Neural network PC tools: a practical guide
Neural network PC tools: a practical guide
Neural Computation
A practical Bayesian framework for backpropagation networks
Neural Computation
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Damage is controlled by the chemistry of the material, initial inclusions or second phase particles' fractions with their size/shape distribution, stress triaxility, strain, stress, strain rate, strain path, grain size, initial crystallographic micro-texture and the temperature of deformation. In this study, a model has been developed to correlate the complex relationship between the extent of damage accumulations (i.e., void area fraction) with its influencing parameters in a variety of high strength low alloy steels under tension. The model has been applied to confirm that the predictions are reasonable in the context of metallurgical principles and other data published in the literatures.