Optimization of municipal wastewater biological nutrient removal using ASM2d
Bibliographic record
Abstract
Activated sludge model No. 2d (ASM2d) was calibrated then used to determine optimal recycle rates and basin retention times, with respect to final N, soluble P (sP) or N plus sP concentrations for Modified Bardenpho (MB), Modified University of Cape Town (MUCT), and anaerobic–anoxic–oxic (A2O) biological nutrient removal processes. Simulations were conducted at two temperatures and three primary effluent (PE) concentrations (COD, TSS, TKN, sP). All BNR processes were shown to be capable of achieving an effluent sP concentration below 1 mg/L at all conditions when effluent N concentration was neglected. None of the processes were capable of producing an effluent with N concentrations below 5 mg/L at high PE concentration. The MB and MUCT processes were both successful in achieving a combined sP and N removal below 1 mg/L and 5 mg/L for low PE concentrations at 10 and 20 ºC. Only the MB process, at 20 ºC with medium PE concentrations, was found to achieve an effluent below 1 mg/L and 5 mg/L, respectively for sP and N. Recycle from the anoxic basin of the MUCT process had an insignificant effect on N and sP removals. All input variables to the MB and A2O process proved to be somewhat significant and it is recommended that they be kept within future experimental designs. Dynamic tests with real Ottawa plant influent flow data indicated that the MB process was more robust with respect to TN, sP, and CBOD5 removal than the MUCT process.Key words: activated sludge, biological nutrient removal, simulation, model, ASM2d.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".