Prediction of Optimum Expanded Polystyrene Densities for Best Thermal Insulation Performances of Polystyrene Composite Particleboards by Using Artificial Neural Network

• Published in: Drvna industrija Vol. 73; no. 4; pp. 385 - 395
• Main Authors: Ozturk, Hasan, Demir, Aydin, Demirkir, Cenk
• Format: Journal Article
• Language: English
• Published: University of Zagreb, Faculty of Forestry and Wood Technology 17.11.2022
• Subjects: ann; eps; polystyrene composite particleboard; thermal conductivity; thermal insulation
• ISSN: 0012-6772; 1847-1153
• DOI: 10.5552/drvind.2022.2119

The objective of this study is to predict the optimum expanded polystyrene (EPS) densities for the best insulation properties of the particleboards manufactured with waste EPS instead of formaldehyde-based adhesives used in particleboard production with artificial neural network (ANN). For this purpose, the waste EPS particles of five different densities were used in the production of composite particleboards. The experimental dana used in the study were obtained from the previous study. Half of the beech, poplar, alder, pine and spruce chips were dried in a drying oven and the other half were naturally conditioned at room temperature, and then 18 mm thick three-layer composite particleboards were produced. The thermal conductivity of panels was determined according to ASTM C 518. The prediction model with the best performance and acceptable deviations was determined by using statistical and graphical comparisons between the experimental data and the prediction values obtained as a result of ANN analysis. Then, using this prediction model, the thermal conductivity coefficient values were estimated for the intermediate EPS densities that were not experimentally tested. According to the analysis findings, the thermal insulation performance for both beech and spruce polystyrene composite particleboards (PCP) panels increased with using of waste EPS foams with a density of 30 kg/m3. The lowest thermal conductivity values were obtained from the EPS waste foams with the density of 18, 13 and 22 kg/m3 for the PCP panels produced with poplar, alder and pine in the natural drying, respectively. In the technical drying, these values were found to be 15, 14 and 11-13 kg/m3, respectively. Technical drying showed much better thermal performance than natural drying while poplar indicated the best performance among the wood species. Cilj je ove studije primjenom umjetne neuronske mreže (ANN) predvidjeti optimalne gustoće ekspandiranog polistirena (EPS) radi postizanja najboljih izolacijskih svojstava iverice proizvedene s otpadnim EPS-om umjesto s ljepilom na bazi formaldehida, kakvo se rabi u proizvodnji iverice. Stoga je za proizvodnju iverice upotrijebljen otpadni EPS pet različitih gustoća. Eksperimentalni podatci primijenjeni u studiji dobiveni su prijašnjim istraživanjem. Jedna je polovica iverja bukovine, topolovine, johovine, borovine i smrekovine osušena u sušioniku, a druga je polovica iverja kondicionirana na sobnoj temperaturi. Od osušenoga i kondicioniranog iverja proizvedene su troslojne kompozitne iverice debljine 18 mm. Toplinska vodljivost ploča određena je metodom ASTM C 518. Predikcijski model najboljih svojstava i prihvatljivih devijacija određen je statističkom i grafičkom usporedbom eksperimentalnih podataka s vrijednostima predviđenima ANN analizom. Potom su primjenom predikcijskog modela procijenjeni koeficijenti toplinske vodljivosti za one gustoće ekspandiranog polistirena koje nisu eksperimentalno ispitane. Prema toj analizi, termoizolacijska svojstva polistirenske kompozitne iverice (PCP) od bukovine i smrekovine poboljšana su pjenom od otpadnog EPS-a gustoće 30 kg/m3. Najniže vrijednosti toplinske vodljivosti za polistirensku kompozitnu ivericu od prirodno osušene topolovine, johovine i borovine dobivene su uz uporabu pjene otpadnog ESP-a gustoće 18, 13 i 22 kg/m3. Za polistirensku kompozitnu ivericu od tehnički osušenog iverja te su vrijednosti bile 15, 14 i 11-13 kg/m3. Tehničkim sušenjem iverja postignuta su znatno bolja toplinska svojstva polistirenske kompozitne iverice nego prirodnim sušenjem, a topolovina je pokazala najbolja svojstva od svih ispitivanih vrsta drva.