Dynamics and stability analysis of gas-phase bulk polymerization of propylene

Luo, Lei; Zhang, Nan; Xia, Zhouhui; Qiu, Tong

doi:10.1016/j.ces.2015.12.018

Cited by 7 publications

(3 citation statements)

References 16 publications

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“…The stability of the open-loop operation reflects the intrinsic characteristics of a nonlinear system. Stability analysis is the basis for diagnosing steady and unsteady states and for finding out the root causes of oscillation, 45 which will be used to determine the operation point and control strategy. Thermal stability of an open-loop fluidized-bed reactor is related to many influencing factors, such as the catalyst and particle properties, reaction kinetics, operating conditions, reactor size, and others.…”

Section: Resultsmentioning

confidence: 99%

Thermal-Stability Analysis of Ethylene-Polymerization Fluidized-Bed Reactors under Condensed-Mode Operation through a TPM−PBM Integrated Model

Fan

Sun

Yang

et al. 2019

Ind. Eng. Chem. Res.

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Thermal stability is a crucial issue for fluidized-bed ethylene-polymerization reactors, especially when the particle-aggregation probability increases as a result of the high reaction temperature or operation under condensed mode. To determine the mean particle size, a population-balance model (PBM) considering particle growth and particle aggregation was implemented in the present study. Then, an integrated model including the two-phase model (TPM), the PBM, and an evaporation model was proposed to describe polymerization of ethylene in liquid-containing fluidized-bed reactors. The results demonstrate that the particle-growth rate and catalyst particle size dominate the particle size of the final product. Thermal stability of fluidized-bed reactors is mainly affected by the catalyst activation energy, the superficial-gas velocity, and the condensed-liquid flow rate.

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Section: Resultsmentioning

confidence: 99%

Thermal-Stability Analysis of Ethylene-Polymerization Fluidized-Bed Reactors under Condensed-Mode Operation through a TPM−PBM Integrated Model

Fan

Sun

Yang

et al. 2019

Ind. Eng. Chem. Res.

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“…Generally, the process models can be classified into firstprinciple and data-driven types. The first-principle models allow one to take deep insights and interpret complex interactions between variables and parameters [1][2][3]. Meanwhile, the data-driven models exhibit excellent performance on high-dimensional data for time series prediction [4], fault diagnosis [5,6], etc.…”

Section: Introductionmentioning

confidence: 99%

“…Mean square error, i.e., MSE 2. The number of features considered for split equals to the square root of the total number.…”

mentioning

confidence: 99%

Association Measure and Compact Prediction for Chemical Process Data from an Information-Theoretic Perspective

Luo

Yue-qun

et al. 2022

Processes

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Mutual information (MI) has been widely used for association mining in complex chemical processes, but how to precisely estimate MI between variables of different numerical types, discriminate their association relationships with targets and finally achieve compact and interpretable prediction has not been discussed in detail, which may limit MI in more complicated industrial applications. Therefore, this paper first reviews the existing information-based association measures and proposes a general framework, GIEF, to consistently detect associations and independence between different types of variables. Then, the study defines four mutually exclusive association relations of variables from an information-theoretic perspective to guide feature selection and compact prediction in high-dimensional processes. Based on GIEF and conditional mutual information maximization (CMIM), a new algorithm, CMIM-GIEF, is proposed and tested on a fluidized catalytic cracking (FCC) process with 217 variables, one which achieves significantly improved accuracies with fewer variables in predicting the yields of four crucial products. The compact variables identified are also consistent with the results of Shapley Additive exPlanations (SHAP) and industrial experience, proving good adaptivity of the method for chemical process data.

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Catalyst Type Effects on Structure/Property Relations of Polypropylene Random Copolymers

Paulik

Tranninger

Wang

et al. 2021

Macro Chemistry & Physics

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Polypropylene (PP) random copolymers are an important class of commercial materials that can be tuned for a wide range of different applications. The structure-property relations are mainly discussed in this article focusing on two major influencing factors, the catalyst system and the type and amount of comonomer. Ziegler-Natta (ZN) catalyst systems still dominate the production of polypropylene and todays sixth-generation ZN catalysts are based on postphthalate donor systems. Metallocene (MC) catalysts offer possibilities to exactly control the microstructure of the polymer even better. Mostly, ethylene is used as comonomer being randomly distributed for up to 7.3 mol% when using ZN catalysts. For single site catalysts, homogenous (single phase) materials can be achieved up to ethylene contents of 20.8 mol%. The incorporated comonomer reduces the crystallization speed and the lamellar thickness of the polymer thus affording soft and highly transparent materials. Random copolymers and terpolymers with higher 𝜶-olefins only play a minor role but offer an additional possibility for property adjustments. PP random copolymers can also be varied in their performance through multistage polymerizations, altering the comonomer content and or the molecular weight in the different polymerization reactors.

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Dynamics and stability analysis of gas-phase bulk polymerization of propylene

Cited by 7 publications

References 16 publications

Thermal-Stability Analysis of Ethylene-Polymerization Fluidized-Bed Reactors under Condensed-Mode Operation through a TPM−PBM Integrated Model

Thermal-Stability Analysis of Ethylene-Polymerization Fluidized-Bed Reactors under Condensed-Mode Operation through a TPM−PBM Integrated Model

Association Measure and Compact Prediction for Chemical Process Data from an Information-Theoretic Perspective

Catalyst Type Effects on Structure/Property Relations of Polypropylene Random Copolymers

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