Pourtangestani, Mojgan (2026) Characterising window design parameters based on occupant behaviour and preferences in single-dwelling residential buildings to reduce energy demand for ventilation in Melbourne. PhD thesis, Victoria University.

Abstract

Achieving both energy efficiency and acceptable indoor air quality in residential buildings requires natural ventilation (NV) strategies that reflect how occupants interact with windows in everyday use. Conventional building performance simulations typically assume fixed or idealised window-operation schedules, creating a persistent gap between predicted and actual ventilation rates and energy performance. This gap is particularly pronounced in temperate climates such as Melbourne (Climate Zone 6), where long transitional seasons create high potential for passive ventilation, yet mechanical cooling use continues to rise. The aim of this research is to develop and test a behaviour-informed (BI) simulation framework that explicitly integrates empirically derived occupant window-use behaviour with key window design parameters for single-dwelling residential buildings and townhouses Class 1 dwellings under the National Construction Code of Australia in Melbourne. A two-stage mixed-methods approach was adopted. First, post-occupancy evaluation (POE) surveys of Melbourne households were conducted to capture actual window-opening probabilities and their behavioural drivers. Second, EnergyPlus simulations were performed to compare a conventional uniform static behaviour schedule against probabilistic behaviour models derived directly from the survey data. Key window parameters examined were window size expressed through height, width, and resulting window-to-wall ratio (WWR) , orientation, and placement. Results demonstrate that probabilistic occupant-behaviour models consistently outperform static assumptions, producing higher and more realistic NV rates across all tested scenarios. Taller window configurations were found to enhance evening exhaust ventilation through buoyancy-driven effects, while wider windows increased morning air intake associated with occupant opening preferences. When combined with occupant-derived schedules, targeted adjustments in window geometry produced substantial improvements in airflow, indoor air quality, and thermal comfort, while reducing reliance on mechanical cooling, particularly during transitional seasons. The study makes three principal contributions. First, it presents the first known integration of post-occupancy-evaluation-derived probabilistic occupant models into NV simulations for Australian residential buildings, offering a replicable method for narrowing the performance gap. Second, it provides quantified evidence of how specific window geometries, taller for exhaust, wider for intake perform under realistic occupant influence, delivering evidence-based guidance directly relevant to architectural design decisions. Third, it delivers practical, BI design guidelines and decision-support tools for Class 1 dwellings in Melbourne’s climate, demonstrating that aligning window dimensions, placement, and orientation with actual usage patterns can significantly improve indoor environmental quality while lowering ventilation-related energy demand. By explicitly coupling human behaviour with window design variables, this research bridges the divide between simulation predictions and lived residential experience. The resulting framework is readily transferable to other temperate climates and provides a robust foundation for future occupant-centric design standards and simulation practices in Australian housing.

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