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Microstructure-property modelling and predictions of 7xxx A1 alloys

Microstructure-property modelling and predictions of 7xxx A1 alloys
Microstructure-property modelling and predictions of 7xxx A1 alloys

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.

University of Southampton
Li, Xiaomei
9a7462ce-570c-4439-ade6-1f433fa287ec
Li, Xiaomei
9a7462ce-570c-4439-ade6-1f433fa287ec

Li, Xiaomei (2002) Microstructure-property modelling and predictions of 7xxx A1 alloys. University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

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.

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Published date: 2002

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Local EPrints ID: 465602
URI: http://eprints.soton.ac.uk/id/eprint/465602
PURE UUID: 3af769a1-4272-4d07-a15f-c3e896882892

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Date deposited: 05 Jul 2022 01:59
Last modified: 16 Mar 2024 20:16

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Author: Xiaomei Li

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