IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Selective heating of different phases of multiphase systems via microwaves can result in energy savings and suppression of side reactions. However, materials properties and operating conditions that maximize temperature gradients are poorly understood. Here we utilize computational fluid dynamics (CFD) computations and temperature measurements in structured flow reactors (monoliths) in a monomodal microwave cavity to assess the temperature difference between the walls and the fluid and develop a simple lumped model to estimate when temperature gradients exist. We also explore the material's thermal and electrical properties of structured reactors for isothermal catalyst conditions. We propose that CFD simulations can be used as a nonintrusive, predictive tool of temperature homogeneity. Importantly, we demonstrate that localized heating in the bed under several conditions rather than selective heating is responsible for the selectivity enhancement. Our results indicate that structured beds made of high thermal conductivity materials avoid arcing and enable temperature homogeneity and low electrical conductivity materials allow microwaves to penetrate the domain. ©

World University root node

Department Of Chemical Engineering

Industrial and Engineering Chemistry Research

Temperature Homogeneity under Selective and Localized Microwave Heating in Structured Flow Reactors

Selective microwave heating can significantly impact the performance of multiphase reactors, such as slurry reactors, where the dispersed (solid particles) and continuum (liquid) phases have different dielectric properties. Lack of tools to measure and predict the temperature difference between the dispersed and continuum phases hinders the understanding and optimization of microwave-heated slurry reactors. We utilize experiments, theory, and multiscale simulations to investigate microwave heating of slurries consisting of microwave absorbing solid particles dispersed in a non-polar liquid. Using controlled experiments and mathematical modeling, we propose an ideal slurry reactor and develop analytical expressions to predict the temperature evolution of the solid and liquid phases during microwave heating. Our experiments show a strong impact of the solid material and concentration on the heating rate of slurries, whereas no difference is observed in conventionally heated slurries. We also perform multiscale simulations of microwave-heated slurries employing a coarse-graining methodology to handle the large separation of length scales in slurries and compare them against experiments. © 2020 Elsevier B.V.

Chemical Engineering Journal

Microwave heating of slurries

Modeling of microwave heating of multiphase systems requires resolving the electromagnetic field from the single particle to the entire cavity. We introduce a multiscale methodology for computationally affordable simulations of microwave heating of multiphase systems consisting of one phase dispersed in a continuum phase. The methodology homogenizes the original multiphase system, by taking advantage of the large separation of length scales, to calculate the effective permittivity, effective thermal conductivity, and volumetric power absorbed in each phase. The methodology is rigorously assessed against particle-resolved detailed numerical simulations of model systems. We demonstrate a significant reduction in computational cost while retaining the accuracy of detailed simulations. The present methodology enables high throughput exploration of novel multiphase system designs utilizing microwave heating.

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Multiscale modeling of microwave-heated multiphase systems

Widespread use of microwave technology requires quantitative scale-up models. Currently, microwave models are typical qualitative in nature. This work focuses on rendering models quantitative and elucidating the scale-up behavior of microwave heating using numerical simulations. A commonly used bench-scale microwave reactor from the CEM Corp. (CEM Discover SP) is used for benchmarking. To enable quantitative modeling, microwave heating experiments are conducted and compared to COMSOL calculations to develop a calibration curve for the set point vs the actually delivered microwave power. Using the validated computational model, microwave-heating of various liquids in a wide range of vial sizes is investigated. The computational study shows that during the scale-up, the volumetric power absorbed passes through a maximum, whereas the energy efficiency and heating uniformity exhibit strongly nonlinear behavior. This work introduces a method for quantitative microwave models and insights into the scale-up of commercial microwave reactors. © 2019 American Chemical Society.

Scaleup of a Single-Mode Microwave Reactor

A recurring challenge among the variety of existing biomass-to-biofuel conversion technologies is the need to ensure optimal and homogeneous contact between the various phases involved. The formulation of robust design rules from an empirical standpoint alone remains difficult due to the wide range of granular flow regimes coexisting within a given reactor. In this work, a volume-filtered Eulerian-Lagrangian framework is employed that solves chemically reacting flows in the presence of catalytic particles. The simulation strategy is used to quantify the role of the particle clustering on catalytic upgrading of biomass pyrolysis vapor in risers. It is shown that particle clustering can reduce the catalytic conversion rate of biomass pyrolysis vapors by up to about 50%. The simulation results are also compared with an engineering model based on continuously stirred tank reactor (CSTR). A one-dimensional Reynolds-averaged transport equation is derived, and the unclosed terms that account for the heterogeneity caused by clusters are evaluated. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3341–3353, 2018. © 2018 American Institute of Chemical Engineers

AIChE Journal

A computational study of the effects of multiphase dynamics in catalytic upgrading of biomass pyrolysis vapor

Recognizing the role of chemistry in the development of novel, more efficient engine technologies, numerical simulations of practical combustion systems are employing increasingly complex chemical kinetic models. A major challenge in such simulations is the cost of evaluating the chemical source terms, which often dominates the overall CPU cost, especially when using implicit numerical methods. In this case, a significant contributor to the chemical source term CPU cost is the evaluation of the jacobian matrix by the stiff ODE solver employed. This contribution can however be significantly decreased if an analytical formulation is explicitly provided to the solver. While automatic analytical jacobian code generators have been developed in the literature, in this work, we extend the concept to handle the case of reduced kinetic models that involve quasi-steady state assumptions. The algorithm includes smart ordering of the quasi-steady-state variables to minimize the number of operations needed to invert the QSS algebraic system, and the automatic generation of the routines needed to evaluate the analytical jacobian corresponding to the non-QSS species. The algorithm is validated and its performance assessed using a reduced n-dodecane oxidation model in the context of partially stirred reactor simulations. © 2018 Eastern States Section of the Combustion Institute. All rights reserved.

2018 Spring Technical Meeting of the Eastern States Section of the Combustion Institute, ESSCI 2018

An analytical jacobian generator for reduced chemical kinetic models involving quasi-steady-state assumptions

Efficient conversion of biomass into biofuels is still a challenge, and predictive modeling tools have the potential to accelerate the development and deployment of new conversion technologies, such as biomass thermochemical conversion. The high variability in the physical properties of biomass and their influence on biomass devolatilization hinder the deployment of detailed particle models for biomass devolatilization. In this work, we focus on the modeling of biomass devolatilization and evaluate the impact of variability in the physical properties of biomass on the validation of devolatilization models against experiments. For this purpose, we develop a one-dimensional spherically symmetric intra-particle heat and mass transfer model that describes the devolatilization of a porous solid biomass particle coupled with a lumped chemical kinetic model. Thermal conductivities of biomass and char, and specific heat capacity of biomass are varied and the predictions of the devolatilization model are compared with the experiments of maple wood sphere devolatilization. © 2018 Eastern States Section of the Combustion Institute. All rights reserved.

Effect of variability in biomass properties on biomass devolatilization

Predictive modeling tools have the potential to accelerate the development and deployment of biomass thermochemical conversion. Considerable progress has been made in the modeling of biomass pyrolysis at the particle level, where chemical kinetics and transport processes are coupled. However, rigorous validation of the corresponding models is challenging because of the considerable uncertainty in the values of several biomass properties. Toward this end, we use the principles of uncertainty quantification (UQ) for a rigorous analysis of the validity of a commonly used one-dimensional wood pyrolysis model. Uncertainty in the modeling parameters of the transport processes is propagated to the simulation results of the pyrolysis model. The model predictions are compared with several detailed experimental measurements for pyrolysis of wood particles. The results show that the uncertainty in the model predictions account for some of the discrepancies with the experimental measurements, especially for the particle temperature profiles and the gas phase species production rates. Experimental targets are identified whose predictions cannot be improved by an accurate knowledge of the transport model parameters and require further improvements in the chemical kinetics model. The use of a systematic optimization technique is also demonstrated to choose the optimal values of uncertain model parameters. © 2018 American Chemical Society.

ACS Sustainable Chemistry and Engineering

On the Validation of a One-Dimensional Biomass Pyrolysis Model Using Uncertainty Quantification

Risers are used in a variety of industries, where rapid mixing between gas and solid particles is essential. More recently, risers are gaining importance in some of the novel combustion technologies, such as Chemical-looping combustion and thermochemical conversion of biomass. These reactor configurations provide challenging modeling issues, as the particulate flow is characterized by a highly fluctuating solid volume fraction due to the formation of dense clusters. This may severely reduce the mixing between gas and solid particles and affect the residence time of the particles in the reactor, and thus, the extent of heterogeneous reactions between gas and solid particles. In this work, we investigate how clustering impacts heterogeneous reactions in risers using a detailed Euler-Lagrange computational framework. For this purpose, three-dimensional laboratory-scale riser simulations are performed. A simplified reaction system is used, where the solid-fluid reaction is represented by a single isothermal reaction step. To asses the effect of multiphase dynamics of the bed on the heterogeneous chemistry, the three-dimensional simulation results are compared with reduced-order models. © 2017 Eastern States Section of the Combustion Institute. All rights reserved.

10th U.S. National Combustion Meeting

Impact of clustering on heterogeneous reactions in a riser

Computational fluid dynamics (CFD) tools are increasingly gaining importance to obtain detailed insight into biomass gasification. A major shortcoming of the current CFD tools to study biomass gasification is the lack of computationally affordable chemical kinetic models, which allows detailed predictions of the yield and composition of various gas and tar species in complex reactor configurations. In this work, a detailed mechanism is assembled from the literature and reduced to a compact model describing the gas-phase reactions of biomass gasification in the absence of oxygen. The reduction procedure uses a graph-based method for unimportant kinetic pathways elimination and quasi-steady-state species selection. The resulting reduced model contains 39 gas species and 118 reactions and is validated against the detailed model and two experimental configurations: the pyrolysis of volatile species, such as levoglucosan, in a tubular reactor, and the fast pyrolysis of biomass particles in a drop tube reactor. The reduced model predicts the evolution of major gas products (e.g., CO, CO2, CH4, H2) and various classes of tar (e.g., single-ring aromatics, oxygenated aromatics, PAHs) produced during biomass gasification. The capability of the reduced model to adequately capture the chemical process in a complex reactor geometry at an acceptable computational cost is demonstrated by employing it in a simulation of a pseudo two-dimensional laboratory-scale fluidized bed reactor.

Energy & Fuels

A Compact Kinetic Model for Biomass Pyrolysis at Gasification Conditions

One of the major requirements of any biomass gasification modeling study is the ability to predict the yield and composition of tar produced under various operating conditions. It requires the use of a detailed chemical kinetic model, able to accurately predict the evolution of various chemical species important in the tar evolution chemistry, integrated with a CFD solver. But these detailed kinetic models consist of thousands of reactions and hundreds of species making their use computationally unaffordable. Therefore, most of the gasification modeling studies rely on global kinetic models that can not provide the details of tar evolution. To tackle this problem, we develop a reduced kinetic model for the secondary gas phase reactions of biomass gasification from the detailed chemical kinetics available in the literature. This model achieves a balance between computational expense and details required. Predictions of our reduced model are compared with the detailed kinetic model and experimental data for a Plug Flow Reactor (PFR) configuration. © 2016, Eastern States Section of the Combustion Institute. All rights reserved.

2016 Spring Technical Meeting of the Eastern States Section of the Combustion Institute, ESSCI 2016

A reduced kinetic model for secondary reactions of biomass gasification

Instabilities of a pressure driven two-layer Poiseuille flow confined between a rigid wall and a Darcy-Brinkman porous layer are explored. A linear stability analysis of the conservation laws leads to an Orr-Sommerfeld system, which is solved numerically with appropriate boundary conditions to identify the time and length scales of the instabilities.fde The study uncovers the coexistence of twin instability modes, (i) long-wave interfacial mode-engendered by the viscosity stratification across the interface and (ii) finite wave number shear mode-originating from the inertial stresses, for almost all combinations of the viscosity (μr) and thickness (h r) ratios of the liquid layers. The presence of the porous layer reduces the frictional influence on the films, which significantly alters the length and time scales of the shear mode while the interfacial mode remains dormant to this effect. This is in stark contrast to the two-layer flow confined between non-porous plates where an unstable interfacial (shear) mode is observed when μr&gt;hr2(μr&lt;hr2). The study reveals that strength of the shear mode, (a) increases with porosity, (b) initially increases and then becomes constant with porous layer thickness, (c) initially increases then reduces with increase in permeability, and (d) reduce with increase in the stress jump coefficient at the porous-liquid interface. Moreover, the gravity expedites the destabilization of both the modes in the inclined channels as compared to the similar non-inclined channels. The parametric study presented can find important applications in enhancing heat and mass transfer, mixing, and emulsification especially in the microscale flows. © 2013 Elsevier Ltd.

Department of Mathematics

Chemical Engineering Science

Instabilities of a confined two-layer flow on a porous medium: An Orr-Sommerfeld analysis

We explore the salient features of the different instability modes of a pressure-driven two-layer plane Couette flow confined between a moving wall and a Darcy-Brinkman porous layer. A linear stability analysis of the conservation laws leads to an Orr-Sommerfeld system, which is solved numerically with appropriate boundary conditions to identify the time and length scales of the instability modes. The study reveals that the movement of the confining wall together with the slippage at the porous-liquid interface originating from the flow inside the porous layer can stimulate a pair of finite-wave-number shear modes in addition to the long-wave interfacial mode of instability. The shear modes dominate the interfacial mode, especially when the frictional influence at the liquid layers is smaller due to the movement of the confining plate or due to the larger slippage at the porous-liquid interface. The shear modes are found to be present under all combinations of the viscosity μr and thickness hr ratios of the liquid layers. This is in stark contrast to the two-layer flow confined between nonporous plates where the interfacial (shear) mode is observed only when μr&gt;hr2 (μr&lt; hr2). Interestingly, the strength of one of the shear modes is found to increase with the velocity of the bounding moving plate, whereas the other shear mode gains strength in the presence of highly porous, permeable, and thick porous layers. The results reported can be of significant importance in the microscale two-phase flows where the presence of a bounding porous layer or moving wall can expedite the intermixing of layers to improve the multiphase mixing, heat and mass transfer, and emulsification characteristics. © 2013 American Physical Society.

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics

Instability modes of a two-layer Newtonian plane Couette flow past a porous medium

The present paper proposes indices for assessing seismic vulnerability of multi-storeyed reinforced concrete buildings with moment resisting frames based on the equivalent static analysis and push-over analysis. Based on the push-over analysis, indices for the lateral load resistance of a building, drift of a building, overall performance of the beams and columns (referred to as members), performance of the columns in individual storeys are proposed. Based on the equivalent static analysis, an index for the storey drifts, an overall index for the demand-to-capacity ratios of the members and an index for the demand-to-capacity ratios of the columns in individual storeys are proposed. The purpose of the indices is to have quantitative and objective measures of the observations from the analyses, which otherwise remain subjective. The indices can be used to compare alternative retrofit schemes. A case study is reported to demonstrate the applicability of each index. From the results it can be concluded that the indices indeed reflect the deficiencies as per the respective analysis. From a push-over analysis, an index can detect a soft storey mechanism and other indices can check the lateral load resistance and drift of the building based on the required performance level. If a pushover analysis cannot be performed, indices based on the equivalent static analysis can detect the high demand in the columns of an open ground storey, and check the storey drifts.