Abstract
Overheating in dwellings is an emerging risk in temperate climates, yet existing assessment frameworks such as CIBSE TM59 produce room-level, pass/fail compliance outputs that are not suitable for stock-level comparative analysis. This paper introduces the Dwelling Overheating Risk Metric (DORM), a continuous, normalised indicator that aggregates TM59 exceedance criteria across all habitable rooms into a single dwelling-scale value, enabling consistent comparison across design configurations while preserving direct traceability to the underlying standard. To demonstrate the metric, a parametric simulation study was conducted using a middle-floor apartment typology representative of the Irish building stock. Dynamic building performance simulations were carried out across 288 configurations, systematically varying orientation, thermal mass, airtightness, wall U-value, window U-value, and window solar transmittance. Orientation-specific Random Forest surrogate models were then trained on the resulting dataset to enable rapid DORM prediction, achieving R² values of 0.92–0.98 and mean absolute errors below 0.11. Results show that around 5% of the parametric configurations exhibit high overheating burden (DORM >2), with 1% falling in the severe category (DORM >3). Following SHAP analysis, window solar transmittance and thermal mass were identified as the dominant determinants of overheating risk, particularly for west- and south-facing dwellings, while wall and window U-values exerted negligible influence under summer conditions. Airtightness was found to increase overheating risk when unaccompanied by controlled ventilation.
| Original language | English |
|---|---|
| Article number | 115036 |
| Journal | Building and Environment |
| Volume | 304 |
| DOIs | |
| Publication status | Published - 1 Oct 2026 |
Keywords
- Building performance simulation
- Cold climate
- Dwelling overheating risk metric (DORM)
- Machine learning surrogate models
- Overheating risk
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