Dmitriy A. Golovatov, A. Tatarkanov, A. A. Shavaev, Sergey A. Gusev
{"title":"The Use of Modern Information Technology in Predicting the Process of Impregnating Composite Preforms with Polymer Resins","authors":"Dmitriy A. Golovatov, A. Tatarkanov, A. A. Shavaev, Sergey A. Gusev","doi":"10.1109/IT&QM&IS.2019.8928415","DOIUrl":null,"url":null,"abstract":"The paper describes the development of automated system for modeling resin frontal spread during the impregnation of fibrous reinforcing agent with regard to resin viscosity and impregnation time. The topicality of the paper is due to the necessity to provide the quality of composite materials by managing a technological process. The method of modeling boundaries of resin spread during reinforcing agent impregnation on the basis of an artificial neural network is offered. A number of experimental studies on a resin spread process in the volume of reinforcing agent, allowing to make a data base for training neural network model, is made. The developed neural network model allows to forecast the specific features of a composite material product impregnation process with regards to rheokinetics of the process.","PeriodicalId":285904,"journal":{"name":"2019 International Conference \"Quality Management, Transport and Information Security, Information Technologies\" (IT&QM&IS)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference \"Quality Management, Transport and Information Security, Information Technologies\" (IT&QM&IS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IT&QM&IS.2019.8928415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The paper describes the development of automated system for modeling resin frontal spread during the impregnation of fibrous reinforcing agent with regard to resin viscosity and impregnation time. The topicality of the paper is due to the necessity to provide the quality of composite materials by managing a technological process. The method of modeling boundaries of resin spread during reinforcing agent impregnation on the basis of an artificial neural network is offered. A number of experimental studies on a resin spread process in the volume of reinforcing agent, allowing to make a data base for training neural network model, is made. The developed neural network model allows to forecast the specific features of a composite material product impregnation process with regards to rheokinetics of the process.