Optimal polymer grade transitions for fluidized bed reactors

Wang, Yajun; Biegler, Lorenz T.; Ostace, George Simion; Majewski, Rita A.

doi:10.1016/j.jprocont.2020.02.001

Cited by 6 publications

(10 citation statements)

References 30 publications

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“…The former requires a tight regulation, leading to the production of an exact target grade, which is also known as a target-to-target transition strategy. On the other hand, the multistage formulation refers to driving the product’s grade to a small specification band that is acceptable. , …”

Section: Closed-loop Simulation Resultsmentioning

confidence: 99%

“…Apart from this demand surge, pulp mills experience frequent grade changes to meet various market demands . Depending on the circumstances, the grade transitions can take a long time to complete and produce a large amount of off-grade pulp, which may be sold at a significantly lower price than in-grade ones . Because of the multiscale nature of grade transition occurring during pulping, the incorporation of a multiscale model into the design of a control system would enhance the profitability of pulp mills.…”

Section: Introductionmentioning

confidence: 99%

“…Although the previous modeling efforts made remarkable contributions on capturing macroscopic phenomena in the pulp digester, important microscopic properties are still partially described; recently developed multiscale models are able to capture the evolution of fiber morphology such as porosity, CWT, and fiber length, − but these models have focused on a batch pulping, which is not applicable to a large-scale commercial continuous pulp digester. Furthermore, even though optimal grade transition techniques have been developed for polymerization processes, ,, very limited efforts have been made to implement the strategies to Kraft pulping processes, despite the need for those techniques to handle the frequent grade changes and unexpected demand surges. Motivated by the limitation, we developed a multiscale model of continuous pulping and designed an inferential model-based feedback controller to regulate blow-line pulp properties and achieve optimal grade transition operations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Inferential Model Predictive Control of Continuous Pulping under Grade Transition

Choi¹,

Son²,

Kwon³

2021

Ind. Eng. Chem. Res.

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Even though continuous pulp processes have been studied for many years, the absence of a model that can accurately describe the evolution of fiber morphology has impeded the application of advanced control techniques. In this study, a multiscale model for continuous Kraft pulping processes, which can capture the spatiotemporal evolution of wood chips and cooking liquor, is developed by integrating a macroscopic model (i.e., Purdue model) with a microscopic model (i.e., kinetic Monte Carlo algorithm). Then, an approximate model is identified to circumvent the high computational requirement of the multiscale model and to handle the input time-delay, followed by designing a soft sensor to infer state variables and primary measurements. This allows the use of an inferential model predictive control strategy in a continuous pulp digester to regulate the blow-line pulp properties (i.e., Kappa number and cell wall thickness) and achieve optimal grade transitions.

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Section: Closed-loop Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Inferential Model Predictive Control of Continuous Pulping under Grade Transition

Choi¹,

Son²,

Kwon³

2021

Ind. Eng. Chem. Res.

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“…Recent related studies for continuous multi‐product polymerization plants can be found in Zavala et al, [ 5 ] Shi et al, [ 6 ] and Wang et al [ 7 ] Shi et al [ 6 ] developed an optimization strategy for polymer grade transitions for a multi‐product continuous loop reactor. In this work, a rigorous mathematical model was developed for the entire reactor‐based process.…”

Section: Introductionmentioning

confidence: 99%

“…These recipes efficiently shorten the transition time and significantly reduce the off‐transition products. A similar approach was proposed by Wang et al [ 7 ] where multi‐stage dynamic optimization was implemented on a gas‐phase fluidized bed polymerization process. In addition to off‐line optimization, they extended this approach to shrinking horizon nonlinear model predictive control, along with an expanding horizon weighted least‐squares estimator for process states and unknown parameters.…”

Section: Introductionmentioning

confidence: 99%

Continuous reactor network design for multiple rigid polyol productions

Wen

Biegler

Ochoa

et al. 2021

J Adv Manuf & Process

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This study focuses on developing continuous reactor network models able to produce multiple rigid polyol products under strict product and safety specifications. We first determine reactor networks and operating decisions for minimum capital cost, and then find reactor networks with optimal profit through multi‐criteria optimization, using a Pareto chart to analyze the relationship between capital cost and net sales. Based on our previous study, we narrow down the types of continuous reactors that can be part of the network to two: plug flow reactor (PFR) with multiple feed injection points and a network of continuous stirred tank reactors (CSTR). The CSTR model can be written as a mixed integer nonlinear programming (MINLP) problem. The PFR model is a differential algebraic equation (DAE) optimization problem. The simultaneous collocation method is applied to transform the resulting DAE model into an MINLP, which is solved as a NLP by fixing the binary terms. Both capital cost and multi‐criteria problems are formulated as multi‐scenario optimization problems to determine the best single network design to produce multiple polymer products.

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Robust dynamic optimization for nonlinear chemical processes under measurable and unmeasurable uncertainties

Liang

Yuan

2022

AIChE Journal

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We formulate an integrated framework for the robust dynamic optimization of nonlinear chemical processes under measurable and unmeasurable uncertainties. An affine decision rule is proposed to approximate the causal dependence of the wait‐and‐see decision variables on the gradually revealed measurable uncertainties. To overcome the computational intractability of the proposed model, a linearization technique based on the first‐order Taylor expansion is introduced around the nominal values of uncertainties to derive the robust dynamic counterpart, which can be discretized to a large‐scale nonlinear programming (NLP) formulation. Effects of first discretizing the dynamic models or introducing the affine decision rule are investigated. The proposed framework is also compared with the state‐of‐the‐art re‐optimization and traditional robust optimization approaches. An illustrative example and an industrial semi‐batch 2‐mercaptobenzothiazole production case are involved to demonstrate the advantages and applicability of the proposed framework.

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Optimal polymer grade transitions for fluidized bed reactors

Cited by 6 publications

References 30 publications

Inferential Model Predictive Control of Continuous Pulping under Grade Transition

Inferential Model Predictive Control of Continuous Pulping under Grade Transition

Continuous reactor network design for multiple rigid polyol productions

Robust dynamic optimization for nonlinear chemical processes under measurable and unmeasurable uncertainties

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