用人工神经网络预测聚苯乙烯复合刨花板最佳隔热性能的最佳发泡密度

IF 0.7 4区 农林科学 Q4 MATERIALS SCIENCE, PAPER & WOOD Drvna Industrija Pub Date : 2022-11-17 DOI:10.5552/drvind.2022.2119
H. Ozturk, Aydin Demir, Cenk Demirkir
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引用次数: 0

摘要

本研究的目的是利用人工神经网络(ANN)预测用废聚苯乙烯(EPS)代替甲醛基胶粘剂生产的刨花板的最佳绝缘性能的最佳密度。为此,利用五种不同密度的废EPS颗粒生产复合刨花板。本研究中使用的实验dana来自于之前的研究。山毛榉、杨树、桤木、松木和云杉的木屑,其中一半在干燥箱中干燥,另一半在室温下自然调理,然后制作18mm厚的三层复合刨花板。面板的导热系数根据ASTM C 518测定。通过将实验数据与人工神经网络分析得到的预测值进行统计和图形比较,确定性能最佳、偏差可接受的预测模型。然后,利用该预测模型,对未经过实验测试的中间EPS密度进行了导热系数估算。根据分析结果,山毛榉和云杉聚苯乙烯复合刨花板(PCP)板的隔热性能随着使用密度为30 kg/m3的废EPS泡沫而提高。以杨木、桤木和松木为原料的PCP板,在自然干燥条件下,密度分别为18、13和22 kg/m3的EPS废泡沫的导热系数最低。在技术干燥中,这些值分别为15、14和11-13 kg/m3。技术干燥的热工性能明显优于自然干燥,其中杨木的热工性能最好。
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Prediction of Optimum Expanded Polystyrene Densities for Best Thermal Insulation Performances of Polystyrene Composite Particleboards by Using Artificial Neural Network
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.
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来源期刊
Drvna Industrija
Drvna Industrija MATERIALS SCIENCE, PAPER & WOOD-
CiteScore
1.80
自引率
9.10%
发文量
32
审稿时长
>12 weeks
期刊介绍: "Drvna industrija" ("Wood Industry") journal publishes original scientific and review papers, short notes, professional papers, conference papers, reports, professional information, bibliographical and survey articles and general notes relating to the forestry exploitation, biology, chemistry, physics and technology of wood, pulp and paper and wood components, including production, management and marketing aspects in the woodworking industry.
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