6533b7d0fe1ef96bd125a307

RESEARCH PRODUCT

Metallurgical Phenomena Modelling in Friction Stir Welding of Aluminium Alloys: Analytical vs. Neural Network Based Approaches

Livan FratiniGianluca Buffa

subject

FSW CDRX RecrystallizationMaterials scienceArtificial neural networkMechanical EngineeringMetallurgyRecrystallization (metallurgy)chemistry.chemical_elementWeldingStrain rateCondensed Matter PhysicsFinite element methodGrain sizelaw.inventionchemistryMechanics of MaterialsAluminiumlawFriction stir weldingGeneral Materials ScienceSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione

description

In this paper, the metallurgical phenomena occurring in friction stir welding processes of AA6082-T6 and AA7075-T6 aluminum alloys are investigated. In particular, to predict the local values of the average grain size, either a simple analytical expression depending on a few material constants or a properly trained neural network is linked to the finite element model of the process. The utilized tools, which take as inputs the local values of strain, strain rate, and temperature, were developed starting from experimental data and numerical results.

yearjournalcountryeditionlanguage
2008-05-22
10.1115/1.2931142http://hdl.handle.net/10447/34903