Modeling of Distillation Column and Reactor Dynamics Using Artificial Neural Networks
Author : Jun-Ku Park
Publisher :
Page : pages
File Size : 39,90 MB
Release : 1993
Category :
ISBN :
Author : Jun-Ku Park
Publisher :
Page : pages
File Size : 39,90 MB
Release : 1993
Category :
ISBN :
Author : Vandana Sakhre
Publisher : de Gruyter
Page : 214 pages
File Size : 43,76 MB
Release : 2021-03-17
Category : Technology & Engineering
ISBN : 9783110656145
Neural Networks is an integral part in machine learning and a known tool for controlling nonlinear processes. The area is under rapid development and provides a tool for modelling and controlling of advanced processes. This book provides a comprehensive overview for modelling, simulation, measurement and control strategies for reactive distillations using neural networks.
Author : Francisco J. Sanchez-Ruiz
Publisher :
Page : 0 pages
File Size : 31,23 MB
Release : 2018
Category : Electronic books
ISBN :
The use of artificial intelligence techniques in the design of processes has generated a line of research of interest, in areas of chemical engineering and especially in the so-called separation processes, in this chapter the combination of artificial neural networks (ANN) is presented and fuzzy dynamic artificial neural networks (DFANN). Applied to the calculation of thermodynamic properties and the design of reactive distillation columns, the ANN and DFANN are mathematical models that resemble the behavior of the human brain, the proposed models do not require linearization of thermodynamic equations, models of mass and energy transfer, this provides an approximate and tight solution compared to robust reactive distillation column design models. Generally, the models must be trained according to a dimensionless model, for the design of a reactive column a dimensionless model is not required, it is observed that the use of robust models for the design and calculation of thermodynamic properties give results that provide better results than those calculated with a commercial simulator such as Aspen Plus (R), it is worth mentioning that in this chapter only the application of neural network models is shown, not all the simulation and implementation are presented, mainly because it is a specialized area where not only requires a chapter for its explanation, it is shown that with a neural network of 16 inputs, 2 hidden layers and 16 outputs, it generates a robust calculation system compared to robust thermodynamic models that contain the same commercial simulator, a characteristic of the network presented is the minimization of overlearning in which the network by its very nature is low. In addition, it is shown that it is a dynamic model that presents adjustment as a function of time with an approximation of 96,Äì98% of adjustment for commercial simulator models such as Aspen Plus (R), the DFANN is a viable alternative for implementation in processes of separation, but one of the disadvantages of the implementation of these techniques is the experience of the programmer both in the area of artificial intelligence and in separation processes.
Author : Edna Treviño
Publisher :
Page : 286 pages
File Size : 37,30 MB
Release : 1993
Category : Distillation apparatus
ISBN :
Author : Urmila Diwekar
Publisher : CRC Press
Page : 402 pages
File Size : 11,53 MB
Release : 2011-12-21
Category : Science
ISBN : 1466515422
Most available books in chemical engineering mainly pertain to continuous processes, with batch distillation relegated to a small section. Filling this void in the chemical engineering literature, Batch Distillation: Simulation, Optimal Design, and Control, Second Edition helps readers gain a solid, hands-on background in batch processing. The seco
Author : Kailas L. Wasewar
Publisher :
Page : 0 pages
File Size : 36,26 MB
Release : 2009
Category :
ISBN :
As a result of good modeling capabilities, neural networks have been used extensively for a number of chemical engineering applications such as sensor data analysis, fault detection and nonlinear process identification. However, only in recent years, with the upsurge in the research on nonlinear control, its use in process control has been widespread. But there is almost no work which has tested the capacity of Artificial Neural Network (ANN) to model Reactive Distillation (RD). The superiority of ANN was tested for the synthesis of 2-methylpropylacetate from 2-methylpropanol and acetic acid by RD. The effects of various parameters like feed, temperature, reflux ratio, and boil-up ratio, each varied at three levels, were studied. At each combination, the composition of distillate and bottom was predicted by Aspen simulation. An appropriate ANN model was fitted using generated data. A three-layered feed-forward back-propagation model, with 3, 5 and 4 neurons in the layers, was fitted. Log-sig function was used in each layer. The model was found to have high R2 (= 0.993) value and good predicting capability.
Author : J.G. Balchen
Publisher : Elsevier
Page : 387 pages
File Size : 28,42 MB
Release : 2014-05-23
Category : Technology & Engineering
ISBN : 1483298779
In addition to the three main themes: chemical reactors, distillation columns, and batch processes this volume also addresses some of the new trends in dynamics and control methodology such as model based predictive control, new methods for identification of dynamic models, nonlinear control theory and the application of neural networks to identification and control. Provides a useful reference source of the major advances in the field.
Author : Vilmar Steffen
Publisher : BoD – Books on Demand
Page : 123 pages
File Size : 47,34 MB
Release : 2019-12-04
Category : Computers
ISBN : 178923915X
The purpose of this book is to offer readers important topics on the modeling, simulation, and optimization of distillation processes. The book is divided into four main sections: the first section is introduction to the topic, the second presents work related to distillation process modeling, the third deals with the modeling of phase equilibrium, one of the most important steps of distillation process modeling, and the the fourth looks at the reactive distillation process, a process that has been applied successfully to a number of applications and has been revealed as a promising strategy for a number of recent challenges.
Author : Joel Charles MacMurray
Publisher :
Page : 228 pages
File Size : 31,92 MB
Release : 1993
Category : Packed towers
ISBN :
Author : J.B. Rawlings
Publisher : Elsevier
Page : 513 pages
File Size : 20,35 MB
Release : 2014-05-23
Category : Technology & Engineering
ISBN : 1483296881
Three important areas of process dynamics and control: chemical reactors, distillation columns and batch processes are the main topics of discussion and evaluation at the IFAC Symposium on Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (DYCORD '95). This valuable publication was produced from the latest in the series, providing a detailed assessment of developments of key technologies within the field of process dynamics and control.