Growth and property development of convection pass deposits in recovery boilers : final project project.
Bibliographic record
Abstract
As part of the U.S. Department of Energy (DOE) Office of Industrial Technologies (OIT) Industries of the Future (IOF) Forest Products research program, the mechanisms of particle deposition and properties of deposits that form in the convection passes of recovery boilers were investigated. Research from experimental facilities at Sandia National Laboratories, the Institute of Paper Science and Technology (IPST), and the University of Toronto (U of T) was coordinated into a single effort to define the controlling mechanisms and rates of deposition. Deposition rates were recorded on a volumetric and mass basis in a Sandia facility for particle sizes in the range of 0.1 to 150 {micro}m. Deposit thickness, mass, spectral emissivity, thermal conductivity, surface temperature, and apparent density were monitored simultaneously and in situ on instrumented probes that allow determination of heat flux and probe surface temperature. Particle composition and mass deposition rates were also recorded in a U of T facility for particle sizes in the range of 100 to 600 {micro}m. These measurements allowed determination of the liquid content and sticking efficiency of carryover particles that inertially impact on a deposition probe. In addition, information on particulates, stable gas species, gas temperature and velocity were obtained from field tests in an operating recovery boiler. The results were used to develop algorithms appropriate for use in computer codes that simulate recovery boilers. Representative calculations were performed using B&W's comprehensive recovery boiler model to demonstrate the use of the algorithms in such computer codes. Comparisons between observations in commercial systems and model predictions were made to identify algorithm strengths and weaknesses.
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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".