Prediction of Ultraviolet Corrosion Levels of High Density Polyethylene Using Artificial Intelligence

Jeongwon Seo, Geumbi Park, Minju Kim, Jae-Hyeong Joo, Jinhwan Koh
{"title":"Prediction of Ultraviolet Corrosion Levels of High Density Polyethylene Using Artificial Intelligence","authors":"Jeongwon Seo, Geumbi Park, Minju Kim, Jae-Hyeong Joo, Jinhwan Koh","doi":"10.1109/CSPA57446.2023.10087881","DOIUrl":null,"url":null,"abstract":"Currently, as the intensity of ultraviolet rays increases due to the severe global warming problem, it is difficult to make materials that exclude ultraviolet rays. As a result, high-density polyethylene (HDPE) is a non-toxic ecofriendly plastic with no environmental hormones detected and has been found to have excellent strength and less damage to ultraviolet rays, and interest in eco-friendly ship technology is increasing. This research predicted damage to high-density polyethylene by adding a carbon black sample, which is a UV stabilizer, to HDPE using a long-lasting UV-A lamp because it requires a lot of time due to the presence or absence of ultraviolet limitation. Since it takes a lot of time and money to check the corrosion of the material using ultraviolet rays, research was conducted using artificial intelligence to solve this problem, and as a result, it was confirmed that the degree of corrosion of HDPE according to the irradiation time can be predicted with 90% accuracy.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA57446.2023.10087881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Currently, as the intensity of ultraviolet rays increases due to the severe global warming problem, it is difficult to make materials that exclude ultraviolet rays. As a result, high-density polyethylene (HDPE) is a non-toxic ecofriendly plastic with no environmental hormones detected and has been found to have excellent strength and less damage to ultraviolet rays, and interest in eco-friendly ship technology is increasing. This research predicted damage to high-density polyethylene by adding a carbon black sample, which is a UV stabilizer, to HDPE using a long-lasting UV-A lamp because it requires a lot of time due to the presence or absence of ultraviolet limitation. Since it takes a lot of time and money to check the corrosion of the material using ultraviolet rays, research was conducted using artificial intelligence to solve this problem, and as a result, it was confirmed that the degree of corrosion of HDPE according to the irradiation time can be predicted with 90% accuracy.
利用人工智能预测高密度聚乙烯紫外线腐蚀水平
目前,由于全球变暖问题严重,紫外线的强度增加,因此很难制造出排除紫外线的材料。因此,高密度聚乙烯(HDPE)是一种无毒的环保塑料,没有检测到环境激素,并且被发现具有优异的强度和对紫外线的伤害较小,对环保船舶技术的兴趣正在增加。由于存在或不存在紫外线限制,需要很长时间,因此该研究使用长时间UV- a灯,在HDPE中加入了紫外线稳定剂炭黑样品,从而预测了高密度聚乙烯的损伤。由于使用紫外线检查材料的腐蚀情况需要花费大量的时间和金钱,因此利用人工智能进行了研究来解决这一问题,并证实根据照射时间预测HDPE的腐蚀程度可以达到90%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书