The September issue of The Canadian Journal of Chemical Engineering features 19 new articles, including four articles from our Process Control, Systems Engineering, and Statistics subject area.
The issue highlights for this month contain two of our mini-reviews from the Experimental Methods in Chemical Engineering special series (freely available until the end of October 2019). The first article conducts an up-to-date analysis on how researchers have been using Artificial Neural Networks (ANNs). A collaboration from researchers at Polytechnique Montréal, McGill University, and University of Cambridge, this article finds that there were more than 13 000 articles mentioning ANNs indexed in Web of Science in the last two years. Analyzing the bibliometric data, the researchers suggest how ANNs can be used for a variety of chemical engineering purposes, like creating models and predictions for fluid dynamics or reactor performance.
The second Experimental Methods in Chemical Engineering article that the September issue highlights explores Fluidized Bed Reactors. The authors, from University of Zaragoza and Polytechnique Montréal, conduct a review of recent literature on fluidized bed reactors and describe how they are currently being used in chemical engineering research. This paper demonstrates that there are five clusters in fluidized bed reactor research: gasification and pyrolysis, combustion and CO2 capture, biomass, simulation and computational fluid dynamics, and coal technology.
The next issue highlight is “Fault Diagnosis in Industrial Chemical Processes using Optimal Probabilistic Neural Network.” This article proposes new solutions for how to better detect and diagnose faults in large-scale industrial settings. Ultimately, this research concludes that combining the modified cuckoo search algorithm with the probabilistic neural network method and the random forest tree bagger algorithm allows for a significant improvement in Tennessee Eastman process fault diagnosis.
Finally, “Application of extended quadrature method of moments for simulation of bubbly flow and mass transfer in gas‐liquid stirred tanks,” rounds out the issue highlights for the month. This paper, from authors at Sherbrooke University, uses OpenFOAM (an open-source computational fluid dynamics package) to model two gas-liquid stirred tanks: the first tank is agitated by a radial impeller and the second uses an axial impeller. The results of this paper’s theoretical modelling achieve a fair agreement with experimental data.