Assessment of T-History Method Variants to Obtain Enthalpy–Temperature Curves for Phase Change Materials With Significant Subcooling
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Bibliographic record
Abstract
To assess the potential of thermal energy storage systems using phase change materials (PCMs), numerical simulations rely on an enthalpy–temperature curve (or equivalent specific heat curve) to model the PCM thermal storage behavior. The so-called “T-history method” can be used to obtain an enthalpy–temperature curve (H versus T) through conventional laboratory equipment and a simple experimental procedure. Different data processing variants of the T-history method have been proposed yet no systematic comparison between these versions exists in the literature nor is there a consensus as to which should be used to obtain reliable enthalpy–temperature curves. In this paper, an inorganic salt hydrate is tested in both heating and cooling. Four different data processing variants of the T-history method are used to characterize the PCM and produce enthalpy–temperature curves for this original experimental data set. Differences in the results produced by the different methods are discussed, the issues encountered are indicated, and possible approaches to overcome these problems are provided. A specific variant is recommended when using the T-history method to determine enthalpy–temperature curves. For PCMs that exhibit subcooling, an alternative interpretation using an absolute temperature interval is described so that the subcooling phase is taken into account in the enthalpy–temperature curve.
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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 | 0.002 | 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) | 0.000 | 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