scholarly journals Multi-Output Soft Sensor with a Multivariate Filter That Predicts Errors Applied to an Industrial Reactive Distillation Process

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1947
Author(s):  
Vladimir Klimchenko ◽  
Andrei Torgashov ◽  
Yuri A. W. Shardt ◽  
Fan Yang
Keyword(s):  
Distillation Column ◽  
Reactive Distillation ◽  
Optimal Estimation ◽  
Soft Sensor ◽  
Methyl Tert Butyl Ether ◽  
Model Errors ◽  
Distillation Process ◽  
Butyl Ether ◽  
Predict Model ◽  
Estimation Of Time

The paper deals with the problem of developing a multi-output soft sensor for the industrial reactive distillation process of methyl tert-butyl ether production. Unlike the existing soft sensor approaches, this paper proposes using a soft sensor with filters to predict model errors, which are then taken into account as corrections in the final predictions of outputs. The decomposition of the problem of optimal estimation of time delays is proposed for each input of the soft sensor. Using the proposed approach to predict the concentrations of methyl sec-butyl ether, methanol, and the sum of dimers and trimers of isobutylene in the output product in a reactive distillation column was shown to improve the results by 32%, 67%, and 9.5%, respectively.

scholarly journals Multi-Aspect Comparison of Ethyl Acetate Production Pathways: Reactive Distillation Process Integration and Intensification via Mechanical and Chemical Approach

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1618
Author(s):  
Branislav Šulgan ◽  
Juraj Labovský ◽  
Zuzana Labovská
Keyword(s):  
Ethyl Acetate ◽  
Case Studies ◽  
Chemical Reaction ◽  
Distillation Column ◽  
Reactive Distillation ◽  
Process Integration ◽  
Distillation Process ◽  
Acetate Production ◽  
Conventional Process ◽  
Set Up

This paper provides a multi-aspect comparison of selected methods of ethyl acetate production and shows the possibility of further reactive distillation process integration and sophisticated intensification including process stream regeneration. The production pathways were selected with respect to their practical applicability and sufficient experimental and feasibility studies already published. A total of four case studies were designed and compared: conventional process set-up (ethyl acetate is produced in a chemical reactor) is designed as a base case study; reactive distillation with a separation unit is derived from the conventional process set-up. The mechanical and chemical approach to reactive distillation process intensification and integration were assumed: reactive distillation column with a stripper and reactive distillation column with an auxiliary chemical reaction (ethylene oxide hydration). Process models were compiled in the Aspen Plus software. Complex process flowsheets of selected case studies including separation and regeneration were designed and optimized. Three different points of view were applied to evaluate the selected process benefits and drawbacks. Process energy, economy, and safety were assessed. As a result, a reactive distillation column with an auxiliary chemical reaction has been proven to be the most suitable pathway for ethyl acetate production assuming all three evaluated aspects.

Recurrent Neural Network based Soft Sensor for Monitoring and Controlling a Reactive Distillation Column

2017 ◽  
Vol 13 (3) ◽  
Author(s):  
Gaurav Kataria ◽  
Kailash Singh
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Distillation Column ◽  
Butyl Acetate ◽  
Closed Loop ◽  
Reactive Distillation ◽  
Dynamic Network ◽  
Open Loop ◽  
Soft Sensor ◽  
Esterification Reaction

Abstract For the real time monitoring of a Reactive Distillation Column (RDC), a Recurrent Neural Network (RNN) based soft sensor has been proposed to estimate the bottoms product composition of the RDC for the synthesis of n-Butyl Acetate using esterification reaction. This soft sensor acts as a measuring element in a closed loop involving a PI controller for the direct control of the RDC’s product concentration. The RNN acts as a dynamic network, which works on the sequential input data and output data with a recurrent connection. While using the RNN based soft sensor in the open loop, it has been observed that the sensor estimated the composition of butyl acetate in the bottoms with such an accuracy that it can be used for the control purpose. Closed loop results demonstrated that the system has been showing precise controlled results and soft sensor is showing small prediction Mean Square Error (MSE) when disturbances in feed flow rate and set point changes are introduced.

scholarly journals Design and simulation of high purity biodiesel reactive distillation process

2019 ◽  
Vol 21 (3) ◽  
pp. 1-7 ◽  
Author(s):  
Syed Sadiq Ali ◽  
Mohammad Asif ◽  
Avijit Basu
Keyword(s):  
High Purity ◽  
Fossil Fuels ◽  
Distillation Column ◽  
Reactive Distillation ◽  
Aspen Plus ◽  
Esterification Reaction ◽  
Distillation Process ◽  
Water Composition ◽  
Product Stream ◽  
Process Simulator

Abstract Biodiesel is a promising energy substitute of fossil fuels since it is produced from renewable and biodegradable sources. In the present work, reactive distillation (RD) process is designed and simulated using Aspen Plus process simulator to produce biodiesel of high purity through esterification reaction. The simultaneous reaction and separation in same unit enhances the biodiesel yield and composition in RD process. Two flowsheets are proposed in present work. In the first flowsheet, the unreacted methanol is recycled back to reactive distillation column. Biodiesel with 99.5 mol% purity is obtained in product stream while the byproduct stream comprises 95.2 mol% water, which has to be treated further. In the second flowsheet, a part of methanol recycle is split and purged. In this case, the biodiesel composition in product stream is 99.7 mol% whereas water composition is 99.9 mol% in byproduct stream, which can be reused for other process without treatment.

Neural - Wiener Model for Multivariable Methyl Tertiary Butyl Ether (MTBE) Reactive Distillation

2013 ◽  
Vol 284-287 ◽  
pp. 409-413
Author(s):  
Sudibyo Sudibyo ◽  
Muhamad Nazri Murat ◽  
Norashid Aziz
Keyword(s):  
Reactive Distillation ◽  
State Space Model ◽  
Nonlinear Behavior ◽  
Distillation Process ◽  
Wiener Model ◽  
Butyl Ether ◽  
Separation Processes ◽  
Tertiary Butyl ◽  
Highly Nonlinear ◽  
Reliable Model

MTBE is a chemical that can be used as anti-knock additive to replace lead additive (tetra ethyl lead) which can be efficiently produced using reactive distillation process. It has been established in the literature that MTBE reactive distillation poses a highly nonlinear behavior due to the combination of reaction and separation processes. A reliable model for predicting the behavior is required especially for the control purposes. In this work, a Neural Wiener model which is one of the available types of oriented block model was utilised to develop the MTBE reactive distillation model. The required data for the Neural Wiener model were generated using a validated Aspen dynamics model for the MTBE reactive distillation process. It is found that the Neural Wiener model is capable to predict the MTBE purity and isobutene conversion with accuracy of 98.55% and 96.95%, respectively. Those values are quantitatively better in comparison to the state space model which gives lower values for prediction accuracy of 87.86% and 82.90%, respectively.

scholarly journals Modeling Of A Reactive Distillation Column: Methyl Tertiary Butyl Ether (Mtbe) Simulation Studies

1970 ◽  
Vol 4 (2) ◽  
Author(s):  
Ismail Mohd Saaid Abdul Rahman Mohamed and Subhash Bhatia
Keyword(s):  
Distillation Column ◽  
Reactive Distillation ◽  
Relaxation Method ◽  
Differential Algebraic Equations ◽  
Operating Conditions ◽  
Integration Scheme ◽  
Algebraic Equations ◽  
Butyl Ether ◽  
Tertiary Butyl ◽  
Proposed Model

A process simulation stage-wise reactive distillation column model formulated from equilibrium stage theory was developed. The algorithm for solving mathematical model represented by sets of differential-algebraic equations was based on relaxation method. Numerical integration scheme based on backward differentiation formula was selected for solving the stiffness of differential-algebraic equations. Simulations were performed on a personal computer (PC Pentium processor) through a developed computer program using FORTRAN90 programming language. The proposed model was validated by comparing the simulated results with the published simulation results and with the pilot plant data from the literature. The model was capable of predicting high isobutene conversion for heterogeneous system, as desirable in industrial MTBE production process. The comparisons on temperature profiles, liquid composition profile and operating conditions of reactive distillation column also showed promising results. Therefore the proposed model can be used as a tool for the development and simulation of reactive distillation column.Keywords: Modeling, simulation, reactive distillation, relaxation method, equilibrium stage, heterogeneous, MTBE

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