A model for predicting the effect of deformation after solution treatment on the subsequent artificial aging behavior of AA7030 and AA7108 alloys

Citation
Wj. Poole et al., A model for predicting the effect of deformation after solution treatment on the subsequent artificial aging behavior of AA7030 and AA7108 alloys, MET MAT T A, 31(9), 2000, pp. 2327-2338
Citations number
40
Categorie Soggetti
Apllied Physucs/Condensed Matter/Materiales Science",Metallurgy
Journal title
METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE
ISSN journal
10735623 → ACNP
Volume
31
Issue
9
Year of publication
2000
Pages
2327 - 2338
Database
ISI
SICI code
1073-5623(200009)31:9<2327:AMFPTE>2.0.ZU;2-S
Abstract
The effect of deformation after solution treatment on the two-step artifici al aging response has been examined for AA7030 and AA7108 alloys. Aging exp eriments were conducted where the prestrain level was varied between 0 and 1.2. It was observed that the kinetics of aging were accelerated and the ma gnitude of the peak strength decreased in the presence of prestrain, This w as attributed to the increased growth/coarsening rate of precipitates on di slocations and the widening of the precipitate-size distribution, respectiv ely. A model was developed based on the internal state variable approach to predict yield stress as a function of the heat treatment and the level of prestrain. The increase in the kinetics of aging was accounted for in an av erage sense by the use of an effective diffusion coefficient that combines bulk and short-circuit diffusion. The precipitation model was based on two variables; the average spacing between precipitates and the average strengt h of precipitates. The variation of the average strength of precipitates wi th precipitate radius was varied to account for the change in the width of the precipitate-size distribution. Static recovery of the deformed structur e during artificial aging was also accounted for in a first-order approxima tion. Good agreement was found between the model predictions and experiment al results. Additional experimental data were obtained after the model was developed, and it was observed that the model made excellent predictions.