Abstract
dc:description.abstractThe microstructure of a steel is often developed by solid-state transformation from austenite. The major transformation products are allotriomorphic ferrite, pearlite, Widmanstatten ferrite, bainite and martensite, differentiated by morphological features, and their nucleation and growth mechanisms. A steel often consists of several phases as a result of dynamic evolution during continuous cooling. The complexity of the calculation of all the transformations simultaneously poses a challenge. There have been a few attempts at integrating all these transformations into an unified scheme. They involve varying degrees of empiricism. For the first time, a model that can predict simultaneously the volume proportions of all the major transformation products has been developed. The algorithm has taken full account of the thermodynamics and kinetics of individual transformations, instead of empirical equations, so the model should in principle generalise well. The predictions of the model are based on a number of input parameters: the chemical composition, austenite grain size and cooling conditions. The model can simulate cooling at constant rates, or isothermal transformations. Therefore it can also generate continuous cooling transformation (CCT), or time-temperature transformation (TTT) diagrams. The model has demonstrated a consistency in its predictions. The validations of the model against published experiment data and experiments conducted in this work have shown the predictions in most cases are reasonable with errors less than a few volume percent. Further research opportunities presented by the work are reviewed.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2009
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Chen, Jiawen
Subjects
dc:subject × 5Rights
dc:rightsIdentifiers
dc:identifier.*- DOI dc:identifier.doi
- https://doi.org/10.17863/CAM.14253
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/217866