Real time, non-intrusive measurement of particle emissivity and gas temperature in coal-fired power plants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We present a novel, remote technique for measuring in situ and in real time (every 2 s) the spectral emissivity of particles at λ = 3.95 µm, in optically thick combustion environments. The novelty lies in the use of spectral information in the mid-IR (the blackbody emission profile of the 4.3 µm CO2 band and the gray emission profile of particles between 3.8 and 4.1 µm) to determine the physical and brightness temperatures of the gas–particle medium, from which particle emissivity can be calculated. The retrieved particle emissivity at 3.95 µm is a reasonable average of total particle emissivity between 1 and 15 µm. Thus, CFD researchers who work with radiation sub-models may use this technique to obtain in situ emissivities at different locations, with a portable, rugged and inexpensive device. A small prototype was built with off-the-shelf components: standard light collection optics, a grating spectrometer and a linear-array pyroelectric detector. The particle emissivity is calculated from the asymptotic solution of the radiative transfer equation for optically thick media with isotropic scatterers. Results from a proof-of-concept test at a full-scale, coal-fired boiler 10 m above the top row of burners showed an average particle emissivity of 0.41 and an average gas temperature of 1533 K. Intrinsic and prototype error as well as the impact of temperature gradients in the line of sight of the instrument are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it