Publications
Over the years, SUSAN has made significant contributions to the field of net-zero-carbon school buildings in New Zealand, resulting in numerous publications. The research group has published a series of scholarly articles and papers that highlight their findings and advancements in sustainable building practices. These publications delve into various aspects, including energy-efficient design principles, renewable energy integration, passive building techniques, and innovative materials for achieving net-zero carbon goals in school buildings. The group's research has been recognized for its innovative approaches and practical insights, and their publications have been widely cited within the academic community and industry. SUSAN's commitment to knowledge dissemination and sharing their research outcomes has played a pivotal role in fostering sustainable practices and inspiring further advancements in the field of sustainable school building design.
Developing analytical model for nighttime cooling of internal thermal mass.
Nighttime mechanical ventilation of internal building thermal mass has the potential to create energy flexibility by shifting peak cooling demand. The research on nighttime cooling of internal thermal mass is limited due to lacking simplified models by considering mass dimension and real-world discrete climate data like hourly outdoor air temperatures.
Computer vision technologies for safety science and management in construction: A critical review and future research directions.
Recent years have seen growing interests in developing and applying computer vision technologies to solve safety problems in the construction industry. Despite the technological advancements, there is no research that exams the theoretical links between computer vision technology and safety science and management.
Bridging the gap between building information modelling education and practice: a competency-based education perspective.
This study reports a case study that investigates the gap between BIM tertiary education and the building industry’s needs in New Zealand (NZ). In specific, it aims to (1) identify the industry’s requirements on BIM competencies, (2) examine the status quo of BIM tertiary education in NZ, and (3) identify and analyse the gaps between current BIM education and the industry’s needs.
​Model predictive control of short-term winter natural ventilation in a smart building using machine learning algorithms.
Natural ventilation in buildings has the potential to reduce building energy consumption and the incidence of sick building syndrome. However, controlling natural ventilation is often challenging. For instance, natural ventilation through operable windows may cause cold draughts for the occupants in winter.