Modeling of Mechanical Properties of Wood-Polymer Composites with Artificial Neural Networks
Yazarlar (3)
Dr. Öğr. Üyesi Mustafa Altay EROĞLU Karabük Üniversitesi, Türkiye
Prof. Dr. Suat ALTUN Karabük Üniversitesi, Türkiye
Doç. Dr. Hasan Hüseyin Ciritcioğlu Düzce Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
|
||
| Dergi Adı | Bioresources (Q2) | ||
| Dergi ISSN | 1930-2126 Dergi Bilgileri (2024) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2024 |
| Cilt / Sayı / Sayfa | 19 / 3 / 4468–4485 | DOI | 10.15376/biores.19.3.4468-4485 |
| Makale Linki | https://bioresources.cnr.ncsu.edu/wp-content/uploads/2024/05/BioRes_19_3_4468_Eroglu_AC_Model_Mechan_Props_Wood_Polymer_Composite_ANN_23240.pdf | ||
| UAK Araştırma Alanları |
Ahşap Esaslı Kompozitler
|
||
| Özet |
| Mechanical properties (tensile strength (TS), modulus of elasticity in tensile (MET), flexural strength (FS), modulus of elasticity (MOE)) of the material to be obtained depending on the production parameters in the production of high-density polyethylene (HDPE) wood-polymer composites with Scots pine wood flour additive were predicted using Artificial Neural Networks (ANN) model and without destructive testing. In the first stage of the study, an ANN model was developed using data from 56 different studies in the literature on the mechanical properties of wood polymer composites. In the second stage, in order to determine the reliability of the model, output values were estimated using input parameters that had not been used in training and testing of the model. Based on the same input parameters, test specimens were produced and mechanical tests were performed. The results obtained from the experiments and … |
| Anahtar Kelimeler |
| Flexural strength | HDPE | MAPE | Modulus of elasticity | Tensile strength |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 7 |
| Scopus | 5 |
| Google Scholar | 7 |