Relevant Publications

Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques

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…

Nonlinear Variable Selection Algorithms for Surrogate Modeling

AIChE Journal 2019

Jianyuan Zhai Fani Boukouvala

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…

Reduced order Discrete Element Method (DEM) modeling

Chemical Engineering Science 2013

F. Boukouvala F.J. Muzzio M.G. Ierapetritou Y. Gao

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…

Improving continuous powder blending performance using Projection to Latent Structures regression

Journal of Pharmaceutical Innovation 2013

Y. Gao F. Boukouvala W. Englisch W. Meng F.J. Muzzio M.G. Ierapetritou

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…

Computational Approaches for Studying the Granular Dynamics of Continuous Blending Processes, 2 – Population Balance and Data-Based Methods

Macromolecular Materials and Engineering 2012

F. Boukouvala A. Dubey A. Vanarase R. Ramachandran F.J. Muzzio M.G. Ierapetritou

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…

Dynamic Data-Driven Modeling of Pharmaceutical Processes

Industrial Engineering & Chemistry Research 2011

F. Boukouvala F.J. Muzzio M.G. Ierapetritou

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…