Interaction between control and design of a SHARON reactor: economic considerations in a plant-wide (BSM2) context
Bibliographic record
Abstract
The combined SHARON-Anammox process is a promising technique for nitrogen removal from wastewater streams with high ammonium concentrations. It is typically applied to sludge digestion reject water, in order to relieve the activated sludge tanks, to which this stream is typically recycled. This contribution assesses the impact of the applied control strategy in the SHARON-reactor, both on the effluent quality of the subsequent Anammox reactor as well as on the plant-wide level by means of an operating cost index. Moreover, it is investigated to which extent the usefulness of a certain control strategy depends on the reactor design (volume). A simulation study is carried out using the plant-wide Benchmark Simulation Model no. 2 (BSM2), extended with the SHARON and Anammox processes. The results reveal a discrepancy between optimizing the reject water treatment performance and minimizing plant-wide operating costs.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".