Mathematical and computational modeling of membrane distillation technology: A data-driven review

Abstract

Membrane distillation (MD) technology is increasingly gaining attention as an environmentally sustainable water treatment method of emerging interest. During last three decades there has been wide efforts to model and improve the performance of this technology. In this study we examine both the mathematical and computational modeling methods used in MD with a data-driven method. To gather the dataset, a broad range of terms related with theoretical modeling of MD were searched in the Scopus database. The collection consists of 526 documents including 116 journals, 14,291 references used by authors, 1252 involved authors and 29.47 % international co-authorship rate. The overall pattern of publications is found to increase over time indicating the enhancing interest on theoretical modeling of MD process. Journal of Membrane Science and Desalination are the top two journals publishing theoretical modeling of MD, with 105 and 100 articles, respectively. Dr. Ghaffour N. contributed with the highest number of articles, 24; and Dr. Khayet M. has the highest articles fractionalized value with 7.08. The dataset was categorized first into mathematical and computational modeling, then into the used mass transport approaches through membrane hydrophobic pores. Recently, in MD field computational modeling has been considered more than mathematical modeling. The combined Knudsen diffusion/ordinary molecular diffusion model is the dominant mass transport approach considered in MD mathematical modeling with 117 articles. On the other hand, computational fluid dynamics is the most used computational method with 114 articles.

Keywords

• Membrane distillation
• Bibliometric analysis
• Data-driven approach
• Data mining
• Data analysis
• Computational modeling