Hot metal de-sulphurisation is a dip-lance process involving the pneumatic injection of fine-grained de-sulphurisation reagents into the molten metal. For maximum efficiency the particles must be dispersed in the ladle as widely as possible to increase the total interfacial area which is primarily controlled by the lance design. Seven different lance configurations were modelled and simulated to determine the most efficient design using physical and mathematical modelling approach. A 0.25 scale plexi-glass model of the 100 T hot metal ladle was fabricated for the study. Residence time and mixing time studies were carried out using the electrical conductivity measurement technique through stimulus response of injected saturated salt solution. Mathematical modelling approach using momentum balance was used to simulate fluid flow profile of lance-ladle assembly under operating conditions using computational fluid dynamics package ANSYS-CFX. Based on the studies a new curved port lance has been designed which resulted in uniform and swirling flow profile inside the ladle without rotating the lance. Injection through the new lance increased the residence time of the particles and reduced the dead zones. The new design was fabricated and experimented at de-sulphurisation stations and has resulted in reduced flux consumption and treatment time.
JSW Steel, Vijayanagar works operates a 44 T, eight-strand billet caster for continuous casting. Such large volume tundish has large differences between the central and the end strands from the shroud which affects the cleanliness and solidification between different strands. With an aim to improve the steel cleanliness in central strands, water modelling studies were carried out in a 0.25-scale perspex water model. Different configurations of dams were studied under steady and unsteady state conditions. The combination of the wedge and V-shaped dam configuration resulted in increasing the mean residence time of the central strand without affecting the flow behaviour of the last strands. Residence time at central strands increased by 15% and does not affect the vortex formation height. It was further validated on a plant scale tundish. Plant trials demonstrated a reduction in inclusion area percentage by 21% confirming the improved steel cleanliness in central strands.
A trendy technique based on computer science called artificial intelligence (AI) creates software and algorithms to make machines smart and effective at carrying out activities that often call for expert human intellect. Machine learning (ML), deep learning (DL), traditional neural networks, fuzzy logic, and speech recognition are only a few of the subsets of AI that have distinctive skills and functions that might enhance the performance of contemporary medical sciences. Biomedical imaging might undergo a revolution thanks to AI, which could increase the efficiency and precision of picture processing and interpretation. Radiologists could miss tiny abnormalities that can be detected by AI systems that have been taught to spot patterns in those pictures that are challenging for humans to interpret. AI may also be used to generate customized medicine by evaluating a patient's medical pictures and other data to customize treatment regimens, as well as to enhance image processing and visualization.
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