Evaluation of a Retrieved Pyrolithic Reactor to Be Used in Small Farms
Bibliographic record
Abstract
The aim of this paper was to evaluate the energy efficiency of a small Generator Motor Group (GMG), driven by internal combustion (fueled with water and gasoline), using pyrolytic reactor technology (GEET). In order to achieve this, the pyrolytic reactor was designed and built, so that when in operation, it obtains extra energy necessary for the pyrolysis process from the thermal energy produced by the combustion of the exhaust gases. In order to determine the efficiency of the small GMG, in conjunction with the GEET, two experiments were carried out: the first one was characterized by the operation and use of the GMG equipped with a carburetor, and when in use it used only ordinary gasoline as fuel. The second experiment was characterized by the insertion of the pyrolytic reactor, which allowed the motor generator group, when in operation, to use water and gasoline as fuel, according to the proportions defined in the methodology. It was possible to verify that the engine, when reaching the voltage near the nominal (115Vac), for the same type and value of load fed, the GEET device presented, during the tests, high and low efficiency results, showing that the experiment is promising, but requires more work and more investigations for correct evaluation of the phenomena observed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".