Finite element-based optimization of industrial low-density polyethylene production in a tubular reactor: Addressing energy and productivity challenges
Optimization at an industrial scale is a complex task requiring fne-tuning large-scale systems to enhance efciency and efectiveness. This challenge arises from increasing system complexity, high processing demands, and the need for optimal performance. In low-density polyethylene (LDPE) production,...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Springer nature link
2025
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/44190/1/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/44190/ https://doi.org/10.1007/s41660-025-00514-x |
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| Summary: | Optimization at an industrial scale is a complex task requiring fne-tuning large-scale systems to enhance efciency and efectiveness. This challenge arises from increasing system complexity, high processing demands, and the need for optimal performance. In low-density polyethylene (LDPE) production, signifcant energy is required for compression, and reactant materials are costly, making process optimization essential for maximizing productivity while minimizing energy consumption. However, optimizing an LDPE tubular reactor is challenging due to the presence of both diferential equations and static constraints. The success of the optimization method depends on a well-formulated mathematical model. This study employs the discretization approach to address the nonlinear diferential equations-based optimization problem, with the orthogonal collocation (OC) technique as a solution method. OC discretizes diferential equations on fnite elements, making it highly efective for this application. This work represents the frst application of OC for simultaneous optimization and parameter estimation in LDPE production, considering productivity, proftability, and energy consumption as key objective functions. The optimized parameters include monomer fow rate (FM), initiator fow rate (FI), solvent fow rate (FS), and reactor inlet pressure (Pin). In contrast, reactor jacket temperature (TJ) is selected as the optimized control variable. Critical production aspects must be estimated before developing an industrial-scale mathematical model, including reactor confguration, operating conditions, heat transfer factors, fow dynamics, kinetic constants, and physical property variations. This study employs an OC-based approach for LDPE production that accounts for product constraints while estimating unknown kinetic constants. The LDPE model is frst validated against industrial data, and three optimization scenarios are evaluated. The optimal reactor performance is identifed based on maximum proft, yielding a maximum conversion of 32.2%, an annual proft of RM 328 million, and a moderate compression power requirement of 5719 kWh. |
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