Gahgah Mounir, Belaadi Ahmed, Boumaaza Messaouda, Alshahrani Hassan, Khan Mohammad K A
Department of Mechanical Engineering, Faculty of Technology, University 20 Août 1955-Skikda, El-Hadaiek Skikda 21000, Algeria.
Laboratory of Civil and Engineering Hydraulic (LGCH), University 8 Mai 1945 Guelma, Guelma 24000, Algeria.
Polymers (Basel). 2023 Jun 29;15(13):2885. doi: 10.3390/polym15132885.
A designer of sustainable biocomposite structures and natural ropes needs to have a high confidence interval (95% CI) for mechanical characteristics data of performance materials, yet qualities for plant-based fibers are very diverse. A comprehensive study of the elements that enhance the performance of biocomposites or sustainable ropes created from vegetable fibers is necessary. The current study included five groups with varying numbers (N) of tests of 20, 40, 60, 80, and 100 on the mechanical characteristics at room temperatures. The purpose of this study was to determine how changing N affects the mechanical properties of sisal yarn. These properties include its strength, Young's modulus, and deformation at rupture. A significance testing program including more than 100 tests was performed. Owing to the heterogeneity of the plant yarn, each group received more than 20 samples at a gauge length (GL) of 100 mm. The tensile strength characteristics of sisal yarns produced a wide range of findings, as is common for natural fibers, necessitating a statistical analysis. Its dispersion was explored and measured using the statistical methods. The Weibull distribution with two parameters and a prediction model with a 95% confidence level for maximum likelihood (ML) and least squares (LS) were used to investigate and quantify its dispersion.
可持续生物复合材料结构和天然绳索的设计者需要对高性能材料的机械特性数据有较高的置信区间（95%CI），然而植物基纤维的质量差异很大。有必要对增强由植物纤维制成的生物复合材料或可持续绳索性能的因素进行全面研究。当前的研究包括五组，分别对室温下的机械特性进行了数量（N）不同的测试，测试次数分别为20次、40次、60次、80次和100次。本研究的目的是确定N的变化如何影响剑麻纱线的机械性能。这些性能包括其强度、杨氏模量和断裂变形。进行了一个包括100多次测试的显著性测试程序。由于植物纱线的异质性，每组在100毫米的标距长度（GL）下接收了20多个样本。剑麻纱线的拉伸强度特性产生了广泛的结果，这对于天然纤维来说是常见的，因此需要进行统计分析。使用统计方法对其离散度进行了探索和测量。采用双参数威布尔分布以及具有95%置信水平的最大似然（ML）和最小二乘法（LS）预测模型来研究和量化其离散度。
