Despite the presence of high-carbon martensite, TRIP-assisted steels possess large uniform elongation. High-carbon martensite is normally brittle. In this thesis, it has been demonstrated that this apparent anomaly is due to the fine size of the martensite plates. The mechanical properties of these steels are due to the transformation of retained austenite into martensite during deformation and hence appear to be dominated by the volume fraction and carbon content of retained austenite. These parameters have been related to the chemical composition and heat treatment of the steels with neural networks, using published data. An optimum alloy was formulated by combining the neural network with a genetic algorithm, to minimise the silicon addition whilst maximising the retained austenite fraction. This resulted in the creation of a radically different microstructure, designated δ-TRIP. Transformation of austenite into martensite during deformation ceases beyond a critical strain. A theory has been developed to predict this limit. Calculations using the theory indicate that the high-carbon austenite in these steels may transform into martensite due to stress, rather strain. These materials are often tested for stretch-flangeability, a measure of formability. Neural network analysis of the published data revealed the ultimate tensile strength to be the most important tensile parameter influencing stretch-flangeability
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