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The performance of thermal comfort utilising machine learning and its acceptability by students and other users at the Professor Sir Edouard Lim Fat Engineering Tower at the University of Mauritius are evaluated in this study. Students and building occupants were asked to fill out surveys on-site as data was gathered from sensors throughout the structure. The Thermal Sensation Vote (TSV) and other important data were collected through the surveys, including the effect of wind on thermal comfort. An adaptive model incorporating solar and wind effects was evaluated using multiple linear regression techniques and RStudio. Three models were used to evaluate thermal comfort, including the adaptive one. Numerous models were compared and evaluated in order to select the best one. It was found that the adaptive model (Model 1) was deemed to be the best model for its application. It was also found that Fanger's PMV/PPD (Model 2) was a very good approach to determining thermal comfort. Through thorough analysis, it was concluded that the range of air temperature and wind speed for thermal comfort was 25.830°C–28.0°C and 0.26 m/s to 0.42 m/s, respectively. In order for cities to remain secure, resilient and sustainable, it will be important to manage thermal comfort and reduce populations' exposure to heat stress (SDG 11). The achievement of income and productivity goals will be hampered if measures to protect populations from heat stress are not taken (SDG 8). Thermal regulation is also necessary for the provision of numerous health services (SDG 3).

This research aims to investigate the influence of building design on the thermal comfort of occupants of naturally ventilated hospital (NVH) wards to identify the aspects with the most significant influence on the thermal comfort of hospital buildings during the hot-dry season in the hot-humid tropics of Southeast Nigeria.

Field measurements, physical observations and a questionnaire survey of 60 occupants of the wards of the Joint Presbyterian Hospital, Uburu in Ebonyi State, Nigeria were undertaken. The data were analysed using Humphreys' neutral temperature formula, descriptive statistics and multiple regression analysis.

The results revealed that the neutral temperature for the wards ranges from 26.2 °C to 29.9 °C, the thermal condition in the wards was not comfortable because it failed to meet the ASHRAE Standard 55 as only 65% of the occupants said the thermal condition was acceptable. The number and sizes of windows, building orientation, the presence of high-level windows and higher headroom significantly influenced the occupants' thermal comfort vote.

This research is valuable in estimating comfort temperature and identifying aspects that require attention in enhancing the capacity of NVH wards to effectively meet the thermal comfort needs of occupants in the hot-humid tropics of Southeast Nigeria and other regions that share similar climatic conditions.

To the best of the authors’ knowledge, this is the first study of this nature that provides valuable feedback for building design professionals on the performance of existing hospital buildings in meeting users' thermal comfort needs in the hot-dry season of the hot-humid tropics in Southeast Nigeria.

Science mapping is an essential application of visualization technology widely used in safety, construction management and environmental science. The purpose of this study was to explore thermal comfort in residential buildings (TCinRB) research in India, identify research trends using a science mapping approach and provide a perspective for recommending future research in TCinRB.

This study used the VOSviewer tool to conduct a systematic analysis of the development trend in TCinRB studies in India based on Scopus Index articles published between 2001 and 2020. The annual numbers of articles, geographical locations of studies, major research organizations and authors, and the sources of journals on TCinRB were presented based on the analysis. Then, using co-authorship analysis, the collaborations among the major research groups were reported. Furthermore, research trends on TCinRB studies were visually explored using keyword co-occurrence analysis. The emerging research topics in the TCinRB research community were discovered by analyzing the authors’ keywords.

The findings revealed that studies had been discovered to pay more attention to north-east India, vernacular architecture, Hyderabad apartments and temperature performance in the past two decades. Thermal adaptation, composite climate, evaporative cooling and clothing insulation are emerging research areas in the TCinRB domain. The findings summarized mainstream research areas based on Indian climatic zones, addressed current TCinRB research gaps and suggested future research directions.

This review is particularly significant because it could help researchers understand the body of knowledge in TCinRB and opens the way for future research to fill an important research gap.

Given the distinct and unique climates in these countries, research conducted in other parts of the world may not be directly applicable. Therefore, it is crucial to conduct research tailored to the specific climatic conditions of Australia and New Zealand to ensure accuracy and relevance.

Given population growth, urban expansions and predicted climate change, researchers should provide a deeper understanding of microclimatic conditions and outdoor thermal comfort in Australia and New Zealand. The study’s objectives can be classified into three categories: (1) to analyze previous research works on urban microclimate and outdoor thermal comfort in Australia and New Zealand; (2) to highlight the gaps in urban microclimate studies and (3) to provide a summary of recommendations for the neglected but critical aspects of urban microclimate.

The findings of this study indicate that, despite the various climate challenges in these countries, there has been limited investigation. According to the selected papers, Melbourne has the highest number of microclimatic studies among various cities. It is a significant area for past researchers to examine people’s thermal perceptions in residential areas during the summer through field measurements and surveys. An obvious gap in previous research is investigating the impacts of various urban contexts on microclimatic conditions through software simulations over the course of a year and considering the predicted future climate changes in these countries.

This paper aims to review existing studies in these countries, provide a foundation for future research, identify research gaps and highlight areas requiring further investigation.

In the context of a developing country, Indian buildings need further research to channelize energy needs optimally to reduce energy wastage, thereby reducing carbon emissions. Also, reduction in smart devices’ costs with sequential advancements in Information and Communication Technology have resulted in an environment where model predictive control (MPC) strategies can be easily implemented. This study aims to propose certain preemptive measures to minimize the energy costs, while ensuring the thermal comfort for occupants, resulting in better greener solutions for building structures.

A simulation-based multi-input multi-output MPC strategy has been proposed. A dual objective function involving optimized energy consumption with acceptable thermal comfort has been achieved through simultaneous control of indoor temperature, humidity and illumination using various control variables. A regression-based lighting model and seasonal auto-regressive moving average with exogenous inputs (SARMAX) based temperature and humidity models have been chosen as predictor models along with four different control levels incorporated.

The mathematical approach in this study maintains an optimum tradeoff between energy cost savings and satisfactory occupants’ comfort levels. The proposed control mechanism establishes the relationships of output variables with respect to control and disturbance variables. The SARMAX and regression-based predictor models are found to be the best fit models in terms of accuracy, stability and superior performance. By adopting the proposed methodology, significant energy savings can be accomplished during certain hours of the day.

This study has been done on a specific corporate entity and future analysis can be done on other corporate or residential buildings and in other geographical settings within India. Inclusion of sensitivity analysis and non-linear predictor models is another area of future scope.

This study presents a dynamic MPC strategy, using five disturbance variables which further improves the overall performance and accuracy. In contrast to previous studies on MPC, SARMAX model has been used in this study, which is a novel contribution to the theoretical literature. Four levels of control zones: pre-cooling, strict, mild and loose zones have been used in the calculations to keep the Predictive Mean Vote index within acceptable threshold limits.

The Purpose of this paper is to identify statistical relationships between visual environment and occupant productivity. Visual environment is one of the most important indoor environmental quality (IEQ) parameters, and it directly impacts occupant productivity in offices. The literature outlines the significance of the impact. Still, there is a lack of investigation, statistical analysis and inter-relationships between the independent variables (IEQ factors), especially in the hot and arid climate.

This study presents a research study investigating the effects and shows statistical relationships between IEQ on occupant comfort and productivity. The study was conducted in the Middle East, and data was collected for 12 months. It used the response surface analysis to perform analysis.

This study outlined seven unique relationships highlighting the recommended range, inter-dependencies. Results include that illumination has maximum effect on visual comfort and temperature, daylight having direct influence and relative humidity, wall type next to the seat and kind of workspace also impact visual comfort and productivity. These findings would help to improve occupant comfort and productivity in office buildings. It is recommended to include results and recommendations on design guidelines for office buildings.

This study presents the unique effects of non-visual IEQ parameters on visual comfort and productivity. This investigation also provides a unique method to develop the statistical relationship between various indoor environmental factors and productivity in different contexts and buildings.

Digital twin (DT) and building information modeling (BIM) are interconnected in some ways. However, there has been some misconception about how DT differs from BIM. As a result, industry professionals reject DT even in BIM-based construction projects due to reluctance to innovate. Furthermore, researchers have repeatedly developed tools and techniques with the same goals using DT and BIM to assist practitioners in construction projects. Therefore, this study aims to assist industry professionals and researchers in understanding the relationship between DT and BIM and synthesize existing works on DT and BIM.

A systematic review was conducted on published articles related to DT and BIM. A total record of 54 journal articles were identified and analyzed.

The analysis of the selected journal articles revealed four types of relationships between DT and BIM: BIM is a subset of DT, DT is a subset of BIM, BIM is DT, and no relationship between BIM and DT. The existing research on DT and BIM in construction projects targets improvements in five areas: planning, design, construction, operations and maintenance, and decommissioning. In addition, several areas have emerged, such as developing geo-referencing approaches for infrastructure projects, applying the proposed methodology to other construction geometries and creating 3D visualization using color schemes.

This study contributed to the existing body of knowledge by overviewing existing research related to DT and BIM in construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research.

As public–private partnerships (PPPs) have become preferred and veritable approach to deliver affordable housing, the seemingly lack of understanding of the significant factors that impact on success has become a notable setback. This study aims to delineate significant factors that can support decisions in affordable PPP public housing delivery.

Largely, a questionnaire survey was adopted to elicit insights from practitioners, policymakers and experts to develop an evaluative decision support model using an analytical hierarchy process and multi-attribute utility technique approach. Further, an expert illustration was conducted to evaluate and validate the results on the housing typologies.

The results revealed that energy efficiency and low-cost green building materials scored the highest weighting of all the criteria. Furthermore, multi-storey self-contained flats were found to be the most preferred housing typology and were significantly influenced by these factors. From the model evaluation, the scores on the factors of sustainability, affordability, cultural values and accountability were consistent across all typologies of housing whereas that of benchmarking, governance and transparency were varied.

The decision support factors captured varied dimensions of key factors that impact on affordable PPP housing that have not been considered in an integrated manner. These findings offer objective and systematic support to decision-making in affordable PPP housing delivery.

As climate change impacts residential life, people typically use heating or cooling appliances to deal with varying outside temperatures, bringing extra electricity demand and living costs. Water is more cost-effective than electricity and could provide the same body utility, which may be an alternative choice to smooth electricity consumption fluctuation and provide living cost incentives. Therefore, this study aims to identify the substitute effect of water on the relationship between climate change and residential electricity consumption.

This study identifies the substitute effect of water and potential heterogeneity using panel data from 295 cities in China over the period 2004–2019. The quantile regression and the partially linear functional coefficient model in this study could reduce the risks of model misspecification and enable detailed identification of the substitution mechanism, which is in line with reality and precisely determines the heterogeneity at different consumption levels.

The results indicate that residential water consumption can weaken the impact of cooling demand on residential electricity consumption, especially in low-income regions. Moreover, residents exhibited adaptive asymmetric behaviors. As the electricity consumption level increased, the substitute effects gradually get strong. The substitute effects gradually strengthened when residential water consumption per capita exceeds 16.44 tons as the meeting of the basic life guarantee.

This study identifies the substitution role of water and heterogeneous behaviors in the residential sector in China. These findings augment the existing literature and could aid policymakers, investors and residents regarding climate issues, risk management and budget management.

The link between relationship typologies and effectiveness of conflict resolution approaches remains to be tested despite its significance in conflict management in construction project delivery. By using the four relationships attributes based on the group attachment theory, the purpose of the study was to explore the cluster of relationships among project teams and organisations and the performance of conflict management strategies across these clusters in the Ghanaian construction industry.

Using a deductive questionnaire survey in the Ghanaian construction industry, a total of 137 responses were gathered and analyzed using cluster analysis, mean scores and ANOVA to reveal the relationship clusters and performance of conflict management strategies across these clusters.

The results revealed eight relationship clusters that exist among project teams and organisations with distinct influence of roles & tasks function, cognition, emotions and behavior attributes across the relationship clusters. In the aspect of the effectiveness of conflict management strategies, it was noted that the performance of these strategies were significantly different across the groups. For instance, integrating as a conflict management strategy was deemed to be effective in resolving conflict in unitary, adversarial, pluralist, mutuality, collaborative and partnering relationship clusters. In the case of coopetitive and coercive relationships, the performance of integrating as a conflict management strategy was less effective. This study thus has empirically proved that, different relationship clusters of teams and organizations exist within the Ghanaian construction industry, and that they perform different roles & tasks functions, cognition, emotions and behavioural attributes in their formation. Additionally, the performance effectiveness of conflict management strategies differed across the relationship clusters.

By aligning the relationship attributes to the dynamics of relationship clusters experienced in project teams and organisations, relationship quality, suitability and effectiveness of conflict management strategies can be optimized. The findings can inform project teams and stakeholders to develop fit-for-purpose relationship attributes among teams and organisations to enhance team effectiveness, relationship quality and conflict management in the industry.