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- W2261735521 abstract "These problems are not easily addressed through the traditional static models because by they reflect interrelated issues of a dynamic nature, for example, lowering the lance close to the bath may accelerate decarburisation, lowering the potential blowing time, but this may result in slopping under certain circumstances. Similarly, changing the sequence of flux additions to a furnace may reduce the risk of slopping but maybe also expose the refractory to attack early during the blow. “Black box” modelling techniques (i.e. neural networks, fuzzy logic and multi-variate statistics) have been used to address the issues such as these and there is some evidence that these techniques can help in optimising the operation. 1,2 & 3 These types of approaches tend to be quite specific to the operation being modelled and also rarely provide insight into the underlying physics and chemistry of the process." @default.
- W2261735521 created "2016-06-24" @default.
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- W2261735521 date "2013-01-01" @default.
- W2261735521 modified "2023-09-23" @default.
- W2261735521 title "Development of dynamic process models for oxygen steelmaking" @default.
- W2261735521 hasPublicationYear "2013" @default.
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