Somnath Basu

Development of indices for quantification of nozzle clogging during continuous slab casting

Abstract Deposition of alumina inclusions inside the submerge entry nozzle is a long standing problem in continuous casting of aluminium killed steel. Clogging of the casting nozzle severely affects productivity and also causes degradation of product quality. Unfortunately, very few numerical tools are available for precise quantification of the magnitude of clogging. Tools for quantifying the extent of clogging were developed during the present work and have been integrated with the control system of a running continuous slab casting shop. Reasonable match has been observed between the estimation from the developed program and the actual observations in the casting shop and subsequent products. In addition to process control, the tools were also found useful for comparing the castability of different steel grades. This feature has been utilised to study nozzle clogging during casting of steel grades that are commonly believed to have poor castability.

Determination of the aggregate fractal dimensions in colloidal nanofluids

Owing to the significant technological implications of nanoscale colloidal suspensions (nanofluids), it is necessary to develop suitable techniques to characterize the nanostructured aggregates in suspension. In the present work, a fractal dimension approach is applied to characterize the agglomerate structure using image analysis by scanning electron microscope photographs of the nanoparticle aggregates. Aqueous suspensions of aluminum oxide nanoparticles (nanofluids) are used for the study. A simple and direct method of projected image manipulation has been used to calculate the aggregate fractal dimensions in colloidal nanofluid. The fractal dimension provides quantitative information about important morphological features of the aggregate structure. A functional relationship is established between the two-dimensional fractal dimension (df2) and the three-dimensional fractal dimension (df3). The present study demonstrates that the optical image analysis technique can be effectively used for fractal dimension analysis of colloidal nanoparticle aggregates.