The Effect of Alkaline Treatment on Mechanical Performance of Natural Fibers-Reinforced Plaster: Part II Optimization Comparison between ANN and RSM Statistics

被引:19
作者
Boumaaza, Messaouda [1 ]
Belaadi, Ahmed [2 ,3 ]
Bourchak, Mostefa [4 ]
机构
[1] Univ 8 Mai 1945, Lab Genie Civil & Hydraul LGCH, Guelma, Algeria
[2] Fac Technol Univ, Dept Genie Mecan, El Liadaiek 21000, Skikda, Algeria
[3] Univ 8 Mai 1945 Guelma, Lab Lspn, Guelma, Algeria
[4] King Abdulaziz Univ, Aerosp Engn Dept, Jeddah, Saudi Arabia
关键词
Natural fibers; plaster; artificial neural network; flexural properties; optimization; COMPRESSIVE STRENGTH; COMPOSITES; CONCRETE; PREDICTION; BEHAVIOR; TAGUCHI; KENAF; HEMP;
D O I
10.1080/15440478.2021.1964129
中图分类号
TB3 [工程材料学]; TS1 [纺织工业、染整工业];
学科分类号
0805 ; 080502 ; 0821 ;
摘要
The present study is a continuation of a previously published by the authors. In Part I, mechanical data of Alkaline-treated natural fibers-reinforced plaster was examined using response surface methodology (RSM) statistics, while in this work (Part II), the data are analyzed using Artificial neural network (ANN) statistics. Many studies have focused on substituting synthetic fibers by natural fibers in plaster matrix. The present study reports ANN statistics data analysis on the mechanical properties of plaster and natural fibers. ANN and RSM methods are employed and their findings discussed. During this study, flexural properties of sodium hydroxide solution (NaOH)-treated natural fibers in plaster mortars were investigated. Experimental data effects were established by analysis of variance (ANOVA) method. Fiber length optimization and NaOH percentage treatment of fibers were also performed utilizing desirability function DF to obtain maximum flexural properties. Experimental results showed good agreement with those obtained statistically. The ANN and RSM models also have correlated highly to the experimental data. However, the ANN model proves more to be accurate.
引用
收藏
页码:8367 / 8382
页数:16
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