Experimental investigations and statistical modeling of specific wear and coefficient of friction in a novel carbon fiber reinforced composite

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引用次数: 1

Abstract

In the present work, experimental investigations were performed to study the effect of various machine parameters like sliding velocity (S_v), sliding distance (S_d), and load (L), on specific wear (W_s) and coefficient of friction (COF). The experiments were performed on a novel carbon fiber reinforced composite consisting of fishbone powder as filler. Response surface methodology (RSM) was used to develop the statistical models to predict the specific wear rate and coefficient of friction (µ) of the developed composite. A set of 20 experiments were designed according to the central composite design technique. Analysis of variance (ANOVA) was carried out at a confidence interval of 95% to determine the parameters that significantly affect (p<0.05) the output responses. It was also found that among the various parameters, the influence of S_d was most significant (33.4%) on W_s followed by S_v (20.3%) and L (17.9%). For COF, the percentage contribution of S_v was maximum i.e. 64%, followed by S_d (17.8%) and L (7.8%).
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新型碳纤维增强复合材料比磨损和摩擦系数的实验研究与统计建模
本文通过实验研究了滑动速度(S_v)、滑动距离(S_d)和载荷(L)等不同机械参数对比磨损(W_s)和摩擦系数(COF)的影响。以鱼骨粉为填料制备了一种新型碳纤维增强复合材料。采用响应面法(RSM)建立了预测复合材料比磨损率和摩擦系数(µ)的统计模型。采用中心复合设计技术设计了一组20个试验。方差分析(ANOVA)以95%的置信区间进行,以确定显著影响输出响应的参数(p<0.05)。在各参数中,S_d对W_s的影响最大(33.4%),其次是S_v(20.3%)和L(17.9%)。对于COF, S_v的贡献率最大,为64%,其次是S_d(17.8%)和L(7.8%)。
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CiteScore
2.60
自引率
0.00%
发文量
22
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