Search Results (22)

Climate change adaptation in buildings is an expanding field, yet methodological approaches remain diverse and fragmented, with no widely adopted unified assessment framework. This study aims to identify and synthesize existing methods and frameworks used to assess climate change adaptation in buildings. A scoping review was conducted to map key concepts, methodological trends, and knowledge gaps in the literature. Following database screening and study selection, 50 articles published between 2010 and 2026 (including one online-first paper with a nominal publication year 2026) were analysed according to assessment methods, frameworks, hazards, building typologies, life-cycle stages, and climate zones. The findings indicate a strong reliance on simulation-based and indicator-based approaches. Heatwaves are the most frequently examined hazard, while thermal comfort is the most commonly assessed adaptation-related outcome; comprehensive multi-hazard assessments remain relatively scarce. Established sustainability certification schemes and technical standards are often adapted for this purpose, whereas dedicated climate adaptation assessment frameworks remain limited. Overall, the field is characterized by considerable methodological fragmentation, highlighting the need for integrated multi-criteria evaluation frameworks that better connect building-scale technical assessment with broader climate policy objectives. Full article

The housing crisis in rapidly transforming earthquake zones represents the exhaustion of conventional construction paradigms. Unlike single-focused analyses, this study compares conventional reinforced concrete and modular steel systems from a holistic lifecycle perspective, using Turkey as a strategic laboratory for urban transformation. Employing qualitative content analysis, it maps in-depth interviews with 14 sector experts onto a ‘Dialectical Life Cycle Matrix’ via frequency-based consensus indicators. Expert assessments indicate that conventional methods face a structural bottleneck driven by architectural uniformity, labour-related weaknesses, rising costs, and prolonged durations, triggering seismic vulnerability, compromised living quality, and non-circular end-of-life outcomes. Modular systems counter this through factory-controlled rapid production, QA/QC mechanisms, and economies of scale, integrating guaranteed safety and the robust option of steel with R&D-driven human comfort. However, transitioning requires relinquishing deep-rooted advantages—financial flexibility, established order, regulatory comfort, cultural perception, and morphological harmony—introducing local trade-offs: high initial investment, geometric plot and logistical constraints, cultural barriers, and design concerns. Consequently, universal technologies cannot be directly transferred. To overcome Turkey’s local barriers, this study proposes a three-stage transition model: (I) civil and public-led legislative and workforce reforms; (II) financial innovation and gradual hybrid adaptation; and (III) industrial maturation transforming housing into a continuously updated living product. Full article

Traditional passive hydraulic dampers face the challenges of extended design cycles, inefficient parameter matching, and fixed performance, limiting their adaptability. This paper proposes an integrated solution that combines inverse parametric design with active, continuously adjustable damping. First, a high-fidelity nonlinear model is developed based on valve plate elasticity and multi-valve coupling dynamics, achieving a simulation error of ≤4%. An improved genetic algorithm is then designed to inversely optimize five key parameters. This optimization reduces the deviation between the prototype’s damping force–velocity characteristics and the target curve to ≤3% and shortens the design cycle by approximately 40%. Building on this foundation, a pilot-operated electro-hydraulic proportional relief valve is integrated to enable continuous damping adjustment. Co-simulation using AMESim2404 and MatlabSimulinkR2022 reveals the influence of solenoid valve parameters on damping characteristics and calibrates the current–damping force mapping. A co-simulation of a skyhook-controlled quarter-vehicle model demonstrates that the semi-active suspension system reduces the root mean square (RMS) of vertical body acceleration by 21.7%, indicating a significant theoretical improvement in ride comfort. This study establishes a complete technical pathway of “modeling → inverse optimization → integration → verification,” providing an efficient and viable core component solution for intelligent suspension systems. Full article

Rapid urbanisation and rising thermal comfort expectations are propelling global energy demand for space cooling and heating in buildings, cementing vapour compression air conditioning as the dominant technology due to its proven simplicity and efficiency. However, conventional mechanical configurations remain constrained by intrinsic thermodynamic irreversibilities and by international protocols mandating the phase-out of high global warming potential refrigerants. While a growing body of research proposes performance-enhancement measures, these advances remain fragmented across technologies and application contexts. This paper critically reviews recent vapour compression cycle developments, structuring the literature around five interrelated thematic pathways: refrigerant-centric strategies, thermodynamic cycle modifications, hybrid system integration, heat exchanger innovations, and control-centric optimisations. The analysis reveals that no single technology can universally optimise vapour compression cycle performance; instead, effective system improvements emerge from context-specific combinations of refrigerant innovation, heat-transfer enhancement, cycle modification, and hybridisation, with the most successful strategies closely aligned to required temperature lifts and regional climatic conditions. This review introduces a simplified constraint–strategy–technology framework in which dominant system constraints (regulatory and proprietary, thermodynamic and climatic conditions, and demand-related) are first identified. Then corresponding technological improvement strategies (cycle modification, hybridisation, material selection, and control optimisation) are mapped out while enabling technologies are evaluated for suitability, scalability, and maturity. Therefore, this framework provides a system-level synthesis that links performance gains to context-specific operating constraints. Full article

Reducing noise in electric multiple-unit (EMU) gearboxes demands prediction tools that are both rapid and reliable. Gear sound pressure levels vary sharply with micrometre-scale changes such as tooth repair, inclination, or profile relief, yet traditional estimates depend on hours-long CAE simulations. We present a data-driven hybrid surrogate that combines k-means clustering and inverse distance weighting (CLS-IDW) within the ODYSSEE A-Eye platform to map geometry modifications directly to broadband noise. Trained on the open 200-case Romax dataset, the model returns predictions within milliseconds and reproduces unseen operating points, with R² = 0.75 and a mean absolute error of 2.33 dB, matching solver repeatability. Sensitivity analysis identifies a −7° tooth inclination coupled with a 10 µm repair depth as the most effective combination, lowering noise by 3–5 dB. Eliminating costly CAE loops, the surrogate supports acoustics-aware optimisation at the concept stage, compressing development cycles and enhancing passenger comfort while maintaining transparency for regulatory review. Full article

Active transport (AT) offers an effective and sustainable strategy to address physical inactivity, reduce traffic congestion, and mitigate environmental challenges. However, participation in AT among young adults (YA) aged 18–25 remains low, leading to public health issues. This review synthesises evidence on how traffic stress (TS), built environment (BE) features, and socioecological factors interact to shape AT behaviour among YA, a relationship that remains insufficiently understood. We systematically reviewed 173 peer-reviewed studies (2015–2025) from Web of Science (WoS), PubMed, and Scopus, following the PRISMA 2020 guidelines. Thematic analysis, bibliometric mapping, and meta-synthesis informed the impact of TS, the Level of Traffic Stress (LTS), the 5Ds of BE, and the Socioecological Model (SEM) on AT among YA. The findings show that high TS, characterised by unsafe road conditions, high-speed motor traffic, and inadequate walking or cycling facilities, consistently reduces AT participation. In contrast, supportive BE features, including street connectivity, land-use diversity, and destination accessibility, increase AT by reducing TS while enhancing safety and comfort. Socioecological factors, including self-efficacy, social norms, and peer support, further mediate these effects. This review introduces two novel metrics: Daily Traffic Stress (DTS), a time-sensitive measure of cumulative daily TS exposure, and the Stress-to-Step Ratio (SSR), a step-based index that standardises how stress exposures translate into AT behaviour. By integrating environmental and psychosocial domains, it offers a theoretical contribution as well as a practical foundation for targeted, multilevel policies to increase AT among YA and foster healthier, more equitable urban mobility. Full article

Cycling-induced vibration significantly affects riding comfort, with road surface conditions and vehicle type identified as primary contributing factors. This study developed a vibration measurement system based on ISO 2631-1, and proposed a method for generating cycling comfort maps grounded in vibration severity levels. Field measurements on 30 campus roads in Nanchang, China, used a Mountain Bike, Shared E-bike, and Shared Bicycle. Triaxial acceleration data were collected to evaluate vibration exposure, and comfort levels were classified to produce spatially resolved maps. Results show the proposed system has strong stability and adaptability across urban environments. The maps effectively captured vibration intensity variations along road segments. Among the three vehicle types, Mountain Bikes showed the lowest vibration exposure, with approximately 90% of segments rated as comfortable. Shared E-bike exhibited moderate vibration levels, with 42% of segments deemed uncomfortable, while Shared Bicycles experienced the highest vibration, with 80% of routes potentially inducing discomfort and only 1% meeting comfort standards. This study offers a framework for objective acquisition and visualization of cycling vibration data. The developed system and mapping method provide tools for assessing vehicle vibration, guiding route selection, and offer potential value for road quality monitoring. Full article

With rapid urbanization and increasing emphasis on sustainable mobility, slow-moving traffic systems, including pedestrian and cycling infrastructure, have become critical to urban transportation and quality of life. Conventional assessment methods are labor-intensive, time-consuming, and limited in coverage. Leveraging advances in deep learning and computer vision, this study develops a framework for bottleneck detection using street-level imagery and the You Only Look Once version 5 (YOLOv5) model. An evaluation system comprising 15 indicators across continuity, safety, and comfort is established. In a case study of Wuhan’s Third Ring Road, the YOLOv5 model achieved 98.9% mean Average Precision (mAP)@0.5, while spatial hotspot analysis (p < 0.05) identified severe demand–infrastructure mismatches in southeastern Wuhan, contrasted with fewer problems in the northern region due to stronger management. To ensure adaptability, a dynamic optimization mechanism integrating temporal imagery updates, transfer learning, and collaborative training is proposed. The findings demonstrate the effectiveness of street-level remote sensing for large-scale urban diagnostics, extend the application of deep learning in mobility research, and provide practical insights for data-driven planning and governance of slow-moving traffic systems in high-density cities. Full article

Background: Scientific research on fly-in/fly-out (FIFO) workers has identified a gap in understanding the dynamics of job stress parameters among forest workers throughout the shift cycle. Methods: This study investigated the relationship between psychological and psychophysiological parameters of job stress and work capacity among loggers. The research was conducted during two simultaneous scientific expeditions in July 2024, involving 47 loggers from two teams with differing socio-psychological characteristics. Data were collected daily (morning and evening) using a battery of psychophysiological and psychological tests. Teams’ socio-psychological characteristics were assessed five times during the 15-day fly-in period. Results: The adaptation (beginning) and fatigue (end) phases of the shift were significantly more stressful than the middle period. During these critical phases, assessments of functional state showed greater consistency but were less favorable. Key findings indicate a psychological mobilization effect at the period’s start, where high subjective comfort coexisted with physiological strain. By the end, functional capabilities were maintained despite high fatigue. Furthermore, loggers in teams with a positive socio-psychological climate exhibited a more favorable functional state throughout the shift. Conclusions: The study’s novelty lies in its comprehensive mapping of the dynamic interplay between job stress and work capacity across the FIFO cycle, using both instrumental and questionnaire-based methods. The results underscore the critical influence of the team’s socio-psychological climate on worker well-being and highlight specific high-stress phases that warrant targeted interventions. Full article

The transition toward sustainability in the construction industry requires integrated tools that align with circular economy principles. This study introduces the Interactive Stakeholder Journey Map in Construction (ISJMC), an innovative visual and systemic tool that supports waste management and circularity throughout the life cycle of construction assets. Although the sector is economically significant, it remains one of the main contributors to environmental degradation due to high resource consumption and low waste recovery rates. Developed according to EN 15643-3:2012, a European standard that provides a framework for assessing the social sustainability of construction works, focusing on aspects such as accessibility, health, and comfort and grounded in the Design Thinking methodology, ISJMC enables mapping stakeholder interactions, touchpoints, and responsibilities across all life cycle stages, including initiative, design, procurement, construction, use, and end of life. A systematic literature review and collaborative workshops guided the tool’s development and validation. The application in a real case involving a medium-sized Brazilian construction company helped identify significant pain points and opportunities for implementing circular practices. The results demonstrate that ISJMC (i) facilitates a systemic and visual understanding of material and information flows, (ii) promotes transparent mapping of resource value to support better decision-making, and (iii) encourages the identification of circularity opportunities while fostering collaboration among stakeholders. The tool revealed critical challenges related to waste generation and management. It supported co-creating sustainable strategies, including improved material selection, lean construction practices, and stronger supplier engagement. By translating complex standards into accessible visual formats, ISJMC contributes to the academic field, supports practical applications, and offers a foundation for expanding circular approaches in construction projects. Full article

This study investigates whether electromyography (EMG) analysis can reflect ergonomic improvements for commuter bike users by assessing muscle activity differences between comfort- and performance-oriented saddle positions. A cohort of 30 city bike riders underwent a comprehensive fitting procedure, where one position was individually established based on a comfort perception questionnaire and adjusted by a bike fitter. The aim was to compare the EMG activity of muscles involved in propulsion and lumbar spine stabilisation across different positions. The Statistical Parametric Mapping (SPM) method was also used to analyse muscle activity throughout the pedalling cycle. The results revealed that the customised position significantly reduced EMG activity in muscles, particularly during key pedalling phases, significantly improving rider comfort and muscle efficiency. SPM analysis highlighted decreased strain in the vastus lateralis and tibialis anterior, indicating improved muscular efficiency and enhanced comfort for urban cyclists. This underscores the importance of personalised bike fitting in promoting comfort and reducing the risk of injury, suggesting that EMG analysis is a valuable tool in both clinical and recreational bike-fitting practices. Future research should explore the long-term effects and potential applications of the proposed fitting method for other bicycle geometries whenever comfort and lower back stability are priorities. Full article

The development of information technologies has been exponentially applied to the architecture, engineering, and construction (AEC) industries. The extent of the literature reveals that the two most pertinent technologies are building information modeling (BIM) and artificial intelligence (AI) technologies. The radical digitization of the AEC industry, enabled by BIM and AI, has contributed to the emergence of “smart cities”, which uses information technology to improve urban operational and sustainable efficiency. Few studies have investigated the roles of AI and BIM in AEC from the perspective of sustainable buildings in assisting designers to make sustainable decisions at building and city levels. Therefore, the purpose of this paper is to explore the research status and future development trends in the relationship between AI and BIM-aided sustainable building in the context of the smart city to provide researchers, designers, and technology developers with potential research directions. This paper adopted a macro and micro bibliographic method, which is used to map out the general research landscape. This is followed by a more in-depth analysis of the fields of sustainable design, sustainable construction, sustainable development, and life cycle assessment (LCA). The results show that the combination of AI and BIM helps to make optimal decisions on materials, cost, energy, construction scheduling, and monitoring and promotes the development of sustainable buildings in both technical and human aspects so to achieve Sustainable Development Goals 7 (ensuring access to affordable, reliable, and sustainable modern energy for all), 9 (building resilient infrastructure, promote inclusive and sustainable industries, and foster innovation), 11 (building inclusive, safe, risk-resilient, and sustainable cities and human settlements), and 12 (ensuring sustainable consumption and production patterns). In addition, the combination of AI, BIM, and LCA technologies offers great potential to improve building performance, and the future development of AI and BIM integration should not only consider the sustainability of buildings but also consider the human-centered design concept and the health, safety, and comfort of stakeholders as one of the goals to realize the multidimensional development of smart city based on city information model. Full article

The further promotion of cycling is a key component for each city to reach its sustainability goals. To make decisions to improve comfort or safety for cyclists, the amount of motorized traffic should be taken into account. Therefore, traffic data play a crucial role not only in the construction of roads but also in cycling planning. This data source provides insights essential for road infrastructure development and optimizing various modes of transportation, such as bike paths. However, processing municipal traffic data becomes a challenge when stationary traffic-counting stations lack geo-referencing in relational databases. In this case, the locations of traffic counters are solely displayed on a PDF-based site map without inherent geo-referencing, and the geo-coordinates are not stored in any relational database. The absence of geo-references poses a significant hurdle for traffic-planning experts in decision-making processes. Hence, this study aims to address this issue by finding a suitable approach to extract the geo-coordinates from the site maps. Several potential solutions are discussed and compared in terms of time dimension, usability, extensibility, error treatment and the accuracy of results. Leveraging the open-source tool QGIS, geo-coordinates may be successfully extracted from the PDF-based site maps, resulting in the creation of a GeoTIFF file incorporating coordinates and the rotated site map. Geo-coordinates can then be derived from the GeoTIFF files using x and y coordinates, computed through the rotation matrix formula. Over 1400 measurement locations may be extracted based on the preferred approach, facilitating more informed decision-making in traffic planning. Full article

This paper presents a warning that there is a need for better consideration of microclimatology in urban planning, particularly when addressing microclimate-related human comfort in designing outdoor public spaces. This paper develops a protocol for microclimate-related street assessment, considering simultaneous dynamic environmental components data gathering and better understanding of microclimatic conditions when commuting by bicycle. The development of new information and communication technologies (ICTs) has the potential for overcoming the gap between microclimatology and urban planning, since ICT tools can produce a variety of soft data related to environmental quality and microclimate conditions in outdoor spaces. Further, the interpretation of data in terms of their applicability values for urban planning needs to be well addressed. Accordingly, this paper tests one particular ICT tool, a prototype developed for microclimate data collection along cycling paths. Data collection was performed in two European cities: Bilbao (Spain) and Ljubljana (Slovenia), where the main objective was the development of a protocol for microclimate-related street assessment and exploration of the potential of the collected data for urban planning. The results suggest that the collected data enabled sufficient interpretation of detailed environmental data and led to a better consideration of microclimatology and the urban planning of cycling lanes. The paper contributes to urban planning by presenting a protocol and providing fine-grained localised data with precise spatial and temporal resolutions. The data collected are interpreted through human comfort parameters and can be linked with rates/levels of comfort. As the collected data are geopositioned, they can be presented on a map and provide links between environmental conditions within a spatial context. Full article

The development of more sustainable urban transportation is prompting the need for better energy management techniques. Connected electric vehicles can take advantage of environmental information regarding the status of traffic lights. In this context, eco-approach and departure methods have been proposed in the literature. Integrating these methods with regenerative braking allows for safe, power-efficient navigation through intersections and crossroad layouts. This paper proposes rule- and fuzzy inference system-based strategies for a coupled eco-approach and departure regenerative braking system. This analysis is carried out through a numerical simulator based on a three-degree-of-freedom connected electric vehicle model. The powertrain is represented by a realistic power loss map in motoring and regenerative quadrants. The simulations aim to compare both longitudinal navigation strategies by means of relevant metrics: power, efficiency, comfort, and usage duty cycle in motor and generator modes. Numerical results show that the vehicle is able to yield safe navigation while focusing on energy regeneration through different navigation conditions. Full article