Reference : Numerical simulation of the Roll forming of thin-walled sections and evaluation of co...
Scientific journals : Article
Engineering, computing & technology : Mechanical engineering
Engineering, computing & technology : Civil engineering
Numerical simulation of the Roll forming of thin-walled sections and evaluation of corner strength enhancement
Rossi, Barbara mailto [Université de Liège - ULiège > Département Argenco : Secteur MS2F > Adéquat. struct. aux exig. de fonct.& perfor. techn.-écon. >]
Degée, Hervé mailto [Université de Liège - ULiège > Département ArGEnCo > Département ArGEnCo >]
Boman, Romain mailto [Université de Liège - ULiège > Département d'aérospatiale et mécanique > Département d'aérospatiale et mécanique >]
Finite Elements in Analysis and Design
Elsevier Science
Yes (verified by ORBi)
The Netherlands
[en] cold rolling ; channel ; FEM ; high-strength steel ; stainless steel ; corner enhancement
[en] Cold roll forming modifies the mechanical properties of thin-walled profiles by strain hardening. The understanding of this phenomenon, which is rather good for profiles made of traditional construction steel, is mandatory for assessing the member resistance. Less information is however available for profiles made of materials exhibiting a pronounced degree of nonlinearity of the stress-strain curve such as high-strength and stainless steels. Current codes generally encounter difficulties for modelling this fabrication process because of the size of industrial mills. Indeed, accurate modelling of the continuous cold roll forming process using finite elements requires a huge number of elements leading to excessive CPU times. Therefore, modellers usually reduce the geometry of the formed sheet or increase the size of the finite elements, inducing a loss of accuracy in the results. In this work, the finite element software METAFOR is used to model cold roll forming of channel profiles made of high-strength and stainless steels. The numerical results, expressed in terms of corner strength enhancement versus radius–to–thickness ratio, are compared against an existing predictive model.

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