Computational fluid dynamics analysis of energy and optical performance in fenestration systems incorporating solid-solid phase change materials
Bibliographic record
Abstract
This study investigates the energy and optical performance of a double-glazed window system incorporating a solid-solid phase change material (DGW-SSPCM) compared to a conventional reference system (DGW-R). Transient CFD simulations were conducted using ANSYS FLUENT for the hottest and coldest days in Montreal, Canada, under sunny and cloudy conditions across four glazing orientations. A 2 mm SSPCM layer was applied to the interior pane, and natural convection (NC) within the glazing air gap was modeled using the solidification/melting and Discrete Ordinates models. Results show that NC has negligible effects during summer due to weak buoyancy-driven airflow, making its inclusion unnecessary for accurate energy and optical analysis under warm conditions. In winter, however, NC significantly impacts the phase change behavior and total energy performance of the system, with heat losses being underestimated by 10 to 23 % when NC is not considered. This behavior is supported by air gap velocity vector analyses, which show well-defined convective loops in winter with air velocities reaching up to 0.14 m/s, Reynolds numbers up to 57, and Rayleigh numbers exceeding 10 4 , while summer flows remain weak and conduction-dominated. While the DGW-SSPCM system offers no substantial energy savings in summer due to nighttime thermal discharge, it achieves winter energy savings of up to 7.6 % and improves indoor thermal comfort. The optical analysis in this study has demonstrated that benefiting from the full cycle of the SSPCM phase transition allows the glazing to remain fully transparent during office hours, making it particularly practical for commercial buildings. The south-facing configuration, incorporating an SSPCM layer with a transition temperature of 15 °C on the interior pane, is identified as the optimal setup. This design ensures full transparency and thermal neutrality throughout the year during office hours, while maximizing latent heat utilization for effective thermal regulation in winter. These findings highlight the potential of SSPCM-integrated glazing systems as a passive strategy for enhancing energy efficiency and indoor comfort in heating-dominated climates, particularly in commercial buildings with daytime occupancy. • 3D CFD modeling of double-glazing with integrated solid-solid phase change material. • Energy and optical performance evaluated for extreme summer and winter conditions. • Neglecting natural convection in summer can reduce computational cost without loss of accuracy. • Omitting natural convection in winter underestimates the heating energy loads by 10–23 %. • SSPCM glazing is recommended for cold-climate commercial buildings with daytime occupancy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".