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   <dc:title>Phase transformations in welded supermartensitic stainless steels</dc:title>
   <dc:identifier xsi:type="dcterms:DOI">10.17863/CAM.14251</dc:identifier>
   <dc:creator>Carrouge, Dominique</dc:creator>
   <dcterms:abstract>Supermartensitic stainless steels have recently been introduced in the oil and&#xd;
gas industries to substitute more expensive duplex stainless steels for onshore and&#xd;
offshore tubing applications. Although easily joined by arc welding processes, the&#xd;
service life of the supermartensitic welded joint in corrosive environments relies to a&#xd;
large extent on the behaviour of the heat-affected zone (HAZ). The microstructure&#xd;
of the HAZ in these new materials has, until now, received little attention.&#xd;
The work presented in this thesis is concerned with the experimental study of&#xd;
the microstructure developing in the HAZ of a range of supermartensitic stainless&#xd;
steels, with particular attention to the retention of the potentially detrimental δ-&#xd;
ferrite phase, and the development of a model to facilitate the choice of a suitable&#xd;
post-weld heat-treatment temperature.&#xd;
The microstructural examination of a variety of welds revealed the presence of&#xd;
retained δ-ferrite in dual-phase and grain-coarsened HAZ regions. Under normal&#xd;
welding conditions, δ-ferrite retention was more pronounced in dual-phase HAZ and&#xd;
in molybdenum containing alloys. However, in multipass welds, δ-ferrite distribution&#xd;
was non-uniform as a result of reheating effects.&#xd;
A number of methods of estimating δ-ferrite retention have been employed. The&#xd;
most corrosion-resistant alloys were successfully predicted to be more prone to δ-&#xd;
ferrite retention.&#xd;
Charpy impact toughness tests performed on simulated heat-affected zones revealed&#xd;
a weak effect of δ-ferrite on the HAZ ductile to brittle transition temperature.&#xd;
In fact, due to its larger grain size, the coarse-grained HAZ determined the impact&#xd;
properties of the tested HAZ.&#xd;
Finally, a neural network in a Bayesian framework has been created to estimate&#xd;
the temperature of the onset of austenite formation as a function of the employed&#xd;
heating rate. The model helps the determination of the appropriate tempering&#xd;
temperature of welded joints to avoid partial austenitisation and can be applied to&#xd;
martensitic stainless steels and low-alloy steels.</dcterms:abstract>
   <uketdterms:institution>University of Cambridge</uketdterms:institution>
   <dcterms:issued>2002-10</dcterms:issued>
   <dc:type>Thesis</dc:type>
   <uketdterms:qualificationlevel>Doctoral</uketdterms:qualificationlevel>
   <uketdterms:qualificationname>Doctor of Philosophy (PhD)</uketdterms:qualificationname>
   <dc:language>eng</dc:language>
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   <dcterms:license>https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/22fbb4c1-5650-464b-aa99-05d9fcf9dc75/download</dcterms:license>
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