Department of Chemical Engineering

Liquid-liquid slug flow regime is characterised by the presence of strong internal circulation which enhances mass transfer. In this work, we develop a mathematical model for conjugate mass transfer in the liquid-liquid slug flow regime in a microchannel. A Lagrangian approach is adopted where the behaviour of a unit cell in the channel is analysed in a moving reference frame. The system is analysed for two cases when (I) the slug is in direct contact with the channel wall and (II) there is a thin film of continuous fluid surrounding the slug. A novel contribution of this work is the extension of the stream function formulation to determine the flow structures in multiply connected domains made up of two liquids in a pressure driven flow. The primary objective of the work is to understand the influence of the flow patterns (which is determined by fluid properties and operating conditions) on the mass transfer of a solute from the slug to the continuous phase. Towards this, the species transport equation is solved numerically using the velocity field obtained. The reliability of the model developed is validated with experiments reported in the literature. This study gives us insights on the influence of the film on the hydrodynamics and its contribution to mass transfer. A key finding of this study is that the rate of mass transfer can be enhanced if the continuous phase has higher viscosity than the slug phase.

We report a numerical study on the collective dynamics of self-propelling and circle-swimming Lennard-Jones (LJ) particles in two dimensions using Brownian dynamics simulations. We investigate the combined role of attraction, self-propulsion and rotation in their phase behavior. At a low rotational speed, the system shows re-entrant phase behavior as a function of self-propulsion similar to active Brownian particles (ABPs). Increasing the rotational speed shifts the point of re-entrance or makes it disappear depending on the attractive strength. Although active rotation is known to suppress motility induced phase separation, the presence of attractive interactions reduces this effect.

The aim of this work is to analyze output feedback distributed control framework based on model predictive control (MPC) for multi-unit systems with multirate and delayed measurements. Primary controlled variable(s) is sampled infrequently, and the measurement is available after a delay. The distributed, unit-specific estimators and controllers communicate through selective information transfer based on process knowledge. The distributed state estimator is designed based on sampled state augmentation method to efficiently compute improved state estimates on arrival of the delayed infrequent measurements. The multirate estimators are appropriately modified to incorporate the disturbance model to handle model-plant mismatch (MPM). The proposed implementation is analyzed using two case studies. A linearized, reactor-separator system is used to demonstrate that multirate estimation is required for offset-free tracking. A more complex variant of the reactor-separator system with recycle demonstrates the ability of nonlinear distributed estimator-MPC framework to incorporate infrequent and delayed primary measurements.

Background: Different formulae have been developed globally to estimate gestational age (GA) by ultrasonography in the first trimester of pregnancy. In this study, we develop an Indian population-specific dating formula and compare its performance with published formulae. Finally, we evaluate the implications of the choice of dating method on preterm birth (PTB) rate. This study’s data was from GARBH-Ini, an ongoing pregnancy cohort of North Indian women to study PTB. Methods: Comparisons between ultrasonography-Hadlock and last menstrual period (LMP) based dating methods were made by studying the distribution of their differences by Bland-Altman analysis. Using data-driven approaches, we removed data outliers more efficiently than by applying clinical parameters. We applied advanced machine learning algorithms to identify relevant features for GA estimation and developed an Indian population-specific formula (Garbhini-GA1) for the first trimester. PTB rates of Garbhini-GA1 and other formulae were compared by estimating sensitivity and accuracy. Results: Performance of Garbhini-GA1 formula, a non-linear function of crown-rump length (CRL), was equivalent to published formulae for estimation of first trimester GA (LoA, − 0.46,0.96 weeks). We found that CRL was the most crucial parameter in estimating GA and no other clinical or socioeconomic covariates contributed to GA estimation. The estimated PTB rate across all the formulae including LMP ranged 11.27–16.50% with Garbhini-GA1 estimating the least rate with highest sensitivity and accuracy. While the LMP-based method overestimated GA by 3 days compared to USG-Hadlock formula; at an individual level, these methods had less than 50% agreement in the classification of PTB. Conclusions: An accurate estimation of GA is crucial for the management of PTB. Garbhini-GA1, the first such formula developed in an Indian setting, estimates PTB rates with higher accuracy, especially when compared to commonly used Hadlock formula. Our results reinforce the need to develop population-specific gestational age formulae.

Enzyme kinetics data play a vital role in the design of reactors and control of processes. In the present study, kinetic studies on pectinases were carried out. Partially purified polymethylgalacturonase (PMG) and polygalacturonase (PG) were the two pectinases studied. The plot of initial rate vs. initial substrate concentration did not follow the conventional Michaelis-Menten kinetics, but substrate inhibition was observed. For PMG, maximum rate was attained at an initial pectin concentration of 3 g/l, whereas maximum rate was attained when the initial substrate concentration of 2.5 g/l of polygalacturonic acid for PG I and PG II. The kinetic data were fitted to five different kinetic models to explain the substrate inhibition effect. Among the five models tested, the combined mechanism of protective diffusion limitation of both high and inhibitory substrate concentrations (semi-empirical model) explained the inhibition data with 96-99% confidence interval.

Time-delay estimation in closed-loop systems is of critical value in the tasks of system identification, closed-loop performance assessment and process control, in general. In this work, we introduce the application of mutual information (MI) theory to estimate process delay under closed-loop conditions. The hallmark of the proposed method is that no exogenous (dither) signal is required to estimate the delay. Further, the method allows estimation of time-delays merely from the step response of the system. The method is based on the estimation of a quantity known as the average mutual information (AMI) computed between the input and output of the system. The estimation of AMI involves estimation of joint probability distribution of the input-output pair and therefore is a superset of the existing correlation-based methods, which only compute second-order moments of the joint distribution. Simulation studies are presented to demonstrate the practicality and utility of the proposed method.

Gasification of solid fuels such as coals, lignite and biomasses has been studied using isothermal and non-isothermal thermogravimetric analysis (TG) with CO2 as gasifying agent. Non-isothermal TG of three Indian coals (two bituminous and one sub-bituminous coal), one lignite and two biomass fuels (Casuarina and empty fruit bunches) at a constant heating rate of 20 °C min-1 in the temperature range from 25 to 1200 °C showed a clear separation of DTG peaks associated with pyrolysis and CO2 gasification. Based on these studies, isothermal TG experiments were conducted in the temperature range from 900 to 1100 °C for coals and from 800 to 1000 °C for biomass fuels. These results show that the CO2 gasification rate follows coal rank for the three coals and the lignite. The two biomasses have significantly higher reactivities than the three coals. The higher reactivity of one coal is attributed to the presence of calcium-containing minerals in its inorganic matter. The kinetic parameters for each fuel were extracted from the isothermal TG results using the volumetric reaction model for the coals and a zeroth-order model for biomass fuels. Biomass and lignite are found to have a much higher reactivity index and much lower conversion time than the three coals under identical conditions.

A binary mixture of oppositely charged colloids can be used to stabilize water-in-oil or oil-in-water emulsions. A Monte Carlo simulation study to address the effect of charge ratio of colloids on the stability of Pickering emulsions is presented. The colloidal particles at the interface are modeled as aligned dipolar hard spheres, with attractive interaction between unlike-charged and repulsive interaction between like-charged particles. The optimum composition (fraction of positively charged particles) required for the stabilization corresponds to a minimum in the interaction energy per particle. In addition, for each charge ratio, there is a range of compositions where emulsions can be stabilized. The structural arrangement of particles or the pattern formation at the emulsion interface is strongly influenced by the charge ratio. We find well-mixed isotropic, square, and hexagonal arrangements of particles on the emulsion surface for different compositions at a given charge ratio. The distribution of coordination numbers is calculated to characterize structural features. The simulation study is useful for the rational design of Pickering emulsifications wherein oppositely charged colloids are used, and for the control of pattern formation that can be useful for the synthesis of colloidosomes and porous shells derived thereof.

The effect of a soluble surfactant on the linear stability of layered two-phase Poiseuille flows through soft-gel-coated parallel walls is studied in this paper. The focus is on determining the effect of the elastohydrodynamic coupling between the fluids and the soft-gel layers on the various flow instabilities. The fluids are assumed Newtonian and incompressible, while the soft gels are modeled as linear viscoelastic solids. The effect of a soluble surfactant on the different instabilities is specifically investigated. The soft-gel-coated plates are maintained at two different solute concentrations. The dynamics of the soluble surfactant in the fluids is captured using a species transport equation. A linear stability analysis is carried out to identify different instabilities in the system. The linearized governing equations are solved numerically using a Chebyshev spectral Collocation technique. The effect of deformability of the soft gels on three distinct instability modes, (a) a liquid-liquid long-wave mode, (b) a liquid-liquid short-wave mode, and (c) a liquid-liquid Marangoni short-wave mode, is analyzed. An analytical expression for the growth rate is obtained in the long-wave length limit using an asymptotic analysis. From the long-wave analysis a stability map is obtained, in which dominant effects in different regions are identified. The Marangoni stresses can either stabilize or destabilize the interfacial instability depending on the direction of mass transfer. They have a predominantly stabilizing effect on the interfacial instability when the mass transfer is from the more viscous broader fluid to the less viscous thinner fluid. Placing a gel closer to the more viscous fluid has a stabilizing effect on this instability. The Marangoni stresses and soft-gel layers can have opposing effects on the stability of the long-wave mode. The dominant of these two opposing effects is determined by the prevailing parameters. Insights into the dominant physical causes of different instabilities are presented.

This study provides baseline information about indoor-outdoor PM concentrations, size-resolved bioaerosol concentration, size distribution and diversity, I/O ratios of PM and bioaerosol, indoor bioaerosol emissions for five locations such as laboratory, students’ office, air-conditioned room, eatery, and residence. While most of the indoor air quality studies reported so far emphasized on a distinct type of indoor environment at a time, this study provides a first-hand account about PM and bioaerosols simultaneously measured and compared from diverse yet commonly encountered indoor locations of southern Indian region. PM2.5 and PM10 was found to have similar concentration distributions at all locations. Elevated cooking activity and human induced floor resuspensions led to the highest indoor-outdoor number concentration of PM at eatery. The I/O mass concentration ratios indicated the influence of outdoor PM on indoor environment of laboratory. Presence of distinct sources that contributed to significant PM mass variations at indoor and outdoor environments were substantiated with ANOVA and chi-square test results. Human occupancy and potted plants was found contributing to the elevated indoor bacterial concentrations (>800 CFU m−3). Fine to coarse bioaerosol fractions implied the abundant presence of coarse mode bacteria and fungi amounting to >80% of total cultivable bioaerosol load across all locations. Bacilli and Gammaproteobacteria dominated the bacterial aerosols while Cladosporium and Aspergillus dominated the fungal aerosols. Fungi contributed highest to the mass fraction of PM10 in comparison to bacteria, both indoor and outdoor. Highest bacterial emission rates were observed at air-conditioned room (4.85 × 105 CFU/h/person) and fungal emissions at laboratory (4.60 × 105 CFU/h/person).