Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Sutrisna MSubject: search.filters.subject.sustainability

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    Enhancing the Energy Performance of Historic Buildings Using Heritage Building Information Modelling: A Case Study
    (MDPI (Basel, Switzerland), 2025-07-02) Kakouei M; Sutrisna M; Rasheed E; Feng Z; Caggiano A; Kamari A
    Heritage building conservation plays a special role in addressing modern sustainability challenges by preserving the cultural identity, retrofitting, restoring, and renovating these structures to improve energy performance, which is crucial for revitalisation. This research aims to use Heritage Building Information Modelling (HBIM) to increase energy efficiency and environmental sustainability in historic buildings. Retrofitting heritage buildings presents unique challenges and opportunities to simultaneously reduce energy consumption and carbon emissions while maintaining historical integrity. Traditional approaches are often insufficient to meet heritage structures’ energy needs. Modern technologies such as information building modelling and energy simulations can offer solutions. HBIM is a vigorous digital framework that facilitates interdisciplinary collaboration and offers detailed insights into building restoration and energy modelling. HBIM supports the integration of thermal and energy efficiency measures while maintaining the authenticity of heritage architecture by creating a comprehensive database. Using a case study heritage building, this research demonstrates how retrofitting the different aspects of heritage buildings can improve energy performance. Evaluating the preservation of heritage buildings’ cultural and architectural values and the effectiveness of using HBIM to model energy performance offers a viable framework for sustainable retrofitting of heritage buildings.
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    In support of sustainable densification in urban planning: a proposed framework for utilising CCTV for propagation of human energy from movement within urban spaces
    (Taylor and Francis Group, 2019-12-18) Jonescu E; Mercea T; Do K; Sutrisna M
    Co-generation of energy derived from human movement is not new. Intentionally accumulating energy, from mass urban-mobility, provides opportunities to re-purpose power. However, when mass-mobility is predictable, yet not harnessed, this highlights critical gaps in application of interdisciplinary knowledge. This research highlights a novel application of geostatistical modelling for the built environment with the purpose of understanding where energy harvesting infrastructure should be located. The work presented argues that advanced Geostatistical methods can be implemented as an appropriate method to predict probability distribution, density, clustering of populations and mass-population mobility patterns from large-scale online distributed and heterogeneous data sets published by the Australian Urban Research Infrastructure Network. Where clear urban spatio-behavioural relationships of density and movement can be predicted–understanding such patterns supports cross-disciplinary city planning and decision-making. A data-informed–predictive spatial decision-making framework is proposed–facilitating the endeavour of cogenerating kinetic human energy within a prescribed space. This novel proposition could further sustainability strategies for compact living for cities such as in Perth, Western Australia which is increasingly economically and geographically pressured to densify. This research argues that surveillance data elucidate a capacity to interpret and understand impacts of densification strategies, efficacy of CCTV networks in existing and emerging cities.