CFD simulation of UV photocatalytic reactors for air treatment
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
Abstract A photocatalytic reactor was simulated through computational fluid dynamics (CFD) with surface reaction for trichloroethylene (TCE) oxidation at various pollutant concentrations, flow rates, and reactor lengths. The results were compared with those from experiments. The experimental work involved using a differential photoreactor for kinetics studies and an annular flow photoreactor for overall removal investigations under various conditions. The modeling predictions agreed closely with the experimental data within the range in which results were examined. The modeling results indicated significant radial TCE concentration gradient and nonuniform flow distributions in the annular photoreactor. CFD was applied to predict the performance of a number of UV photocatalytic reactor design concepts, to study the impacts of some design parameters on the reactor efficiency. The modeling results demonstrated that under similar flow rate conditions, the thickness of the contaminated air layer flowing over the photocatalyst surface could substantially influence the reactor performance. Thinner contaminated air layers provided more uniform radial concentration distribution of TCE and improved the reactor performance. © 2005 American Institute of Chemical Engineers AIChE J, 2005
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