Design of a Pentagonal Frustum-Shaped Gas Chamber for Multi-Gas NDIR Sensing
Bibliographic record
Abstract
To address the trade-off between miniaturization and optical path length in non-dispersive infrared (NDIR) gas sensors, this study proposes a novel reflective pentagonal frustum-shaped integrated gas chamber. By establishing a stable five-fold reflection path, the structure enables effective infrared path extension within a limited volume while enhancing light intensity uniformity at the detection plane. Coupled optical-fluidic simulations were employed to systematically optimize key structural parameters, including the cone side angle, baffle height, and number of gas apertures. The results indicate that with a cone angle of 60°, a baffle height of 30 mm, and six apertures per side, the design achieves stable gas concentration within 3 seconds and maintains the escaped ray rate below 3.9% while ensuring high optical efficiency. Furthermore, a 97%-reflective aluminum coating was employed on the inner walls to balance cost-efficiency and minimize optical energy loss. This study achieves a balance between compact structure, long optical path, high sensitivity, and fast response, offering a valuable reference for the structural design and optimization of multi-component NDIR gas sensors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".