School of Future Environments - Huri te Ao

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https://hdl.handle.net/10292/13907
AUT is home to a number of renowned research institutes in architecture and creative technologies. The School of Future Environments - Huri te Ao strong industry partnerships and the unique combination of architecture and creative technologies within one school stimulates interdisciplinary research beyond traditional boundaries.

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Now showing 1 - 5 of 70
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    Design and Testing of a Self-Centering Friction Damper-Brace for Compression Ultimate Limit State: Inelastic Buckling
    (Elsevier BV, 2024-04-01) Yousef-beik, SMM; Veismoradi, S; Zarnani, P; Quenneville, P
    This paper investigates the design procedures and experimental testing of a low-damage brace equipped self-centering friction-based connection named Resilient Slip friction Joint (RSFJ). The brace energy dissipation and restoring force is provided by the damper component. Previous studies have shown that the damper ultimate compression strength might be jeopardized due to damper rotational flexibility, which might lead to premature elastic buckling of the brace. To address the issue, a concept of telescopic tubes was introduced to be put in parallel to the damper(s). The design of the telescopic tube requires a thorough framework that considers different possible failure loads and the collapse modes, so that the brace ultimate strength can be accurately estimated. Such a process tends to be more complex than the conventional Concentrically Braced Frames (CBFs), due to the non-continuity(ies) appearing as damper installation which may lead to possible plastic hinge formation in different locations of the brace. This study aims to employ second-order plastic analysis for the design of the damper-brace assembly. The proposed method is, is then validated with current international codes’ procedure and also with destructive tests on the self-centring brace specimens. Finally, the seismic design considerations including the design of the connections and protected members are discussed in this paper. The current procedure could also be recruited for other new emerging damper-braces as well.
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    Interrelations of the Factors Influencing the Whole-Life Cost Estimation of Buildings: A Systematic Literature Review
    (MDPI, 2024-03-09) Samarasekara, Herath Mudiyanselage Samadhi Nayanathara; Purushothaman, Mahesh Babu; Rotimi, Funmi
    The global GDP has witnessed a significant upswing, majorly due to the growth of the construction industry. Embracing the whole-life costing (WLC) approach, the construction sector strategically manages expenses across a construction project’s life cycle. However, despite its widespread adoption, accurate cost forecasting remains a major challenge. The intricate interplay of various influencing factors has not been fully explored, leading to inaccurate cost estimations. A comprehensive understanding of specific factors and their interrelationships is crucial to address this issue. Therefore, it is imperative to conduct further research to identify and explore the subtle nuances of these factors that impact whole-life cost estimation. Our study fills this gap, analysing 51 factors from 84 papers across prominent repositories. We assess interrelationships using a systematic literature review and pairwise comparison as in the analytical hierarchy process. The International Construction Measurement Standards (ICMS) framework structures these relationships and is represented in the causal loop diagrams (CLDs). The pioneering CLDs are a notable contribution, illustrating interrelationships and polarities among the 51 WLC factors. Six reinforcing loops and one balancing loop provide valuable insights into their dynamic nature. Importantly, lower-level factors do not always directly connect with upper-level factors. Instead, they interact within the same level before linking to top-level factors. These findings are significant for professionals, such as cost estimators, quantity surveyors and scholars, offering a comprehensive understanding of the WLC system.
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    Estimating Construction Waste in New Zealand: A Focus on Urban Areas, Residential and Non-residential Building Activities
    (IOP Publishing, 2024-02-26) Albsoul, Hadeel; Doan, Dat Tien; GhaffarianHoseini, Ali
    This paper examines the significant increase in construction waste (CW) due to urbanisation and population growth in New Zealand and worldwide. The aim is to estimate CW using available data in New Zealand and identify relevant indicators to employ estimation methods. Various methods and models for estimating CW at the urban level and from building activities are reviewed. According to the best available data, the paper uses the per-capita multiplier and waste generation rate methods to estimate CW in New Zealand. New Zealand's per-capita multiplier for CW is 943.46 kg/per capita. The waste generation method using the floor area indicator is applied at residential and non-residential building levels. The estimated CW in 2021 was 531,109 tonnes for residential and non-residential buildings using the floor area indicator. The findings reveal a positive relationship between residential building activity and population growth, with Auckland generating the highest rate of CW. Because of the limitations of the available data and estimation methods, the paper highlights the need for standardised data collection systems and outreach programs to improve CW estimation practices. Further research is recommended to enhance waste reduction strategies and identify high-waste-generating materials and methods. It is vital to have accurate CW estimations to support project waste management plans and sustainable construction practices and to inform waste management policies and regulations at the regional or national level.
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    Towards a Sustainable Future: Timber Waste Management in New Zealand’s Construction Industry
    (Springer Nature Singapore, 2024-02-02) Doan, Dat; Sun, Ping
    This research paper provides a comprehensive overview of construction and demolition waste (C&DW) management, specifically emphasising timber waste. Firstly, it assesses timber’s environmental and functional advantages in the construction industry. Despite the benefits of timber, the paper identifies significant challenges in managing chromated copper arsenate (CCA)-treated timber waste due to its potentially hazardous impacts. To address these issues, the study proposes enhanced public understanding, innovative timber treatment processes, and effective waste management strategies. The role of stakeholders and policymakers in shaping sustainable waste management practices is also explored, highlighting the importance of implementing site waste management schemes and extended producer responsibility programs. The paper culminates in the presentation of innovative approaches for waste management, encompassing statistical modelling, automation, and systemic carbon reduction strategies. The research concludes with a set of recommendations aimed at promoting sustainable material selection, managing CCA-treated timber, enhancing stakeholder engagement, and adopting lifecycle consideration in material selection.
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    Development of Deep Neural Network-Based Strain Values Prediction Models for Full-Scale Reinforced Concrete Frames Using Highly Flexible Sensing Sheets
    (Destech Publications, Inc., 2023-09-12) Zhang, Hui; Beskhyroun, Sherif
    Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. These include abnormal changes due to strain fields and abnormal symptoms of the structure, such as damage and deterioration. At present, large-scale deployment of sensors in existing structures to cover large areas is still difficult to overcome, while increasing maintenance costs. In this study, a strain sensing sheet with high tensile strength is used to collect the strain data set generated on the concrete surface of the full-scale reinforced concrete (RC) frame structure when the cyclic load is applied to its limit. On this basis, two prediction models of deep neural network for frame beam and frame column are established. The training results show that they can predict the strain value accurately and have good generalization ability. These two deep neural network prediction models will also be deployed in SHM systems in the future as part of the intelligent strain sensor system.
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