Natural convective heat transfer from interrupted rectangular fins
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
Heatsinks are widely used in various industrial applications to cool electronic, power electronic, telecommunications, and automotive components. Those components might be either high-power semiconductor devices, e.g., diodes, thyristors, IGBTs and MOSFETs, or integrated circuits, e.g. audio amplifiers, microcontrollers and microprocessors. More precisely, the passive cooling heatsinks are widely used in CPU cooling, audio amplifiers and power LED cooling. In the work herein, steady-state external natural convection heat transfer from verticallymounted rectangular interrupted finned heatsinks is investigated. After regenerating and validating the existing analytical results for continuous fins, a systematic numerical, experimental, and analytical study is conducted on the effect of the fin array and single wall interruption. FLUENT and COMSOLMultiphysics software are used in order to develop a twodimensional numerical model for investigation of fin interruption effects. To perform an experimental study and to verify the analytical and numerical results, a custom-designed testbed was developed in Simon Fraser University (SFU). Results show that adding interruptions to vertical rectangular fins enhances the thermal performance of fins and reduces the weight of the fin arrays, which in turn, can lead to lower manufacturing costs. The optimum interruption length for maximum fin array thermal performance is found and a compact relationship for the Nusselt number based on geometrical parameters for interrupted walls is presented using a blending technic for two asymptotes of interruption length.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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