{"title":"用离散元方法模拟具有双峰和伪全粒径分布的涂层力学性能","authors":"Dan Varney, M. Toivakka, D. Bousfield","doi":"10.32964/tj22.7.491","DOIUrl":null,"url":null,"abstract":"The mechanical properties of paper coating layers are important in converting operations such as calendering, printing, and folding. While several experimental and theoretical studies have advanced our knowledge of these systems, a particle level understanding of issues like crack-at-the-fold are lacking.\nA discrete element method (DEM) model is used to describe bending and tension deformations of a coating layer. The particles in the model are either bimodal distributions or pseudo-full particle size distributions of spherical particles. The impact of particle size distribution on the predicted mechanical properties of the coating layer is reported. Inputs to the model include properties of the binder film and the binder concentration. The model predicts crack formation as a function of these parameters and also calculates the modulus, the maximum stress, and the \nstrain-to-failure. \nThe simulation results are compared to previous experimental results. Reasonable predictions were obtained for both tensile and bending for a range of latex-starch ratios and at various binder concentrations. The influence of particle packing density on mechanical properties is reported.","PeriodicalId":22255,"journal":{"name":"Tappi Journal","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A discrete element method to model coating layer mechanical properties with bimodal and pseudo-full particle size distributions\",\"authors\":\"Dan Varney, M. Toivakka, D. Bousfield\",\"doi\":\"10.32964/tj22.7.491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The mechanical properties of paper coating layers are important in converting operations such as calendering, printing, and folding. While several experimental and theoretical studies have advanced our knowledge of these systems, a particle level understanding of issues like crack-at-the-fold are lacking.\\nA discrete element method (DEM) model is used to describe bending and tension deformations of a coating layer. The particles in the model are either bimodal distributions or pseudo-full particle size distributions of spherical particles. The impact of particle size distribution on the predicted mechanical properties of the coating layer is reported. Inputs to the model include properties of the binder film and the binder concentration. The model predicts crack formation as a function of these parameters and also calculates the modulus, the maximum stress, and the \\nstrain-to-failure. \\nThe simulation results are compared to previous experimental results. Reasonable predictions were obtained for both tensile and bending for a range of latex-starch ratios and at various binder concentrations. The influence of particle packing density on mechanical properties is reported.\",\"PeriodicalId\":22255,\"journal\":{\"name\":\"Tappi Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tappi Journal\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.32964/tj22.7.491\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATERIALS SCIENCE, PAPER & WOOD\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tappi Journal","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.32964/tj22.7.491","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATERIALS SCIENCE, PAPER & WOOD","Score":null,"Total":0}
A discrete element method to model coating layer mechanical properties with bimodal and pseudo-full particle size distributions
The mechanical properties of paper coating layers are important in converting operations such as calendering, printing, and folding. While several experimental and theoretical studies have advanced our knowledge of these systems, a particle level understanding of issues like crack-at-the-fold are lacking.
A discrete element method (DEM) model is used to describe bending and tension deformations of a coating layer. The particles in the model are either bimodal distributions or pseudo-full particle size distributions of spherical particles. The impact of particle size distribution on the predicted mechanical properties of the coating layer is reported. Inputs to the model include properties of the binder film and the binder concentration. The model predicts crack formation as a function of these parameters and also calculates the modulus, the maximum stress, and the
strain-to-failure.
The simulation results are compared to previous experimental results. Reasonable predictions were obtained for both tensile and bending for a range of latex-starch ratios and at various binder concentrations. The influence of particle packing density on mechanical properties is reported.
期刊介绍:
An internationally recognized technical publication for over 60 years, TAPPI Journal (TJ) publishes the latest and most relevant research on the forest products and related industries. A stringent peer-review process and distinguished editorial board of academic and industry experts set TAPPI Journal apart as a reliable source for impactful basic and applied research and technical reviews.
Available at no charge to TAPPI members, each issue of TAPPI Journal features research in pulp, paper, packaging, tissue, nonwovens, converting, bioenergy, nanotechnology or other innovative cellulosic-based products and technologies. Publishing in TAPPI Journal delivers your research to a global audience of colleagues, peers and employers.