Numerical and Experimental Investigation of the Thermal Characteristics of Quartz Infrared Lambs
Bibliographic record
Abstract
Examining the thermal performance of infrared (IR) lamps is very important in industrial applications to ensure that the desired heating power can be obtained in the most efficient way.Reasons such as high operating temperatures, complex geometric structures and dominant radiative heat dissipation properties make it very difficult to carry out analytical calculations about their working principles.In this article, the thermal performances of four vertically placed IR lamps were examined experimentally and numerically under different parameters.An experimental test setup (ETS) and a thermal mathematical model (TMM) were created to examine the power, distance, location of heat flux sensor (HFS) and angle parameters precisely.Many studies were examined to obtain the input parameters to be defined in the numerical model, and two equations created using the net radiation method were used to calculate the quartz and filament temperatures of IR lamps.These equations were solved numerically with a MATLAB code using the Newton-Raphson method.The TMM was validated thanks to the experimental data and the obtained input values.The average relative error rates between numerical results and experimental results were calculated as 5.1%, 3.7%, 6.4% and 3.2% for location, distance, angle and power parameters, respectively.In addition, with the help of the verified TMM, it was examined how the thermal performance of IR lamps changes in a vacuum environment and with the changing emissivity coefficient of the ceramic coated rear surface of them.
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.
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".