Data-driven Process Systems Engineering Lab
Data-driven Process Systems Engineering Lab
Relevant Publications
Optimization Letters 2019
Optimization of simulation-based or data-driven systems is a challenging task, which has attracted significant attention in the recent literature. A very efficient approach for optimizing systems without analytical expressions is through fitting surrogate models. Due to their increased flexibility, nonlinear…
AIChE Journal 2019
Having the ability to analyze, simulate and optimize complex systems is becoming more important in all engineering disciplines. Decision-making using complex systems usually leads to nonlinear optimization problems, which rely on computationally expensive simulations. Therefore, it is often challenging to…
Chemical Engineering Science 2013
Reduced-order modeling (ROM) techniques are playing a very significant role in the recent literature bridging the gap between computationally expensive simulators and their application in optimization and control of distributed parameter systems. In modeling of solid-based processes, Discrete Element Method…
Journal of Pharmaceutical Innovation 2013
Purpose There has been increasing interest in the last few years especially within the pharmaceutical industry towards continuous powder blending. In this paper, the effects of different design and operating parameters are investigated, which include blade speed, shaft angle, weir…
Macromolecular Materials and Engineering 2012
The application of computationally inexpensive modeling methods for a predictive study of powder mixing is discussed. A multidimensional population balance model is formulated to track the evolution of the distribution of a mixture of particle populations with respect to position…
Industrial Engineering & Chemistry Research 2011
In many pharmaceutical process operations, first-principle models describing the behavior of the processed powders are difficult to derive or computationally very expensive and thus can be considered as “black-box” processes. Kriging is an efficient data-driven methodology that has been shown…