{"title":"一种新的非连续纤维增强热塑性塑料拉伸性能数值分析方法","authors":"Dawei Zhang, P. Qu, Yuxi Jia","doi":"10.1177/2633366X20977496","DOIUrl":null,"url":null,"abstract":"For predicting the mechanical properties of discontinuous carbon fiber-reinforced thermoplastics (DCFRTP), it is essential to consider the microstructure, including the fiber orientation and the properties of the constituting materials. In the present study, a heterogeneous particle model, considering the microscopic factors, is constructed on the basis of the peridynamic (PD) theory to investigate the tensile properties of DCFRTP. Two kinds of randomly oriented DCFRTP, with different constituents and volume fractions of carbon fiber, are used for the verification of this numerical model. A comparison between the PD simulations and the experimental results shows a good agreement. The effect of the model size on the prediction is discussed.","PeriodicalId":10608,"journal":{"name":"Composites and Advanced Materials","volume":"26 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A new numerical method for the tensile property analysis of discontinuous fiber-reinforced thermoplastics\",\"authors\":\"Dawei Zhang, P. Qu, Yuxi Jia\",\"doi\":\"10.1177/2633366X20977496\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For predicting the mechanical properties of discontinuous carbon fiber-reinforced thermoplastics (DCFRTP), it is essential to consider the microstructure, including the fiber orientation and the properties of the constituting materials. In the present study, a heterogeneous particle model, considering the microscopic factors, is constructed on the basis of the peridynamic (PD) theory to investigate the tensile properties of DCFRTP. Two kinds of randomly oriented DCFRTP, with different constituents and volume fractions of carbon fiber, are used for the verification of this numerical model. A comparison between the PD simulations and the experimental results shows a good agreement. The effect of the model size on the prediction is discussed.\",\"PeriodicalId\":10608,\"journal\":{\"name\":\"Composites and Advanced Materials\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Composites and Advanced Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/2633366X20977496\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Composites and Advanced Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/2633366X20977496","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new numerical method for the tensile property analysis of discontinuous fiber-reinforced thermoplastics
For predicting the mechanical properties of discontinuous carbon fiber-reinforced thermoplastics (DCFRTP), it is essential to consider the microstructure, including the fiber orientation and the properties of the constituting materials. In the present study, a heterogeneous particle model, considering the microscopic factors, is constructed on the basis of the peridynamic (PD) theory to investigate the tensile properties of DCFRTP. Two kinds of randomly oriented DCFRTP, with different constituents and volume fractions of carbon fiber, are used for the verification of this numerical model. A comparison between the PD simulations and the experimental results shows a good agreement. The effect of the model size on the prediction is discussed.