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Evaluation of optimization techniques for an extractive alcoholic fermentation process.

Aline C da Costa1, Rubens Maciel Filho

  • 1DPQ/FEQ/UNICAMP, Cx. Postal 6066, Campinas, SP, 13081-970 Brazil. accosta@feq.unicamp.br

Applied Biochemistry and Biotechnology
|April 1, 2004
PubMed
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Mathematical optimization of continuous alcoholic fermentation with vacuum flash distillation maximized yield and productivity. Simplified models offer acceptable results when rigorous models are impractical.

Area of Science:

  • Chemical Engineering
  • Process Optimization
  • Biotechnology

Background:

  • Continuous alcoholic fermentation is crucial for industrial ethanol production.
  • Process optimization is key to maximizing yield and productivity.
  • Vacuum flash distillation is an energy-efficient separation technique.

Purpose of the Study:

  • To mathematically optimize a continuous alcoholic fermentation process coupled with vacuum flash distillation.
  • To maximize fermentation yield and productivity using advanced modeling techniques.

Main Methods:

  • Surface response analysis, modeling, and simulation were employed.
  • Nonlinear programming and successive quadratic programming (SQP) were utilized for optimization.
  • Both deterministic (experimentally parameterized) and statistical (factorial design) models were evaluated.

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Main Results:

  • The rigorous deterministic model yielded the best results for yield and productivity.
  • The simplified statistical model provided acceptable performance metrics.
  • Optimization using SQP demonstrated the effectiveness of the chosen techniques.

Conclusions:

  • Mathematical optimization effectively enhances continuous alcoholic fermentation processes.
  • Simplified models are viable alternatives when complex models are not feasible.
  • The study validates the use of SQP for optimizing fermentation and separation processes.