ABSTRACT The rapid expansion of rural tourism in China has driven the conversion of rural houses into rural tourism homestays (RTHs), many of which rely on energy-intensive systems for indoor climate control, raising sustainability concerns. Natural ventilation offers a low-cost strategy to improve energy efficiency and indoor airflow comfort, yet its effectiveness in RTHs remains underexplored. This study investigates wind-driven natural ventilation in three representative RTH typologies in North China, selected from previously optimized prototypes developed through a multi-objective optimization framework balancing energy use, daylighting, and thermal comfort. Computational fluid dynamics (CFD) simulations were conducted using the Butterfly plugin within Rhino/Grasshopper under prevailing summer wind conditions, and mesh convergence and discretization uncertainty were assessed using a three-grid Grid Convergence Index (GCI) analysis. Baseline simulations revealed that all typologies contained indoor areas with suboptimal ventilation. Optimization was performed on operable window openings, operable skylight openings, and courtyard configurations, and the tested parametric scenarios across typologies increased the comfortable velocity area ratio by up to 8.46% and the average air velocity by up to 2.42% (relative to the baseline) at the building or floor level. Finally, typology-specific passive design recommendations were put forward for RTHs in North China. The study further establishes a parametric CFD-based workflow for ventilation-oriented design optimization, contributing to low-carbon rural revitalization and evidence-based decision-making in sustainable rural tourism development. Highlights Explores natural ventilation in rural tourism homestays in North China. Applies a parametric CFD-based workflow using Butterfly in Rhino/Grasshopper. Optimizes operable window openings, skylight openings and courtyard design. Proposes passive ventilation strategies for different homestay typologies.

ABSTRACT This study investigates the role of the air-to-radiant temperature offset, defined as the difference between air temperature and mean radiant temperature, in predicting thermal sensation in naturally ventilated office buildings located in warm Mediterranean climates. Although machine learning has advanced thermal comfort modeling by capturing complex relationships among environmental and physiological variables, most models continue to treat radiant effects indirectly, blending them into operative temperature rather than modeling the offset as a distinct predictor. This approach limits their ability to reflect the directional influence of radiative asymmetries commonly found in naturally ventilated environments. To address this gap, a data-driven approach using machine learning was employed. A curated subset of the ASHRAE Global Thermal Comfort Database II was used, filtered for naturally ventilated office spaces in the Csa climate zone during warm seasons. Eleven regression algorithms were compared to predict occupants’ thermal sensation votes based on operative temperature, air-to-radiant temperature offset, relative humidity, air velocity, and metabolic rate. Among these, a tuned Random Forest model achieved the highest performance, significantly outperforming traditional thermal comfort predictions. Feature importance and SHAP analysis revealed that the air-to-radiant temperature offset was an influential predictor, with clear non-linear effects on perceived comfort.

ABSTRACT As traditional roles within the design-bid-build delivery system have changed over decades, literature has presented the effects on perceptions of the architectural profession from the standpoint of major stakeholders. This narrative literature review explores these changes through descriptive analysis that identifies, compares, and contrasts the priorities of facility owners, architects, and GCs as related to design-bid-build delivery system projects within the United States. In addition, the perspectives of United States academic instructors teaching architectural design are explored to show how instructors, who hold significant sway for shaping the ideologies of future architects, view the responsibilities of the architectural profession. Authors identify two contexts through which priorities of stakeholder groups are discussed: those pertaining to moral purpose for practice behavior, and those pertaining to standard practice.

ABSTRACT Building structural designs, utilizing materials such as steel, concrete, and cross-laminated timber, contribute significantly to embodied carbon emissions in construction projects. However, traditional carbon accounting methods employed to quantify and record these emissions are often characterized by a lack of traceability, transparency, and immutability. This limitation undermines the reliability of emissions data, making it challenging for stakeholders to establish credible emissions records and implement regulatory strategies, such as carbon credits, taxes, subsidies, and green certifications, for building’s structural designs and materials. This paper addresses these challenges by proposing a transformational emissions accounting system that integrates Building Information Modeling (BIM) for automatic extraction of emissions-relevant data, alongside blockchain-enabled smart contracts to ensure traceability and immutability of emissions records. The proposed system enables data-driven decision-making for low-carbon structural designs and materials, while also facilitating the application of emissions regulations to support their implementation based on trustworthy emissions accounting.

ABSTRACT The implementation of artificial intelligence (AI) and machine learning (ML) in the architecture, engineering, and construction (AEC) domain has gained significant attention within academic research and construction technology companies. The scientific field often relies on information collected from the industry for theoretical development and sometimes test cases. However, to the best of the authors’ knowledge, there has been no systematic effort to compare academic and industry trends and developments. In this work, we examine the development and application of ML in the AEC domain from both academic and industry perspectives. To investigate both perspectives, we implement a mixed-methods approach including an academic literature review, a web-based mapping of construction technology companies worldwide, and an online questionnaire targeting practitioners and technology companies. Overall, our mixed methods analysis reveals a strong alignment between academic research and industry practice in targeting early design and post construction phases, with both communities prioritizing the application of ML for energy efficiency, facility management, and site safety, particularly within the context of Building Information Modeling (BIM). However, industry devotes more effort to sustainability, cost and scheduling solutions, whereas academia lags in these areas and often relies on limited or synthetic datasets. Finally, both sectors identify data availability and quality, particularly the scarcity of large, labeled, domain-specific repositories, as the primary barrier to wider ML adoption in the AEC industry.

ABSTRACT The renewal of urban industrial heritage in the era of people-oriented urban regeneration necessitates a deeper understanding of how spatial elements foster people’s emotional attachment to specific spaces. This study explores the impact of natural, artificial, and interactive environmental features on people's emotional responses within Beijing Langyuan Station, a welcomed renewed industrial heritage site. A multimodal neuro-architectural methodology was employed in an immersive virtual reality environment, synchronously recording behavioral, physiological, and neural data from fifty-two participants alongside emotional attachment scales. Results indicate that artificial elements (e.g. brick, glass, metal) most strongly facilitated emotional attachment, eliciting rapid visual engagement, elevated autonomic arousal, and increased cognitive alertness. Interactive elements, such as public artworks and graphic signs, promoted attachment through intuitive recognizability and experiential richness. Natural elements, though less directly tied to attachment, served essential regulatory functions by mitigating industrial rigidity and supporting spatial identity. The study demonstrates the value of neuroscientific tools in decoding human emotional experience in architectural environments. It provides an evidence-based framework for designing affectively engaging spaces and offers methodological insights for future neuro-architectural research in urban regeneration contexts.

ABSTRACT This study explores the relationship between courtyard geometry and the spatial organization of historical houses in Mashhad during the Qajar and Pahlavi periods. It examines how courtyard dimensions (length, width, and height) affect spatial hierarchy and domestic layout, aiming to quantify this relationship and to inform culturally responsive contemporary residential design. An analytical-exploratory approach was applied in three stages. First, a literature review identified key factors influencing spatial organization in traditional Iranian houses. Second, the DEMATEL method was used to analyze causal relationships and assess the relative importance of these factors. Third, a purposive sample of 37 historical houses (15 Qajar and 22 Pahlavi) was modeled in AutoCAD 2013, and their geometric data were statistically analyzed using SPSS 2016. The findings demonstrate a significant linear relationship between courtyard geometry and spatial organization, expressed as y = kx. The coefficient k was calculated as 1.7 for Qajar houses and 1.48 for Pahlavi houses, indicating a gradual shift in spatial proportionality over time. DEMATEL results reveal that courtyard geometry is the most influential factor in shaping spatial organization, with the highest prominence value (23.80%), followed by climatic and socio-political factors. Overall, the study contributes original value by applying DEMATEL to housing spatial analysis and by transforming the traditional central courtyard from a descriptive typology into a measurable and replicable model. The results offer practical, evidence-based guidance for designing culturally responsive, sustainable, and human-centered contemporary housing.

ABSTRACT The prevalence of aggression towards healthcare workers presents a serious threat to the well-being of clinicians globally. Up to 95% of healthcare workers have experienced workplace violence, with prevalence in emergency departments being among the highest. The purpose of this study was to develop and assess the feasibility of a decision support tool, based on a quality function deployment approach, to prioritize design considerations that may reduce the risk of violence against clinicians in emergency department settings. Specific objectives were to (1) explore antecedents of violence against healthcare workers, (2) identify environmental design strategies that may moderate the risk of violence, and (3) develop a decision-support tool to help healthcare designers and administrators design emergency departments that potentially reduce risks to staff. Data extracted from thematic analysis of relevant literature and space syntax analysis informed the development of technical performance measures and design dependent parameters which served as the basis for a quality function deployment matrix to serve as a decision support tool. The preliminary tool was reviewed by subject matter experts and refined. We concluded that quality function deployment is a feasible approach to developing a decision support tool to inform emergency department design and may be applicable in other types of healthcare settings. Dissemination of the tool to a larger sample of clinicians and healthcare designers to prioritize design strategies may reduce future assaults against emergency department staff.

ABSTRACT The rapid expansion of urban underground engineering has made three-dimensional geological modeling an indispensable tool for visualizing, digitizing, and parametrically displaying engineering geology. This is particularly crucial in the design, construction, and management of urban underground space projects. To better study the applicability and feasibility of 3D geological modeling in integrated transportation hub project. The effectiveness of the Earth Volumetric Studio stratigraphic-lithological modeling method was demonstrated through its application to the Guangzhou Baiyun (Tangxi) Station integrated transportation hub project. The analysis methods were systematically introduced, followed by research on 3D geological modeling. This included excavation analysis, earthwork volume measurement, and the analysis of adverse engineering geology, such as karst caves. Additionally, specialized designing of enclosure structures in water-rich sand layers was performed. The application results demonstrate that three-dimensional geological modeling in urban underground space projects can provide a scientific decision-making basis and reliable data support for project investment estimation, construction plan formulation, and identification of adverse geology. The findings of this paper provide valuable insights and practical applications in the field of urban underground engineering, demonstrating the benefits of 3D geological modeling for the design, construction, and management of urban underground space projects.

ABSTRACT The transition to a circular economy aims to reduce the consumption of raw materials and minimise waste. Building circularity assessment (BCA) at the early design stages is crucial for achieving circularity and sustainability objectives, which are often considered separately and can occasionally conflict. Although building information modelling (BIM) has been leveraged to support decision-making, current BIM-based BCA tools focus mainly on geometric information extraction without offering decision-making support. To address these gaps, this study adopts a design science research (DSR) methodology to develop a BIM-based decision support system (DSS) that integrates BCA with life cycle assessment (LCA) and life cycle costing (LCC), supporting simultaneous evaluation of circularity and sustainability from a life cycle perspective aligned with the EU Level(s) framework, while facilitating trade-offs and the straightforward comparison of design alternatives. Multi-criteria decision analysis is employed to facilitate trade-offs and selection among design alternatives. The DSS enables assessment at the element, system, and building levels and enhances traceability and documentation via circular material passports and a material bank interface. As a pilot demonstrated on a simplified case study, the proposed framework was tested in a controlled environment through a proof-of-concept simulation experiment using a hypothetical building model and generic data. This conceptual validation demonstrates the feasibility and utility of the artefact. The empirical validation with practitioners and real building projects remains a matter for future research. The DSS shows the potential to optimise material use and resource efficiency, contributing to the twin transition of a sustainable circular economy and digitalisation.