Search Results (4,235)

Precise assessment of commercial service facilities (CSFs) is a vital pillar for megacity governance. However, existing evaluations rely on static population and 2D metrics, overlooking behavioral heterogeneity and 3D spatial supply at the micro scale. This study constructs a “3D Supply–Group Demand–Matching” framework at the community level. On the supply side, a Building Coupling Entropy (BCE) model integrates 3D volume and morphology to characterize service capacity. On the demand side, a dynamic behavioral model measures multi-group needs. Mismatch patterns are identified using the Entropy-modified Spatial Disparity Ratio (ESDR). Using Guangzhou as a case, the results reveal three paradigms: (1) Core districts exhibit rigid path dependency, where first-tier sub-districts rose from 48 to 51, and elderly service shortages in old areas plummeted by nearly 80% via micro-regeneration; (2) Growth poles show spatial fragmentation, with core labor demand spilling over but infrastructure lagging, creating a fast production–slow urbanism mismatch; (3) Far-suburban areas reduced extreme-shortage sub-districts from 38 to 34, identifying resource islands besieged by residential demand. Overall, the framework elucidates the shape–flow mismatch mechanism and provides a transferable basis for precision zonation governance, supporting a shift from static quantity-based allocation to dynamic quality-oriented provision in high-density megacities. Full article

Depression represents one of the most prevalent mental health challenges globally, affecting individuals across diverse populations and settings. Based on the neurogenesis-informed hypothesis that stair use may likely elevate brain-derived neurotrophic factor (BDNF) in humans that in turn may have an antidepressant effect, this study takes residential buildings as a controlled environment to test whether there is a difference in depression symptoms based on single- or multi-storey housing. This study examined associations between staying at home and depression symptoms using the Public Health Questionnaire-8 (PHQ-8) data from 128 adults in England who spend most of their time at home. Residents in single-storey flats in apartment buildings had significantly higher overall depression scores than multi-storey house residents. Among the PHQ-8 items, only Item 8, psychomotor agitation/retardation (moving or speaking too slowly, or restlessly moving around more than usual), approached but did not reach statistical significance after Bonferroni correction (p = 0.056). After adjusting for gender, age, number of residents, activity level, and income, apartment living (vs. multi-storey houses) (β = −0.362, p < 0.001) and loneliness (β = 0.221, p = 0.016) were significant independent predictors of psychomotor agitation/retardation. Future research is needed to explore this relationship using a larger sample size and to explore whether the use of stairs explains this potential relationship through a change in BDNF. Full article

This study investigates food-oriented revitalisation (FOR) of Poland’s large-panel housing estates, focusing on the widely used OWT-67 prefabricated system, and proposes an architectural framework for integrating food production into residential retrofit. The research combines (i) a critical review of scholarship on coupling housing and productive functions with (ii) a design-led case study that evaluates the potential of flat rooftops for cultivation, developed for an OWT-67 building in the Kolorowa estate (Ursus, Warsaw), and complemented by an analysis of available financing pathways. The case study translates structural and operational constraints into a buildable rooftop farming scheme based on lightweight cultivation devices arranged around a central circulation deck. The financing review shows that renovation support in Poland is dispersed and predominantly credit-based, suggesting that rooftop food programmes are most feasible when packaged with eligible measures such as energy upgrades, roof refurbishment, climate-adaptation actions and renewable-energy installations. Overall, the proposed rooftop production would meet approximately 8% of the annual fruit-and-vegetable demand in the 45-resident scenario and about 4% in the 100-resident scenario. Accordingly, the OWT-67 roof is best understood as a source of seasonal fresh produce and a socio-educational infrastructure that supplements—rather than replaces—conventional food supply systems. Full article

Semi-prefabricated and prefabricated concrete construction is today widely accepted as the standard method for industrial facilities, warehouse halls, and similar structures. In addition to such buildings, increasing attention has recently been given to prefabricated construction of residential buildings using load-bearing prefabricated walls. System simplicity, rapid construction, efficient site organization, and robust load transfer have stimulated the development of multiple systems and technologies, mainly differing in panel infill and connection type. In all these systems, panel connections represent the key structural detail. The connections must transfer all foreseeable forces, but their number and complexity must not be excessive, so as not to compromise the fundamental advantages of this construction method. This paper presents a review of the current state of knowledge on the behavior of prefabricated concrete wall panels and their connections by analyzing the results of numerical and experimental investigations. Current codes and guidelines relevant to prefabricated wall systems are reviewed in the context of design and construction practice in Europe and worldwide, showing that they are largely based on general recommendations rather than explicit design provisions. Key disadvantages of existing models and areas requiring additional experimental validation and numerical model calibration are identified. Finally, the study contributes to a better understanding of the factors that affect the reliability and cost-effectiveness of prefabricated wall panels in the building industry. Full article

Rapid population growth is increasing housing demand and accelerating the expansion of the built environment in Egypt. However, practical and sustainable residential building decarbonization remains constrained by limited supplies of supplementary cementitious materials, limited structural timber resources, code restrictions on cement reduction, and cost sensitivity. This study evaluates two Egyptian multi-unit residential case studies—one affordable housing project and one middle-class housing project—to assess whether wall-system substitution can reduce both embodied and operational carbon under local material, code, and cost constraints. An integrated BIM-based digital twin workflow was used to link quantity takeoff, finite-element structural assessment, and whole-building energy simulation. An architectural BIM model was used for material quantification, wall-system definition, and energy-model inputs. A structural model was used to assess the effects of reducing wall density on reinforcement and concrete demand under gravity and seismic load combinations. Operational performance was assessed through cooling-focused energy simulations under hot-arid climatic conditions representative of Egypt’s new desert cities. Alternative wall systems were then evaluated through scenario- based material substitution and revised structural and energy assessments. The results show that reinforcement, concrete, and wall- core materials account for about 80% of total embodied carbon, while cooling accounts for about 72% of operational emissions. Non-structural cement uses, mainly mortars and finishes, account for 36% of total cement demand, ranging from 161 to 229 tons per building across the two case studies. Replacing conventional partition walls with lightweight, energy-efficient alternatives reduced embodied carbon by up to 35.2%, operational carbon by about 15.7% to 16.5%, and total life-cycle carbon by about 17.4% to 17.5% over a 60- year service life. The average savings per building corresponded to avoiding about 30 tons of steel, 165 m³ of ready-mix concrete, and 191 m³ of mortar, with net cost savings of about 3.15 million EGP per building. These results identify a practical pathway toward more sustainable, lower-carbon Egyptian residential buildings without increasing project cost. Full article

Construction projects depend heavily on manual labor; however, workforce productivity is frequently constrained by poor planning and communication. This paper proposes a methodological framework that combines Building Information Modeling (BIM) with the Lines of Balance (LOB) technique to estimate, allocate, and visually coordinate crews in repetitive building work. Using a Design Science Research approach, the study draws on a systematic review of 29 eligible studies that identified 23 processes for human resource planning and allocation. These processes are structured into five planning categories: scope and duration, structuring and quantification, resource estimation and allocation, schedule baseline, and cost baseline. BIM support is operationalized through seven high-utility BIM applications identified by expert assessment (RUI > 0.75), including phase planning, scheduling, site utilization planning, and cost estimation. The framework connects model-based quantity takeoff and productivity assumptions with LOB-based sequencing and crew assignment. This integration enables early detection of spatiotemporal overlaps and workload imbalances through consistent BIM–LOB visualization. The method was implemented and calibrated in two residential case studies (one covering 295 m² over 3 months and the other 3660 m² over 22 months), resulting in workforce plans comprising 10 workers across five crews and 72 workers across nine crews. An evaluation involving 31 professionals indicates a high perceived utility, particularly in reducing errors in quantity and productivity estimation (RUI = 0.90) and crew quantification (RUI = 0.88). Full article

Residential buildings are a major source of urban carbon emissions, yet the uptake of smart home retrofitting remains far below the level required to meet decarbonization and sustainability targets. While technical solutions for energy-efficient renovation are well established, less is known about how behavioral, psychological, and institutional factors jointly shape household retrofit decisions and their broader sustainability implications. This study develops an integrated analytical framework that combines UTAUT2 with perceived risk, trust, innovativeness, and regulatory pressure, interpreted through a socio-technical systems perspective, to examine smart home retrofitting in Thailand and its contribution to Sustainable Community Development Goals (SCDG). Survey data were collected from 448 households in Bangkok and Chonburi and analyzed using structural equation modeling. The results show that traditional UTAUT2 predictors such as performance expectancy, effort expectancy, and social influence do not significantly influence adoption intention in this high-cost retrofit context. Instead, innovativeness, trust, price value, perceived risk, and regulatory pressure emerge as key behavioral and institutional drivers, while facilitating conditions and habits shape actual use behavior. Actual retrofit behavior is found to generate significant economic, environmental, socio-cultural, technological, and public-policy sustainability outcomes aligned with SCDG. These findings demonstrate the limitations of conventional technology acceptance models in infrastructure-based contexts and provide a mechanism-based explanation of how retrofit adoption is driven in high-cost sustainability contexts. Full article

With heat pump adoption falling behind expectations, the UK faces a strategic challenge in meeting residential decarbonisation targets. This study investigates the barriers hindering adoption through an in-depth case analysis of a complete household heat pump adoption journey in a pre-Second World War family home in the UK. Combining an autoethnographic approach with quantitative analysis of 4.7 years of household data, it provides a rare, detailed examination of consumer experience in the UK. The analysis applies both rational and relational perspectives, showing that relational factors, such as trust and social networks, are particularly influential in early-stage markets. Key challenges are identified in retrofit system complexity, social engagement, installer capability and electricity pricing. Although the initial assessment found the heat pump was uneconomic, post-installation results showed an annual SPF of 3.22, a 59% reduction in energy demand and a 12% reduction in costs compared with a gas boiler. Behavioural adaptation contributed to demand reduction and lowered the effective electricity price by ~3 pence/kWh. However, a further 7 pence/kWh reduction is required to reach cost parity with a gas boiler, implying an electricity-to-gas price ratio of 2.3. The findings highlight important areas for policy intervention. Full article

High-resolution multispectral remote sensing imagery for accurate building footprint extraction and reliable height estimation often faces numerous challenges in complex urban environments with diverse building structures, heterogeneous shadow patterns, and widespread occlusions. This study proposes a sparse edge-aware convolutional-transformer neural network model, SECT-Net, for precise extraction of building footprints and their cast shadows from high-resolution Jilin-1 multispectral images covering Shanghai, China. A shadow-based height estimation workflow was then developed to characterize building heights from their shadow lengths. Results show that the SECT-Net achieves high performance in building footprint extraction, with an IoU of 77.96%, an F1 score of 87.62%, and an overall accuracy of 97.16%, respectively. Building heights for more than 750,000 buildings were estimated across the entire Shanghai, with R² = 0.74 and RMSE = 5.66 m. A slight systematic underestimation of building heights is attributed to occlusions of high-rise buildings and the disruption of vegetation in residential communities in dense urban central areas. This study demonstrates that the proposed SECT-Net can accurately and precisely extract building footprints from high-resolution spaceborne remotely sensed images. The estimated building heights provide a reliable underpinning for urban morphology analysis and building monitoring in urban planning and scientific management. Full article

The increasing demand for efficient and sustainable building design has led to the development of nD BIM, which integrates multiple dimensions such as time (4D), cost (5D), and environmental performance (6D and beyond). However, existing approaches often lack an integrated decision-making framework that supports the simultaneous evaluation of these criteria, particularly in the early design phase of building envelope systems. This study proposes a unified nD BIM-based decision-making framework for building assemblies, using authoring tools, namely the BIM approach and LCA methodology. The proposed framework is applied in an empirical case study, where several design variants of a multi-residential building are developed and analyzed through 4D and 5D BIM models to assess construction time and costs, while environmental impacts are evaluated using selected key indicators, e.g., Global Warming Potential (GWP), Acidification Potential (AP), and the consumption of non-renewable primary energy (PENRT). The outcomes of these analyses are integrated into a multi-criteria decision-making model based on a weighting system. The results demonstrate that an nD BIM-based unified weighted decision model enhances decision-making by enabling transparent comparison of design alternatives and identification of trade-offs, thereby supporting more efficient and sustainable building envelope design while improving decision quality and reducing uncertainty for designers, engineers, and project investors. Full article

The reduction in energy demand in buildings through the adaptation of energy-efficient strategies is attracting significant attention from the research community. In this context green building concepts can contribute towards achieving national sustainable development goals (SDGs) and NetZero targets. Given the substantial energy demand associated with heating and cooling in commercial and residential buildings, enhancing energy efficiency has become essential for achieving sustainable development, particularly amid ongoing global energy challenges. The Envelope Thermal Transfer Value (ETTV) model has been established as a simplified method of calculating building loads; however, its integration with green building elements remains limited, particularly in subtropical climates. Furthermore, the combined effects of living walls, green façades, and green roofs on building energy performance have not been comprehensively investigated. In this study, an extensive experimental investigation was conducted using prototype buildings under controlled conditions to evaluate the thermal performance of green elements. Modified ETTV formulations incorporating green envelope systems have been developed, and the thermodynamic effects of these green elements on the building energy performance have been analysed. The results demonstrate that integrating green elements significantly reduces thermal heat gain and cooling energy demand. Specifically, a combination of a living wall on a west facing wall and a green roof could reduce the thermal heat gain by up to 30%. Full article

The present study aims to explore the relationship between theory and practice by evaluating the feasibility of quantification and evaluation for assessing the spatial performance and circulation logic in historic domestic architecture to inform adaptive reuse strategies. The study examines several courtyard houses in a representative residential area within Erbil Citadel in the Kurdistan Region of Iraq, an area of immense cultural, architectural, and historical value. The selection of the sample is based on the chronological, typological, and spatial diversity of residential architecture in Erbil Citadel. The study uses an integrated methodological approach to investigate the spatial configuration of each sample building. To ensure increased analytical rigor and to compare its findings with similar studies in different contexts, the results are further validated using Euclidean distance and Pearson correlation to assess the compatibility of existing characteristics with proposed adaptive reuse strategies across different contexts. The results show that quantitative spatial analysis can be an effective tool in identifying the potential of existing residential architecture in terms of its spatial configuration while preserving its cultural value. The study concludes that its proposed approach can serve as an effective model for adaptive reuse planning in similar contexts. Full article

In this work, a novel entropy-weighted fuzzy c-means variation, referred to as Group-based Entropy Weighted Fuzzy C-Means (GEWFCM), is proposed. This variation introduces a semantic level of partitioning of features into groups. This approach enables the provision of optimal semantic meaning to the clusters, thereby capturing the intrinsic structure of the features, which are naturally grouped into homogeneous semantic sets; the weights are independent of the clusters. The cluster weights provide a direct measure of the importance of each group, determining which dimensions of the phenomenon are relevant, and the intragroup weights determine the most relevant features within a group. Additionally, GEWFCM is computationally more efficient than other cluster-specific weighted fuzzy clustering algorithms, due to the independence of the weights from the clusters. The efficacy of the method was assessed by evaluating census data from 16 Italian cities, with the objective of partitioning urban settlements based on characteristics of residential buildings, including construction technique, period, number of floors, and state of conservation. The findings suggest that the proposed algorithm effectively captures the semantic meaning of clusters. In addition, a comparative analysis between GEWFCM and the well-known Entropy Weighted Fuzzy C-Means (EWFCM) algorithm showed that, although both algorithms provide high similarity of results for all case studies, GEWFCM is significantly faster. Full article

Urban renewal in China increasingly focuses on extensive residential historic areas embedded within cities. Recent practice emphasizes refined and progressive renewal strategies, which require multi-dimensional evaluations of micro-scale spatial elements and the formulation of differentiated renewal pathways. The progressive renewal also requires repeated evaluation and adjustment. However, conventional evaluation and decision-making largely rely on manual judgment, which can be subjective and inefficient when dealing with complex information. To address these limitations, this study proposes a digital methodological workflow integrating multi-objective analysis with design decision-making. The workflow targets spatial design issues at three hierarchical levels—streets, plots, and buildings—and is implemented through a multi-module platform. The platform consists of an analytical evaluation module and a design decision module. The analytical module provides quantitative assessments across morphological and non-morphological dimensions, while the design decision module combines analytical results with expected parameters to generate optimization suggestions for spatial structures and identify renewal pathways for spatial elements. Tested in the conservation and renewal planning of Hehuatang in Nanjing, the platform demonstrates the ability to efficiently compare spatial structure schemes and rapidly determine renewal pathways, improving the scientific rigor and efficiency of renewal planning. Full article

Despite the operational phase being the most cost-intensive in a building’s lifecycle, Facility Management (FM) resource optimization continues to face challenges due to fragmented and low-structured data. Building Information Modeling (BIM) offers a centralized data environment, but interoperability gaps persist between design-oriented BIM models and operational Computerized Maintenance Management Systems (CMMSs). This paper presents a scalable, standards-based methodology for BIM-CMMS integration based on the extension of Industry Foundation Classes (IFCs) and the enrichment of FM data. The proposed Python-based application leverages the open-source IfcOpenShell library to inject custom, FM-specific Property Sets (Psets), including asset condition, criticality, and maintenance schedules, directly into IFC entities. The approach transforms standard IFC files into data-rich Asset Information Models (AIMs) without relying on proprietary middleware. The methodology was validated through two residential building case studies. IFC models were successfully checked through the buildingSMART validation service, providing full interoperability across multiple IFC-compatible platforms. Integration with OpenMAINT automatically generates a complete asset database, minimizing manual data entry and reducing inconsistencies. The results confirm the feasibility of a repeatable open-standard workflow. The future development is the definition of a functional/cognitive DT, with the scope of improving the lifecycle BIM model quality and enhancing the efficiency of facility operations. Full article