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<p>Optimization at an industrial scale is a complex task requiring fine-tuning large-scale systems to enhance efficiency and effectiveness. This challenge arises from increasing system complexity, high processing demands, and the need for optimal performance. In low-density polyethylene (LDPE) production, significant 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 differential 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 differential equations-based optimization problem, with the orthogonal collocation (OC) technique as a solution method. OC discretizes differential equations on finite elements, making it highly effective for this application. This work represents the first application of OC for simultaneous optimization and parameter estimation in LDPE production, considering productivity, profitability, and energy consumption as key objective functions. The optimized parameters include monomer flow rate (FM), initiator flow rate (FI), solvent flow rate (FS), and reactor inlet pressure (Pin). In contrast, reactor jacket temperature (T<sub>J</sub>) is selected as the optimized control variable. Critical production aspects must be estimated before developing an industrial-scale mathematical model, including reactor configuration, operating conditions, heat transfer factors, flow 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 first validated against industrial data, and three optimization scenarios are evaluated. The optimal reactor performance is identified based on maximum profit, yielding a maximum conversion of 32.2%, an annual profit of RM 328 million, and a moderate compression power requirement of 5719 kWh.</p>

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Finite Element-Based Optimization of Industrial Low-Density Polyethylene Production in a Tubular Reactor: Addressing Energy and Productivity Challenges

  • 期刊论文

  • 发表日期：

    2025年5月12日

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  • Fakhrony Sholahudin Rohman,
  • Sharifah Rafidah Wan Alwi,
  • Dinie Muhammad,
  • Nur Hazwani Yusoff Azudin,
  • Muhamad Nazri Murat,
  • Ashraf Azmi‬‬‬‬‬

摘要

Optimization at an industrial scale is a complex task requiring fine-tuning large-scale systems to enhance efficiency and effectiveness. This challenge arises from increasing system complexity, high processing demands, and the need for optimal performance. In low-density polyethylene (LDPE) production, significant 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 differential 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 differential equations-based optimization problem, with the orthogonal collocation (OC) technique as a solution method. OC discretizes differential equations on finite elements, making it highly effective for this application. This work represents the first application of OC for simultaneous optimization and parameter estimation in LDPE production, considering productivity, profitability, and energy consumption as key objective functions. The optimized parameters include monomer flow rate (FM), initiator flow rate (FI), solvent flow 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 configuration, operating conditions, heat transfer factors, flow 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 first validated against industrial data, and three optimization scenarios are evaluated. The optimal reactor performance is identified based on maximum profit, yielding a maximum conversion of 32.2%, an annual profit of RM 328 million, and a moderate compression power requirement of 5719 kWh.