A rate-based dynamic model of multicomponent distillation column for 18O isotope separation

Lashkarboluki, R.; Mallah, Mohammad Hassan

doi:10.1016/j.seppur.2019.115745

Cited by 6 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [42][43][44], mathematical models are proposed for separation processes, but having constant parameters. In this case, the usage of AI is not necessarily due to the absence of the necessity to learn variable parameters.…”

Section: Introductionmentioning

confidence: 99%

AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

et al. 2021

View full text Add to dashboard Cite

In the paper, the comparison between the efficiency of using artificial intelligence methods and the efficiency of using classical methods in modelling the industrial processes is made, considering as a case study the separation process of the 18O isotope. Firstly, the behavior of the considered isotopic separation process is learned using neural networks. The comparison between the efficiency of these methods is highlighted by the simulations of the process model, using the mentioned modelling techniques. In this context, the final part of the paper presents the proposed model being simulated in different scenarios that can occur in practice, thus resulting in some interesting interpretations and conclusions. The paper proves the feasibility of using artificial intelligence methods for industrial processes modeling; the obtained models being intended for use in designing automatic control systems.

show abstract

Section: Introductionmentioning

confidence: 99%