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合成材料:力学,计算和应用

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ISSN 打印: 2152-2057

ISSN 在线: 2152-2073

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 0.2 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 0.3 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00004 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.08 SJR: 0.153 SNIP: 0.178 CiteScore™:: 1 H-Index: 12

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PREDICTION OF EROSION WEAR OF GRANITE-FILLED JUTE−EPOXY COMPOSITES USING AN ARTIFICIAL NEURAL NETWORK

卷 6, 册 3, 2015, pp. 193-205
DOI: 10.1615/CompMechComputApplIntJ.v6.i3.20
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摘要

The erosion wear process is considered as a complex nonlinear problem due to its operating variables. The wear process depends on various parameters such as impact velocity, impingement angle, material, erodent size, etc. In order to obtain a minimum erosion rate, experiments have to be conducted on a material with a combination of these parameters. Therefore, it becomes expensive and time consuming for finding out the minimum erosion rate of a material. In this regard, an artificial neural network (ANN) is a robust tool for predicting the erosion rate of a material. ANN is capable of representing nonlinear systems and can be applied to a wide variety of fields. In the present work, waste granite powder is used as a filler in a jute fiber-reinforced−epoxy composite. Four different weight proportions of granite (0, 5, 10, and 15 wt.%) are used to fabricate four different composites. It is observed that the predicted values of erosion rate have shown good agreement with experimental values.

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