Thermal Response Analysis of a Cross-Flow PCM Heat Exchanger Based on Air and Liquid Flow
Bibliographic record
Abstract
Due to the mismatch between energy supply and demand in thermal systems, this paper introduces a novel phase change material (PCM) heat exchanger based on two working fluids to provide thermal energy storage for the airside. The PCM is integrated into a compact single-slabbed crossflow heat exchanger based on air and liquid flow. A three-dimensional computational fluid dynamics (CFD) simulation is employed to perform a numerical analysis of fluid flow and heat transfer in the model. The dynamic thermal performance of the system is presented for both the PCM charging and discharging processes. The PCM stores excess thermal energy in the charging process, which is then released to the airside during periods of demand when the system's hot working fluid is unavailable. Results have been presented based on fluid temperatures, PCM average solid fraction, PCM phase transition procedure, and heat transfer rates during the charge and discharge processes. It has been observed that, in the discharge process, the stored thermal energy provides the airside with a heating load of 117.9 kJ, which leads to approximately 150 seconds of heating time. Moreover, heat transfer analysis shows that between the air outlet temperature of 28C and 18C, latent heat transfer dominates over the sensible heat transfer, causing most of the delay in air outlet temperature drop to occur in this region. Furthermore, it is concluded that using PCM in the heat exchanger can provide extra thermal energy of 100.7 kJ during the discharging process with the share of latent heat of 48% in the PCM heat transfer process. The findings attained in this study will shed light on the development of PCM heat exchangers and guide future research in designing more effective and efficient PCM heat exchangers, leading to enhanced overall system performance.
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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) | 0.000 | 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) | 0.002 | 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 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".