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Verifying and validating explosion-resistant design models are challenging tasks due to the difficulties in accurately capturing the failure evolution within a setup influenced by the combined effects of fluid–solid interactions (FSI), blast waves, fragmentation, and impact. Curtain wall system, as a key structural component, is widely used in various types of buildings for its aesthetic appeal and weather protection. Hence, optimizing the explosion-resistance of such systems is necessary to improve building safety. In this work, we develop computational procedures that can be used to enhance the design of blast-resistant structures. This paper focuses on studying a representative component (e.g., window panels) from a typical curtain wall system, as well as a small-scale modeling of shock tube testing. For that, the material point method (MPM) simulations are verified against the finite element method (FEM) simulations, and the computational results are validated against shock tube testing. The work objective is to evaluate the simulation fidelity of explosion responses in several case studies. The first case study demonstrates how the MPM captures damage and fragmentation in a typical confined explosion event involving FSI, thus, providing an improved physical description compared to the FEM. The second case study qualitatively compares the MPM’s ability to simulate the shock tube response with experimental observations. Since the second study validates that the MPM solution is qualitatively consistent with the experimental data, the MPM model is then used in the third case study to establish an FEM model that could capture the same physics. This FEM model can be scaled up to model field experiments. The fourth case study involves the development of an FEM model for a representative curtain wall system component, which is validated against experimental results and then scaled down and employed to validate a corresponding MPM model. The proposed procedure provides a feasible approach to verifying and validating explosion-resistant designs for more general cases.

Blockages in sewers and drains often result in overflows and flooding that cause significant environmental pollution and public health risks, particularly in hospitals, where the consequences can be catastrophic. Due to their low “visibility”, sewers and drains are inherently difficult to monitor and maintain, resulting in a reactive management approach whereby maintenance or repair is carried out only after a system failure has occurred. This paper investigates the feasibility of applying the reflected wave technique, a unique sonar-like monitoring approach capable of identifying changes in the geometry of closed-pipe conduits, as a means of proactive system monitoring. The technique uses a 10 Hz sinusoidal air pressure wave which is transmitted into the drainpipe. When the pressure wave encounters a system boundary, a reflection is generated which alters the measured test pressure response. Analysis of the reflections generated by a changed system boundary, such as the formation of a blockage, can provide information related to the location of that boundary within the system. An experimental setup was developed to simulate a horizontal drain using standard pipework of 100 mm diameter and 70 m length. The technique was able to detect applied blockages with cross-sectional coverage of 30% and 75%, and lengths ranging from 30 mm to 3000 mm. Accuracy was improved when the pressure sensor was positioned closer to the blockage. When the sensor was 3.4 m from the blockage, location estimates were very accurate (−2% to 3% error). At a 14 m distance from the blockage, the error increased to between 4% and 33%. The accuracy of blockage detection and location improved with increasing blockage cross-sectional area and length. Overall, the reflected wave technique could provide a potentially continuous monitoring solution for blockage detection in sewers and drains.

Green construction is considered to be a construction model that pursues high resource efficiency and the utilization of reduced environmental impacts through technological innovation and management optimization under the realization of the project’s iron triangle. The realization of its performance relies on the level of stakeholder capability configuration. To reveal the optimal capability configuration and interaction between regulators and executors, this study constructed a utility model based on a post-positivist methodology. By analyzing the optimal capability configuration and coordination levels of regulators and executors according to the practices and constraints of green construction, this study conducted a static analysis to compare the effects of marginal value on regulators’ capability input and coordination coefficients. Finally, a sensitivity analysis uncovers the changes in capability configuration interaction and coordination coefficients at different stages of green construction. The results indicate that high levels of coordination in green construction cannot be maintained in the long term; continuous capability input from regulators is required for sustained support. Only by eliminating external uncertainties, reducing the variable costs for executors in advancing green construction, and controlling their risk aversion can executors be truly motivated to promote green construction. The capability configuration of both regulators and executors adjusts with corresponding marginal values. The capability configuration of executors shows a trend of initially increasing and then decreasing as the progressive coefficient rises. The model proposed in this study ensures that the final coordination level stabilizes at a relatively high level, which is between 0.6 and 0.7. In summary, the breakthrough findings provide critical insights into green construction management, contributing to the achievement of the anticipated green construction objectives.

The global drive for sustainable development and carbon neutrality has heightened the need for energy-efficient buildings. Photovoltaic buildings, which aim to reduce energy consumption and carbon emissions, play a crucial role in this effort. However, the potential of the building envelope for electricity generation is often underutilized. This study introduces an efficient hybrid method that integrates Particle Swarm Optimization (PSO), Support Vector Machine (SVM), Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. This integrated approach was used to optimize the external envelope structure and photovoltaic components, leading to significant reductions: overall energy consumption decreased by 41% (from 105 kWh/m2 to 63 kWh/m2), carbon emissions by 34% (from 13,307 tCO2eq to 8817 tCO2eq), and retrofit and operating costs by 20% (from CNY 13.12 million to CNY 10.53 million) over a 25-year period. Sensitivity analysis further revealed that the window-to-wall ratio and photovoltaic windows play crucial roles in these outcomes, highlighting their potential to enhance building energy performance. These results confirm the feasibility of achieving substantial energy savings and emission reductions through this optimized design approach.

In the context of China’s sustainable development and dual carbon goals, research on thermodynamic architecture theory and vernacular architecture increasingly aligns with international trends, developing distinct characteristics. This research addresses the challenge of rapid changes in the built environment by focusing on climate adaptability and passive technologies. However, the development of thermodynamic theory in vernacular architecture faced technical limitations in the early 21st century and was later overshadowed by the industry’s reliance on active technologies to meet green building standards, resulting in a reduced role for architects in the green building field. This article traces the origins of passive architecture, rooted in vernacular architecture, and applies thermodynamic theory to explore architectural prototypes. It examines the theoretical feasibility of architectural design in achieving low-carbon and sustainable goals, aiming to fill a gap in thermodynamic theory within the broader context of sustainable architectural development. After demonstrating the various passive prototypes inherent in vernacular architecture, this paper proposes a courtyard prototype focused on residential comfort for design translation and analysis. The research methods employed include bioclimatic charting, balance point temperature analysis in time series, and extensive computer simulations. Through the process of prototype extraction, performance analysis, validation, and optimization, the paper systematically discusses sustainable design methods within the framework of thermodynamic architecture theory. It also provides practical demonstrations of these methods across four distinct climate regions in China. By translating vernacular architectural designs, this research systematically organizes the theoretical framework for architects’ early involvement in low-carbon and green building design, offering a theoretical foundation for initiating the design process through prototype translation while guiding the generation of green ecological buildings.

With the rapid pace of global urbanization, the urbanization of resettlement communities in China has garnered increasing attention from scholars. This study, grounded in experiential value theory, delves into the relationship between public spaces in resettlement communities and their social cohesion. Focusing on resettlement communities in the central urban area of Fuzhou, this study employs a mixed-method approach to analyze the functional characteristics of public spaces using geospatial data, including their green coverage ratio, spatial accessibility, facility configuration, and neighborhood density. A correlation analysis and multiple linear regression were employed to identify the key elements influencing social cohesion. The results indicate significant disparities in the green coverage, accessibility, facility configuration, and neighborhood density of public spaces. These differences are evident in the quantitative metrics used and also reflect imbalances in spatial layout and resource distribution, highlighting potential pathways for optimizing the quality of public spaces. Further data analyses revealed that both emotional value (β = 0.602, p < 0.01) and functional value (β = 0.136, p < 0.01) have significant positive impacts on social cohesion, with emotional value being particularly influential. This study offers insights for urban planners and policymakers by providing scientific evidence for the optimization of public space design in resettlement communities, with implications for community governance and urban sustainability.

An improved meshfree method that considers cracking, contact behaviour and fluid–solid interaction (FSI) was developed and employed to shed light on the progressive failure of the water-resistant stratum and inrush process in a karst tunnel construction. Hydraulic fracturing tests considering different scenarios and inrush events of the field-scale Jigongling karst tunnel in three scenarios verify the feasibility of the improved meshfree method. The results indicate that the brittle fracture characteristics of the rock mass are captured accurately without grid re-meshing by improving the kernel function of the meshfree method. The complex contact behaviour of rock along the fracture surface during inrush is correctly captured through the introduction of Newton’s law-based block contact algorithms. FSI processing during inrush is accurately modelled by an improved two-phase adaptive adjacent method considering the discontinuous particles without coupling other solvers and additional artificial boundaries, which improves computational efficiency. Furthermore, the improved meshfree method simultaneously captures the fast inrush and rock failure in the Jigongling karst tunnel under varying thicknesses and strengths of water-resistant rocks and sizes of karst caves. As the thickness and strength of water-resistant rock increase, the possibility of an inrush disaster in the tunnel decreases, and a drop in the water level and an increase in the maximum flow velocity have significant delayed effects during the local inrush stage.

In practical engineering, a shed-tunnel structure often encounters repeated impacts from rockfall during its whole service life; therefore, this research focuses on exploring the dynamic response characteristics of shed-tunnel structures under repeated impacts from rockfall with a numerical method. First of all, based on a model test of a shed tunnel under rockfall impacts as a reference, an FEM (finite element method)-SPH (Smoothed Particle Hydrodynamics) coupled numerical calculation model is established based on the ANSYS/LS-DYNA finite element code. Numerical simulation of the dynamic response of the shed-tunnel structure under rockfall impacts is realized, and the rationality of the model is verified. Then, with this model and the full restart technology of the LS-DYNA code, the effects of four factors, e.g., rockfall mass, rockfall impact velocity, rockfall impact angle and rockfall shape, on the impact force and impact depth of the buffer layer, the maximum plastic strain and axial force of the rebar, the shed roof’s vertical displacement and plastic strain of the shed tunnel are studied. The results show that the impact force, impact depth, roof displacement and plastic strain of the shed tunnel are positively correlated with the rockfall mass, velocity and angle under multiple rockfall impacts. The impact force, roof displacement and plastic strain of the shed-tunnel structure generated by the impact of rockfall consisting of cuboids are all greater than those under spherical rockfall, and the impact depth generated by the impact of spherical rockfall is greater than that of rockfall consisting of cuboids. For rockfall consisting of cuboids, the impact depth, roof displacement and plastic strain are negatively correlated with the contact area. Under repeated rockfall impacts, the peak impact force usually increases first and then tends to be stable.

For building projects, the manager is responsible for coordinating the work of subcontractors at the construction site. This includes operations, material flows, and storage. In summary, one of their main roles is to ensure smooth team rotation, maintain fluid circulation, and avoid congestion or relaxation on the site. However, traditional tools lack the ability to consider the planning and management of worksite spaces when calculating the execution schedule and critical path. Consequently, three-week planning is usually carried out separately on independent plans, often using spreadsheets. In addition, a construction site is highly dynamic and mobile in nature, and the positioning of resources and workers can change daily. This makes the management of available space even more complex, and effective space management becomes an imperative. To address this challenge, this paper develops visual dynamic artifacts that present different operation types. The methodology and the conceptual framework facilitate the calculation of the Occupancy Rate (OR) that enables construction project managers to create simple yet dynamic spatiotemporal models of the construction schedule. By incorporating factors such as crew turnover and occupancy evolution, managers can simplify the calculation process and effectively optimize construction work by utilizing site occupancy rates. In summary, this paper presents the Dynamic Model of the Occupancy Rate Schedule (DMORS), a methodology developed through design science. This model utilizes created artifacts representing various operation types to ensure accurate calculations of dynamic occupancy by floor and sector in a site. Consequently, it enables the construction of a more realistic schedule based on critical space ideologies. The DMORS enables managers to use the OR for different floors and sectors of a site, allowing for better space management. A proof of concept demonstrates that this tool can enhance the efficiency and productivity of construction projects by optimizing crew schedules and resource allocation based on site OR.

Government agencies, energy consumers, and other societal groups have all shown concern and attention for the energy management of buildings. Relevant statistical data, however, indicate that most public buildings continue to consume large amounts of energy overall and that the issues of low energy usage and energy waste have not materially improved. As a result, this study reviewed the state of progress and potential directions for future research in the field of building energy management in public buildings using a data-driven approach. Relevant studies were obtained from three databases—Web of Science, Scopus, and China National Knowledge Infrastructure—based on certain search phrases. The text mining program VOS viewer was then used to examine the material. We provide a thorough examination of the study techniques and material, as well as a visual representation of the keywords and current state of the field. According to this study, the range of data processing outcomes; the flexibility of research system standards; and the availability of a comprehensive, unified assessment system are the main factors contributing to the practical issues facing building energy management today. Based on the geographic distribution and state of energy development, this study is the first to examine possible research avenues for building energy management in public buildings through cross-fusion research on passive energy-saving design and subjective behavioral energy-saving. It offers a foundation for developing the building energy management system best practice model in the future.

Pre-treated waste cooking oil (WCO) and organic montmorillonite (OMMT) were employed for the recycling of aged asphalt, which resulted in the improvement of the design of WCO asphalt rejuvenators and the enhancement of high-temperature performance of WCO-recycled asphalt. The effect of the rejuvenator and the properties of recycled asphalt were evaluated by viscosity, dynamic shear rheometer (DSR), bending beam rheometer (BBR) and scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and gel permeation chromatography (GPC) tests. The results indicated that aged asphalt could be obviously softened and restored to the level of original asphalt by adding 6% WCO. However, the high-temperature properties of recycled asphalt would be declined by adding too large a dose of WCO rejuvenator. The high-temperature performance of recycled asphalt was significantly improved by the WCO-OMMT complex rejuvenator, and the viscosity and rutting factor of recycled asphalt were increased. Light components of aged asphalt could be supplemented by WCO of the complex rejuvenator. The volatilization of small molecules could be slowed down by the peel structure formed by OMMT and small molecules of the asphalt, which resulted in the proportion of small molecular substances (SMS) being increased by 4% and improvement of the colloidal structure of aged asphalt. The high-temperature and low-temperature performance of recycled asphalt can be improved concurrently by the combination of 6% WCO and 1% OMMT, and this was evidenced by the fact that the high-temperature and low-temperature PG were all upgraded by one level.

The influence of mobility modes within Positive Energy Districts (PEDs) has gained limited attention, despite their crucial role in reducing energy consumption and greenhouse gas emissions. Buildings in the European Union (EU) account for 40% of energy consumption and 36% of greenhouse gas emissions. In comparison, transport contributes 28% of energy use and 25% of emissions, with road transport responsible for 72% of these emissions. This study aims to design and optimize a synthetic PED in Istanbul that integrates renewable energy sources and public mobility systems to address these challenges. The renewable energy sources integrated into the synthetic PED model include solar energy, hydrogen energy, and regenerative braking energy from a tram system. Solar panels provided a substantial portion of the energy, while hydrogen energy contributed to additional electricity generation. Regenerative braking energy from the tram system was also utilized to further optimize energy production within the district. This system powers a middle school, 10 houses, a supermarket, and the tram itself. Optimization techniques, including Linear Programming (LP) for economic purposes and the Weighted Sum Method (WSM) for environmental goals, were applied to balance cost and CO2 emissions. The LP method identified that the PED model can achieve cost competitiveness with conventional energy grids when hydrogen costs are below $93.16/MWh. Meanwhile, the WSM approach demonstrated that achieving a minimal CO2 emission level of 5.74 tons requires hydrogen costs to be $32.55/MWh or lower. Compared to a conventional grid producing 97 tons of CO2 annually, the PED model achieved reductions of up to 91.26 tons. This study contributes to the ongoing discourse on sustainable urban energy systems by addressing key research gaps related to the integration of mobility modes within PEDs and offering insights into the optimization of renewable energy sources for reducing emissions and energy consumption.

The application of semantics in facade elements mainly involves the association between architectural elements and their cultural, historical, or functional significance. By analyzing the shape, layout, and decoration of various elements (such as windows, doors, decorative patterns) in facades, semantics helps us understand the symbolic meanings and cultural implications behind these design choices. This study selects twenty-eight pavilions and buildings from five temples and Taoist sites in Jingzhou City as the research objects, exploring the composition and patterns of religious architectural facades in Jingzhou through the extraction of structural and decorative elements. The study establishes the “Semantic System of Façade Elements in Jingzhou Religious Architecture”, from which the distinctive characteristics of Jingzhou religious building façades are identified. The study finds that side halls predominantly feature hard gable roofs, while the main halls use double-eave hip-and-gable roofs, reflecting differences in architectural hierarchy. The sack with three arrows pattern is the most widely used in door and window decorations, demonstrating the aesthetic preferences of the Jingchu region. Both side halls and main halls commonly adopt high podiums, with the main hall podiums typically exceeding twenty steps in height, which is closely related to Jingzhou’s climatic conditions and architectural hierarchy. This study provides scientific evidence for the preservation, new design, and harmonious integration of traditional culture and architectural features in regional religious architecture.

This study studies the deformation characteristics of the diversion tunnel of Jinping II Hydropower Station in order to guarantee the safety of the excavation of a large-section soft rock tunnel with a depth of 1000 m and increased ground stress. Using field data, theoretical computations, and numerical modeling, the proper reserved deformation of a deep soft rock tunnel is investigated, taking into consideration the size, in situ stress, and grade of the surrounding rock. The study reveals that (1) The diversion tunnel’s incursion limit, which is typically between 20 and 60 cm, is serious; (2) The surrounding rock level > geostress > tunnel size are the influencing parameters of reserved deformation that remain unchanged while using the numerical simulation method, which is more accurate in simulating field conditions; (3) The west end of the Jinping diversion tunnel has a 30–60 cm reserved deformation range for the chlorite schist tunnel. The deformation law of a large-section, 1000 m-deep soft rock tunnel is better understood, and it also offers important references for high-stress soft rock tunnel engineering design, construction, and safety management.

In recent years, active research has been conducted using deep learning to evaluate damage to aging bridges. However, this method is inappropriate for practical use because its performance deteriorates owing to numerous classifications, and it does not use photos of actual sites. To this end, this study used image data from an actual bridge management system as training data and employed a combined learning model for each member among various instance segmentation models, including YOLO, Mask R-CNN, and BlendMask. Meanwhile, techniques such as hyperparameter tuning are widely used to improve the accuracy of deep learning, and this study aimed to improve the accuracy of the existing model through this. The hyperparameters optimized in this study are DEPTH, learning rate (LR), and iterations (ITER) of the neural network. This technique can improve the accuracy by tuning only the hyperparameters while using the existing model for bridge damage identification as it is. As a result of the experiment, when DEPTH, LR, and ITER were set to the optimal values, mAP was improved by approximately 2.9% compared to the existing model.

Noise pollution negatively impacts people’s mental and physiological health. Unfortunately, not only is noise present in hospital environments, but its level frequently exceeds recommended thresholds. The efficacy of passive acoustic absorbers in reducing indoor noise in these scenarios has been well-documented. Conversely, given their inorganic composition and their origin in the petrochemical industry, most of these materials present a risk to human health. Over the last few years, there has been a notable increase in research on eco-friendly, low-toxicity, and biocompatible materials. This work outlines a methodology for fabricating recycled acoustic panels from plastic bottles and PET felt composites. This study encompasses three key objectives: (i) a comprehensive biocompatibility assessment of the panels, (ii) an evaluation of their thermal and acoustic properties, and (iii) their applicability in several case studies to evaluate potential acoustic enhancements. Specifically, antifungal resistance tests, Volatile Organic Compound (VOC) emission assessment, and cell viability experiments were conducted successfully. Additionally, experimental procedures were performed to determine the thermal conductivity and thermal resistance of the proposed material, along with its sound absorption coefficients in diffuse field conditions. Finally, the potential benefits of using this biomaterial in healthcare environments to reduce noise and improve acoustic comfort were demonstrated.

Evaluating the seismic vulnerability of facades of historic masonry buildings is essential not only for their significant historical and heritage value, but also to evaluate the safety of this type of construction. This work applies a simplified methodology to assess the seismic vulnerability of the facade of masonry buildings in the historic center of Morelia, Michoacán, México. The historic center of Morelia was declared a World Cultural Heritage Site by UNESCO in 1991. On the facades, there is ornamentation with sculptural and vegetal decorative elements. The methodology involved conducting visual inspections to identify the location, type of structure, construction materials, doors, windows, balconies, cornices, ironwork, pediments, niches, and sculptures, among other characteristic elements of colonial architecture. The seismic demands were determined specifically for the city’s historic center based on a recent seismic hazard assessment of Morelia. Based on the methodology and the compiled database, characterized vulnerability indices were defined for the different damage scenarios that buildings may present. Results indicate that earthquakes with intensities greater than VIII on the Modified Mercalli scale risk collapsing heritage masonry buildings’ facades.

The reconstruction of buildings is a complex process that often requires the consideration of the construction load when selecting correct building materials. Autoclaved aerated concrete (AAC)—which has a lower bulk density (compared to traditional masonry materials)—is very beneficial in such applications. A current trend in AAC development is the utilization of secondary raw materials in high-performance AAC, characterized by higher bulk density and compressive strength than regular AAC. The increase in bulk density is achieved by increasing the content of quartz sand in the mixing water. In this study, part of the siliceous component was replaced by ladle slag, foundry sand, furnace lining, and chamotte block powder. These materials are generated as by-products in metallurgy. The substitution rates were 10% and 30%. The samples were autoclaved in a laboratory autoclave for 8 h of isothermal duration at 190 °C with a saturated water vapor pressure of 1.4 MPa. The physical–mechanical parameters were determined, and the microstructure was described by XRD and SEM analyses. The results were compared with traditional AAC, with silica sand being used as the siliceous component. The measurement results show that sand substitution by the secondary raw material is possible, and it does not have a significant impact on the properties of AAC, and in a proper dosage, it can be beneficial for AAC production.

Background: With an aging population and the continuous advancement of smart technology, the Chinese government is exploring smart elderly care models to address the challenges posed by aging. Although smart home systems are viewed as a promising solution, their adoption rate among older people remains low. Objectives: This study aimed to investigate the factors influencing the behavioral intention to use smart home systems among older people in Linyi City, Shandong Province, China. Methods: A literature review revealed a lack of quantitative research on older people’s behavioral intention toward smart home systems based on the Innovation Diffusion Theory. This study developed an extended model based on the Innovation Diffusion Theory, Technology Acceptance Model, and external variables, incorporating eight variables: intergenerational technical support, perceived cost, self-reported health conditions, compatibility, observability, trialability, perceived usefulness, perceived ease of use, and behavioral intention. Results: Analysis of 387 valid questionnaires showed that compatibility and trialability significantly and positively affect perceived ease of use, while self-reported health conditions, perceived ease of use, and perceived usefulness have significant effects on behavioral intention. In addition, perceived cost had a negative influence on behavioral intention. Contributions/Significance: These findings highlight the importance of considering these factors in the design of smart home systems to improve user experience and provide valuable practical guidance to smart home system developers, R&D institutions, and policymakers.

Prior studies have failed to adequately address intangible characteristics and lacked a comprehensive quantification of cultural dimensions. Additionally, such works have not merged supervised and unsupervised classification methodologies. To address these gaps, this study employed multidimensional numerical techniques for precise spatial pattern recognition and urban morphology classification at the block scale. By examining building density, mean floor numbers, functional compositions, and street block mixed-use intensities, alongside historical and contemporary cultural assets within blocks—with assigned weights and entropy calculations from road networks, building vectors, and POI data—a hierarchical categorization of high, medium, and low groups was established. As a consequence, cluster analysis revealed seven distinctive morphology classifications within the studied area, each with unique spatial configurations and evolutionary tendencies. Key findings include the dominance of high-density, mixed-use blocks in the urban core, the persistence of historical morphologies in certain areas, and the emergence of new, high-rise clusters in recently developed zones. The investigation further elucidated the spatial configurations and evolutionary tendencies of each morphology category. These insights lay the groundwork for forthcoming studies to devise morphology-specific management strategies, thereby advancing towards a more scientifically grounded, rational, and precision-focused approach to urban morphology governance.

In air conditioning systems, air curtains play a crucial role in reducing the exchange of hot and cold air between the interior and exterior environments. Nevertheless, the majority of current air curtains suffer from limited airtightness and real-time performance due to their complex jet trajectory, relying on traditional control methods. Thus, this paper introduces an angle control algorithm for air curtains based on a GA-optimized quadratic BP neural network. Initially, the BP neural network is trained using the Hayes dataset to develop the prediction model for temperature-jet angle. Subsequently, the optimization model for jet angles-windshield angle is constructed, and the optimal angles set meeting the fitness function is identified using GA global search. Later, the prediction model and the optimal angles set are once again trained using the BP neural network to generate prediction model for temperature-jet angles and windshield angle. Following CFD simulation, the airtightness indicator demonstrated a 26.5% improvement with the proposed control method compared to traditional ones, highlighting the superior airtightness. In comparison to other algorithms, the proposed algorithm demonstrates a remarkable 89% enhancement in real-time performance and stronger robustness. This study presents a novel approach for the intelligent control of air curtains, holding significant importance in advancing the intelligent development of air curtain technology and facilitating energy efficiency and emission reduction.

The historical monuments of the National Preserve “Kyiv-Pechersk Lavra” play an important role in the context of preserving the UNESCO World Heritage. The scientific understanding of the buildings and structures safety management the priority of conducting repair and restoration works, the organization of their technical condition monitoring, and changes in the components of the geological environment in their locations is crucial. The purpose of this study is to identify potentially hazardous areas on the territory of the Lavra for the operation of structures by conducting a point-based integral assessment of the stability potential of the natural and technogenic system with the integration of geospatial methods and to rank the structures using the analytical hierarchy process. According to the modeling results by 17 stability factors and using ArcGIS, 37% (8.7 ha) of the Lavra territory is located in the zone of moderate hazard, 23% (5.4 ha) in the zone of potential hazard, where the manifestation and conditions of more than five dangerous engineering and geological processes intersect, and 40% (9.4 ha) in the zone of relative safety. In each zone, 10 representative structures were selected for ranking according to the stability of natural and technogenic operating conditions and their current technical condition, which is determined by nine criteria. The analysis using two methods identified the areas most at risk from seasonal fluctuations and possible military impacts and allowed us to scientifically substantiate the priority of repair and restoration work and the possibility of properly planning management measures for the selected structures, as well as to offer recommendations for improving the monitoring of the geological environment of the Lavra.

The construction industry is heavily influenced by the volatility of material prices, which can significantly impact project costs and budgeting accuracy. Traditional econometric methods have been challenged by their inability to capture the frequent fluctuations in construction material prices. This paper reviews the application of data-driven techniques, particularly machine learning, in forecasting construction material prices. The models are categorized into causal modeling and time-series analysis, and characteristics, adaptability, and insights derived from large datasets are discussed. Causal models, such as multiple linear regression (MLR), artificial neural networks (ANN), and the least square support vector machine (LSSVM), generally utilize economic indicators to predict prices. The commonly used economic indicators include but are not limited to the consumer price index (CPI), producer price index (PPI), and gross domestic product (GDP). On the other hand, time-series models rely on historical price data to identify patterns for future forecasting, and their main advantage is demanding minimal data inputs for model calibration. Other techniques are also explored, such as Monte Carlo simulation, for both price forecasting and uncertainty quantification. The paper recommends hybrid models, which combine various forecasting techniques and deep learning-advanced time-series analysis and have the potential to offer more accurate and reliable price predictions with appropriate modeling processes, enabling better decision-making and cost management in construction projects.

The waiting area in dental clinics is a known source of stress for patients. However, positive distractions and comfortable design elements might reduce stress levels and provide mental stimulation while awaiting treatment. While ambient elements might play an important role in patient well-being, few studies have directly explored the impact of various design attributes of dental clinic waiting areas on patients’ perceived stress. This study intended to bridge that gap and employed a discrete choice experiment method where 250 participants randomly selected a block and evaluated six pairs of computer-generated images of dental clinic waiting areas created based on eight interior design attributes with various levels: ambient lighting, false ceiling, window size, window view, indoor plants, wall shape, wall material, and seating options. Each visitor chose their preferred option in relation to its presumed effect on stress mitigation. The results suggest that the presence of ambient lighting, a false ceiling with a nature design, large window dimensions, a nature window view, green indoor plants, a curved wall shape, natural wall materials, and mixed seating options all can contribute to mitigating patients’ perceived stress. Additionally, our findings indicate that age, gender, and education might influence choices across some levels of these variables. Overall, these results might assist architects and designers in shaping clinic environments mitigating patient stress during visits. Further studies would be needed to validate our findings and should also consider additional design attributes, more immersive stimuli presentation technologies, as well as potential differences across cultural contexts.

This research aims to develop principles for assessing the impact of mega-cyclic vibrodynamic loads on the reliability of construction structures. The relevance of the reasons for the development and improvement of algorithms for numerical modeling of multicycle dynamic loads on building structures is due to the steadily increasing intensity of such loads on buildings and structures in megacities, as well as the acute practical problem of significant differences in the dynamic characteristics of buildings and structures obtained as a result of mathematical modeling and determined by experimental methods. The article presents research materials on computational equivalent models of dynamic load sources for numerical modeling of the behavior of construction structures under their influence, using the method of vibroacoustic analogies. The article examines models of sources of dynamic impact on construction sites. Algorithms and final formulas for computational modeling of the simplest sources of dynamic load are developed using the method of vibroacoustic analogies. The dynamic properties of the simplest dynamic load sources were analyzed. A significant difference between the computational models of real and ideal dynamic load sources. The article presents research and development results intended for calculating the distribution of dynamic loads on elements of construction structures in industrial and civil engineering projects located in areas with high levels of transport vibrodynamic impacts. An important property of the proposed computational equivalent models of sources of dynamic impact on building structures is the possibility of computational verification of critical elements, points, or nodes of load-bearing structures of buildings and structures under dynamic overloads. The position of these critical elements, points, and nodes of load-bearing structures under dynamic loads can differ significantly from their position determined using static and quasistatic computational modeling methods.

The mechanisms underlying the effects of wind and buoyancy on ventilation in urban street canyons are unclear. This study investigated the effects of facade heating on ventilation and pollutant transport in an idealized street canyon with a 1.67 aspect ratio through computational fluid dynamics simulations. The dispersion pattern of discharged hot pollutants was also studied. A primary recirculation was observed when facade heating was not applied; this recirculation was promoted in leeward-wall and ground heating cases. However, the recirculation was bifurcated into two recirculations in windward-wall heating cases, restricting ventilation. Enhanced recirculation increased the ventilation and decreased the pollution level; by contrast, air pollution increased considerably when the recirculation was bifurcated and ventilation was restricted. In the hot-pollutant case, similar results to those in the ground-heating case were observed. The hot discharged pollutant enhanced ventilation, reducing pollution. The pollutant transport mechanism was determined through an analysis of pollutant fluxes. For the one-recirculation pattern, air convection transported the pollutant from the ground level to the top boundary, and turbulent diffusion then caused pollutant removal. For the two-recirculation pattern, turbulent diffusion contributed substantially to pollutant transport both in the junction between the recirculations and through the top boundary of the street canyon.

In recent times, climate change has become more evident than ever, and measures to slow down its negative effects are imperative for the future of the world. The scientific and economic communities of countries around the world, under the force of international climate agreements, are identifying solutions to reduce greenhouse gas (GHG) emissions by establishing appropriate measures and developing new strategies. In the context of these objectives, the effort to identify eco-sustainable practices for the construction industry is growing significantly. Recently, much research has focused on solutions for producing green building materials, as well as applying circular economy principles to achieve a balance between anthropogenic emissions and absorptions by greenhouse gas absorbers. The relevant indicators of the level of achievement of these major objectives can be identified, already from the construction design phase, with the help of Life Cycle Assessment (LCA) analysis. This paper presents a series of environmental impact analyses for an eco-friendly solution of precast concrete masonry blocks. Ecological concrete is manufactured with aggregates from biological waste resulting from hemp crops. Impact assessments were performed with the SimaPro 9.5 software application. Research has shown that in the production chain, which includes the materials resulting from the recycling and reuse of hemp concrete blocks, the contribution to the effort to achieve neutrality in terms of global warming is significant. The Cradle-to-Cradle scenario revealed that the recycling of hemp concrete masonry blocks at the end of their use, for a functional unit of 0.5 m3, has a GHG emission of 33.5228 [kg CO2-eq] and CO2 uptakes can reach the negative value of −53.8397 [kg CO2-eq]. Thus, the balance of GHG emissions is negative, with values of approximately −20.3169 [kg CO2-eq]. The LCA analyses also reflect a decreased damage to human health, natural resources, and biodiversity when hemp concrete is used for masonry blocks.

In 2009, the International Building Code (IBC) introduced a new requirement for an additional exit stair or evacuation elevators in buildings (except residential buildings) over 420 ft. (128 m) tall. This new requirement has emerged as a critical innovation in occupant evacuation in supertall buildings, offering the potential for faster egress during emergencies. In the 2018 edition of the IBC, the analysis of full building evacuation with elevators is further required to demonstrate an evacuation time of less than 1 h. This paper examines the implementation of evacuation elevators in accordance with recent building code developments, such as the International Building Code (IBC), Chinese “General Code for Fire Protection of Buildings and Constructions” (GB 55037-2022), and the Korean Building Code (KBC). This study provides a comparative analysis of these regulations, highlighting the evolving acceptance of elevator-based evacuation methods. Since the requirements on means of egress in the codes in China and Korea follow similar concepts in the IBC, case studies of supertall buildings in China and Korea, where evacuation elevators were integrated into the overall egress strategy, are carried out to demonstrate the capability of evacuation elevators in achieving the IBC’s requirement for full evacuation within one hour. Using computer-based egress modeling, the study evaluates practical solutions for reducing evacuation times, exploring factors such as elevator capacity, speed, and coordination with traditional stairwell egress. The results suggest that, while evacuation elevators can significantly improve evacuation efficiency, achieving the one-hour target remains a challenge in complex, high-occupancy environments. The study indicates the importance of optimizing the balance between stair and elevator usage and explores the future role of artificial intelligence (AI) in enhancing evacuation systems.

This study explores the deformation characteristics of surrounding rock during tunnel construction through fault fracture zones. A numerical model is established using ABAQUS to analyze the interaction between the shield machine, support system, and geotechnical materials. The model incorporates key factors, including palm face support force, grouting pressure, and the friction between the shield shell and surrounding rock. The results show that the plastic zone of the surrounding rock is concentrated within the fault zone and at the junction with normal rock, propagating along the contact surface. In the loosening zone, stress and strength are significantly reduced, leading to crack expansion and plastic slip. Without adequate support, these conditions can result in tunnel destabilization. The displacement of the surrounding rock is most prominent during the detachment of the shield tail and the synchronized grouting phase. These findings provide valuable insights for improving tunnel construction safety and stability in fault fracture zones, where the integrity of the surrounding rock is compromised by fractures and fissures. However, the constructed models may restrict the ability to capture all complex material behaviors and interactions that could arise in actual field conditions.

The article explores passive systems for regulating microclimates in residential settings, with a focus on modular constructions. It investigates the use of the trombe wall system for passive ventilation to ensure comfort and hygiene. The study examines building designs that enable effective air circulation without using mechanical systems. Furthermore, the effectiveness of the passive system of using solar energy with the trombe wall as a ventilation device in modular houses has been experimentally confirmed. Although the research confirms the effectiveness of this solar system in modular homes, there is limited documentation regarding its overall efficiency, particularly concerning the impact of the surface pressure coefficient on ventilation. The study establishes the correlations governing the thermosiphon collector’s effectiveness at varying air layer thicknesses. Optimal parameters, such as maximum air consumption (L = 120 m3h−1), are identified at an air layer thickness (δ) of 100 mm and outlet openings area (F) of 0.056 m2. These findings pave the way for improving passive systems aimed at maintaining optimal thermal and air conditions in modern homes. The findings suggest the potential for more efficient and sustainable housing solutions. Further research is essential to understand how factors like building design and wind speed affect ventilation system efficacy.

Quito, the capital of Ecuador, a development pole, has experienced a population growth of 9% in the last five years. The structural system commonly chosen for housing is reinforced concrete frames with flat slabs, embedded beams, and masonry infill. This typology covers approximately 60% of the residential buildings in the city. Adding to the site’s seismic hazard, this fact results in a city with a high seismic risk. The research presented here is carried out within a probabilistic framework to determine the economic consequences of the main structural typology in the city. The methodology defines the seismic hazard by scaling a database of 200 records to the design spectrum. It models the typology to capture the variability between structures with a solid parametric study. Each capacity curve is analyzed through a nonlinear time history analysis using an equivalent one-degree-of-freedom system. The results show an average annual loss ratio of 0.16%. This metric indicates the vulnerability of the typology and the high repair costs of buildings that will be observed in case of an earthquake. The practical implications of these findings are significant as they contribute to urban planning and policy decisions. Finally, it is observed that the probabilistic method used efficiently generates fragility and vulnerability curves, saving computational time and obtaining expected results.

Aiming to solve the problems that a wind turbine foundation with a foundation pipe may suffer from grouting, where the concrete around the interface collapses and the interface disintegrates under a long-term wind load, a kind of wind turbine foundation with a constrained structural shear connector is proposed. In this article, the scaling model tests and a finite element simulation of a traditional stud foundation pipe, perforated steel shear connector foundation pipe, and three groups of constrained structural shear connector foundation pipes with different anchored depths are presented. The force transmission mechanism and damage mechanism of constrained structural shear connector wind turbine foundations are revealed, and the shear resistance of a constrained structural shear connector is analyzed. The influences of buried depth and other parameters on the mechanical properties of the shear connector are also investigated. The results show that the constrained structural shear connector has the advantages of stronger interfacial stiffness and significant force transfer and diffusion, and can more effectively connect the foundation pipe and concrete foundation to work together. It can give full play to the material advantages of concrete and reinforcements, and effectively improve the embedded stiffness and durability of concrete foundations. It can solve the problem of cracks in concrete caused by local pressure. At the same time, it is suggested that the diameter of the surrounding concrete should be in the range of 3 to 4 D, and the embedment depth of the stud should not be less than 0.4 D to give full play to the performance of the constrained structural shear connector.

Every country in the world, except for African nations, faces significant challenges due to the increasing older population, with China being particularly affected. This issue is more pronounced in rural areas compared to urban centers. To better understand consumer attitudes and willingness to pay (WTP) for age-friendly retrofitting and to identify industry development shortcomings, this study designed a retrofitting scenario and organized a questionnaire survey to collect WTP and its influencing factors from respondents in the Wuhu area of Anhui Province, China. This study determined the retrofit cost to be CNY 12,224.4 and found that over 80% of respondents intended to pursue age-friendly retrofitting. The analysis results indicated that respondents’ education level, perceived psychological benefits, and perceived social benefits were positively correlated with their WTP. Additionally, education level, monthly personal income, and choice of retirement area positively influenced retrofitting budgets, whereas age bracket, employment status, and perceived situational risk negatively influenced them. The study’s findings will assist consumers in making informed retrofitting decisions and support the government in formulating appropriate policies to enhance the quality of rural residential environments and improve the living standards of the elderly.

Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with strategic objectives. A key factor in effectively implementing Lean to improve strategic control is developing specific strategies and planning that consider their complex interactions. Thus, this paper aims to propose a quantitative network-based model by integrating Interpretive Structural Modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) under complex network theory to develop a Lean implementation framework for effective strategy formulation. Specifically, 17 Lean implementation strategies for PC in the context of the Chinese prefabrication industry were identified via an extensive literature review and expert interviews. Then, ISM-MICMAC quantitatively identifies the direct and indirect relationships among strategies, while subsequent analysis of Topological Structure Weight (TSW) and Structural Degree Weight (SDW), as complex network parameters, is used to evaluate the importance of each strategy. The findings show that the strategic planning for Lean implementation in PC consists of four levels, i.e., foundation, organizational, technical, and control. Selecting appropriate Lean tools and technologies is crucial for PC implementation, which must be built on a top-level management team and foster a Lean culture. Moreover, it involves building a standardized system of processes and activities, enhancing both internal and external collaboration, and continuously improving processes in response to changes. On one hand, this in-depth network-based analysis offers practical insights for PC stakeholders, particularly in China, on Lean implementation in line with PC performance and strategic control and objectives. On the other hand, the network-based model can be future-implemented globally. Additionally, this study expands the current body of knowledge on Lean in PC by exploring the interrelationships of Lean implementation strategies.

The overall reinforcement of soft soil foundation has the disadvantages of large engineering quantity and high cost. When the pile foundation bears horizontal loads in the soil, the mechanical properties of the soil near the surface have a greater impact on it compared to the deep soil. Therefore, studying the influence of shallow soil reinforcement on the horizontal bearing capacity of pile foundations has important engineering significance. Studying the influence of shallow soft soil reinforcement around piles on the horizontal bearing performance of piles is of great significance for improving the economic efficiency of pile foundation reinforcement technology in soft soil areas. In this paper, seven pile-soil finite element models are established based on ABAQUS 2022 software to study the influence of shallow reinforcement on the horizontal bearing capacity of single pile. The models were established on the basis of a field test and its validity was verified. The influence of different reinforcement degrees on the horizontal bearing capacity of piles is analyzed by taking the reinforcement width and reinforcement depth as variables. The results indicate that shallow ground improvement significantly enhances the horizontal bearing capacity of the pile. The horizontal bearing capacity of the pile is increased by 83.0%, 104.3%, and 224.4%, respectively, corresponding to a reinforcement width of 2 times, 3 times, and 4 times the diameter of the pile, respectively. With the increase of the reinforcement width, the bending moment and deformation of the pile under the same horizontal load decrease significantly, while it has no significant effect on the location of the maximum bending moment of the pile. The bearing capacity of the pile foundation gradually increases with the increase of the reinforcement depth. Compared with the unreinforced situation, the horizontal bearing capacity of the pile body is increased by 224.4%, 361.3%, and 456.8%, respectively, corresponding to a reinforcement depth of 0.1 times, 0.2 times, and 0.3 times the pile length. As the reinforcement depth increases, the corresponding increase in bearing capacity does not increase linearly, but gradually decreases. This indicates that blindly carrying out deep soil reinforcement without comprehensive evaluation is not advisable.

Shrinkage of concrete during hardening is a serious problem in attempts to maintain the integrity of concrete structures. One of the methods of combating shrinkage is compensating for it using an expansive agent. The purpose of this work is to develop and study an expanding agent to concrete, including high-calcium fly ash and calcium nitrate as an expansion activator. The content of Ca(NO3)2 can be used to regulate the degree of expansion of the additive itself during hydration and, accordingly, to control shrinkage, thus obtaining shrinkage-free or expanding concrete. Shrinkage–expansion deformations of concrete can also be regulated by the amount of expanding additive replacing part of the cement. With the Ca(NO3)2 content of fly ash being 10% or more, concrete experiences expansion in the initial stages of hardening. The transition of deformation through 0 to the shrinkage region occurs depending on the composition and content of the additive after 8–15 days of hardening. It has been established that replacing cement with pure fly ash with a curing period of 90 days or more has virtually no effect on the strength of concrete, either in bending or in compression. The use of an expanding additive containing 5–15% Ca(NO3)2 reduces the strength of concrete by an average of 9%, despite the fact that calcium nitrate is a hardening accelerator.

Rock-filled concrete (RFC) is an advanced construction material that integrates high-performance self-compacting concrete (HSCC) with large rocks exceeding 300 mm, providing advantages such as reduced hydration heat and increased construction processes. The elastic modulus of RFC is a critical parameter that directly influences its structural performance, making it vital for modern construction applications that require strength and stiffness. However, there is a scientific gap in understanding the effects of rock size, shape, arrangement, and volumetric ratio on this parameter. This study investigates these factors using mesoscale finite element models (FEMs) with spherical and polyhedral rocks. The results reveal that polyhedral rocks increase the elastic modulus compared to spherical rocks, enhancing RFC’s load-bearing capacity. Additionally, a 5% increase in the elastic modulus was observed when the rockfill ratio was increased from 50% to 60%, demonstrating a direct correlation between rock volume and mechanical performance. Furthermore, the elastic modulus rises significantly in the early stages of placement, followed by a gradual increase over time. Optimal rock sizes and a balanced mix of rock shapes allow for improved concrete flow and mechanical properties, making RFC a highly efficient material for construction. These findings offer valuable insights for designers and engineers looking to optimize RFC for structural applications.

The spatial variability of land surface temperature (LST) is considerably affected by urban morphology. Previous research has focused separately on the thermal effects of urban morphology and the cooling effects of water bodies and urban parks. However, the combined influence of intra- and extra-block factors on LST has not been thoroughly examined. To bridge this research gap, we conducted an extensive analysis of 17 urban morphology factors in Hangzhou by employing a novel stacked ensemble approach. Results showed that the stacked ensemble models outperformed commonly used techniques, such as random forest and boosted regression trees. Extra-block factors, alongside building density, average building height, and vegetation coverage within blocks, predominantly influenced the LST distribution across all seasons. Building density was positively correlated with LST, with a maximum influence of 1.5 °C in spring, whereas building height was negatively correlated with it, with a maximum influence of 1.8 °C in winter. The cooling distance of the Qiantang River extends up to 2500 m into the urban blocks and has a maximum effect of 2 °C in summer. These insights deepen our comprehension of the interplay between LST and intra- and extra-block urban morphologies, thus offering valuable guidance for urban planners and policymakers.

Managing the fragmented nature of information generated on construction sites and firms is the need of the hour. Building Information Modeling (BIM) and Enterprise Resource Planning (ERP) are the most prevalent information systems (ISs) used in the construction industry, with varied capabilities but also with significant overlap. It is essential to analyze the current state of Common Data Environments (CDEs) that support both BIM and ERP as separate systems, as well as those that facilitate their integration. This analysis will ultimately help establish a practical framework for implementing this integration, enabling smoother information flow and enhanced utilization in construction projects. This paper presents a bibliometric analysis and provides a global perspective on research developments in the field of construction ERP and its integrations with BIM. It consolidates publication data from various databases (e.g., Scopus and Web of Science) as per geographical spread, authors, and number of publications as per the keyword search. It observes key research themes in each phase of the analysis. This paper concludes that although the existing literature has established the benefits of BIM and ERP integration, research is still in its nascent stage and identifies research gaps that can be taken up for further research.

The pavilion is a time-honored architectural form in the Chinese silhouette with strong regional characteristics. Its appearance and technical means are often adaptively combined according to the characteristics of local architecture. The “kiln–house isomorphism” is a unique construction technology of the Shanxi construction type in China. Therefore, the “kiln–house isomorphism” is generally adopted for the construction of pavilions in Shanxi. This study focuses on Xiaonanzhuang Village, Yuci District, Jinzhong City, Shanxi Province. Taking the Xiang-ming Pavilion, the core building of the village, as an example, we analyze the architectural characteristics of the “kiln–house isomorphism” in the pavilion in this area, describe the general construction rules of the region, and conduct a deep investigation of the five “cultural isomerism” factors of the pavilions in the region, namely, geomancy, etiquette and music, beliefs, clans, and cultivation and study. The results of this research will enrich the regional knowledge of such pavilions and add new objects for the protection of local architectural heritage, providing a theoretical basis for the contemporary adaptive reuse of pavilions in the Yuci area from a cultural perspective.

Precast concrete components have attracted a lot of attention due to their efficient production on off-site production lines. However, in the precast component production process, unreasonable production sequence and mold layout will reduce production efficiency and affect the workload balance between each process. Due to the multi-species and small-lot production characteristics of precast concrete components, the number of molds corresponding to each precast concrete component is generally limited. In this paper, a production sequence and layout optimization model for assembling precast concrete components under a limited number of molds is proposed, aiming to improve the comprehensive utilization efficiency of the mold tables and balance the workload between each production process of precast components. In order to obtain a better production sequence and a richer combination of mold layout schemes, a multi-objective teaching-learning-based optimization algorithm based on the Pareto dominance relation is developed, and an enhancement mechanism is embedded in the proposed algorithm. To verify the superior performance of the enhanced teaching-learning-based optimization algorithm in improving the comprehensive utilization efficiency of the mold tables and balancing the workload between various processes, three different sizes of precast concrete component production cases are designed. The research results show that the proposed model and optimization algorithm can help production managers to efficiently formulate more reasonable precast component production sequence and layout schemes, especially for those enterprises that are struggling to improve the efficiency of precast concrete component production.

To investigate the nonlinear flutter characteristics of long-span suspension bridges under different deck ancillary structures and configurations, including those with and without a central wind-permeable zone, as well as to analyze the hysteresis phenomenon of a subcritical flutter and elucidate the mechanisms leading to the occurrence of nonlinear flutter, this paper studies first the post-flutter characteristics of the torsion single-degree-of-freedom (SDOF) test systems and vertical bending–torsion two-degree-of-freedom (2DOF) test systems under different aerodynamic shape conditions are further analyzed, and the role of the vertical vibration in coupled nonlinear flutter is discussed. The results indicate that better flutter performance is achieved in the absence of bridge deck auxiliary structures with a central wind-permeable zone. The participation of vertical vibrations in the post-flutter vibration increases with the increase in wind speed, reducing the flutter performance of the main girder. Furthermore, the hysteresis phenomenon in the subcritical flutter state is observed in the wind tunnel experiment, and its evolution law and mechanism are discussed from the perspective of amplitude-dependent damping. Finally, the vibration-generating mechanism of the limit oscillation ring is elaborated in terms of the evolution law of the post-flutter vibration damping.

The housing market in Dar es Salaam, Tanzania, is expanding and with it a need for increased market transparency to guide investors and other stakeholders. The objective of this paper is to evaluate machine learning (ML) methods to appraise real estate in formal and informal housing markets in this nascent market sector. Various advanced ML models are applied with the aim of improving property value estimates in a market with limited access to information. The dataset used included detailed property characteristics and transaction data from both market types. Regression, decision trees, neural networks, and ensemble methods were employed to refine property appraisals across these settings. The findings indicate significant differences between formal and informal market valuations, demonstrating ML’s effectiveness in handling limited data and complex market dynamics. These results emphasise the potential of ML techniques in emerging markets where traditional valuation methods often fail due to the scarcity of transaction data.

Following the Northridge and Kobe earthquakes, research has increasingly focused on achieving high ductility in beam-to-column connections. This study investigates the seismic performance of connections featuring widened beam-end flanges in mid-flange H-beams and box columns, an area with limited prior research compared to I-section columns and narrow-flange H-beams. Detailed finite element modeling using ABAQUS 6.1.4 demonstrates that widened beam-end flanges significantly improve bending capacity and ductility by relocating the plastic hinge away from the connection, thereby enhancing seismic resilience. Key findings include the identification of optimal design parameters: flange length ranging from 0.55 to 0.75 times the beam flange width, beam flange cutting length between 0.36 and 0.39 times the beam depth, and flange cutting depth from 0.19 to 0.23 times the beam flange width. These parameters ensure effective plastic hinge development and improved structural performance. This study introduces a novel approach that emphasizes geometric optimization over material-based enhancements, offering a cost-effective and practical solution for improving seismic performance and extending previous research insights.

Most of the current machine learning algorithms are applied to predict the jacking force required in micro-tunneling; in contrast, few studies about long-distance, large-section jacking projects have been reported in the literature. In this study, an intelligent framework, consisting of a differential evolution (DE), a bidirectional gated re-current unit (BiGRU), and attention mechanisms was developed to automatically identify the optimal hyperparameters and assign weights to the information features, as well as capture the bidirectional temporal features of sequential data. Based on field data from a pipe jacking project crossing underneath a canal, the model’s performance was compared with those of four conventional models (RNN, GRU, BiGRU, and DE–BiGRU). The results indicated that the DE–BiGRU–attention model performed best among these models. Then, the generalization performance of the proposed model in predicting jacking forces was evaluated with the aid of a similar case at the site. It was found that fine-tuning parameters for specific projects is essential for improving the model’s generalization performance. More generally, the proposed prediction model was found to be practically useful to professionals and engineers in making real-time adjustments to jacking parameters, predicting jacking force, and carrying out performance evaluations.

In the context of global warming and the frequent occurrence of extreme weather, coastal cities are more susceptible to the heat island effect and localized microclimate problems due to the significant influence of the oceanic climate. This study proposes a computer-driven simulation optimization method based on a multi-objective optimization algorithm, combined with tools such as Grasshopper, Ladybug, Honeybee and Wallacei, to provide scientific optimization decision intervals for morphology control and evaluation factors at the initial stage of coastal city block design. The effectiveness of this optimization strategy is verified through empirical research on typical coastal neighborhoods in Dalian. The results show that the strategy derived from the multi-objective optimization-based evaluation significantly improves the wind environment and thermal comfort of Dalian neighborhoods in winter and summer: the optimization reduced the average wind speed inside the block by 0.47 m/s and increased the UTCI by 0.48 °C in winter, and it increased the wind speed to 1.5 m/s and decreased the UTCI by 0.59 °C in summer. This study shows that the use of simulation assessment and multi-objective optimization technology to adjust the block form of coastal cities can effectively improve the seasonal wind and heat environment and provide a scientific basis for the design and renewal of coastal cities.

Monitoring the actual vibration coverage is critical for preventing over- or under-vibration and ensuring concrete’s strength. However, the current manual methods and sensor techniques fail to meet the requirements of on-site construction. Consequently, this study proposes a novel approach for estimating the pose of concrete vibrator racks. This method integrates the Linear Spatial Kernel Aggregation (LSKA) module into the You Only Look Once (YOLO) framework to accurately detect the keypoints of the rack and then employs the vanishing point theorem to estimate the rotation angle of the rack without any 3D datasets. The method enables the monitoring of the vibration impact range for each vibrator’s activity and is applicable to various camera positions. Given that measuring the rotation angle of a rack in reality poses is challenging, this study proposes employing a simulation environment to validate both the feasibility and accuracy of the proposed method. The results demonstrate that the improved YOLOv8-Pose achieved a 1.4% increase in accuracy compared with YOLOv8-Pose, and the proposed method monitored the rotation angle with an average error of 6.97° while maintaining a working efficiency of over 35 frames per second. This methodology was successfully implemented at a construction site for a high-arch dam project in China.

This paper is based on research placed within the broader framework of the growing environmental impact requirements of building materials. Given this context, wood-based composite materials have emerged as a promising and innovative solution for structural elements. The current work aims to define a system for testing the mechanical behavior of glued laminated timber elements when exposed to high temperatures, in the neighborhood of the pyrolytic decomposition of materials. These tests monitor the transient behavior of the composite material and characterize the parameters involved in the thermo-mechanical analysis of elements constructed using this type of engineered wood product. The tests are used for the calibration of the material models involved in the numerical analysis and for the analysis of potential prototypes, considering the transient thermal load and heat propagation through the materials. By taking such tests, benchmark models and laboratory procedures are defined that can be used in the future to evaluate different materials, existing or new, and material combinations used to construct such a composite.

The floating hoisting of floating production storage and offloading (FPSO) production modules introduces substantial challenges due to the propensity for excessive deformation within the typical tubular truss structures during operations. This research proposes a temporary reinforcement scheme, leveraging finite element method simulations under wind, wave, and current loads, to mitigate deformation concerns. Utilizing DNV GeniE software, this study establishes a finite element model, simulating the floating lifting process and conducting a comparative analysis between pre- and post-reinforcement scenarios. The results demonstrate a significant reduction in maximum stress and deformation, substantiating the efficacy of the reinforcement strategy and underscoring the safety and reliability of such operations. The successful execution of this methodology heralds a promising avenue for marine engineering practices, advocating for the optimization of large-scale offshore module installation.

In this study, 3D-printed reinforced concrete beams were tested for flexural performance and compared with the analytical model based on the material test results. Two cementitious mixes (PSU and GCT) were designed for concrete printing and were mechanically tested and compared. Anisotropies in the compressive strength and modulus of elasticity of printed concrete were observed, applied to the analytical prediction of flexural bending behavior, and validated by actual test results. Significant differences between analytical predictions and experimental tests of the bending behaviors of the printed concrete beams were observed. Furthermore, higher compressive strengths and moduli of elasticity were observed when the loading direction was perpendicular to the printed layers or with the PSU mix. The effect of anisotropic mechanical properties on a reinforced beam was compared to the flexural bending tests for both mixes. The analytical model based on the material test results was compared to the flexural bending test results. The significant errors in the prediction of printed concrete’s structural performance, from 10% to 50%, suggest that factors other than reduced compressive strengths may influence the structural behaviors of printed concrete beams.