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

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

Model Order Reduction
Exponential increase in computation time with grids size. Grid count represents the total number of bins in each dimension
List of Publications from this Research Area:
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