Bibliographic record
Abstract
Microwave heating is considered as a very beneficial heating methodology for liquids because it can provide non-contact delivery of energy. Recent studies are focusing on the use of an electrically small resonator, such as a split-ring resonator for liquid heating purposes for its ability to concentrate electric energy in its gap which can be translated into heating. The thesis proposes a novel and effective microwave water heating system based on split-ring resonators which cultivates a completely innovative approach resulting in more energy efficient outcomes. The thesis also provides a clear and step-by-step manual for conducting numerical analysis for microwave heating carried out by using multiple software tools, which can save valuable time for future researchers. The major section of the thesis presents the structure, dimensions and heating performance of the proposed heating elements, and different comparisons have been carried out for characteristic and performance realization of the heaters. The system provides very promising heating results numerically, such as for an input power of only 2 watts the system heats water up to 41 °C from room temperature in 60 seconds. These results establish that along with eliminating the shortcomings faced by currently employed household water heating systems, the proposed model is destined to be a promising and more energy efficient solution for meeting household water heating demand in future years.
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 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".