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Managing quality risks of prefabricated components is one of the challenges for prefabricated construction. The quality liability insurance for prefabricated components (QLIPC) is an effective approach to transfer such risks; however, limited research has been conducted on the development of QLIPC. This study introduces an evolutionary game theory (EGT)-based approach incorporating decisions from both government and insurance companies. In the EGT model, a payoff matrix under disparate strategies is constructed and the evolutionary stable strategies (ESS) are deduced. The simulation calculation is then carried out by MATLAB using virtual sample data to demonstrate the analysis. The results show that the government should act as the game promoter because the QLIPC can reduce governance cost and has significant social benefits. This research contributes a theoretical framework to analyze the QLIPC development using the EGT theory, and it could help the government develop long-term strategies for developing the QLIPC market.

PurposeEffective maintenance of construction supply chains is paramount to business continuity during the pandemic. Focusing on a large private Australian construction company, this research aims to investigate to what extent the current pandemic has affected the daily operations of this company. This research touches on the broader effect on the industry, while it narrows the focus on how effective construction supply chain management can minimise a pandemic's negative impact on a company. The critical question will be how private contractors that primarily rely on social infrastructure projects can fortify their supply chains and general operations during the global pandemic.Design/methodology/approachA mixed qualitative and quantitative approach is employed in this research. Based on literature review and question design, data is collected through interviews with various stakeholders. Moreover, operation data is also collected from the case company to support the results and findings.FindingsThe respondents have generally agreed that the case company has effectively managed its supply chains to this point of the pandemic through the implementation of supply chain monitoring processes and maintaining stable relationships with stakeholders. This is supported by the operation data of the case company.Originality/valueThis is timely-conducted research, and it is original research with invaluable operation data. This case study is conducted during a pandemic and provides lessons learned for global supply chain management in the post-pandemic period.

CO2 emissions from building operations have increased to their highest level globally, moving away from the Paris Agreement goal of below 2 °C. While geothermal is recognised as a promising renewable source, the lack of an integrated framework guiding investigating ground source heat pumps for building operations, along with the incapability of well-known simulation tools in accurately capturing ground thermal performance, hinders its application. This research aims to unlock ground source heat pumps for building operations through an integrated framework, including an overarching improved U.S. National Renewable Energy Laboratory (NREL) monitoring guideline, a sensor-based monitoring prototype, and a g-function-based simulation approach. This research proposes amendments and improvements to the NREL guideline for monitoring geothermal energy by separating Thermal Energy Net Production from Thermal Energy Gross Production. A state-of-the-art case building located in Melbourne, Australia, housing advanced technologies, including ground source heat pump systems, is used to demonstrate and validate the research framework. A typical winter month in the southern hemisphere, July 2021, is monitored for the ground source heat pump systems designed and used for space heating. The findings reveal that the thermal energy generation during working days in July 2021 is close to the simulation results, with a difference of 2.2% in gross thermal energy production and a difference of 0.92% in inlet temperature. This research develops and validates an integrated approach for evaluating ground source heat pump systems, contributing to the utilisation of geothermal energy for building operations.

The current development of shading systems which respond to both environmental and human inputs; leads to envisioning an envelope that is multifunctional, responsive and dynamic, named as Adaptive Facades (AFs). The key aspect of any external shading system is to control solar radiation that might cause unwanted thermal and visual stresses for occupants which can lead to higher cooling loads significantly. Recent studies attempted to develop non-conventional AFs such as folding structures to fulfill the incapability of conventional systems (e.g. venetian blinds) for delivering multi-objective user demands due to their different design features. Therefore, in this paper motorized venetian blinds were initially used as conventional AFs in Energy Management System (EMS) of EnergyPlus to develop a reference case study. Furthermore, an automatic control was assigned to venetian blinds based on two indoor sensors to control slat angles on hourly basis, Daylight Glare Index (DGI) and task horizontal illuminance. Then, two new control algorithm were derived as hourly transmittance schedule (hTs) and shade factor through extended calculation methods that were used to modify the properties of a roller shade as to take into account the same adjustment of venetian blinds based on indoor sensors. Finally, a comparison was conducted based on annual energy consumption including heating and cooling loads, in which results showed that both methods have discrepancy lower than 6% and can be alternative solutions to evaluate the performance of non-conventional adaptive systems. However, there are several limitations and applicability of the suggested methodologies that were also discussed.

PurposeThe operational phase of a building's lifecycle is receiving increasing attention, as it consumes an enormous amount of energy and results in tremendous detrimental impacts on the environment. While energy simulation can be applied as a tool to evaluate the energy performance of a building in operation, the emergence of Building Information Modeling (BIM) technology is expected to facilitate the evaluation process with predefined and enriched building information. However, such an approach has been confronted by the challenge of interoperability issues among the related application software, including the BIM tools and energy simulation tools, and the results of simulation have been seldom verified due to the unavailability of corresponding experimental data. This study aims to explore the interoperability between the commonly used energy simulation and BIM tools and verifies the simulation approach by undertaking a case study.Design/methodology/approachWith Autodesk Revit and EnergyPlus selected as the commonly used BIM and energy simulation tools, respectively, a valid technical framework of transferring building information between two tools is proposed, and the interoperability issues that occur during the data transfer are studied. The proposed framework is then employed to simulate the energy consumption of a single-family house, and sensitivity analysis and analysis on such parameters as schedule are conducted for building operations to showcase its applicability.FindingsThe simulation results are compared with monitored data and the results from another simulation tool, HOT2000; the comparison reveals that EnergyPlus and HOT2000 predict the total energy consumption with a difference from the monitoring data of 8.0 and 7.1%, respectively.Practical implicationsThis research shows how to efficiently use BIM to support building energy simulation. Relevant stakeholders can learn from this research to avoid data loss during BIM model transformation.Originality/valueThis research explores the application of BIM for building energy simulation, compares the simulation results among different tools and validates simulation results using monitored data.

PurposeThis research aims to propose a comparative environmental analysis of conventional and prefabricated construction techniques utilizing a building information modelling (BIM) technique.Design/methodology/approachA set of indicators are selected to assess the environmental emissions throughout the construction life cycle, based on BIM platform. An existing project involving ten apartment buildings in Shanghai is selected as a case study.FindingsThe results reveal that prefabricated construction demonstrates environment-friendly performance with some exceptions of acidification and mineral resource consumption. Environmental impacts can also be further reduced by increasing the projected area ratio and percentage of project prefabrication.Originality/valueOverall, the proposed method can be used to identify relevant environmental merits and for decision-making of appropriate construction techniques in building construction projects.

Australia is receiving an average of 58 million PJ of solar radiation per year, which is about 1000 times larger than its total energy generation. Roof-top solar photovoltaic (PV) systems alone can supply a phenomenal fraction of the nation’s total energy. The architectural design and orientation of roofs have considerable impacts on the energy efficiency of roof-top solar PV systems. These aspects, however, have received scant academic attention within the literature. To address this knowledge gap, this research seeks to increase the energy production of roof-top solar PV systems through roof design. The energy generation of roof-top solar PV systems is modelled using Helioscope software, and then validated using real-time monitored data. Based on the verified model, the impact of different tilt angles and shading from surrounding obstructions upon energy generation are analyzed in detail. To ground the research in practical terms, the aesthetic design of five typical roof design patterns (including flat, shed, gable, hip, and butterfly roof) are explored to compare the energy generated from solar PV systems fitted to each design. Findings indicate that: (1) the simulated energy generation from the solar PV system is close to the monitored data, with equal annual generation; (2) the shading of surrounding obstructions can reduce the energy generation of roof-top solar PV systems considerably, where up to 24% energy loss is reported; (3) the optimal tilt angle is about 35°, which is close to the latitude angle of the studied location; and (4) the shed roof design provides the maximum potential for solar energy generation when compared to that of other roof design patterns. The energy generation variation of other aesthetic roof patterns is also presented, providing support for informed decision making on the roof design. This study contributes to the field through improving the energy production of roof-top solar PV systems based on roof design along with considering aesthetic concerns. Novel insights generated will be beneficial for researchers and government policy makers alike; the work also introduces simulation-based methodological approaches for practitioners who seek to improve the energy generation of roof-top solar PV systems.

Being a node of the energy-water consumer and carbon dioxide (CO2) emitter, the household is one key sector to pilot integrated energy-carbon-water (ECW) management. This study developed an integrated framework to explore China’s provincial household ECW nexus as well as their drivers from the years 2000 through 2016. The absolute amount and growth rate of household energy use (HEU), household CO2 emissions (HCE), and household water use (HWU) were abstracted to reveal the dynamic characteristics of the household ECW nexus. Efficiency advance, income growth, urbanization, family size, and household number were defined to explain the changes in the household ECW nexus. This study revealed that there is a huge regional heterogeneity in China’s household ECW nexus. Developed regions such as Zhejiang, Jiangsu, Guangdong, and Shanghai are the most important household ECW nexus nodes with larger amounts and growth rates of household ECW. Income growth overwhelmingly increases ECW, while efficiency advance effectively curbs its growth. Comparatively, household number, family size, and urbanization have small effects. Therefore, implementing differentiated management and focusing on the synergy of socioeconomic factors are the keys to achieving integrated household ECW management. And the analytical framework can be used to analyze ECW nexus from a sector, city, or country perspective.

As the cost of solar photovoltaic (PV) systems decreases and incentives such as feed-in tariffs (FiTs) are offered, solar-PV homes are becoming popular. Furthermore, solar-PV homes integrated with hybrid or electric vehicles (EVs) are emerging as a paradigm for future homes. Given the fact that there exists a considerable price difference between grid electricity supply and FiTs, decision making of energy storage using batteries becomes an imperative topic. This research proposes an innovative and generic framework for the decision making of energy storage using batteries based on Smart Meter data, which incorporates the actual energy generation and consumption patterns of solar-PV homes. The proposed energy storage decision is based on a developed economic model, with the consideration of the electricity price from the grid, the FiTs, and the storage cost using batteries (i.e. the average price per kWh of battery capital cost and maintenance cost). Moreover, an intelligent algorithm is developed to calculate the electricity quantities, i.e. electricity supplied from the grid, fed into the grid and stored in a battery of a given capacity, based on the monitored data obtained from a Smart Meter over a year. The results reveal that at the present utility prices of $0.3/kWh and a feed-in-tariff of $0.10/kWh in the studied region, energy storage with a battery cost of $0.2/kWh or more is excessive and not economically feasible. However, with the increasing cost of electricity in recent years and constant changes in battery price, the outcomes could quickly reverse. This research contributes an innovative framework for battery storage decision-making of solar-PV homes, based on economic analysis and Smart Meter data.

Prefabricated construction has been widely accepted as an alternative to conventional cast-in-situ construction, given its improved performance. Great efforts have also been made to develop prefabricated construction technologies in China. However, there is a lack of an appropriate pattern for evaluating its comprehensive economic merits, and reasonable mathematical models for providing a comparative analysis of conventional cast-in-situ and prefabricated building projects have yet to be developed. Therefore, the research in this paper aims to comprehensively evaluate the economic benefits of implementing prefabricated construction techniques in order to surpass the economic barrier and promote the development of prefabricated buildings in China. The comprehensive economic evaluation is formulated in terms of resource-use efficiencies, project progress, and incentive policies. An apartment building in Shanghai is selected as a case study. Construction progress is simulated on the BIM platform when the same case study is rationally transformed from the prefabricated to the conventional cast-in-situ construction technique. The results reveal that the comprehensive economic merit can reach ¥739.6/m2 when selecting the prefabricated construction process. The economic benefit brought by shortening the construction period can be regarded as the most significant contributor. Yet, the current incentive policies only contribute 7.1% of the comprehensive economic evaluation. Overall, this research contributes an assessment framework for decision-making in the technique management of building construction. The BIM-based simulation approach can greatly help investors to identify the relevant economic factors and adopt the latest incentive policies.

The urban metro system is a complex system that is vulnerable to various kinds of hazards and subjected to dynamics, where errors in any part are very likely to cause system failures and accidents. A better understanding of evolutional dynamics of the system vulnerability over time enables to ensure the safety and security in its operation and provide guidance for long-term operation and maintenance for the metro system. However, there are limited studies considering the long-term evolutional dynamics and uncertainties of the vulnerability in urban metro system. To solve the concern, the objective of this research is to develop a hybrid approach that integrates system dynamics (SD) and Monte Carlo (MC) simulation to evaluate the vulnerability of the metro system in operation from a long-term perspective. By merging multi-resource information, an SD model consisting of 4 sub-systems (i.e., workforce vulnerability, organizational vulnerability, equipment vulnerability, and environmental vulnerability) and 16 feedback loops is constructed to reveal complex relationships among various factors and simulate the overall system vulnerability. The MC simulation is used to analyze the sensitive factors and improvement strategies of vulnerability in urban metro systems under uncertainty. The operation network of the Wuhan metro system in China is utilized as a case study to verify the applicability of the proposed approach. Results indicate that (i) It is predicted that the overall system vulnerability will decrease at the early stage of operation and rise at the later stage with the rapid decline of equipment system status; (ii) The workforce sub-system is discovered to be more sensitive to the overall metro system globally than the other three sub-systems, with the 10% and 20% fluctuations in input factors’ variations considered; (iii) The strategy that aims to improve the safety training and equipment maintenance and operation frequency is identified as the most effective strategy to reduce the vulnerability of the overall metro system. The developed approach can be used as a decision tool that is capable of modeling the long-term vulnerability of the overall metro system and discovering appropriate improvement strategies towards more sustainable transit development. Ministry of Education (MOE) Nanyang Technological University The Ministry of Education Tier 1 Grant, Singapore (No. 04MNP000279C120, NO. 04MNP002126C120) and the Start-Up Grant at Nanyang Technological University Singapore (No. 04INS000423C120) are acknowledged for their financial support of this research.

The defect in quality caused by the noncompactness of sleeve grouting has become the main obstacle restricting the further implementation of the prefabricated building in China. Studies have been conducted to explore the influencing factors of inadequate grouting; however, few studies attempt to investigate the complex interrelationship and lack of systematic cognition among these factors. To fill this gap, this study conducted a comprehensive literature review to collect the influencing factors of sleeve grouting and verified the reliability of these factors using the combined methods of brainstorming and semistructured expert discussion. A total of 18 key factors were identified and determined. The structural interpretation model (SIM) and Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) approaches were then used to analyze, depict, and explain the internal relationships between the factors. The results indicate that all factors were classified into six levels, among which poor responsibility of supervisors and weather conditions are the most basic factors, while grouting speed and a loose-sealing rubber plug are the most important factors. Finally, a three-level control strategy was proposed to improve the compactness quality of sleeve grouting. The research findings provide valuable guidelines for managers to eliminate the grouting quality defect and to further the development of prefabricated buildings in China.

In prefabricated construction, building components are manufactured off-site before shipping to the site for installation. Accurate design and planning are essential for smooth on-site execution and improved efficiency, which requires evaluations of various design options. However, due to the design process’s complexity, such evaluations cannot be achieved without automation and optimization. Meanwhile, the recent advancement of digital design technologies (e.g., building information modelling (BIM)) has enabled flexibility in the design process. The integration of BIM with other analytical algorithms also allows optimization of designs, such as the generative design that can parametrize the design. This study proposes a generative design approach that utilizes the optimization of the drywall installation layout to improve overall project efficiency. The framework includes a decision support module that considers environmental, cost, and aesthetic aspects to identify the optimal layout. The framework’s practical applicability has been successfully demonstrated through a case study. After implementation, three “best” design alternatives were found according to the decision aspects. The design improvements achieved were 37.5%, 7%, and 54% for the environmental, cost, and aesthetic factors, respectively. Accordingly, practitioners can make better decisions on planning drywall projects. This approach has proven effective in planning drywall installation and can be applied in similar design scenarios for other prefabricated construction processes.

Off-site construction entails various advantages compared with the traditional construction method; however, the fragmentation of the prefabrication and assembly results in a complex supply chain. Both general contractors and factories often encounter production deviation, making the original component delivery plan nonoptimal. Traditionally, both parties tend to rely on internal resources or third-party resources to manage schedule changes, paying little attention to the optimisation of the component delivery process. The static compensation mechanisms reported in existing literature require factories to manage demand fluctuations but fail to encourage general contractors to control schedule deviations. Therefore, a dynamic compensation mechanism is proposed to achieve just-in-time component delivery, with which a factory shares possible changes for each component’s delivery date to its clients on an inverse Kanban system. First, unfavourable changes for the factory schedule are allocated with surcharges, and the general contractor should compensate the factory if it accepts the date changes; secondly, schedule changes that are beneficial for the factory are assigned as incentives, and the general contractor receives the factory’s incentive upon agreeing to the changes. Based on these two scenarios, genetic algorithm-based optimisation models are developed to achieve optimal delivery planning solutions. General contractors can obtain an optimal component delivery date to reduce the additional cost when they have changed the assembly schedule. General contractors can also optimise their component delivery schedule to trade their duration flexibility for incentives offered by factories. The models can help both parties to reduce component delivery waste when either side has the motivation to change the original component delivery schedules.

Offsite construction (OSC) is attracting increasing attention from both industry and academia due to its benefits, such as improved productivity and quality, as well as reduced waste. However, the current building panelization design in OSC is a time-consuming and experience-based manual process, and the generated panelization design may result in unbalanced manufacturing processes. One reason is that the prefabrication of building components involves a highly variable product mix and there is a lack of a computational framework to evaluate panelization design. The objective of this research is, thus, to propose a BIM-based generative framework that automatically generates the design of production components with the aim of improving production productivity. This framework consists of a building information extraction module, a generative design algorithm, and a simulation-based performance evaluation model. The building information extraction module is designed to extract building component information from a BIM model and classify building components into different production groups in accordance with functionalities and materials. The generative design algorithm is then developed to formulate panelization design alternatives in consideration of the structural, production, and logistics constraints. On this basis, the generated panelization designs are quantitatively assessed by a simulation-based evaluation model in terms of productivity. A case study was used to verify and validate the framework. This research contributes to the body of knowledge by a computational framework of building panelization design, which leverages the generative design algorithm and BIM-simulation integration for optimized panelization design.

Off-site construction is receiving increasing attention as this construction method offers such benefits as improved productivity, shortened duration, greater quality, less whole-life cost, and less environmental impact. The concept of just-in-time has been applied in the manufacturing industry, improving performance and reducing waste; however, it has not been commonly used in the construction industry. When optimal delivery dates of components deviate from the schedule due to unexpected events, contractors and manufacturers tend to comply with contracts instead of seeking coordination to achieve just-in-time, which results in non-optimal solutions. In addressing this issue, the proposed conceptual model incorporates a dynamic and distributed solution: (1) manufacturers provide the surcharges or incentives of potential delivery changes via an information-sharing platform; (2) based on data from manufacturers and on-site resources, contractors carry out automated changes of the delivery plans when their progress deviates from the assembly schedule; (3) contractors make possible automated changes to the assembly schedule when manufacturers offer incentives for delivery delay. This paper investigates the development of just-in-time application in prefabricated building and proposes a solution to reduce the time and storage waste resulted from underutilised resources in component delivery. The proposed model incorporates a data-sharing platform, dynamic resource management system of manufacturers and optimisation system of contractors, which encourages stakeholders to coordinate to reach optimal. The model is expected to contribute to just-in-time delivery with dynamic compensation and offer a solution to balance the benefits of stakeholders.

The construction sector contributes about 40% of global carbon dioxide (CO2) emissions, and it is more active under great potential to reduce carbon emissions and speed down global warming. Even though Australia only takes 0.33% of the population in the world, its per capita carbon emission level is the biggest of the world, the Australian construction sector also accounts for a great part in economic development and carbon emissions. As there are extensive and complicated connections in industrial sectors, it is necessary to investigate the carbon emission linkages among the Australian construction sector and other sectors. Based on the data from the world input-output database (WIOD) during 1995 to 2009, this research aimed to quantify the CO2 emission linkages associated with the Australian construction sector by combing the hybrid multi-regional input-output (MRIO) model and hypothesis extraction method. As the net backward CO2 emission was much higher than the net forward CO2 emission, indicating the Australian construction sector was a final demand sector. From the inter-regional level, the construction sector in Australia had continual international trade with China, ROW, and Japan. For the inter-sectoral perspective, the construction sector imported most CO2 emissions from S17 (electricity, gas, and water supply), S11 (other non-metallic mineral), and S12 (basic metals and fabricated metal) and exported the biggest flows to S31 (public admin and defence; compulsory social security), and S29 (real estate activities). By using the results, the study tries to give some countermeasures for the construction sector in Australian, which is used to promote energy productivity, develop industrial structure promotion, and update the policy direction for CO2 emission reduction.

The uptake of prefabrication within the commercial construction sector has significantly increased over previous decades, given the proven benefits including provisions for lower construction costs, reduced project durations, and materials wastage, fewer defects, and improved profitability. However, it is found that defects caused by prefabrication cost significantly more to resolve compared with conventional construction, resulting in substantial impacts on project performance. Furthermore, defect management systems specific to prefabricated construction are found absent, especially within the commercial sector in Australia. This research studies the defect occurrence, identifies the causes of these defects, and proposes defect management for building prefabrication. A mixed research method of combined qualitative and quantitative approaches, i.e., literature review and an online survey, is employed in this research, based on which a depiction outlining common defects and stages of occurrence is presented, and a defect management process is proposed at an empirical level. It is found that most defects occur in manufacturing plant, and aesthetic defect is the most common type. The results also show that most defects can be linked to workmanship issues during fabrication. Subsequently, the management process of engaging an independent consultant employed by the government to undertake specialised inspections during design, manufacture, and installation has been proposed as an effective solution to reduce defect occurrence into the future, for which specific legislation for prefabrication is required.