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Achieving Optimal Paper Properties: A Layered Multiscale kMC and LSTM-ANN-Based Control Approach for Kraft Pulping. Processes (Basel) 2023. [DOI: 10.3390/pr11030809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023] Open
Abstract
The growing demand for various types of paper highlights the importance of optimizing the kraft pulping process to achieve desired paper properties. This work proposes a novel multiscale model to optimize the kraft pulping process and obtain desired paper properties. The model combines mass and energy balance equations with a layered kinetic Monte Carlo (kMC) algorithm to predict the degradation of wood chips, the depolymerization of cellulose, and the spatio-temporal evolution of the Kappa number and cellulose degree of polymerization (DP). A surrogate LSTM-ANN model is trained on data generated from the multiscale model under different operating conditions, dealing with both time-varying and time-invariant inputs, and an LSTM-ANN-based model predictive controller is designed to achieve desired set-point values of the Kappa number and cellulose DP while considering process constraints. The results show that the LSTM-ANN-based controller is able to drive the process to desired set-point values with the use of a computationally faster surrogate model with high accuracy and low offset.
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Bijok N, Fiskari J, Gustafson RR, Alopaeus V. Chip scale modelling of the kraft pulping process by considering the heterogeneous nature of the lignocellulosic feedstock. Chem Eng Res Des 2023. [DOI: 10.1016/j.cherd.2023.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
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Shibani B, Ambure P, Purohit A, Sutaria P, Bhartiya S. Control of batch pulping process using data-driven constrained iterative learning control. Comput Chem Eng 2023. [DOI: 10.1016/j.compchemeng.2023.108138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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Zhang L, Xie J, Dubljevic S. Sensor Location Selection for Continuous Pulp Digesters with Delayed Measurements. AIChE J 2022. [DOI: 10.1002/aic.17862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Lu Zhang
- Department of Chemical & Materials Engineering University of Alberta Edmonton AB Canada
| | - Junyao Xie
- Department of Chemical & Materials Engineering University of Alberta Edmonton AB Canada
| | - Stevan Dubljevic
- Department of Chemical & Materials Engineering University of Alberta Edmonton AB Canada
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Jung J, Choi HK, Son SH, Kwon JSI, Lee JH. Multiscale modeling of fiber deformation: Application to a batch pulp digester for model predictive control of fiber strength. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2021.107640] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Xiao T, Wu Z, Christofides PD, Armaou A, Ni D. Recurrent Neural-Network-Based Model Predictive Control of a Plasma Etch Process. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c04251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Tianqi Xiao
- College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Zhe Wu
- Department of Chemical and Biomolecular Engineering, National University of Singapore, 117585, Singapore
| | - Panagiotis D. Christofides
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, California 90095-1592, United States
- Department of Electrical and Computer Engineering, University of California, Los Angeles, California 90095-1592, United States
| | - Antonios Armaou
- Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Department of Chemical Engineering, University of Patras, 26243 Patras, Greece
| | - Dong Ni
- College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
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Son SH, Choi H, Kwon JS. Application of offset‐free Koopman‐based model predictive control to a batch pulp digester. AIChE J 2021. [DOI: 10.1002/aic.17301] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Sang Hwan Son
- Artie McFerrin Department of Chemical Engineering Texas A&M University College Station Texas USA
| | - Hyun‐Kyu Choi
- Artie McFerrin Department of Chemical Engineering Texas A&M University College Station Texas USA
| | - Joseph Sang‐Il Kwon
- Artie McFerrin Department of Chemical Engineering Texas A&M University College Station Texas USA
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Choi HK, Son SH, Sang-Il Kwon J. Inferential Model Predictive Control of Continuous Pulping under Grade Transition. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.0c06216] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Hyun-Kyu Choi
- Artie McFerrin Department of Chemical Engineering, 3122 TAMU, 100 Spence Street, College Station, Texas 77843, United States
- Texas A&M Energy Insitute, 1617 Research Parkway, College Station, Texas 77843, United States
| | - Sang Hwan Son
- Artie McFerrin Department of Chemical Engineering, 3122 TAMU, 100 Spence Street, College Station, Texas 77843, United States
- Texas A&M Energy Insitute, 1617 Research Parkway, College Station, Texas 77843, United States
| | - Joseph Sang-Il Kwon
- Artie McFerrin Department of Chemical Engineering, 3122 TAMU, 100 Spence Street, College Station, Texas 77843, United States
- Texas A&M Energy Insitute, 1617 Research Parkway, College Station, Texas 77843, United States
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