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The aim of this paper is to demonstrate the use of historical building performance data to identify potential issues with the build quality and operation of a building, as a means of narrowing the scope of in-depth further review.

The response of a room to the difference between internal and external temperatures is used to demonstrate patterns in thermal response across monitored rooms in a single building, to clearly show where rooms are under-performing in terms of their ability to retain heat during unconditioned hours. This procedure is applied to three buildings of different types, identifying the scope and limitation of this method and indicating areas of building performance deficiency.

The response of a single space to changing internal and external temperatures can be used to determine whether it responds differently to other monitored buildings. Spaces where thermal bridging and changes in use from design were encountered exhibit noticeably different responses.

Application of this methodology is limited to buildings where temperature monitoring is undertaken both internally for a variety of spaces, and externally, and where knowledge of the uses of monitored spaces is available. Naturally ventilated buildings would be more suitable for analysis using this method.

This paper contributes to the understanding of building energy performance from a data-driven perspective, to the knowledge on the disparity between building design intent and reality, and to the use of basic commonly recorded performance metrics for analysis of potentially detrimental building performance issues.

Buildings and their use is a complex process from design to occupation. Buildings produce huge volumes of data such as building information modelling (BIM), sensor (e.g. from building management systems), occupant and building maintenance data. These data can be spread across multiple disconnected systems in numerous formats, making their combined analysis difficult. The purpose of this paper is to bring these sources of data together, to provide a more complete account of a building and, consequently, a more comprehensive basis for understanding and managing its performance.

Building data from a sample of newly constructed housing units were analysed, several properties were identified for the study and sensors deployed. A sensor agnostic platform for visualising real-time building performance data was developed.

Data sources from both sensor data and qualitative questionnaire were analysed and a matrix of elements affecting building performance in areas such as energy use, comfort use, integration with technology was presented. In addition, a prototype sensor visualisation platform was designed to connect in-use performance data to BIM.

This work presents initial findings from a post occupancy evaluation utilising sensor data. The work attempts to address the issues of BIM in-use scenarios for housing sector. A prototype was developed which can be fully developed and replicated to wider housing projects. The findings can better address how indoor thermal comfort parameters can be used to improve housing stock and even address elements such as machine learning for better buildings.

Refurbishing houses is considered a key measure to improve the energy efficiency of the built environment. However, little is known about the implementation and outcome of housing renovation for energy upgrades in the Vietnamese practice. The purpose of this paper is to investigate the energy performance of the current housing stock in Vietnam and the potential to reduce energy use in households.

The paper is based on a survey with 153 respondents in three major climatic regions of Vietnam. The survey focusses on building characteristics, environmental performance, energy performance and refurbishment activities. Data collected from the survey were statistically analysed to give insight into the current performance of the housing stock and its energy saving potential.

This paper concludes that building design and construction, particularly the building envelope, have a significant influence on the occupants’ comfort. However, the energy consumption in houses is not statistically associated with building design and indoor environment. It is suggested that financial status and occupants’ behaviour currently have a strong influence on the household energy use. The survey also showed that refurbishment improves the housing performance, especially if improving the indoor environment was one of the drivers.

There are very few studies on energy use in households in Vietnam, especially with regards to actual energy consumption. This paper brings insights into the actual energy consumption and reveals the “performance gap” in Vietnamese housing stock.

The purpose of this paper is to present a review of the implications building information modelling (BIM) is having on the building energy modelling (BEM) and design of buildings. It addresses the issues surrounding exchange of information throughout the design process, and where BIM may be useful in contributing to effective design progression and information availability.

Through review of current design procedures and examination of the concurrency between architectural and thermophysical design modelling, a procedure for information generation relevant to design stakeholders is created, and applied to a high-performance building project currently under development.

The extents of information key to the successful design of a buildings energy performance in relation to its architectural objectives are given, with indication of the level of development required at each stage of the design process.

BIM offers an extensible medium for parametric information storage, and its implementation in design development offers the capability to include BEM parameter-integrated construction information. The extent of information required for accurate BEM at stages of a building’s design is key to understanding how best to record performance information in a BIM environment.

This paper contributes to the discussion around the integration of concurrent design procedures and a common data environment. It presents a framework for the creation and dissemination of information during design, exemplifies this on a real building project and evaluates the barriers experienced in successful implementation.

Decisions taken during the early design of adaptive façades involving kinetic, active and responsive envelope for complex commercial buildings have a substantial effect on inclusive building functioning and the comfort level of inhabitants. This study aims to present the application of an analytic network process (ANP) model indicating the order of priority for high performance criteria that must be taken into account in the assessment of the performance of adaptive façade systems for complex commercial buildings.

The nominal group technique (NGT) stimulating and refining group judgments are used to find and categorize relevant high performance attributes of the adaptive façade systems and their relative pair-wise significance scores. An ANP model is applied to prioritize these high performance objectives and criteria for the adaptive façade systems.

Embodied energy and CO₂ emission, sustainability, energy saving, daylight and operation maintenance were as the most likely and crucial high performance criteria. The criteria and the weights presented in this study could be used as guidelines for evaluating the performance of adaptive façade systems for commercial buildings in planning and design phases.

This research primarily provides the required actions and evaluations for design managers in accomplishing a high performance adaptive façade system, with the support of an ANP method. Before beginning the adaptive façade system of a building design process, the design manager must determine the significance of each of these attributes as high performance primacies will affect the results all through the entire design process.

In this research, a relatively innovative, systematic and practical approach is proposed to sustain the decision-making procedure for evaluation of the high performance criteria of adaptive façade systems in complex commercial buildings.

The purpose of this paper is to propose a novel data-driven approach for predicting energy performance of buildings that can address the scarcity of quality data, and consider the dynamic nature of building systems.

This paper proposes a reinforcing machine learning (ML) approach based on transfer learning (TL) to address these challenges. The proposed approach dynamically incorporates the data captured by the building management systems into the model to improve its accuracy.

It was shown that the proposed approach could improve the accuracy of the energy performance prediction compared to the conventional TL (non-reinforcing) approach by 19 percentage points in mean absolute percentage error.

The case study results confirm the practicality of the proposed approach and show that it outperforms the standard ML approach (with no transferred knowledge) when little data is available.

This approach contributes to the body of knowledge by addressing the limited data availability in the building sector using TL; and accounting for the dynamics of buildings’ energy performance by the reinforcing architecture. The proposed approach is implemented in a case study project based in London, UK.

The current fire protection measures in buildings do not account for all contemporary fire hazard issues, which has made fire safety a growing concern. Therefore, this paper aims to present a critical review of current fire protection measures and their applicability to address current challenges relating to fire hazards in buildings.

To overcome fire hazards in buildings, impact of fire hazards is also reviewed to set the context for fire protection measures. Based on the review, an integrated framework for mitigation of fire hazards is proposed. The proposed framework involves enhancement of fire safety in four key areas: fire protection features in buildings, regulation and enforcement, consumer awareness and technology and resources advancement. Detailed strategies on improving fire safety in buildings in these four key areas are presented, and future research and training needs are identified.

Current fire protection measures lead to an unquantified level of fire safety in buildings, provide minimal strategies to mitigate fire hazard and do not account for contemporary fire hazard issues. Implementing key measures that include reliable fire protection systems, proper regulation and enforcement of building code provisions, enhancement of public awareness and proper use of technology and resources is key to mitigating fire hazard in buildings. Major research and training required to improve fire safety in buildings include developing cost-effective fire suppression systems and rational fire design approaches, characterizing new materials and developing performance-based codes.

The proposed framework encompasses both prevention and management of fire hazard. To demonstrate the applicability of this framework in improving fire safety in buildings, major limitations of current fire protection measures are identified, and detailed strategies are provided to address these limitations using proposed fire safety framework.

Fire represents a severe hazard in both developing and developed countries and poses significant threat to life, structure, property and environment. The proposed framework has social implications as it addresses some of the current challenges relating to fire hazard in buildings and will enhance overall fire safety.

The novelty of proposed framework lies in encompassing both prevention and management of fire hazard. This is unlike current fire safety improvement strategies, which focus only on improving fire protection features in buildings (i.e. managing impact of fire hazard) using performance-based codes. To demonstrate the applicability of this framework in improving fire safety in buildings, major limitations of current fire protection measures are identified and detailed strategies are provided to address these limitations using proposed fire safety framework. Special emphasis is given to cost-effectiveness of proposed strategies, and research and training needs for further enhancing building fire safety are identified.

This article aims to establish a dynamic Energy Performance Contract (EPC) risk allocation model for commercial buildings based on the theory of Incomplete Contract. The purpose is to fill the policy vacuum and allow stakeholders to manage risks in energy conservation management by EPCs to better adapt to climate change in the building sector.

The article chooses a qualitative research approach to depict the whole risk allocation picture of EPC projects and establish a dynamic EPC risk allocation model for commercial buildings in China. It starts with a comprehensive literature review on risks of EPCs. By modifying the theory of Incomplete Contract and adopting the so-called bow-tie model, a theoretical EPC risk allocation model is developed and verified by interview results. By discussing its application in the commercial building sector in China, an operational EPC three-stage risk allocation model is developed.

This study points out the contract incompleteness of the risk allocation for EPC projects and offered an operational method to guide practice. The reasonable risk allocation between building owners and Energy Service Companies can realize their bilateral targets on commercial building energy-saving benefits, which makes EPC more attractive for energy conservation.

Existing research focused mainly on static risk allocation. Less research was directed to the phased and dynamic risk allocation. This study developed a theoretical three-stage EPC risk allocation model, which provided the theoretical support for dynamic EPC risk allocation of EPC projects. By addressing the contract incompleteness of the risk allocation, an operational method is developed. This is a new approach to allocate risks for EPC projects in a dynamic and staged way.

The work described below compares three very different residential typologies in terms of their energy performance in operation. The purpose of this paper is to identify the influence of building typologies and corresponding urban morphologies on operational energy demand and the potential for building integrated energy production.

Two of the typologies studied are apartment buildings while the third comprises single-family homes located on small plots. An important factor under consideration is the insertion into the respective urban design configuration so that mutual shading of the buildings and the ensuing impact on energy performance is evaluated. Heating and cooling demands, as well as the potential for building-integrated electricity production were investigated for four different European climates in a dynamic thermal simulation environment.

The results show that the investigated apartment buildings have a lower operational energy demand than the single-family home in all climates. This advantage is most pronounced in cool climate conditions. At the same time the investigated single-family home has the highest potential for building integrated renewable energy production in all climates. This advantage is most pronounced in low latitudes.

The study builds up on generic buildings that are based on a common urban grid and are easily comparable and scalable into whole city districts. Still, these buildings are planned into such detail, that they provide fully functional floor plans and comply with national building regulations. This approach allows us to draw conclusions on the scale of individual buildings and at an urban scale at the same time.

This study investigates the barriers and drivers of using green methods and technologies (GMTs) in supportive educational buildings (SEBs) in South Africa, and assesses their impact on the circular economy (CE) in achieving net-zero carbon goals. While there has been extensive literature on green building technologies, there is limited research on the barriers and drivers of using GMT in SEBs, as well as their impact on the circular economy (CE) in achieving net-zero carbon goals.

This study adopts an interpretivist approach with an ontological basis, using an overarching case study of a SEB at the University of Cape Town (UCT). Semistructured interviews were conducted with executive UCT management, and a field survey of a UCT supportive education building was performed.

At UCT, multiple GMTs have been installed across various buildings to enhance monitoring and management of water and energy consumption. Moreover, initiatives to positively influence student behavior, such as water and energy-saving campaigns around UCT premises, have been introduced. The findings further indicate that UCT has recently emphasized the implementation of GMTs, resulting in improved resource efficiency, CE practices and progress toward achieving net-zero carbon targets for supportive education buildings and the university as a whole.

This research highlights the positive impact of GMTs on a SEB’s CE and net-zero carbon operations. As a result, facility managers should consider incorporating GMTs when planning the development or refurbishment of SEBs.