A cascaded thermoelectric generation system for low‐grade heat harvesting
Bibliographic record
Abstract
Thermoelectric generation (TEG) has its unique advantages in terms of distributed energy supply, low-grade heat recovery, and clean energy technology, but its low efficiency has constrained its application and promotion seriously. In order to obtain satisfactory efficiency and realize the adaptability to different heat sources, a novel cascaded TEG system (CTEG) is proposed. According to the temperature of heat source, three types of thermoelectric modules are used in the generator system. The module arrangement, cooling medium, and mode directly affect the performance of this whole system, since that the detailed model and CFD simulation were conducted to obtain the optimal collocation. Based on the optimization modeling, a CTEG prototype was constructed. From the experimental results, the efficiency of the CTEG achieved 5.92%, which significantly improved about 21.56% compared with the TEG which only contains one stage. Moreover, the key parameters of the system were identified. The stability and the improvement of the system were discussed comprehensively. For TEG system, CTEG increase the utilization of high-temperature heat sources, but also provides a structure for a TEG adapting to multiple temperature heat sources.
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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".