{"title":"Perfect Cones Are as Weak as They Seem","authors":"Marric Stephens","doi":"10.1103/physics.16.s137","DOIUrl":null,"url":null,"abstract":"P hysicists simplify problems to make calculations easier, but doing so risks neglecting important physical properties, as illustrated by the fabled spherical cow in a vacuum, for example. For decades, oversimplification was thought to explain why thin-walled cones crumple under smaller loads than predicted by theory. Researchers suspected that the descrepancy might result from imperfections in real cones that are absent from theoretically ideal cones. Now Daniel Duffy of the University of Cambridge and his colleagues show that the biggest problem is not that models lack those microscopic details, but that the models assume the wrong boundary conditions [1]. Their result could have implications for the emerging field of soft robotics.","PeriodicalId":20136,"journal":{"name":"Physics","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1103/physics.16.s137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
P hysicists simplify problems to make calculations easier, but doing so risks neglecting important physical properties, as illustrated by the fabled spherical cow in a vacuum, for example. For decades, oversimplification was thought to explain why thin-walled cones crumple under smaller loads than predicted by theory. Researchers suspected that the descrepancy might result from imperfections in real cones that are absent from theoretically ideal cones. Now Daniel Duffy of the University of Cambridge and his colleagues show that the biggest problem is not that models lack those microscopic details, but that the models assume the wrong boundary conditions [1]. Their result could have implications for the emerging field of soft robotics.