Optimization of Continuously Stirred Tank Bioreactor Design for Cost Minimization: Effect of Microbial Species and Operating Conditions
Bibliographic record
Abstract
The operation of continuously stirred tank bioreactors (CSTBs) at minimum cost is a major concern of operators. In this work, a CSTB design strategy is presented where impeller stirring speed and aeration rate are optimized to meet the oxygen demand of growing cells, simultaneously minimizing the capital and operating cost. The operating cost is limited to the cost of utilities. The optimization scheme assumes a given fermentor tank size, and that the properties of the culture medium and the oxygen respiratory requirements of the microorganisms being cultivated are known. It is possible to choose between two different turbine impellers during the design process. The equations, constraints, and the CSTB design strategy employed by the program are described. The effect of microbial species, ions in the culture medium, impeller style, as well as changing CSTB size and biomass input density on the optimum operating conditions, is examined. The mass transfer coefficient, gas holdup, mixing speed, and aeration rate are all reported at optimized cost conditions. A study of the effects of various parameters on the CSTB design are shown.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".