In situ combustion measurements of CO, H_2O, and temperature with a 158-µm diode laser and two-tone frequency modulation
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
An optical near-infrared process sensor for electric are furnace pollution control and energy efficiency is proposed. A near-IR tunable diode laser has performed simultaneous in situ measurements of CO (1,577.96 nm), H2O (1,577.8 and 1,578.1 nm), and temperature in the exhaust gas region above a laboratory burner fueled with methane and propane. The applicable range of conditions tested is representative of those found in a commercial electric arc furnace and includes temperatures from 1,250 to 1,750 K, CO concentrations from 0 to 10%, and H20 concentrations from 3 to 27%. Two-tone frequency modulation was used to increase the detection sensitivity. An analysis of the method's accuracy has been conducted with 209 calibration and 105 unique test burner setpoints. Based on the standard deviation of differences between optical predictions and independently measured values, the minimum accuracy of the technique has been estimated as 36 K for temperature, 0.5% for CO, and 3% for H2O for all 105 test data points. This accuracy is sufficient for electric arc furnace control. The sensor's ability to nonintrusively measure CO and temperature in real time will allow for improved process control in this application.
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 | 0.000 | 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 it