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首页> 外文期刊>High temperature materials and processes >Predictive Models for Modulus of Rupture and Modulus of Elasticity of Particleboard Manufactured in Different Pressing Conditions
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Predictive Models for Modulus of Rupture and Modulus of Elasticity of Particleboard Manufactured in Different Pressing Conditions

机译：不同压制条件下刨花板断裂模量和弹性模量的预测模型

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摘要

Determining the mechanical properties of particleboard has gained a great importance due to its increasing usage as a building material in recent years. This study aims to develop artificial neural network (ANN) and multiple linear regression (MLR) models for predicting modulus of rupture (MOR) and modulus of elasticity (M0E) of particleboard depending on different pressing temperature, pressing time, pressing pressure and resin type. Experimental results indicated that the increased pressing temperature, time and pressure in manufacturing process generally improved the mechanical properties of particleboard. It was also seen that ANN and MLR models were highly successful in predicting the MOR and M0E of particleboard under given conditions. On the other hand, a comparison between ANN and MLR revealed that the ANN was superior compared to the MLR in predicting the MOR and MOE. Finally, the findings of this study are expected to provide beneficial insights for practitioners to better understand usability of such composite materials for engineering applications and to better assess the effects of pressing conditions on the MOR and M0E of particleboard.
机译：由于刨花板近年来越来越多地用作建筑材料，因此确定刨花板的机械性能已变得非常重要。这项研究旨在开发人工神经网络（ANN）和多元线性回归（MLR）模型，根据不同的压制温度，压制时间，压制压力和树脂类型，预测刨花板的断裂模量（MOR）和弹性模量（M0E） 。实验结果表明，制造过程中压制温度，时间和压力的增加，总体上提高了刨花板的力学性能。还可以看出，在给定条件下，ANN和MLR模型在预测刨花板的MOR和M0E方面非常成功。另一方面，ANN和MLR之间的比较表明，在预测MOR和MOE方面，ANN优于MLR。最后，该研究的结果有望为从业人员提供有益的见解，以更好地了解此类复合材料在工程应用中的可用性，并更好地评估压制条件对刨花板MOR和M0E的影响。

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  • 来源
    《High temperature materials and processes》 |2017年第6期|623-634|共12页
  • 作者

    Sebahattin Tiryaki; Ugur Aras; Huelya Kalaycioglu; Emir Erisir; Aytac Aydin;

  • 作者单位

    Department of Forest Industry Engineering, Faculty of Forestry, Karadeniz Technical University, 61080 Trabzon, Turkey;

    Department of Forest Industry Engineering, Faculty of Forestry, Karadeniz Technical University, 61080 Trabzon, Turkey;

    Department of Forest Industry Engineering, Faculty of Forestry, Karadeniz Technical University, 61080 Trabzon, Turkey;

    Department of Forest Industry Engineering, Faculty of Forestry, Karadeniz Technical University, 61080 Trabzon, Turkey;

    Department of Forest Industry Engineering, Faculty of Forestry, Karadeniz Technical University, 61080 Trabzon, Turkey;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    model comparison; modulus of elasticity,modulus of rupture; particleboard; prediction; wood;

    机译：模型比较;弹性模量;断裂模量;刨花板;预测;木;

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