Search Results (298)

The selection of an appropriate formwork system represents a critical decision in the planning of reinforced concrete multi-story buildings. While this decision has traditionally been deferred to the construction phase, increasing evidence of time and cost overruns in construction projects has highlighted the necessity of addressing it during earlier stages, particularly in design and planning. Early identification and selection of the optimal formwork system enhances the likelihood of achieving significant improvements in both time efficiency and cost effectiveness. To facilitate this process, a decision-support framework based on the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods has been developed. This framework provides decision-makers with a structured and systematic approach for evaluating alternatives and selecting the most suitable formwork system for a given project. By offering an analytical foundation for the decision-making process, the framework assists designers and engineers in mitigating risks associated with delays and potential standstills during construction. The findings indicate that the proposed decision-support framework ensures both clarity and consistency in decision-making outcomes, irrespective of the analytical method employed. Consequently, it contributes to more robust planning and execution of construction projects. Full article

The growing need for safe, cheap and sustainable earthquake-resistant buildings means that efficient methods for optimal seismic design must be found. The complexity and nonlinearity of the problem can be addressed using advanced automated techniques. This paper presents an intelligent three-step procedure for optimally designing earthquake-resistant buildings based on the training (1st step) and successive inversion (2nd step) of Multi-Layer Perceptron Neural Networks. This involves solving the inverse problem of determining the optimal design parameters that meet pre-assigned, code-based performance targets, by means of a gradient-based optimization algorithm (3rd step). The effectiveness of the procedure was tested using an archetypal multistory, moment-resisting, concentrically braced steel frame with active tension diagonal bracing. The input dataset was obtained by varying four design parameters. The output dataset resulted from performance variables obtained through non-linear dynamic analyses carried out under three earthquakes consistent with the Chilean code spectrum, for all cases considered. Three spectrum-consistent records are sufficient for code-based seismic design, while each seismic excitation provides a wealth of information about the behavior of the structure, highlighting potential issues. For optimization purposes, only information relevant to critical sections was used as a performance indicator. Thus, the dataset for training consisted of pairs of design parameter sets and their corresponding performance indicator sets. A dedicated MLP was trained for each of the outputs over the entire dataset, which greatly reduced the total complexity of the problem without compromising the effectiveness of the solution. Due to the comparatively low number of cases considered, the leave-one-out method was adopted, which made the validation process more rigorous than usual since each case acted once as a validation set. The trained network was then inverted to find the input design search domain, where a cost-effective gradient-based algorithm determined the optimal design parameters. The feasibility of the solution was tested through numerical analyses, which proved the effectiveness of the proposed artificial intelligence-aided optimal seismic design procedure. Although the proposed methodology was tested on an archetypal building, the significance of the results highlights the effectiveness of the three-step procedure in solving complex optimization problems. This paves the way for its use in the design optimization of different kinds of earthquake-resistant buildings. Full article

Lighting systems in sports venues have a significant impact on both the user experience and quality of events. However, owing to the large number of luminaires, high individual lamp power, and strict lighting standards, the lighting energy consumption of sports venues is high, accounting for approximately 30% of the total energy use. Therefore, introducing natural light through appropriate means during non-event periods and ensuring adequate lighting via collaborative control between natural light and artificial-lighting systems are crucial for reducing the lighting energy consumption of sports venues. Light pipe systems are a novel form of natural lighting and can effectively supplement artificial lighting. However, no clear methodology for selecting light pipes or designing light pipe systems in high spaces such as sports venues currently exists. Furthermore, developing a method for collaborative control between artificial-lighting systems and light pipe systems under various natural light conditions is an urgent issue in the optimization of the design of sports venue lighting. Therefore, we considered a conventional sports venue as a case study. By conducting HOLIGILM simulation experiments, we first investigated the factors affecting the transmission efficiency of light pipe systems and proposed optimization parameters for system design in terms of the pipe diameter, length, and configuration. Subsequently, using the Chinese Standard for Daylighting Design of Buildings (GB50033-2013) and the construction cost as optimization objectives, we optimized the pipe diameter, length, and placement of the light pipe system by applying non-dominated sorting genetic algorithm II. The simulation results showed that the optimized design of the light pipe system in the sports venue achieved a daylight factor of 1%, which met the standard requirements while reducing the construction cost by approximately 27%. Finally, to meet the indoor Class I (non-tournament) lighting standards stipulated in the Standard for Lighting Design and Test of Sports Venues (JGJ153-2016) and taking energy conservation as the optimization goal, we proposed a strategy for achieving collaborative control between the light pipe system and artificial-lighting system based on a greedy algorithm. The results indicated that under various weather conditions, the collaborative control strategy enabled the lighting of the field of play to meet Class I illuminance standards while reducing the annual lighting energy consumption by 35%. Thus, this study provides a methodological reference for optimizing the design of light pipe systems and achieving collaborative control with artificial-lighting systems in large-scale venues. Although these results were obtained based on meteorological data from Xi’an, China, the research method presented in this study can also be applied to other regions. The study provides a methodological reference for the design and optimization of light pipe systems and associated control systems to operate light pipes alongside artificial lighting systems in sports venues and other large multistory buildings. Full article

Reinforced concrete (RC) non-seismic frames in Middle Eastern multistory buildings often have beam–column connections with discontinuous bottom reinforcement, heightening the risk of progressive collapse if an outer column fails. This study aimed to reduce the potential for progressive collapse when a column is lost by investigating the use of bolted steel plates to enhance the beam–column joints of such frames. In this regard, high-fidelity finite element (FE) analysis was carried out on ten half-scale, two-span, two-story RC frames to simulate the removal of a center column. The numerical analysis accounted for the nonlinear rate-dependent response of steel and concrete, as well as the bond-slip model at steel bars/concrete interaction. The analysis matrix had three unstrengthened specimens that served as references for comparison, in addition to seven assemblies, which were strengthened using bolted steel plates. In the upgraded assemblies, the studied variables were the grade of steel plate (three grades were examined) and the upgrading scheme (three different schemes were investigated). The performance of the specimens was evaluated by comparing their failure patterns and the characteristics of load versus displacement of the middle column during both flexural and catenary action phases. Based on this comparison, the most efficient strengthening method was suggested. Full article

The construction sector contributes significantly to global greenhouse gases, accounting for 39% of worldwide emissions. Multi-story wood buildings (MSWBs) present a sustainable alternative to traditional emissions-intensive construction materials like concrete and steel. However, only a few studies have investigated how potential customers perceive MSWBs, which influences their acceptance and demand. This study uses a concept-driven scoping review to explore perceptions and concerns about living in MSWBs and to understand barriers to their adoption. Through a narrative synthesis of 20 peer-reviewed articles, this study uncovered five key themes: environmental sustainability, fire safety, human well-being, structural durability, and costs. These findings highlight opportunities and challenges for MSWBs’ market growth and inform future communication strategies to enhance public acceptance and promote sustainable construction and the built environment. Full article

This study investigates the influence of rear setback geometry and façade design parameters on microclimatic conditions, indoor thermal comfort, and energy performance in multi-story residential buildings in hot arid climates, addressing the growing need for climate-responsive design in regions with extreme temperatures and high solar radiation. Despite increasing interest in sustainable strategies, the combined effects of urban geometry and building envelope design remain underexplored in these environments. A coupled simulation framework was developed, integrating ENVI-met for outdoor microclimate modeling with Design Builder and EnergyPlus for dynamic building performance analysis. A total of 270 simulation scenarios were examined, combining three rear setback aspect ratios (1.5, 1.87, and 2.25), three window-to-wall ratios (10%, 20%, and 30%), three glazing types (single-, double-, and triple-pane), and two wall insulation states, using customized weather files derived from microclimate simulations. Global sensitivity analysis using rank regression and multivariate adaptive regression splines identified the glazing type as the most influential parameter (sensitivity index ≈ 0.99), especially for upper floors. At the same time, higher aspect ratios reduced peak Physiological Equivalent Temperature (PET) by up to 5 °C and decreased upper-floor cooling loads by 37%, albeit with a 9.3% increase in ground-floor cooling demand. Larger window-to-wall ratios lowered lighting energy consumption by up to 35% but had minimal impact on cooling loads, whereas wall insulation reduced annual cooling demand by up to 29,441 kWh. The results emphasize that integrating urban morphology with optimized façade components, particularly high-performance glazing and suitable aspect ratios, can significantly improve thermal comfort and reduce cooling energy consumption in hot arid residential contexts. Full article

The application of tuned mass dampers (TMDs) to high-rise buildings or slender bridges can significantly decrease the dynamical vibrations due to external excitation, such as wind or earthquake loads. However, the individual properties of a TMD such as mass, stiffness and damping have to be designed carefully with respect to the dynamical properties of the investigated structure. In real-world structures, the influence of uncertain system properties might be critical for the performance of a TMD and thus the whole structure. Therefore, the design under uncertainty of such systems is an important issue, which is addressed in the current paper. For our investigations, we consider linear single-degree-of-freedom (SDOF) systems, where analytical formulas for the deterministic design already exist, and linear multi-degree-of-freedom (MDOF) systems, where a time integration and numerical optimization algorithms are usually applied to obtain the optimal TMD parameters. If the numerical optimization should be coupled with a sampling-based uncertainty quantification method, such as Monte Carlo sampling, the design procedure would require the evaluation of a coupled double-loop approach, which is very demanding from the computation point of view. Therefore, we focus the following paper on an efficient analytical uncertainty quantification approach, which estimates the mean and scatter from a Taylor series expansion. Additionally, we introduce an efficient mode decomposition approach for MDOF systems with multiple TMDs, which estimates the maximum displacements using a modal analysis instead of a demanding time integration. Different optimal design problems are formulated as single- or multi-objective optimization tasks, where the statistical properties of the maximum displacements are considered as safety margins in the optimization goal functions. The application of numerical optimization algorithms is straightforward and not limited to specific algorithms. As numerical examples, we investigate an SDOF system with single TMD and a multi-story frame with multiple TMDs. The presented procedure might be interesting for the design process of structures, where the dynamical vibrations reach a critical threshold. Full article

The accurate estimation of building heights using very-high-resolution (VHR) synthetic aperture radar (SAR) imagery is crucial for various urban applications. This paper introduces a deep learning (DL)-based methodology for automated building height estimation from single VHR COSMO-SkyMed images: an object-based regression approach based on bounding box detection followed by height estimation. This model was trained and evaluated on a unique multi-continental dataset comprising eight geographically diverse cities across Europe, North and South America, and Asia, employing a cross-validation strategy to explicitly assess out-of-distribution (OOD) generalization. The results demonstrate highly promising performance, particularly on European cities where the model achieves a Mean Absolute Error (MAE) of approximately one building story (2.20 m in Munich), significantly outperforming recent state-of-the-art methods in similar OOD scenarios. Despite the increased variability observed when generalizing to cities in other continents, particularly in Asia with its distinct urban typologies and the prevalence of high-rise structures, this study underscores the significant potential of DL for robust cross-city and cross-continental transfer learning in building height estimation from single VHR SAR data. Full article

A steel modular building is a highly prefabricated form of steel construction. It offers rapid assembly, a high degree of industrialization, and an environmentally friendly construction site. To promote the application of multi-story steel modular buildings in earthquake fortification zones, it is imperative to conduct in-depth research on their seismic behavior. In this study, a seven-story modular steel building is investigated using shaking table tests. Three seismic waves (artificial ground motion, Tohoku wave, and Tianjin wave) are selected and scaled to four intensity levels (PGA = 0.035 g, 0.1 g, 0.22 g, 0.31 g). It is found that no residual deformation of the structure is observed after tests, and its stiffness degradation ratio is 7.65%. The largest strains observed during the tests are 540 × 10⁻⁶ in beams, 1538 × 10⁻⁶ in columns, and 669 × 10⁻⁶ in joint regions, all remaining below a threshold value of 1690 × 10⁻⁶. Amplitudes and frequency characteristics of the acceleration responses are significantly affected by the characteristics of the seismic waves. However, the acceleration responses at higher floors are predominantly governed by the structure’s low-order modes (first-mode and second-mode), with the corresponding spectra containing only a single peak. When the predominant frequency of the input ground motion is close to the fundamental natural frequency of the modular steel structure, the acceleration responses will be significantly amplified. Overall, the structure demonstrates favorable seismic resistance. Full article

Corrosion can accelerate the deterioration of the mechanical properties of steel structures. However, few studies have systematically evaluated its impact on seismic performance, particularly with respect to seismic economic losses. In this paper, the seismic fragility and loss assessment of a multi-story steel frame with viscous dampers (SFVD) building are investigated through experimental and numerical analysis. Based on corrosion and tensile test results, OpenSees software 3.3.0 was used to model the SFVD, and the effect of corrosion on the seismic fragility was evaluated via incremental dynamic analysis (IDA). Then, the economic losses of the SFVD during different seismic intensities were assessed at various corrosion times based on fragility analysis. The results show that as the corrosion time increases, the mass and cross-section loss rate of steel increase, causing a decrease in mechanical property indices, and theprobability of exceedance of the SFVD in the limit state increases gradually with increasing corrosion time, with an especially significant impact on the collapse prevention (CP) state. Furthermore, the economic loss assessment based on fragility curves indicates that the economic loss increases with corrosion time. Thus, the aim of this paper is to provide guidance for the seismic design and risk management of steel frame buildings in coastal regions throughout their life cycle. Full article

Urbanization has profoundly transformed land surface morphology and amplified thermal environmental modifications, culminating in intensified urban heat island (UHI) phenomena. Local climate zones (LCZs) provide a robust methodological framework for quantifying thermal heterogeneity and dynamics at local scales. Our study investigated the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZXA) as a case study and systematically examined spatiotemporal patterns of LCZs and land surface temperature (LST) from 2002 to 2019, while elucidating mechanisms influencing urban thermal environments and proposing optimized cooling strategies. Key findings demonstrated that through multi-source remote sensing data integration, long-term LCZ classification was achieved with 1,592 training samples, maintaining an overall accuracy exceeding 70%. Landscape pattern analysis revealed that increased fragmentation, configurational complexity, and diversity indices coupled with diminished spatial connectivity significantly elevate LST. Rapid development of the city in the vertical direction also led to an increase in LST. Among seven urban morphological parameters, impervious surface fraction (ISF) and pervious surface fraction (PSF) demonstrated the strongest correlations with LST, showing Pearson coefficients of 0.82 and −0.82, respectively. Pearson coefficients of mean building height (BH), building surface fraction (BSF), and mean street width (SW) also reached 0.50, 0.55, and 0.66. Redundancy analysis (RDA) results revealed that the connectivity and fragmentation degree of LCZ_8 (COHESION8) was the most critical parameter affecting urban thermal environment, explaining 58.5% of LST. Based on these findings and materiality assessment, the regional cooling model of “cooling resistance surface–cooling source–cooling corridor–cooling node” of CZXA was constructed. In the future, particular attention should be paid to the shape and distribution of buildings, especially large, openly arranged buildings with one to three stories, as well as to controlling building height and density. Moreover, tailored protection strategies should be formulated and implemented for cooling sources, corridors, and nodes based on their hierarchical significance within urban thermal regulation systems. These research outcomes offer a robust scientific foundation for evidence-based decision-making in mitigating UHI effects and promoting sustainable urban ecosystem development across urban agglomerations. Full article

This study presents a computational approach to optimize the stiffness distribution of large deformable elastic braces (LDEBs), which possess a high elastic deformation capacity and are designed to enhance the seismic performance of building structures. An optimization problem was formulated to minimize the seismic response of two-story buildings modeled as multi-degree-of-freedom systems, in which both the building frame and the LDEBs were represented by spring elements. Seismic responses under earthquake excitations were evaluated through time-history analyses. Particle swarm optimization (PSO) was employed to determine the optimal stiffness ratios of LDEBs that minimize the maximum story drift. Extensive round-robin analyses were conducted to verify the validity of the PSO results, generating response surfaces that mapped the maximum story drift against the LDEBs’ stiffness under three different earthquake records. The analysis revealed that the optimal solutions obtained from the PSO coincided with the global minimum identified in the round-robin response surfaces. These results confirm the effectiveness of the proposed optimization framework and demonstrate the potential of LDEBs for enhancing seismic resilience in structural designs. Full article

The spatial layout of residential communities has a significant impact on the local microclimate. These microclimate changes subtly affect the daily feelings and health status of residents. This study takes hypertension as a case to simulate the outdoor microclimate characteristics of different types of communities, and to analyze the potential correlation between spatial design and the health of residents, providing a scientific basis for the design of health-oriented communities. Initially, the microclimate characteristics of communities are obtained through computational fluid dynamics (CFD) simulation. Subsequently, the correlation between the outdoor microclimate and the incidence of hypertension in communities is discussed. The study area covers communities within a 4 km radius of Zhongnan hospital. The results indicate that microclimatic factors, such as temperature, Predicted Mean Vote (PMV), and Universal Thermal Climate Index (UTCI), are significantly negatively correlated with the incidence of hypertension in communities of different building heights. For temperature, the absolute value of the correlation coefficient for multi-story communities is 0.431, slightly lower for mid-rise communities at 0.323, and further drops to 0.296 for high-rise communities. Correspondingly, the values for PMV are 0.434, 0.336, and 0.306, respectively. The values for UTCI are 0.442, 0.310, and 0.303, respectively. This effect gradually weakens as building heights increase. Fluctuations in wind speed appear to weakly influence the incidence of hypertension. These results provide a scientific basis for health-oriented urban planning. Full article

This paper presents a detailed analysis of the dynamics of indoor environmental parameters under three simulated fire scenarios in a multi-story building, using the PyroSim platform (based on the Fire Dynamics Simulator—FDS). The study compares two smoke control strategies, organized natural ventilation (a passive system) and mechanical pressurization (an active system), evaluating their influence on temperature, differential pressure, air velocity, heat release rate (HRR), and toxic gas distribution. The simulations revealed that passive systems, relying on the stack effect and vertical natural ventilation, do not ensure the effective control of smoke infiltration into evacuation routes, allowing significant heat accumulation and reduced visibility. The results highlight the superior effectiveness of unidirectional mechanical pressurization in maintaining a stable flow regime, functional visibility, and a safe evacuation environment. A key finding is the transition from static pressure control to velocity-based flow control at the moment of door opening toward the fire source. The results confirm that a dynamically adapted application of mechanical pressurization—synchronized with the opening of access pathways—not only reinforces existing principles for protecting egress routes, but also provides a precise operational approach for optimizing emergency responses in high-rise buildings. Full article

Decarbonisation in hot climates demands innovative cooling solutions that minimise environmental impact through renewable energy integration and advanced system optimisation. This study investigates the energetic and economic feasibility of a thermo-mechanical vapour compression (TMVC) cooling system that integrates a conventional vapour compression cycle with an ejector and a thermally driven second-stage compressor powered by solar-heated water from evacuated flat-plate collectors. The system is designed to reduce mechanical compressor work and enhance cooling performance in hot climates. A comprehensive 4E (energy, exergy, economic, and environmental) analysis is conducted for a multi-story residential building in Baghdad, Iraq, with a total floor area of approximately 8000 m² and a peak cooling demand of 521.75 kW. Numerical simulations were conducted to evaluate various configurations of solar collector areas, thermal storage tank volumes, and collector mass flow rate, aiming to identify the most energy-efficient combinations. These optimal configurations were then assessed from economic and environmental perspectives. Among them, the system featuring a 600 m² collector area and a 34 m³ storage tank was selected as the optimal case based on its superior electricity savings and energy performance. Specifically, this configuration achieved a 28.28% improvement in the coefficient of performance, a 22.05% reduction in energy consumption, and an average of 15.3 h of daily solar-assisted operation compared to a baseline vapour compression system. These findings highlight the potential of the TMVC system to significantly reduce energy usage and environmental impact, thereby supporting the deployment of sustainable cooling technologies in hot climate regions. Full article