Use of neural networks in process engineering thermodynamics, diffusion, and process control and simulation applications

  • F. OTERO Ecopetrol S.A. – Instituto Colombiano del Petróleo, A.A. 4185 Bucaramanga, Santander, Colombia
Keywords: process engineering, neural networks, process control, process modeling, process simulation


This article presents the current status of the use of Artificial Neural Networks (ANNs) in process engineering applications where common mathematical methods do not completely represent the behavior shown by experimental observations, results, and plant operating data. Three examples of the use of ANNs in typical process engineering applications such as prediction of activity in solvent-polymer binary systems, prediction of a surfactant self-diffusion coefficient of micellar systems, and process control and simulation are shown. These examples are important for polymerization applications, enhanced-oil recovery, and automatic process control.


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How to Cite
OTERO, F. . (1998). Use of neural networks in process engineering thermodynamics, diffusion, and process control and simulation applications. CT&F - Ciencia, Tecnología Y Futuro, 1(4), 49–64.


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