Flow rate perturbations for enhanced heat transfer and fouling mitigation in once-through steam generators
Bibliographic record
Abstract
• Examine flow rate perturbation and its impact on heat transfer in an OTSG pass. • Ten minutes of doubled flow rate every six hours yields lower tube wall temperature. • Perturbation lowers peak tube temperature mitigating risk of overheating. • Perturbation improves heat transfer efficiency between flue gas and tube wall. • Perturbation reduces impact of fouling with respect to tube overheating. Once-through steam generators (OTSGs) are widely employed in Steam-Assisted Gravity Drainage (SAGD) operations. Boiler feedwater, composed of treated produced water and fresh make-up water, retains dissolved solids that precipitate during steam generation, leading to fouling on tube surfaces, affecting heat transfer. This fouling causes localized temperature spikes on the tube walls, which can result in tube failure, operational shutdowns, and expensive repairs. This study investigates, for the first time, the impact of flow rate perturbations on heat transfer within a single pass of an operational OTSG by using a detailed multi-phase computation fluid dynamics model of a OTSG pass. Specifically, a controlled flow rate increase, doubling the baseline rate, is applied for 10 min every six hours. This perturbation effectively lowers tube wall temperatures, enhances heat transfer between the flue gas and tube wall, lowers the peak temperature in the tubes even in the presence of fouling. The moderation of tube overheating reduces the risk of tube failure. Consequently, the operational efficiency of the OTSG could be improved due to mitigation of fouling-related maintenance.
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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 | 0.000 | 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".