Search Results (711)

This study proposes an integrated analytical framework (IAF) as a tool to simultaneously assess vulnerable social groups within their administrative context. This study hypothesizes that analyzing vulnerable groups through socio-spatial delineation reveals subnational disparities and sub-regional heterogeneity in energy poverty (EP) indicators, associated with additional context-sensitive environmental consequences of energy use. Using Hungarian deprived rural settlements (DRSs) (n = 300) as an example, mixed methods were applied to examine national–regional disparities, intra-regional variations, and the environmental implications of extreme household energy use practices. Results show that both socio-economic indicators and building energy efficiency, and energy-use profiles, fall short of national indicator performance. The sample outlined by the IAF performed homogeneously regarding socio-economic circumstances and showed mild differences in housing quality and energy access. These results indicate not structural differences but variation in underlying regional drivers, highlighting the region-specific manifestation of EP. The energy-use-related environmental assessment was performed using a parametrized building-stock model and the two most extreme energy-use scenarios for households relying on solid fuels. The results suggest that the use of substitute fuels substantially increases the combined emissions of CO₂, CO, PM, NOx, and SOx by up to 32 percentage points. Although limitations constrain the reporting of empirically representative results, findings underscore the potential policy relevance of DRSs in national climate objectives. Full article

This article investigates the response of an unprotected three-storey steel moment-resisting frame subjected to a suite of horizontally traveling fire scenarios. A series of multi-step finite-element simulations was conducted to analyze the impact of traveling fires on both the global and local responses of a low-rise building frame. The research considers a range of fire types, both uniform and spatially varying, as well as different locations, and sizes to capture a diverse array of fire scenarios. Non-uniform compartment fires are modeled using the improved traveling fire method (iTFM), while uniform fires are simulated using the Eurocode parametric (EC) fire model. Four traveling fire scenarios with floor area coverage ranging from 5% to 48% are examined. The resulting deformation patterns, along with bending moment and axial force distributions in critical beam and column sections within the fire compartments, are thoroughly evaluated. The findings reveal that, within the case study frame and the range of parametric analyses, a uniform compartment fire does not necessarily yield the worst-case scenario commonly assumed in design codes. Instead, global and local structural responses are primarily influenced by traveling fire scenarios. Full article

This study presents HGRN2-based Flexible Dynamic Encoder Personal VAD (FDE-HGRN2), a recurrent framework for personal voice activity detection (PVAD). Building on the original LSTM-based FDE-RNN backbone, we replace all recurrent modules with the recently introduced HGRN2 gated linear RNN and adopt a cosine-annealing learning rate schedule to improve both detection accuracy and efficiency. HGRN2 uses gated linear recurrence with non-parametric state expansion, enlarging the recurrent state without increasing the number of trainable parameters and enabling more expressive long-range temporal modeling than conventional LSTMs. We evaluate FDE-HGRN2 on a LibriSpeech-derived PVAD benchmark, where multi-speaker mixtures are constructed by concatenating one to three speakers per utterance and randomly designating a target speaker, following established PVAD data construction practices to ensure direct comparability with prior work. The system uses 40-dimensional Mel-filterbank features as acoustic inputs and conditions the detector on 256-dimensional d-vector embeddings extracted from a pretrained speaker verification network. Experimental results show that FDE-HGRN2 consistently outperforms the original FDE-RNN baseline and several state-of-the-art PVAD models in terms of mean Average Precision and frame-level accuracy, while reducing the parameter count of the recurrent backbone by roughly 15% and yielding substantially smaller models than many competing systems. These findings indicate that HGRN2 provides a more temporally expressive and parameter-efficient alternative to LSTM for PVAD, offering a favorable accuracy–efficiency trade-off for real-world, deployment-oriented personalized speech interfaces. Full article

Buildings account for nearly 40% of global energy consumption and one-third of greenhouse gas emissions. Exterior walls significantly influence building energy performance and, consequently, Life Cycle Cost (LCC) and Life Cycle Assessment (LCA). However, most previous studies focus on specific case studies and lack generalizability across varying building characteristics. This study proposes an integrated LCC–LCA framework for selecting optimal exterior wall systems for residential buildings in Egypt, incorporating parametric modeling and machine learning to predict energy consumption. The framework considers essential building characteristics, including location, orientation, dimensions, and window properties. Initially, commonly used exterior wall configuration options in Egypt are modeled within a representative residential building and parametrically simulated to generate a comprehensive database of energy consumption. This database is then used to train an artificial neural network (ANN) model to predict the energy performance of alternative wall systems. Based on the predicted energy demand, LCC and LCA indicators are calculated. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to identify the optimal wall option. The proposed framework is validated using case study buildings. The findings demonstrate that the proposed model provides a reliable and robust approach for exterior wall selection in residential buildings. Full article

The construction sector contributes to global CO₂ emissions and resource consumption, highlighting the need for sustainable design strategies. In this context, building envelope performance plays a key role, supported by digital technologies. This study proposes an automated BIM-MCDM workflow to select the optimal wall stratigraphy with Aerogel, EPS, and Rock Wool thermal insulation layers. The evaluation indicators are organized into three thematic clusters: Thermal Performance (TPI), Environmental Sustainability (ESI), and Economic Indicators (EI). Insulation alternatives and indicators are modeled in Autodesk Revit, enabling parametric variation in insulation layers and generating multiple stratigraphic configurations. Performance indicators are automatically calculated through a BIM-VPL integration using Dynamo, Microsoft Excel, and Tally. Fully interoperable parametric scripts enable data extraction from the BIM model, regulatory compliance verification, and the transfer of results back to the BIM model. Finally, indicator values are weighted and evaluated using an MCDM analysis based on the AHP method, fully implemented in Dynamo. The results indicate that EPS ranks first due to its strong performance in TPI and ESI, followed by Aerogel, influenced by EI, and Rock Wool, which shows a lower contribution to ESI. This research contributes to data-driven decision-making and the digitalization of sustainability-oriented performance assessment for building envelopes. Full article

As the most prevalent type of existing building in China, masonry structures are susceptible to cracking due to the low tensile strength of the masonry material. In the event of a sudden, strong earthquake, they are highly prone to brittle collapse, leaving occupants little time and space to escape. Based on this, combining the advantages of the elastoplastic mechanical theory and the nonlinear finite element (FE) method, this study adopts different modeling methods: integral modeling (IM), contact element discrete modeling (CEDM), spring element discrete modeling (SEDM), and co-node discrete modeling (CNDM). FE models of unreinforced masonry walls (UMWs) are established, respectively, and a monotonic pushover mechanical performance analysis is carried out. The accuracy of the adopted modeling methods is verified against existing test results for UMW specimens. Through parametric analysis of aspect ratios (0.5, 0.75, 1.0, and 1.25), axial compression ratios (0.1, 0.3, 0.5, 0.7, and 0.8), and mortar strengths (M5, M7.5, and M10), the characteristic mechanical performance factors of UMWs are determined. A novel strength index is proposed to discriminate between failure modes and elucidate the damage mechanism of UMWs. The results indicate that the ultimate load and its corresponding displacement change systematically with variations in aspect ratios, axial compression ratios, and mortar strengths. Furthermore, integrating stress cloud maps with the proposed strength index provides a quantitative basis for discriminating between flexural and shear failure modes in UMWs. All four modeling methods can, to varying degrees, capture the pushover behavior of UMWs, and quantifiable selection schemes are provided to balance analysis accuracy and computational cost. The analytical methods and findings presented in this work can be applied to performance assessment, seismic design, and engineering practice of UMWs. Full article

Air-to-water heat pumps (ASHPs) are a key technology for residential heating decarbonization; however, their seasonal performance is highly sensitive to outdoor temperature variability. Although thermal energy storage (TES) is widely recognized as a means of improving system efficiency, reported performance gains vary due to differences in climatic datasets, control strategies, and modeling assumptions. This study presents a systematic multi-year assessment of the impact of a water-based TES tank on the seasonal performance of a residential ASHP under measured microclimatic conditions. Hourly simulations were conducted for a single-family house at three locations in eastern Croatia using eight years (2018–2025) of measured meteorological data. Building characteristics, system configuration, and operating strategy were kept identical to isolate the influence of storage volume. TES integration reduced annual electricity consumption by 4.8–9.1%, with a multi-year average reduction of 7.02%, and consistently increased the seasonal coefficient of performance (SCOP) across all analyzed years and locations. The highest relative improvements occurred under less favorable microclimatic conditions, emphasizing the importance of diurnal temperature distribution rather than seasonal averages alone. A parametric analysis identified an optimal storage volume of approximately 1000–1500 L when both energy and economic indicators are considered. The results demonstrate that stable and reproducible seasonal efficiency gains can be achieved through a simple, non-predictive operating strategy under continental climatic variability. Full article

Stadiums are large buildings that attract attention due to their high energy consumption and environmental impact. Considering the effects of climate change, the integration of sustainable energy solutions and energy efficiency is of great importance in the design and planning of these buildings. This study focuses on pitch lighting, which accounts for a significant and fluctuating share of energy consumption in stadiums, and aims to reduce its carbon footprint through the integration of renewable energy. This study aims to analyze the feasibility of achieving a net-zero annual energy balance for different levels of field lighting of a football stadium in accordance with FIFA lighting standards with solar energy systems in different climate zones and under future climate change scenarios. In addition, it is aimed at revealing the effect of climate change scenarios and climate zone differences on the azimuth angle, tilt angle, and area of the solar panel. In the study, a stadium model was created using parametric design—Grasshopper—and optimization software; lighting systems were designed according to FIFA standards, and lighting performance on the field was optimized with simulations through ClimateStudio and Galapagos. Based on Liverpool FC’s home match data, the annual illumination time is calculated, and the azimuth angle, tilt angle, and area of the solar panel systems are optimized for different climate scenarios. The most useful result of this study is that it demonstrates that the solar panel area required to meet stadium lighting needs varies depending on climate scenarios and geographical conditions and that the same energy production can be achieved with less panel area in low-emission scenarios. For instance, simulation results for Liverpool under the RCP 2.6 scenario show a decrease in the required panel area from 86.09 m² in 2050 to 84.27 m² by 2100. Similarly, in Moscow for the year 2050, the medium-emission scenario (RCP 4.5) requires a larger panel area (92.22 m²) compared to the low-emission RCP 2.6 scenario (88.12 m²) to achieve the same energy output. Full article

Scour has been a topic of significant concern among coastal geotechnical engineers in recent years. The Shields number serves as a crucial parameter for erosion calculations, reflecting the balance between sediment particle conditions and hydrodynamic forces, derived from the mechanics of sediment particle equilibrium. Seepage flow, a common phenomenon driven by pressure in soil, further influences the movement of sediment particles. Building upon the classical three-dimensional two-slope angle erosion model, this study incorporates the vertical seepage force. It comprehensively considers slope angles, sediment response angles, incident current angles, and vertical seepage intensities to adjust the Shields number for sediment particles on slopes. The calculation encompasses both transverse and longitudinal slope configurations. Based on the derived formula and parametric analysis, the study draws the following conclusions: 1. The modified Shields number (${\theta }_{cr}/{\theta }_{cr0}$) decreases non-linearly with the increase of slope angle; 2. ${\theta }_{cr}/{\theta }_{cr0}$ is central and has axial symmetry about 180° incident current angles for transverse and longitudinal slopes, respectively; 3. ${\theta }_{cr}/{\theta }_{cr0}$ increases non-linearly with the increase of soil angle of response; 4. ${\theta }_{cr}/{\theta }_{cr0}$ decreases linearly with the increase of seepage intensity; 5. There exists an approximately zero ${\theta }_{cr}/{\theta }_{cr0}$ area when the response angle approaches the slope angle, and the area increases non-linearly as the seepage intensity becomes greater. Full article

The smart city concept has become a dominant framework for contemporary urban governance, largely driven by advances in digital technologies and data-driven decision-making. However, the prevailing technocratic orientation of smart city development risks marginalising the sociopolitical dimensions of urban governance, particularly citizen and stakeholder participation. Although smart governance frameworks increasingly recognise participation as a normative principle, limited empirical attention has been paid to the participation motivators that drive engagement among different urban stakeholder groups. This study addresses this gap by analysing the key motivators influencing stakeholder participation in urban development within a smart city context. Building on established behavioural and participation theories, the article develops an Urban Participation Motivator Model comprising four core motivators: social pressure, emotional trigger, rational motivation, and reward for participation. The model is empirically tested using quantitative survey data from 620 respondents representing four stakeholder groups in Riga, Latvia: municipal residents, municipal employees, municipal politicians, and real estate developers. Data are analysed using descriptive statistics and non-parametric methods, including the Kruskal–Wallis test. The results reveal statistically significant differences in the perceived importance of participation motivators across stakeholder groups. Emotional triggers and social pressure emerge as the most influential motivators overall, while rational motivation is particularly salient for professional stakeholders. Reward for participation plays a weaker but differentiated role, being most relevant for municipal employees. These findings highlight the need for differentiated motivator-sensitive urban communication and participation strategies to enhance inclusiveness, democratic legitimacy, and long-term engagement in smart city development. Full article

Space-deployable antennas have development requirements of an ultra-large aperture, high stiffness, and multi-frequency multiplexing. To address the challenge of stiffness characterization in the multi-closed-loop complex systems of deployable mechanisms, this paper proposes a parametric stiffness modeling method and a static stiffness model is established, ranging from components and limbs to the overall mechanism. The motion/force mapping model of the deployable mechanism is obtained using screw theory, and the stiffness mapping from joint space to workspace is achieved via the Jacobian matrix. A comprehensive stiffness model of the deployable mechanism incorporating joint effects is established based on the principle of virtual work and the superposition principle of deformations, and its validity is verified through finite element simulation. Building on this, stiffness characteristics based on structural configuration are investigated, and structural forms with excellent stiffness performance are selected through comprehensive evaluation. Six configurations of the deployable mechanism are derived topologically from this structure, and the optimal configuration is selected based on stiffness performance. The parametric stiffness modeling method proposed in this study can effectively characterize the contribution of each component to the overall system stiffness. It lays a theoretical foundation for establishing a quantitative relationship between stiffness performance and configuration, enabling performance-based configuration optimization and dimensional optimization. Full article

This work proposes a design-oriented numerical modelling approach for predicting the seismic response of multi-storey Cross-Laminated Timber (CLT) buildings. The model is based on a phenomenological approach and is capable of accurately replicating the seismic behaviour of multi-storey CLT wall systems by means of a properly calibrated equivalent wall stiffness, taking into account both connections and panel deformability. An extensive set of multi-parametric linear analyses is performed to calibrate the wall equivalent stiffness by varying significant design parameters such as: CLT wall geometry, connection pattern, seismic mass and level of seismic intensity. An ad hoc iterative procedure is developed in order to calibrate the wall equivalent stiffness in terms of significant design parameters (e.g., principal elastic period, internal forces in the connection elements and inter-storey drifts). The aim of the procedure was to minimise the error between the results obtained with the proposed phenomenological model and those obtained with refined numerical models. The latter were designed to accurately reproduce the actual response of the CLT systems analysed. The results of the multi-parametric analyses are discussed and summarised in a design abacus that allows a direct implementation of the proposed phenomenological model and, therefore, a simple and efficient seismic analysis for CLT buildings. Full article

This study develops an interpretable machine learning (ML) surrogate to predict hourly indoor air temperature and discomfort indicators for a representative Mexican social-housing prototype in San Luis Potosí (cold semi-arid, Köppen–Geiger BSk). A four-zone EnergyPlus model with constant window opening (50%) and no internal gains was used to generate a parametric dataset spanning 24 building orientations, seven roof solar absorptance levels, and two neighborhood configurations (surrounded vs. corner). Zone-specific bagged-tree regression models were trained in MATLAB using weather predictors, temporal indicators, and weather-memory features (including outdoor temperature lags and rolling averages). Orientation and roof absorptance were included as explicit design predictors, enabling the surrogate model to generalize across the full combinatorial design space rather than requiring a separate model for each configuration. Interpretability was assessed with SHAP values. Evaluated on orientation–absorptance combinations deliberately held out during training, the surrogate achieved high accuracy across zones of the house (R² = 0.98–0.99; RMSE = 0.31–0.67 °C) with stable, near-zero-centered residuals. When propagated into adaptive-comfort metrics computed directly relative to the monthly neutral temperature $T_n$, ML predictions preserved the main cold and hot discomfort degree-hour patterns across the full design space. The proposed surrogate enables rapid, physically consistent comfort-oriented screening of roof finishes and orientation choices in naturally ventilated social housing. Full article

Pipe-embedded walls offer a promising approach to reducing winter heating demand by mitigating envelope heat loss while maintaining indoor thermal comfort. However, most existing studies focus on single-pipe systems operating under high-flow conditions, with limited attention to low-flow operation and its implications for energy flexibility. This study investigates a parallel pipe-embedded wall system operating at low flow velocity as a flexible heating strategy. A three-dimensional CFD model was developed to analyze the coupled hydraulic and thermal behavior of the wall, including the effects of connecting columns, and was validated through experiments under identical boundary conditions. Parametric analyses examined the influence of main pipe size, branch spacing, flow velocity, water temperature, and column-induced thermal bridging. The results show that variations in flow velocity and branch spacing lead to flow distribution differences of up to 6%, while causing negligible changes in inner-surface temperature (below 0.1 °C). In contrast, increasing column size significantly intensifies thermal bridging, increasing inner-surface heat flux by approximately 21% as the column edge length increases from 200 mm to 400 mm. Overall, the results demonstrate that parallel pipe-embedded walls can enhance building energy flexibility by enabling stable thermal performance under low-flow operation. Full article

Prefabricated reinforced concrete shear wall structures have attracted significant attention due to their advantages in industrialized construction and sustainability. However, the structural performance of prefabricated shear wall systems still requires further investigation to ensure reliable seismic behavior under earthquake loading. In this study, a fully prefabricated shear wall system incorporating keyway interlocking joints and concentrated reinforcement connections is proposed, and its nonlinear seismic behavior is systematically investigated through finite element modeling, parametric analysis, nonlinear time history analysis, and incremental dynamic analysis. The finite element models were validated against available experimental results and reproduced the hysteretic response, stiffness degradation, and load-carrying capacity with good agreement. The relative errors in peak load were within 5%, indicating the reliability of the adopted modeling approach. Parametric analyses indicate that axial compression ratio, concrete strength, and wall thickness significantly affect structural performance, while prefabricated walls exhibit slightly lower stiffness and strength than cast-in-place walls, with mean reduction factors of 0.88 and 0.91. An eight-story prefabricated shear wall building subjected to multiple scaled ground motions exhibits stable flexure-dominated deformation without joint sliding or soft-story mechanisms. Peak roof displacements reached 19.71 mm and 32.85 mm in the X and Y directions, with maximum interstory drift ratios of 1/892 and 1/724. These values are significantly smaller than the commonly adopted collapse drift limit of 1/120 specified in seismic design guidelines, indicating a relatively large deformation safety margin under the ground motions considered. Probabilistic seismic demand models were established based on both PGA and Sa(T₁, 5%) intensity measures, showing strong correlations with the maximum interstory drift ratio. Fragility analysis demonstrates a high probability of remaining in intact or slight damage states under frequent and design-level earthquakes and a low collapse probability under rare earthquakes. These findings provide valuable insights for the design of next-generation prefabricated shear wall systems with mechanical interlocking joints and concentrated reinforcement connections. Full article