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Statistical analysis of mechanical properties of wood-PLA composites prepared via additive manufacturing
International Journal of Polymer Analysis and Characterization ( IF 1.9 ) Pub Date : 2019-06-24 , DOI: 10.1080/1023666x.2019.1630940
K. Vigneshwaran 1 , N. Venkateshwaran 1
Affiliation  

Abstract Additive manufacturing circumscribes numerous technologies that allow for the construction of three-dimensional parts by superimposing layers of material. These technologies have undergone greater development in recent years. In this work, using 3D additive printing technology, the samples are prepared using biodegradable wood-PLA composite by varying the layer height (0.08 mm, 0.16 mm, and 0.24 mm), infill (30%, 60%, and 90%) and three different patterns such as layer, triangle, and hexagon. Using universal testing machines tensile properties, energy absorption, and toughness of samples are evaluated as per ASTM standards. The results show that better values are achieved with increase in the infill percentage and layer pattern provides better strength and stiffness. A statistical linear regression model was successfully developed to predict the mechanical properties with an accuracy of 96% predicted in layer pattern when compared to other. Linear regression method helps to find the relationships between two sub-properties of mechanical property of different types of materials and helps to predict the properties of unknown materials.

中文翻译:

增材制造木聚乳酸复合材料力学性能统计分析

摘要 增材制造限制了许多技术,这些技术允许通过叠加材料层来构建三维零件。近年来,这些技术得到了较大的发展。在这项工作中,使用 3D 增材打印技术,通过改变层高(0.08 毫米、0.16 毫米和 0.24 毫米)、填充(30%、60% 和 90%)和可生物降解的木聚乳酸复合材料制备样品。三种不同的图案,如层、三角形和六边形。使用万能试验机,根据 ASTM 标准评估样品的拉伸性能、能量吸收和韧性。结果表明,随着填充百分比的增加,可以获得更好的值,层图案提供更好的强度和刚度。成功开发了统计线性回归模型来预测力学性能,与其他模型相比,层状模式预测的准确率为 96%。线性回归方法有助于发现不同类型材料力学性能的两个子属性之间的关系,有助于预测未知材料的性能。
更新日期:2019-06-24
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