Temperature Control to Improve Performance of Hempcrete-Phase Change Material Wall Assemblies in a Cold Climate
Bibliographic record
Abstract
Phase change material (PCM)-enhanced building envelopes can control indoor temperatures and save energy. However, PCM needs to undergo a phase change transition from solid to liquid and back to be fully effective. Furthermore, most previous research integrated PCM with high embodied energy materials. This study aims to advance the existing research on integrating PCM into carbon-negative wall assemblies composed of hempcrete and applying temperature control strategies to improve wall systems’ performance while considering the hysteresis phenomenon. Four hempcrete and hempcrete-PCM (HPCM) wall design configurations were simulated and compared under different control strategies designed to reduce energy demand while enhancing the phase change transition of the microencapsulated PCM. The HPCM wall types outperformed the hempcrete wall assembly through heating (~3–7%) and cooling (~7.8–20.7%) energy savings. HPCM walls also maintained higher wall surface temperatures during the coldest days, lower during the warmest days, and within a tighter range than hempcrete assembly, thus improving the thermal comfort. However, the results also show that the optimal performance of thermal energy storage materials requires temperature controls that facilitate their charge and discharge. Hence, applied control strategies reduced heating and cooling energy demand in the range of ~4.4–21.5% and ~14.5–55%, respectively.
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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 | 0.000 | 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) | 0.000 | 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".