My Research |Welcome to Dr. Rao's Arena

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Research Profile on Research Gate

Projects

Real-time Process Monitoring, Diagnostics,and Model Identification

Proj: Accurate prediction and reliable forecast of water levels and currents in Singapore Regional Waters

Developed a numerical grid model using Finite Element Model (FEM) to estimate nonlinear tidal interactions in and around Singapore.
Data driven techniques were developed to integrate the data and model outputs.
Kalman filter (KF) based data assimilation techniques are implemented to estimate the model states and corrected based on the Kalman residual gain.
For accurate and long prediction forecast of water levels and currents, variants of Kalman filters like extended Kalman filter (EKF), Ensemble Kalman filter (EnKF) and Steady state Kalman filter (SSKF) are applied.
A navigation tool box is developed for precise docking and unloading of ships which play a key role in the economic growth of Singapore.

Water-Energy Nexus,

Energy efficiency

Proj: Optimal Design of Systems in Chilled Water Plant Rooms

Design and performance of existing chilled water systems is investigated
To maximize their efficiency via system-wide optimization procedures that ensures all sub-systems and their interactions are duly considered and accounted for.
An improved chilled water system proposed has a lower operating cost and energy efficient thus significantly reduce energy consumption, and lower the carbon footprint of buildings substantially.

Java based software development for Operational Management System

Proj: OpenDA: computationally intensive software tool

Developed computationally intensive evolutionary algorithms for data assimilation.
Developed a calibration and computationally intensive software tool called as OpenDA to implement on nonlinear high dimensional models.
Implementing evolutionary optimization techniques for estimating the model states and improve the tidal and forcing constituents at the open boundaries.
This software is developed with the collaboration of research centre in Deltares, Delft University of Technology, and the scientific software engineering firm VORtech, all in the Netherlands.
This tool box is successfully applied to various applications from weather prediction, oceanography, oil exploration and chemical engineering applications.

Process modeling and Optimisation of Adsorption Process

Goal: To apply optimization tool to estimate the process parameters in isotherm and kinetic modelling of adsorption process..
Proposed hybrid evolutionary optimizations tools:
1. Differential evolution
2. Ant colony optimization
3. Particle Swarm Optimization
4. Artificial Bee Colony
5. Mine Blast optimization
6. Water cycle optimization

Data driven Modelling
1. ANN
2. RBFN
3. Genetic Algorithm

Optimized control strategy, Multivariable control, Operational Management System

Proj : Multi Objective Multiple Reservoir Management

Developed a multi objective scheme to integrate and control the reservoirs to meet the future enormous demand of water supply and minimize flooding.
Operational schematization is developed to integrate reservoirs located within Singapore that are widely with different spatial characteristics.
Control strategy is developed taking into the account of water quality and quantity control objectives.
Model uncertainties and the coordination between the controllers within and across the hierarchy were evaluated.
With a flexible and reliable control strategy, the Centralized Model Predictive Control (CMPC) is implemented via the Operational Management System (OMS)
State-of-the-art technologies have been developed and investigated to support appropriate management decisions

Machine Learning, Data Assimilation, Big Data analytics, Data-Model Integration

Proj : Punggol Serangoon Reservoir Predictive Water Quality modelling and study

Developed mitigative measures for integration of Punggol and Serangoon Reservoirs and the water way.
Performed scenario analysis with the models to assess the water quality in terms of climate change, sea level rise and extreme conditions.
Assessment of hydrological and hydrodynamic parameters on water quality and quantity.
Developed comprehensive study and Operational Management System and a water quality management plan.

Control of highly exothermic runaway reactions

Proj: Control of highly exothermic runaway reactions

Studied and analyzed various runaway reactions and their severe causalities in process industries.
Sensitivity studies are carried out to identify the system parameters and operating conditions that lead to thermal runaway when operated beyond the threshold value.
Various experimental studies are performed to identify the severity of the reaction and condition that leads to thermal explosion of the reactor.
Highly nonlinear kinetic model for the reaction system is developed and validated with the experimental data.
A Graphical User Interface (GUI) is developed in visual basic which interfaces the experimental setup via the SCADA and DCS network, with controller embedded in the back end.
Advanced controllers like Fuzzy Logic Control (FLC), Generic Model Control (GMC), Internal Model Control (IMC) and Model Predictive Control (MPC) are successfully applied to the control the reactor temperature at the desired temperature trajectory.
With complete automation of the reactants input into the reactors, hybrid evolutionary controllers with stochastic optimizers like Simulated Annealing Nonlinear Model Predictive Control (SANMPC) and Genetic Algorithm Model Predictive Control (GAMPC) were developed and implemented.
The controller thus developed is modified for its robustness to control any exothermic reaction systems especially which is likely to runaway and all the safety measures are incorporated to avert runaway and prevent losses.