Economic and Performance Analysis of Modified Solar Distillation System Coupling Different Integrations Using Carbon Quantum Dot Nanoparticles: Generalized Thermal Model
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Clean drinking water and electricity production utilizing non-conventional sources of energy is the global demand for sustainable development. Ultrafast heat transfer fluids have delivered impressive results in photovoltaic (PV)-integrated solar thermal systems, in recent times. Efforts have been made for the productivity and electricity augmentation of solar still equipped with helically coilled heat exchanger and coupled with different integrations, viz., (a) partially covered N-photovoltaic thermal compound parabolic concentrator (N-PVT-CPC), (b) partially covered N-photovoltaic thermal flat plate collector (N-PVT-FPC), (c) N-FPC-CPC, and (d) N-flat plate collector (N-FPC). System design has also been modified by adding a roof-top semi-transparent PV module and built-in passive copper condenser (circulation mode), and effect of carbon quantum dots (CQDs) water-based nanofluids, nanoparticles volume concentration, and packing factor (βc) of the PV module has been studied by developing generalized thermal modeling of the system (special cases). Overall, 41.1%, 21.52%, 22.01%, and 10.01% rise in evaporative HTCs is observed in FPC-CPC, PVT-CPC, FPC, and PVT-FPC integrations, respectively. Thermal exergy is found to be higher for FPC-CPC integration, and it follows the enhancement order as FPC-CPC (max-0.147 kW) > PVT-CPC (0.088 kW) > FPC (0.038 kW) > PVT-FPC (0.028 kW). In reference to the base fluid, significant enhancement in the daily productivity is observed for FPC-CPC (10.9%) and PVT-CPC (5.16%) integrations using CQD-NPs. The production cost of potable water has also been estimated for all the cases for n = 30 and n = 50 years life span and i = 4% and 8% interest rates, and it is found to be the lowest (0.014 $/L) for FPC-CPC integration using CQD-NPs (n = 30 years, i = 4%).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 it