Education History

Guest Lectures

1. Workshop on Multiphysics Modeling using Finite Elements Method at the Penang Skills Development Centre (PSDC), Penang, Malaysia, Nov. 28, 2006.
2. A two day workshop on COMSOL Multiphysics Modeling at the Institute of High Performance Computing (IHPC), Singapore, Aug. 10 & 11, 2006.
3. MATLAB for Numerical computing, IEEE Student chapter, National University of Singapore, 2005.
4. Simulation & Modeling of Catalytic Reverse Flow Reactor, i-Math-A*Star Seminar on Multi-physics Modeling: FEMLAB and Grid-enabled FEMLAB, Singapore, Jan. 2005.
5. Transport in an Electrokinetic Valve, i-Math Biomedical Conference, Singapore, June 2004.

Research Interests

Overview

My research interest is mainly focused on Modeling, Optimization and Control of Various Systems. In specific:

• Dynamic modeling of Multi-Phase Reactor Systems used in Aluminum Production, Multi-Scale Modeling in Industrial Applications.
• Inventory Control of Moving Bed Reactors.
• Moving Boundary Problems - Modeling based on Level Set Method.
• Advanced Control Strategies such as Learning Control, Repetitive Model Predictive Control of Hybrid Systems.
• Modeling Various Systems from First Principles (simulated using the Multiphysics Modeling Software - COMSOL) and Scaling Analysis.
• Population Balance Modeling of Tumor Cells using Finite Elements Method.

Here is a brief description of some of my current research activities:

1. Carbothermic Aluminum Reduction Process (in collaboration with Yuan)

In this project, the focus is on developing a dynamic model for the entire carbothermic aluminum reduction process. Carbon and aluminum oxide are reacted at very high temperatures (> 2000°C) to produce aluminum. Thus, in order to study the process characteritics, the fluid flow dynamics and the heat transfer properties must be modeled carefully. The modeling part of this particular process can be divided into three main streams :

• Main Reactor - Smelting Stage (stage 1 and 2) - To model the reaction between carbon and alumina along with slag, vapors and other byproducts formation.
• VRR - Vapor Recovery Reactor (stage 3) - To capture the aluminum vapors produced in the main reactor by reacting the vapors with carbon particles - To model the reaction between vapors and carbon along with other byproducts formation
• Purification (stage 4) - To purify the aluminum produced in the main reactor - To model the process of extracting the aluminum metal from the alloy.

To obtain a clear picture of the process behavior, all the above mentioned stages have to be modeled as a whole as they are interlinked in a complex fashion. After modeling the process satisfactorily, studies will be carried out for optimal operation under various operating conditions. Many different concepts such as thermodynamic equilibrium, shrinking core model, mass, momentum and energy balances are to be modeled together. Thus, different software packages (FACTSAGE, CHEMAPP, COMSOL, MATLAB and C++) which are well known for their respective applications are to be used and linked together. We are interested in devising a complete model for such a complex process followed by further studies in understanding the behavior of the process through computer simulations.

Pilot plant data for model verification is obtained from ALCOA, the worlds leading producer of Aluminum.

2. Advanced Modeling, Sensitivity Analysis & Control of the Moving Bed Reactor - VRR (in collaboration with Mohit)

A distributed parameter model that describes mass transfer and heat transfer in a non-porous moving bed is studied in this work. The modeling is used to simulate the VRR operating in transient or steady-state regime. The external transfer of the gaseous species onto the surface of the solid particle, the diffusion through the pores of the solid product layer, and the heterogeneous chemical reaction at the surface of the solid reactant are taken into account. The reactions are mass-transfer-limited and hence a shrinking core model is used to describe the reaction rate. Preliminary results obtained from the VRR modeling is shown in the following figures.

A slight exothermic reaction in the reactor increases the temperature of the streams to a small extent and at the same time helps in maintaining the reactor temperature within a specified range.

The extent of carbon conversion in the reactor to capture the aluminum vapors shown in the following figure shows that, if operated appropriately, VRR can be used effectively to decrease the aluminum loss, thereby increase the yield of carbothermic reduction process.

We are interested in further modeling of VRR for accurate results by including dust formation, effect of feed impurities in the model.

Although distributed parameter models are advatageous in predicting the process accurately, from control point of view, such models are seldom used due to the complexity of the model and high computation time. Thus, we intend to implement an inventory control based on the total energy and total mass holdup in the system. This control strategy is believed to be computationally inexpensively and effective for such complex systems. Improved Modeling, Sensivity Analysis and Inventory Control of the reactor have to be performed to advance further into the implementation stages of the VRR at ALCOA.

Publications

1. Balaji, S., Lakshminarayanan, S., Krantz, W. B. Scaling and Sensitivity Analysis of a Reverse Flow Reactor, Chemical Engineering Science, 2008, 63, pp. 342-355.

2. Balaji, S., Lakshminarayanan, S., Forbes, J.F., & Hayes, R. E. Repetitive Model Predictive Control of a Reverse Flow Reactor, Chemical Engineering Science, 2007, 62, pp. 2154-2167.

3. Balaji, S., Lakshminarayanan, S. Novel design of Microchannel plate geometry for Uniform Flow Distribution, Canadian Journal of Chemical Engineering, 2006, 84, pp. 715-721.

4. Balaji, S., Lakshminarayanan, S. Performance Comparison of Autothermal Reactor Configurations for Methane Combustion, Industrial Engineering & Chemistry Research, 2006, 45 (11), pp. 3880-3890.

5. Balaji, S., Lakshminarayanan, S. Heat Removal from Reverse Flow Reactors used in Methane Combustion, Canadian Journal of Chemical Engineering,2005, pp. 695- 704.

1. Balaji, S., Erik Ydstie, B., (2008). Inventory Control of Vapor Recovery Reactor in Carbothermic Aluminum Production, to be presented at Advanced Control in Industrial Processes, Jasper, Alberta, Canada, May 4-6.

2. Fu Cehao, Kariwala, V., Balaji, S., (2008). Inferential Control of a Catalytic Flow Reversal Reactor with Mass and Heat Extraction Strategies, to be presented at Advanced Control in Industrial Processes, Jasper, Alberta, Canada, May 4-6.

3. Balaji, S., Lakshminarayanan, S., (2007). Control of Reverse Flow Reactors used for Methane Combustion: an overview, International Conference on Cleaner Technologies and Environmental Management, Pondicherry, India, Jan. 4-6.

4. Lakshminarayanan, S., Balaji, S., Raghuraj Rao, K., (2007). Role of Process Systems Engineering in Sustainable Development. International Conference on Cleaner Technologies and Environmental Management, Pondicherry, India, Jan. 4-6.

5. Balaji, S., Lakshminarayanan, S., Krantz, W. B., (2006). Scaling and Sensitivity Analysis of Simulated Moving Bed Reactors, American Institute of Chemical Engineers Conference (AIChE), San Francisco, Nov. 12-17.

6. Lakshminarayanan. S, Krantz, W. B., Balaji, S., (2006). Pedagogical and Learning Advantages Realizable Through Scaling and Non-Dimensionalization, American Institute of Chemical Engineers Conference (AIChE), San Francisco, Nov. 12-17.

7. Balaji, S., Lakshminarayanan, S., (2006). Learning Control for Periodic Systems with Unknown Periods, Asian Pacific Confederation of Chemical Engineering Congress, Kualalumpur, Malaysia, Aug. 27-30.

8. Lakshminarayanan, S., Raghuraj Rao, K., Balaji, S., (2006). “CONSIM”, MS Excel Based Student Friendly Simulator for Teaching Process Control Theory, Asian Pacific Confederation of Chemical Engineering Congress, Kualalumpur, Malaysia, Aug. 27-30.

9. Lakshminarayanan, S., Balaji, S., Raghuraj Rao, K., (2005). Impact of Process Design on Achievable Control Loop Performance, CHEMCON, 58th annual Indian session of the Institute of Chemical Engineers, New Delhi, India, Dec. 14-17.

10. Balaji, S., Lakshminarayanan, S., Forbes, J. F., & Hayes, R. E., (2005). Repetitive Model Predictive Control for Reverse Flow Reactors, CSChE (Canadian Society for Chemical Engineers) conference, Toronto, ON, Oct. 16-19.

11. Balaji, S., Zheng Suni, Lakshminarayanan, S., Nandakumar, K., (2005). Generation of Desired Concentration Profiles in Micro-fluidic Networks, 2nd Annual Graduate Student Symposium, National University of Singapore, Oct. 6.