Development & Implementation of Efficient Numerical & High-performance Computational Techniques 

Here, we seek to develop better numerical techniques and model reduction techniques to solve complex process models (e.g. PBM and PBM-DEM ) with reduced simulation times whilst maintaining high accuracy. We also work on the massive parallelization of population balance models using high performance and distributed computing techniques. 

Cell-average Technique
Cell-average Technique

Three-dimensional non-linear grid showing bins of varying sizes in each dimension

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Parallel Computing
Parallel Computing

Piechart representation of MATLAB's profiler results for a serial version of the 4-D granulation PBM code run on a single worker

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Model Order Reduction
Model Order Reduction

Exponential increase in computation time with grids size. Grid count represents the total number of bins in each dimension

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List of Publications from this Research Area: