Use this URL to cite or link to this record in EThOS:
Title: Microstructure-property modelling and predictions of 7xxx Al alloys
Author: Li, Xiaomei
ISNI:       0000 0001 3609 5089
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2002
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
This thesis has investigated the effect of compositional variations on microstructure, electrical conductivity (which is a measure of stress corrosion resistance) and yield strength balance of a wide range of Zr-containing and Cr-containing 7xxx alloys. Twenty-two 7xxx Al alloys within composition windows of 7010, 7x50 and 7x75 aerospace alloys have been studied and modelled. Differential scanning calorimetry (DSC), scanning electron microscopy (SEM) along with energy dispersive X-ray spectrometry (EDS), and transmission electron microscopy (TEM) have been employed to study phase transformation, grain structure, coarse intermetallic particles of these alloys. Specifically, detailed analysis of precipitation and dissolution reactions of these alloys has been investigated using DSC, and conditions for the presence of coarse intermetallic particles (S and T phase) have been analysed and interpreted in terms of physical and metallurgical principles. This has provided useful information on alloy design and thermo-mechanical processing of high strength 7xxx alloys via microstructural control. To provide predictive tools for conductivity and yield strength, two physically based models for conductivity and yield strength have been presented in this thesis. For modelling of electrical conductivity, 9 Zr-containing and 5 Cr-containing 7xxx alloys aged at 172≡C and a 7475 alloy aged at three different temperatures have been modelled. Modelling results indicate that the model can fit and predict the conductivity data of 7xxx alloys very well with an accuracy better than 1%IACS (RMSE). Specifically, the model fits best to the conductivity of 9 Zr-containing alloys with training error (RMSE) about 0.38%IACS and test error (RMSE) about 0.44%IACS, and fits the data of 6 Cr-containing alloys with training error (RMSE) about 0.56%IACS and test error about 0.61%IACS.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available