortar. It can be considered as a new possibility of producing lightweight mortar as a building material. The test values were checked/verified using Artificial Neural Network (ANN). Also multivariable equations were generated to predict the strength of mortar. Finally it was seen that prediction using ANN has closer position with the test result instead of the equations.