Search Results (152)

Reusing existing buildings is a valid response to the architectural challenge associated with addressing climate change and can aid the regeneration of the historic built environment. This demands sensitive architectural conservation strategies that improve thermal comfort, indoor environmental quality, and energy efficiency. In addition, energy retrofit solutions that balance performance improvements with the conservation of cultural and architectural values are needed to achieve higher performance while preserving cultural heritage, architectural features, and identity. Energy retrofits of post-war, mid-20th-century buildings pose particular challenges, including low ceiling heights, full-height windows, external decorative components, and other structural aspects, as these features hinder thermal upgrades. Concrete buildings from this period are frequently demolished due to limited guidance on effective retrofit methods. This study explores the most effective energy retrofit strategies for balancing energy efficiency with conservation requirements in such buildings, and assesses the risks associated with condensation and thermal bridging arising from internal insulation strategies. This paper examines internal insulation as a retrofit solution, where external insulation is not feasible. Internal wall insulation (IWI) reduces overall heat loss but concentrates thermal transfer at uninsulated junctions, thereby increasing the risk of condensation. In the simulated case, a relatively thin, short strip of slab insulation, combined with wall insulation, significantly reduced condensation and mould risk, suggesting a potential solution for mid-century building types. The analysis shows that applying insulation asymmetrically worsens conditions on the uninsulated side. Full-height window replacement, coupled with internal slab insulation, results in the most significant improvement; however, slab insulation alone can mitigate condensation risks where window replacement is not permitted. Findings highlight that partial insulation at balconies, parapets, and roof junctions is minimally effective, reinforcing the importance of integrated internal strategies for successful retrofits. Full article

Urban recreational spaces (URSs) are pivotal for enhancing resident well-being, making the accurate assessment of public perceptions crucial for quality optimization. Compared to traditional surveys, social media data provide a scalable means for multi-dimensional perception assessment. However, existing studies predominantly rely on single-modal data, which limits the comprehensive capturing of complex perceptions and lacks interpretability. To address these gaps, this study employs cutting-edge large vision–language models (LVLMs) and develops an interpretable model, Qwen2.5-VL-7B-SFT, through supervised fine-tuning on a manually annotated dataset. The model integrates visual-linguistic features to assess four perceptual dimensions of URSs: esthetics, attractiveness, cultural significance, and restorativeness. Crucially, we generate textual evidence for our judgments by identifying the key spatial elements and emotional characteristics associated with specific perceptions. By integrating multi-source built environment data with Optuna-optimized machine learning and SHAP analysis, we further decipher the nonlinear relationships between built environment variables and perceptual outcomes. The results are as follows: (1) Interpretable LVLMs are highly effective for urban spatial perception research. (2) URSs within Beijing’s Third Ring Road fall into four typologies, historical heritage, commercial entertainment, ecological-natural, and cultural spaces, with significant correlations observed between physical elements and emotional responses. (3) Historical heritage accessibility and POI density are identified as key predictors of public perception. Positive perception significantly improves when a block’s POI functional density exceeds 4000 units/km² or when its 500 m radius encompasses more than four historical heritage sites. Our methodology enables precise quantification of multidimensional URS perceptions, links built environment elements to perceptual mechanisms, and provides actionable insights for urban planning. Full article

Cultural heritage museums, as integral components of the urban built environment and public cultural space, not only preserve historical memory but also subtly shape visitors’ psychological experiences and well-being. Yet the mechanisms linking museum environmental quality with visitor mental experiences remain insufficiently explored. Drawing on 10,684 visitor reviews collected from Dianping, Weibo, and Ctrip, this study applies text mining and semantic analysis to construct an evaluation framework of visitor behavioral preferences and psychological experiences in heritage museums. The findings show that attention to spatial remains, historical artifacts, and cultural symbols is closely associated with positive emotions such as mystery, awe, and beauty, while adverse environmental conditions such as queuing and crowding often trigger negative feelings including fatigue, disappointment, and boredom. Further analysis reveals a clear pathway linking objects, behaviors, and experiences: spatial remains evoke psychological resonance through immersive perceptions of authenticity; artifacts are primarily linked to visual pleasure and emotional comfort; and cultural symbols are transformed into cognitive gains and spiritual meaning through interpretation and learning. Cross-regional comparison highlights significant differences among museums with distinct cultural backgrounds in terms of architectural aesthetics, educational value, and emotional resonance. This study not only offers a practical framework for the refined management and spatial optimization of heritage museums, but also demonstrates that high-quality cultural environments can promote mental health and emotional restoration. The results extend the interdisciplinary framework of museum research and provide empirical evidence for environmental improvement and public health promotion in cultural heritage spaces in the digital era. Full article

Sustainable management of built heritage is a complex process made more difficult by the need to maintain significance and comply with any associated protections. Historic Building Information Modelling (HBIM), an information management and modelling process, has the potential to assist with this. This paper investigates how a pre-existing Historic Building Information Modelling (HBIM) model can be used to assist the energy-efficient interventions at the historic Rowheath Pavilion in Bournville, England. Two potential methods (HBIM and building energy modelling integration and HBIM and thermal image integration) are evaluated against their outputs and the available resources. Subsequently, the paper presents a case study wherein a thermal image survey was undertaken at Rowheath Pavilion and the resulting images were integrated with the pre-existing HBIM model. The apparent thermal performance of the pavilion was qualitatively evaluated. The described method was easy to apply and repeat. The integration of thermal images combined with the visualisation capabilities of HBIM resulted in the identification of energy inefficiencies and allowed the Rowheath staff to implement immediate small-scale changes to improve the sustainability of the pavilion. Full article

The Seaport City of Valparaíso, Chile, declared a World Heritage Site (WHS) by the United Nations, is known for its built landscape shaped during the first phase of globalization in the late 19th century, including early transport systems. However, the city now faces growing 21st-century urban and transport challenges common in Latin America. Amid the rise of electric micromobility in Chile, this study explores the potential use of electric bicycles (E-Bikes) in Valparaíso’s historic quarter. A qualitative methodology was employed, including participatory mapping to identify strengths, weaknesses, opportunities, and threats (SWOT), and focus group discussions supported by AI-based text analysis. Findings reveal that barriers to E-Bike use extend beyond topography and infrastructure, highlighting concerns such as deteriorated public spaces, lack of green areas, and safety issues. Promoting E-Bike adoption will require improving infrastructure, launching educational campaigns, optimizing routes, and fostering community participation. This study aims to inform local decision-makers on how to enhance sustainable mobility by integrating E-Bikes into the historical electric transport of Valparaíso, thereby contributing to the modernization of mobility within a heritage context. Full article

Gulf cities have embarked on ambitious public transport infrastructure initiatives in recent decades to foster more livable and sustainable cities. This investigation explores the interpretations and implementation of Transit-Oriented Development (TOD) principles in two prototypical urban districts: Doha’s West Bay, Qatar, and Riyadh’s King Abdullah Financial District (KAFD), Saudi Arabia. By following a comparative case study approach, the study explores how retrofitted (West Bay) and purpose-built (KAFD) TOD configurations fare regarding land use mix, density, connectivity, transit access, and environmental responsiveness. The comparative methodology was selected to specifically capture the spatial, climatic, and socio-economic complexities of TOD implementation in hyper-arid urban environments. Based on qualitative evidence from stakeholder interviews, spatial assessments, and geospatial indicators—such as metro access buffers, building shape compactness, and TOD proximity classification—the investigation reflects both common challenges and localized adaptations in hot-desert Urbanism. It emerges that, while benefiting from integrated planning and multimodal connectivity, KAFD’s pedestrian realm is delimited by climatic constraints and inactive active transport networks. West Bay, on the other hand, features fragmented public spaces and low TOD cohesion because of automotive planning heritages. However, it holds potential for retrofit through infill development and tactical Urbanism. The results provide transferable insights that can inform TOD strategies in other Gulf and international contexts facing similar sustainability and mobility challenges. By finalizing strategic recommendations for urban livability improvement through context-adaptive TOD approaches in Gulf cities, the study contributes to the wider discussion of sustainable Urbanism in rapidly changing environments and supplies a reproducible assessment frame for future TOD planning. This study contributes new knowledge by advancing a context-adaptive TOD framework tailored to the unique conditions of hyper-arid Gulf cities. Full article

The historic mortuary at Zagreb’s Mirogoj Cemetery, built in 1886, sustained moderate damage during the 2020 Mw 5.3 earthquake. Aiming to preserve heritage value while meeting Croatia’s Level 4 seismic safety requirements, the structure was assessed using in situ and laboratory tests followed by macro-element modeling with 3Muri software. The study evaluated four scenarios: (A) post-earthquake damaged state, (B) reinforcement with new masonry and RC walls, (C) partial fiber-reinforced cementitious matrix (FRCM) plastering, and (D) systematic FRCM plastering. Results show that Case B improved Ultimate Limit State (ULS) scaling factors from 0.64/0.56 to 0.92/0.90 (X/Y), while Case D raised them to 1.03/1.17, satisfying Eurocode 8 and national renovation criteria. Systematic FRCM application improved story shear capacity by up to 57% and shifted failure modes from brittle shear to ductile rocking. Partial plastering proved insufficient, highlighting the need for comprehensive global retrofitting. While the solution is minimally invasive and reversible, uncertainties remain regarding long-term durability and out-of-plane performance. This hybrid retrofitting strategy offers a replicable model for heritage masonry buildings in seismically active regions. Full article

Built environment elements management involving heritage buildings requires a nuanced approach that balances cultural preservation, planning efficiency, and resource optimization. Conventional evaluation methods frequently neglect public perception, leading to misaligned priorities and ineffective heritage resource deployment. To address this gap, this study proposes a Sandglass Tiered Model that integrates public perception into the value assessment process of culturally significant buildings. By integrating multi-source perception data and cultural ontology through a structured, tiered data collection mechanism, the model translates subjective views into four quantifiable indices: symbolizability, authenticity, readability, and regionality. These indices form the basis of an AHP-GRA–driven assessment framework, facilitating value-based prioritization and spatial zoning of heritage elements within construction projects. The model was empirically validated in the Yiling Cultural Heritage Area, where it effectively facilitated differentiated building strategies, optimized resource sequencing, and improved alignment between project goals and stakeholder expectations. Importantly, the model provides a transferable framework that embeds cultural awareness into the lifecycle of heritage building projects—from pre-design evaluation to renovation and adaptive reuse. By integrating public perception into construction workflows, this approach provides a dynamic and participatory framework for managing complex heritage assets within urban development contexts. It improves the precision, responsiveness, and cultural sensitivity of construction planning, offering practical insights for policymakers, architects, and construction managers working in resource-intensive or culturally rich environments. Full article

The built environment requires retrofitting on a massive scale to both mitigate the impacts of climate change and adapt to future conditions. Buildings of high thermal mass offer useful insights into the limits of passive measures in futureproofing against overheating. Historic buildings typically have a higher thermal mass and also offer a paragon case to study improvement options that do not compromise heritage or character. This paper focuses on the Tower of London as a case study. Data from pre- and post-COVID-19 allows insights into the building performance in the absence of end users. A thermal model is calibrated to accurately represent both the physics of the building and the impacts of its occupants in use. Future weather files then test the extent to which the building’s thermal mass can mitigate against overheating under a range of climate warming scenarios. The results suggest that prolonged heat waves pose a serious risk to passive mitigation strategies as the mass of the building stores heat it cannot shed overnight. These scenarios also reduce the heating demand in winter. The results suggest that the built environment faces subtle design challenges in understanding the limits for passive design techniques versus the need for cooling in a warming climate. For the Tower in particular, a significant increase in overheating is likely in the coming decades. Full article

This study presents the diagnostics and microclimate analysis of four case studies located in the Alps region in Valtellina and Valposchiavo. The primary focus is on evaluating and comparing microclimatic conditions, encompassing temperature (T°C), relative humidity (RH%), mixing ratio (MR), and dew point depression (DPD). The choice of the variables and statistic metrics depends substantially on the aim to identify the risk factor for the preservation of the historical materials of historical buildings, and the procedures for identifying the anomalies in the trends useful to study how to prevent these anomalies in the future. The paper has the target to support the activities of restorers and building managers for improving the restoration process. While various moisture detection methodologies have been studied, no single approach is preferred for analyzing moisture via microclimate monitoring in built heritage. Therefore, this research delves into the influence of various factors, including altitude, location, building type, structure, materials, orientation, and use, on the microclimatic parameters. Altitude and building use significantly influence indoor microclimates: unoccupied structures exhibit greater stability, whereas seasonal use increases condensation risks. Key risks included high RH% and critical T-RH zones (T > 25 °C + RH > 65%), exacerbating material stress. Probability density function (PDF) analysis reveals temperature and RH% distributions, highlighting bimodal T°C patterns and prolonged RH% in high-elevation exposed sites. The findings underscore the need for tailored conservation strategies and targeted interventions to mitigate microclimate-induced deterioration in Alpine heritage. Full article

The Adriatic–Ionian region is seismically very active and poses a major challenge for risk mitigation. Each country has developed laws, standards, and techniques to reduce seismic vulnerability. The ADRISEISMIC project created a database of existing regulatory and incentive frameworks, based on a comprehensive study conducted in six countries. The study covered seismic norms, building regulations, urban planning regulations, incentive frameworks, and post-earthquake planning. A comparative matrix was developed in which key parameters, such as year of issuance, references to EU regulations, level of enforcement, mandatory status, target groups, reference period in relation to earthquake occurrence, and consideration of cultural heritage, were analyzed. The database aims to support a harmonized strategy to reduce seismic vulnerability by promoting measures based on common reference standards. This increases safety, improves the built environment, and minimizes risks to people and nature. Particular attention will be paid to historic urban areas that are both vulnerable and rich in cultural heritage. The collected regulatory and incentive framework will serve as a basis for future research to support the identification of good practices and the formulation of customized roadmaps to apply them to reduce seismic vulnerability. Full article

The lack of cultural spaces and the inadequate preservation of architectural heritage hinder the development of ecotourism in Ollantaytambo. This research aims to propose an architectural design for green infrastructure that supports the growth of ecotourism at the Ollantaytambo archeological site, located in the Urubamba Province, Peru. The study consists of three main phases: a literature review; a site analysis focusing on climate, flora, and fauna; and the development of a comprehensive architectural proposal. The process is supported by digital tools, including Google Earth Pro 2024, OpenStreetMap 2024, SketchUp 2024, Lumion 2024, Photoshop 2024, and 3D Sun-Path 2024. The resulting design includes the implementation of a sustainable cultural center, conceived to ensure seasonal thermal comfort through the use of green roofs and walls, efficient irrigation systems, and native vegetation. The proposal incorporates elements of Cusco’s vernacular architecture by combining traditional earth-based construction techniques, such as rammed earth, adobe, and quincha, with contemporary materials, such as bamboo and timber, in order to improve the energy and environmental performance of the built environment. Furthermore, the project integrates a rainwater-harvesting system and a photovoltaic lighting system. It includes 30 solar-powered luminaires with an estimated monthly output of 72 kWh, and 135 photovoltaic panels capable of generating approximately 2673 kWh per month. In conclusion, the proposed design blends naturally with the local environment and culture. It adheres to principles of sustainability and energy efficiency and aligns with Sustainable Development Goals (SDGs) 3, 6, 7, 11, and 15 by promoting heritage conservation, environmental regeneration, and responsible ecotourism. Full article

This study investigated the nuanced influence of urban morphology on the thermal performance of nine mass housing blocks (21–26, 28–30) in New Belgrade’s Central Zone. These blocks, showcasing diverse structures, provided a robust basis for evaluating the design parameters. ENVI-met simulations were used to assess two scenarios: an “asphalt-only” environment, isolating the urban structure’s impact, and a “real-world” scenario, including green infrastructure (GI). Overall, the findings emphasize that while GI offers mitigation, the inherent urban built structure fundamentally determines thermal outcomes. An urban block’s thermal performance, it turns out, is a complex interplay between morphological factors and local climate. Crucially, simple metrics like Green Area Percentage (GAP) and Building Coverage Ratio (BCR) proved unreliable predictors of thermal performance. This highlights the critical need for urban planning regulations to evolve beyond basic surface indicators and embrace sophisticated, context-sensitive design principles for effective heat mitigation. Optimal performance arises from morphologies that actively manage heat accumulation and facilitate its dissipation, a characteristic exemplified by Block 22’s integrated design. However, even the best-performing Block 22 remains warmer compared to denser central areas, suggesting that urban densification can be a strategy for heat mitigation. Given New Belgrade’s blocks are protected heritage, targeted GI reinforcements remain the only viable approach for improving the outdoor thermal comfort. Full article

Modern heritage (MH) is a key component of our built environment; however, it currently lacks widespread recognition and a clear, universally accepted definition, placing it in an emerging phase. This category of heritage, understood within the context of modernisation processes and the changes characteristic of the late modern period, remains underrepresented and warrants further study. The objective of this article is to fill the identified research gap, thereby fostering awareness of MH, improving its accessibility and enhancing its visibility and appreciation. It offers a diagnostic analysis of the corpus on MH through the design and development of a concrete methodology, which is transferable to the other heritage categories. This study reveals insights into the present understanding of the term ‘Modern Heritage’ and its relevance within an international framework. This understanding prompts a reflection on the terminology used to describe this concept, which serves not only as a significant result in itself but also as a foundation for future research. Despite the close association of modern heritage with the 20th century, this research identifies a cross-cutting nature that needs to be recognised, encompassing a wide range of periods, themes and typologies in this category. Full article

In recent years, automatic segmentation and classification of data from digital surveys have taken a central role in built heritage studies. However, the application of Machine and Deep Learning (ML and DL) techniques for semantic segmentation of point clouds is complex in the context of historic architecture because it is characterized by high geometric and semantic variability. Data quality, subjectivity in manual labeling, and difficulty in defining consistent categories may compromise the effectiveness and reproducibility of the results. This study analyzes the influence of three key factors—annotator specialization, point cloud density, and sensor type—in the supervised classification of architectural elements by applying the Random Forest (RF) algorithm to datasets related to the architectural typology of the Franciscan cloister. The main innovation of the study lies in the development of an advanced feature selection technique, based on multibeam statistical analysis and evaluation of the p-value of each feature with respect to the target classes. The procedure makes it possible to identify the optimal radius for each feature, maximizing separability between classes and reducing semantic ambiguities. The approach, entirely in Python, automates the process of feature extraction, selection, and application, improving semantic consistency and classification accuracy. Full article