Abhilash Singh

Rate of mass transfer in a semifluidized bed

Abstract Data on mass transfer in a semifluidized bed have been obtained for 2-naphthol-, succinic acid-, and ammonium oxalate-water systems. The parameters investigated include particle size (0.043–0.187 cm), initial bed height (2–10 cm), bed expansion ratio (3–10) and flow rates. Two correlations have been suggested for predicting volumetric mass-transfer coefficients, k L a . In the first case, k L a has been correlated as a function of particle Reynolds number, bed expansion ratio and particle-to-column diameter ratio, while in the latter, the generalized approach for predicting mass-transfer coefficient applicable to packed and fluidized beds, has been extended to semifluidization.

Friction factor in a semifluidized bed

Abstract Experimental data on pressure drop in liquid—solid semifluidization have been interpreted in terms of a newly defined friction factor (f), which has been successfully correlated as a function of particle Reynolds number. The concept of f has been found to be applicable for gas—solid systems as well

Evaluation of POSSUM Score for Outcome Prediction in Patients Undergoing Emergency Laparotomy

Background: Emergency Laparotomy is one of the most common surgical procedures performed in Surgical Emergencies, which leads to significant mortality and morbidity. The aim of this study was to evaluate the patients undergoing emergency midline laparotomy, utilizing POSSUM scoring system to help to predict morbidity and mortality in patients, and assuring improved management in present setup. Methods: Total 104 consecutive patients underwent emergency midline laparotomy over a period of two years were included in this prospective study. Surgical outcome was assessed and compared with POSSUM scoring system. The relevant data was recorded on predesigned proforma and analysed. Results: We studied 104 emergency midline laparotomy patients, which resulted in 15 deaths (14.4% Mortality rate). On applying POSSUM, we found that the expected number of deaths for our study group was 24 (O: E= 0.63), relationship was statistically significant. Observed morbidity was 61 (58.65%). On applying POSSUM we found that the expected number of morbidity for our study group was 65 (O: E= 0.93), relationship was statistically significant. Conclusion: The present study validates that the POSSUM is an accurate scoring system for predicting postoperative adverse outcome among patients undergoing major general surgeries in present setup.