کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6701711 | 1428457 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Artificial neural network evaluation of cement-bonded particle board produced from red iron wood (Lophira alata) sawdust and palm kernel shell residues
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
ANNMORPKSThickness swelling - تورم ضخیمWater absorption - جذب آبWaste - زبالهArtificial Neural Network - شبکه عصبی مصنوعیmodulus of elasticity - مدول الاستیسیتهModulus of rupture - مدول پارگیConstruction material - مصالح ساختمانیMOE - وزارت صنایعPalm kernel shell - پوسته کرنل پالمParticleboard - کمربند
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
As a way of promoting environmental sustainability, it becomes paramount to salvage the quantity of agricultural wastes being destroyed or disposed into the environment. A novel strategy to reduce these wastes is by reusing them. In the present study, the physical and mechanical properties of particleboards produced from red iron wood (Lophira alata) sawdust and palm kernel shell (PKS) was evaluated by artificial neural network (ANN). The production of this particle boards involved the synergistic combination of effective parameters such as percentage composition of cement, sawdust and palm kernel shell varied between 25-40, 20-50 and 20-50 respectively. The boards were tested for physical properties such as water absorption (WA), thickness swelling (TS), density and mechanical properties such as modulus of rupture (MOR) and modulus of elasticity (MOE). The networks was trained and tested by Multilayer Normal Feed Forward Perceptron (MNFFP), with a quick propagation learning algorithm. The performance of the ANN network shows it has a high potential for predicting the properties of cement bonded particle board.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Case Studies in Construction Materials - Volume 9, December 2018, e00185
Journal: Case Studies in Construction Materials - Volume 9, December 2018, e00185
نویسندگان
Olumoyewa D. Atoyebi, Temitope F. Awolusi, Iyinoluwa E.E. Davies,