A residential micro tri-generation system based on a gas fired stirling engine CHP and thermo-chemical accumulator (TCA)
Bibliographic record
Abstract
Cooling production has application in a considerable number of fields in human life, such as: food processing, air-conditioning, pharmaceuticals, etc. The conventional refrigeration system driven by the vapour compression cycle in general inhibits sustainable development due to it's association with high electricity consumption as well as global warming. Tri-generation can address this problem as it produces electricity, heating and cooling from a single fuel source, and it also uses an environmentally friendly working fluid. This thesis describes in detail the development of a residential tri-generation system based on ClimateWell® technology and a gas fired co-generation unit. Detailed design of a tri-generation system and a multi-tank cascade storage system has been developed. Based on the design, a residential tri-generation system has been installed and commissioned at the House-B of the TRCA, located in Vaughan, Ontario. The installed tri-generation system is instrumented with over 30 different sensors and the experimental data collected were analyzed to evaluate the performance of the system. It has been found that the multi-tank system is capable of preheating the incoming water main cold water by 6-7°C by utilizing the rejected heat of the tri-generation system. Experimental data show that the co-generation system has a thermal efficiency of 71% and the COP of the ClimateWell® system is 0.365. A TRNSYS model of the tri-generation system and the multi-tank storage system has also been developed and the models were validated with the experimental data. The models were also used to simulate the performance of the integrated system for different input conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".