Buildings

29 pages, 7183 KB

Open AccessArticle

Exploring Urban Spatial Quality Through Street View Imagery and Human Perception Analysis

by Yonghao Li, Jialin Lu, Yuan Meng, Yiwen Luo and Juan Ren

Buildings 2025, 15(17), 3116; https://doi.org/10.3390/buildings15173116 (registering DOI) - 31 Aug 2025

Amid the global challenges of rapid urbanization, understanding how micro-scale spatial features shape human perception is critical for advancing livable cities. This study pro-poses a data-driven framework that integrates street view imagery, deep learning-based semantic segmentation, and machine learning interpretation models including SHAP [...] Read more.

Amid the global challenges of rapid urbanization, understanding how micro-scale spatial features shape human perception is critical for advancing livable cities. This study pro-poses a data-driven framework that integrates street view imagery, deep learning-based semantic segmentation, and machine learning interpretation models including SHAP analysis to explore the relationship between urban spatial characteristics and subjective perceptions. A total of 12,604 street-level images from Xi’an, China, were analyzed to ex-tract seven spatial indicators. These indicators were then linked with perceptual data across six emotional dimensions derived from the Place Pulse 2.0 dataset. The analysis revealed that natural elements significantly enhance perceived comfort and aesthetics, while high-density built environments can suppress perceived safety and liveliness. Spatial clustering further identified three urban typologies—traditional, transitional, and modern—with distinct perceptual signatures. These findings offer scalable and transferable insights for perception-informed urban design and renewal, particularly in dense urban settings worldwide. Full article

(This article belongs to the Special Issue Computational Design for Low-Carbon and Climate-Responsive Architecture and Urban Environments)

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32 pages, 7267 KB

Open AccessArticle

Solar PV Potential Assessment of Urban Typical Blocks via Spatial Morphological Quantification and Numerical Simulation: A Case Study of Jinan, China

by Yanqiu Cui, Hangyue Zhang and Hongbin Cai

Buildings 2025, 15(17), 3115; https://doi.org/10.3390/buildings15173115 (registering DOI) - 31 Aug 2025

Abstract

With rapid urbanization, rooftop photovoltaic (PV) systems play an important role in mitigating the energy crisis and reducing emissions, yet achieving scientific and cost-effective deployment at the urban block scale remains challenging. This study proposes a transferable framework that integrates spatial morphology quantification, [...] Read more.

With rapid urbanization, rooftop photovoltaic (PV) systems play an important role in mitigating the energy crisis and reducing emissions, yet achieving scientific and cost-effective deployment at the urban block scale remains challenging. This study proposes a transferable framework that integrates spatial morphology quantification, clustering, and numerical simulation to evaluate PV potential in residential blocks of Jinan, China. Six key morphological indicators were extracted through principal component analysis (PCA), and blocks were classified into five typical types, followed by simulations under different PV material scenarios. The main findings are: (1) Block type differences: Cluster 1 achieved the highest annual generation, 61.76% above average, but with a 75.08% cost increase and a 3.54-year payback. Clusters 4 and 5 showed moderate generation and the shortest payback of 2.91–2.97 years, reflecting better energy–economic balance. (2) PV materials: monocrystalline silicon (m-Si) yielded the highest generation, suitable for maximizing output; polycrystalline silicon (p-Si) produced slightly less but reduced costs by 32.43% and shortened payback by 19.58%, favoring cost-sensitive scenarios. (3) Seasonal variation: PV output peaked in February–March and September–December, requiring priority in grid operation and maintenance. The proposed framework can serve as a useful reference for planners in developing PV deployment strategies, with good transferability and potential for wider application, thereby contributing to urban energy transition and low-carbon sustainable development. Full article

(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

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25 pages, 1379 KB

Open AccessArticle

Multi-Agent Deep Reinforcement Learning-Based HVAC and Electrochromic Window Control Framework

by Hongjian Chen, Duoyu Sun, Yuyu Sun, Yong Zhang and Huan Yang

Buildings 2025, 15(17), 3114; https://doi.org/10.3390/buildings15173114 (registering DOI) - 31 Aug 2025

Abstract

Deep reinforcement learning (DRL)-based HVAC control has shown clear advantages over rule-based and model predictive methods. However, most prior studies remain limited to HVAC-only optimization or simple coordination with operable windows. Such approaches do not adequately address buildings with fixed glazing systems—a common [...] Read more.

Deep reinforcement learning (DRL)-based HVAC control has shown clear advantages over rule-based and model predictive methods. However, most prior studies remain limited to HVAC-only optimization or simple coordination with operable windows. Such approaches do not adequately address buildings with fixed glazing systems—a common feature in high-rise offices—where the lack of operable windows restricts adaptive envelope interaction. To address this gap, this study proposes a multi-zone control framework that integrates HVAC systems with electrochromic windows (ECWs). The framework leverages the Q-value Mixing (QMIX) algorithm to dynamically coordinate ECW transmittance with HVAC setpoints, aiming to enhance energy efficiency and thermal comfort, particularly in high-consumption buildings such as offices. Its performance is evaluated using EnergyPlus simulations. The results show that the proposed approach reduces HVAC energy use by 19.8% compared to the DQN-based HVAC-only control and by 40.28% relative to conventional rule-based control (RBC). In comparison with leading multi-agent deep reinforcement learning (MADRL) algorithms, including MADQN, VDN, and MAPPO, the framework reduces HVAC energy consumption by 1–5% and maintains a thermal comfort violation rate (TCVR) of less than 1% with an average temperature variation of 0.35

^{\circ} C

Moreover, the model demonstrates strong generalizability, achieving 16.58–58.12% energy savings across six distinct climatic regions—ranging from tropical (Singapore) to temperate (Beijing)—with up to 48.2% savings observed in Chengdu. Our framework indicates the potential of coordinating HVAC systems with ECWs in simulation, while also identifying limitations that need to be addressed for real-world deployment. Full article

(This article belongs to the Special Issue AI-Driven Cooling, Refrigeration, and Energy Solutions for Built Environments)

34 pages, 10137 KB

Open AccessArticle

Urban-to-Rural Migration as an Influential Factor for Vernacular Village Revitalization: A Building-Scale Assessment of Migrants’ Spatial–Lifestyle Interventions on Traditional Values in Zhejiang, China

by Zhaoteng Jin and Kai Gong

Buildings 2025, 15(17), 3113; https://doi.org/10.3390/buildings15173113 (registering DOI) - 30 Aug 2025

Abstract

Urban-to-rural migration is reshaping vernacular villages through transformations in both architectural form and everyday life. This study focuses on three villages in Zhejiang Province, China, and their migrants from urban areas, investigating—through field surveys and interviews—how urban-to-rural migrants’ spatial and lifestyle interventions influence [...] Read more.

Urban-to-rural migration is reshaping vernacular villages through transformations in both architectural form and everyday life. This study focuses on three villages in Zhejiang Province, China, and their migrants from urban areas, investigating—through field surveys and interviews—how urban-to-rural migrants’ spatial and lifestyle interventions influence the preservation and transformation of traditional architecture and local cultural practices. Findings indicate that urban-to-rural migrants exhibit diverse spatial preferences and lifestyle patterns, leading to varied modes of building adaptation. Some prioritize modern styles and commercial functions, while others emphasize cultural continuity, community engagement, or individual expression. Most buildings undergo incremental modifications rather than complete reconstruction, reflecting a balance among regulatory constraints, financial considerations, and personal aspirations. Furthermore, some migrants retain traditional spatial hierarchies and layout logic in their architectural designs, thereby sustaining vernacular lifestyles such as intergenerational cohabitation and neighborhood interaction. These building practices also have demonstrative effects within the village, encouraging others to value local culture and spatial traditions. In contrast, other migrants, driven by modern aesthetics or commercial objectives, restructure or even disrupt traditional spatial models, resulting in the fragmentation and weakening of established value systems. These insights contribute to a deeper understanding of how urban-to-rural migration reshapes the spatial organization of traditional villages and can inform more flexible and context-sensitive rural planning practices. Full article

(This article belongs to the Special Issue Renewal Design and Challenge of Urban and Rural Livable Environments in the Age of Population Shrinkage)

30 pages, 4983 KB

Open AccessArticle

Multi-Energy Interplay in a Planned District Community with a Large Share of PV-Produced Electricity in a Nordic Climate

by Vartan Ahrens Kayayan, Diogo Cabral, Mattias Gustafsson and Fatemeh Johari

Buildings 2025, 15(17), 3112; https://doi.org/10.3390/buildings15173112 (registering DOI) - 30 Aug 2025

Abstract

The world’s energy system faces major challenges due to transitions from fossil fuels to other alternatives. An important part of the transition is energy-efficient homes that partially produce their own electricity. This paper explores the energy interactions between heating, cooling, and electricity usage [...] Read more.

The world’s energy system faces major challenges due to transitions from fossil fuels to other alternatives. An important part of the transition is energy-efficient homes that partially produce their own electricity. This paper explores the energy interactions between heating, cooling, and electricity usage in a planned residential area in Sweden where a significant portion of the electricity is generated by solar PV systems. Conventional district heating and cooling systems and a low-temperature district heating system that uses return cascading technology were compared with heat pump systems. Electricity sharing in an energy community has a low impact on the calculated national energy efficiency metric. It is also shown that electrifying space heating with heat pumps improves the calculated energy efficiency metric, but heat pumps increase the peak power demand in the winter due to high heat demand and a lack of solar production. Using heat pumps for heating domestic hot water and compressor chillers for cooling offers a more balanced use/production of electricity since the electric cooling load is mostly met by local solar production, as shown by an increase in self-consumption of 8% and stable self-sufficiency. There is, however, a time mismatch between production and the peak electricity demand, which could be addressed by using energy storage systems. Full article

(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

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21 pages, 2197 KB

Open AccessArticle

Experimental and Numerical Bearing Capacity Analysis of Locally Corroded K-Shaped Circular Joints

by Ying-Qiang Su, Shu-Jing Tong, Hai-Lou Jiang, Xiao-Dong Feng, Jian-Hua Li and Jian-Kun Xu

Buildings 2025, 15(17), 3111; https://doi.org/10.3390/buildings15173111 (registering DOI) - 29 Aug 2025

Abstract

This study systematically investigates the influence of varying corrosion severity on the bearing capacity of K-shaped circular-section joints, with explicit consideration of weld line positioning. Four full-scale circular-section joint specimens with clearance gaps were designed to simulate localized corrosion through artificially introduced perforations, [...] Read more.

This study systematically investigates the influence of varying corrosion severity on the bearing capacity of K-shaped circular-section joints, with explicit consideration of weld line positioning. Four full-scale circular-section joint specimens with clearance gaps were designed to simulate localized corrosion through artificially introduced perforations, and axial static loading tests were performed to assess the degradation of structural performance. Experimental results indicate that the predominant failure mode of corroded K-joints manifests as brittle fracture in the weld-affected zone, attributable to the combined effects of material weakening and stress concentration. The enlargement of corrosion pit dimensions induces progressive deterioration in joint stiffness and ultimate bearing capacity, accompanied by increased displacement at failure. A refined finite element model was established using ABAQUS. The obtained load–displacement curve from the simulation was compared with the experimental data to verify the validity of the model. Subsequently, a parametric analysis was conducted to investigate the influence of multiple variables on the residual bearing capacity of the nodes. Numerical investigations indicate that the severity of corrosion exhibits a positive correlation with the reduction in bearing capacity, whereas web-chord members with smaller inclination angles demonstrate enhanced corrosion resistance, when θ is equal to 30 degrees, K_s decreases from approximately 0.983 to around 0.894. Thin-walled joints exhibit accelerated performance deterioration compared to thick-walled configurations under equivalent corrosion conditions. Furthermore, increased pipe diameter ratios exacerbate corrosion-induced reductions in structural efficiency, when the corrosion rate is 0.10, β = 0.4 corresponds to K_s = 0.98, and when β = 0.7, it is approximately 0.965. and distributed micro-pitting results in less severe capacity degradation than concentrated macro-pitting over the same corrosion areas. Full article

(This article belongs to the Special Issue Transformable and Modular Building Systems: Mechanics, Design, and Applications Innovations)

19 pages, 1279 KB

Open AccessArticle

Deteriorated Cyclic Behaviour of Corroded RC Framed Elements: A Practical Proposal for Their Modelling

by José Barradas-Hernández, Dariniel Barrera-Jiménez, Irving Ramírez-González, Franco Carpio-Santamaría, Alejandro Vargas-Colorado, Sergio Márquez-Domínguez, Rolando Salgado-Estrada, José Piña-Flores and Abigail Zamora-Hernández

Buildings 2025, 15(17), 3110; https://doi.org/10.3390/buildings15173110 - 29 Aug 2025

Abstract

Corrosion is a phenomenon that significantly impacts the durability of reinforced concrete (RC) structures, particularly in highly corrosive environments like coastal regions. The existing numerical modelling often relies on complex approaches that are impractical for structural assessment. For this reason, this study proposes [...] Read more.

Corrosion is a phenomenon that significantly impacts the durability of reinforced concrete (RC) structures, particularly in highly corrosive environments like coastal regions. The existing numerical modelling often relies on complex approaches that are impractical for structural assessment. For this reason, this study proposes a simplified numerical modelling approach to simulate the cyclic behaviour of existing RC framed structures with corrosion levels (η) below 25%. The proposed modelling employs concentrated plasticity hinges for beams and fiber sections for columns, incorporating corrosion-induced degradation through modified backbone curves and material properties based on the corrosion level of the structural element. The modelling approach was validated against experimental results from the literature; the proposed model adequately captures hysteretic energy, lateral load, and deformation capacities, with maximum errors of 11% for maximum lateral load, 12% for ultimate load, and 33% for dissipated energy in RC frames. For isolated columns, the errors were 11, 12, and 22%, respectively. In addition, a maximum difference of 7% was found in the lateral load capacity of the corroded frames associated with the Life Safety limit state. Finally, it was concluded that the proposed methodology is suitable for representing the cyclic behaviour of corroded RC columns and frames and provides engineers with a tool to evaluate the behaviour of corroded structures without resorting to complex models. Full article

(This article belongs to the Special Issue Seismic Performance and Durability of Engineering Structures)

67 pages, 3109 KB

Open AccessReview

Assessment of Phase Change Materials Incorporation into Construction Commodities for Sustainable and Energy-Efficient Building Applications

by Ihsan Ur Rahman, Oronzio Manca, Bernardo Buonomo, Meriem Bounib, Shafi Ur Rehman, Hala Salhab, Antonio Caggiano and Sergio Nardini

Buildings 2025, 15(17), 3109; https://doi.org/10.3390/buildings15173109 - 29 Aug 2025

Abstract

The significant energy consumption and contribution to greenhouse gas emissions by the construction sector need careful attention to explore innovative sustainable solutions for improving the energy efficiency and thermal comfort of building envelopes. The integration of phase-change materials (PCMs) into building commodities is [...] Read more.

The significant energy consumption and contribution to greenhouse gas emissions by the construction sector need careful attention to explore innovative sustainable solutions for improving the energy efficiency and thermal comfort of building envelopes. The integration of phase-change materials (PCMs) into building commodities is a favorable technology for minimizing energy consumption and enhancing thermal performance. This review paper covers the impact of PCM incorporation into construction materials, such as walls, roofs, and glazing units. Additionally, it examines different embedding techniques like direct incorporation, immersion, macro and micro-encapsulation, and form and shape-stable PCM. Factors affecting the thermal performance of PCM-integrated buildings, including melting temperature, thickness, position, volumetric change, vapor pressure, density, optical properties, latent heat, thermal conductivity, chemical stability, and climate conditions, are elaborated. Furthermore, the latest experimental and numerical simulations, as well as modeling techniques, evident from case studies, are investigated. Ultimately, the advantages of PCM integration, including energy savings, peak load reduction, improvement in interior comfort, and reduced heating, ventilation, and air-conditioning dependence, are explained alongside the limitations. Finally, the recent progress and future potential of PCM-integrated construction materials are discussed, focusing on innovations in this field, addressing the status of policies in line with the United Nations Sustainable Development Goals, and outlining research potential for the future. Full article

(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

21 pages, 3833 KB

Open AccessArticle

Classifying Metro Station Areas for Urban Regeneration: An RFM Model Approach and Differentiated Strategies in Beijing

by Xiangyu Li, Yinzhen Li, Hongyan Wang, Wenxuan Ma and Nan Zhang

Buildings 2025, 15(17), 3108; https://doi.org/10.3390/buildings15173108 - 29 Aug 2025

Abstract

Amid growing demands for urban regeneration, metro station areas (MSAs) have emerged as critical spatial units for assessing renewal potential. However, their highly heterogeneous functional and spatial attributes pose challenges to precise classification and targeted strategy development. This study introduces the RFM (recency, [...] Read more.

Amid growing demands for urban regeneration, metro station areas (MSAs) have emerged as critical spatial units for assessing renewal potential. However, their highly heterogeneous functional and spatial attributes pose challenges to precise classification and targeted strategy development. This study introduces the RFM (recency, frequency, and monetary) model—originally used in marketing—to the urban renewal domain. By mapping POI (point of interest) data, population density, and land price to the RFM dimensions, a three-dimensional evaluation framework is constructed. Using QGIS to process multi-source data for 118 MSAs in Beijing, we apply an improved five-quantile stratification method to classify station areas into eight renewal potential types. The results reveal a concentric spatial gradient: 24% of core-area MSAs are identified as Key-Value MSAs, while 23% of peripheral MSAs are categorized as General-Retention MSAs. Based on the classification, differentiated renewal strategies are proposed: high-potential MSAs should prioritize public space enhancement and walkability improvements, whereas low-potential MSAs should focus on upgrading basic transit infrastructure. The study provides a replicable method for classifying MSAs based on spatial and economic indicators, offering new theoretical insights and practical tools to guide evidence-based urban regeneration and station–city integration in high-density metropolitan areas such as Beijing. Full article

(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)

18 pages, 3914 KB

Open AccessArticle

Design and Performance of High-RAP-Content Asphalt Mixture: A Case Study in Jianghe Expressway

by Haiqi Zhang, Zhiyong Ma, Yimin Huang, Zhengquan Zhang, Xiaomiao Xiang, Mingkun Luo and Huayang Yu

Buildings 2025, 15(17), 3107; https://doi.org/10.3390/buildings15173107 - 29 Aug 2025

Abstract

Rapid expansion of global transportation infrastructure leads to the accumulation of vast quantities of reclaimed asphalt pavement (RAP). Recycling RAP is essential for reducing environmental impacts. However, current recycling practices typically limit RAP content to below 30%. Increasing RAP content in asphalt mixtures—especially [...] Read more.

Rapid expansion of global transportation infrastructure leads to the accumulation of vast quantities of reclaimed asphalt pavement (RAP). Recycling RAP is essential for reducing environmental impacts. However, current recycling practices typically limit RAP content to below 30%. Increasing RAP content in asphalt mixtures—especially beyond 50%—offers a more sustainable approach, but also introduces challenges in performance, design, and implementation. This study presents a case in which the hot central plant recycling asphalt mixture containing 50% RAP, enhanced with an active rejuvenating agent, was used for the lower layer of the Jianghe Expressway. The aggregate gradation was designed using the Marshall method, with the optimal asphalt–aggregate ratio determined to be 3%. The average compaction degree was 98.9%, the infiltration coefficient ranged from 6.43 mL/min to 23.77 mL/min, and the standard deviation of flatness did not exceed 1.0. However, material shoving was observed during paving, suggesting that, with appropriate adjustments, the technique can be optimized for large-scale implementation. The gradation of the RAP material showed minimal deviation from the design gradation, remaining within ±5%. The compaction scheme with eight roller passes and a loose paving coefficient of 1.35 yielded superior compaction performance. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

17 pages, 2171 KB

Open AccessArticle

Seismic Damage Assessment of SRC Frame-RC Core Tube High-Rise Structure Under Long-Period Ground Motions

by Lianjie Jiang, Guoliang Bai, Lu Guo and Fumin Li

Buildings 2025, 15(17), 3106; https://doi.org/10.3390/buildings15173106 (registering DOI) - 29 Aug 2025

Abstract

To accurately assess the seismic damage of high-rise structures under long-period ground motions (LPGMs), a 36-story SRC frame-RC core tube high-rise structure was designed. Twelve groups of LPGMs and twelve groups of ordinary ground motions (OGMs) were selected and bidirectionally input into the [...] Read more.

To accurately assess the seismic damage of high-rise structures under long-period ground motions (LPGMs), a 36-story SRC frame-RC core tube high-rise structure was designed. Twelve groups of LPGMs and twelve groups of ordinary ground motions (OGMs) were selected and bidirectionally input into the structure. The spectral acceleration S_90c considering the effect of higher-order modes was adopted as the intensity measure (IM) of ground motions, and the maximum inter-story drift angle θ_max under bidirectional ground motions was taken as the engineering demand parameter (EDP). Structural Incremental Dynamic Analysis (IDA) was conducted, the structural vulnerability was investigated, and seismic vulnerability curves, damage state probability curves, vulnerability index curves, as well as the probabilities of exceeding performance levels and vulnerability index of the structure during 8-degree frequent, design, and rare earthquakes were obtained, respectively. The results indicate that structural damage is significantly aggravated under LPGMs, and the exceeding probabilities for all performance levels are greater than those under OGMs, failing to meet the seismic fortification target specified in the code. When encountering an 8-degree frequent earthquake, the structure is in a moderate or severe damage state under LPGMs and is basically intact or in a slight damage state under OGMs. When encountering an 8-degree design earthquake, the structure is in a severe damage or near-collapse state under LPGMs and is in a moderate damage state under OGMs. When encountering an 8-degree rare earthquake, the structure is in a near-collapse state under LPGMs and in a severe damage state under OGMs. Full article

(This article belongs to the Special Issue Building Safety Assessment and Structural Analysis)

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17 pages, 1822 KB

Open AccessArticle

Mechanical Behavior of Geopolymers Containing Soil and Red Mud Stabilized by Alkali Activation

by Ana Carolina Pereira da Silva, Klaus Henrique de Paula Rodrigues, Gustavo Henrique Nalon, Heraldo Nunes Pitanga, Natália Assunção Brasil Silva, Taciano Oliveira da Silva, Emerson Cordeiro Lopes and Mateus Henrique Ribeiro Rodrigues

Buildings 2025, 15(17), 3105; https://doi.org/10.3390/buildings15173105 - 29 Aug 2025

Abstract

The urgent demand for environmentally responsible construction practices has intensified interest in geopolymer concrete mixtures, which offer low-carbon alternatives to conventional Portland cement by enabling the valorization of industrial by-products. Since the large volume of waste generated by mining activities represents a significant [...] Read more.

The urgent demand for environmentally responsible construction practices has intensified interest in geopolymer concrete mixtures, which offer low-carbon alternatives to conventional Portland cement by enabling the valorization of industrial by-products. Since the large volume of waste generated by mining activities represents a significant environmental liability, this research aimed to utilize the alkali activation technique in mixtures of soil and bauxite residue, commonly known as red mud (RM), for application in green construction. All raw materials were characterized based on their physical and chemical properties. To evaluate the influence of waste content on the mechanical behavior of the geopolymers, specimens were prepared with soil contents ranging from 70% to 100% and RM dosages ranging from 0% to 30%. These mixtures underwent compaction tests using the standard Proctor energy method to determine maximum dry density and optimum moisture content. Using the optimal mixture compositions, specimens were prepared for unconfined compressive strength (UCS) tests, with NaOH at a concentration of 6 mol/L added as an activator. The experimental tests provided UCS results ranging from 2.23 MPa to 3.05 MPa. X-ray diffraction (XRD) analyses were performed on raw materials and mixtures containing 70% soil and 30% waste to assess changes in mineralogical compositions due to waste incorporation. The results confirmed the potential of alkali activation for stabilizing mixtures of soil and RM for sustainable construction. Full article

(This article belongs to the Special Issue Recent Advances in Sustainable Low-Carbon Materials for Green Concrete)

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24 pages, 6201 KB

Open AccessArticle

Study on Physical Properties and Bearing Capacity of Quaternary Residual Sand for Building Foundations: A Case Study of Beaches in Quanzhou, China

by Lin Su, Feng Zhang, Chuan Peng, Guohua Zhang, Liming Qin, Xiao Wang, Shuqi Yang and Wenyao Peng

Buildings 2025, 15(17), 3104; https://doi.org/10.3390/buildings15173104 - 29 Aug 2025

Abstract

This study addresses engineering challenges associated with sandy residual deposits in the coastal zone of Quanzhou, China, characterized by high void ratios (e > 0.8), low cohesion (c < 10 kPa), and strong liquefaction tendencies induced by marine dynamic forces. Focusing [...] Read more.

This study addresses engineering challenges associated with sandy residual deposits in the coastal zone of Quanzhou, China, characterized by high void ratios (e > 0.8), low cohesion (c < 10 kPa), and strong liquefaction tendencies induced by marine dynamic forces. Focusing on the beach sands of Shenhu Bay and Qingshan Bay, 123 in situ dynamic penetration tests and 12 laboratory physical–mechanical tests (including water content, particle gradation, relative density, and triaxial shear strength) were conducted. The correlations between the physical and mechanical properties of these coastal sandy soils and their foundation bearing capacity were systematically analyzed. Results reveal that the sands, predominantly medium-to-fine grains with 8–15% biogenic debris, are generally in a loose-to-medium dense state (relative density ~34%), with negligible cohesion. Shear strength depends primarily on the internal friction angle (28.89–37.43°). Correlation analyses show that water content (17.8–31.92%) and particle gradation parameters (uniformity coefficient C_u and curvature coefficient C_c) significantly influence bearing capacity, with bearing capacity increasing by 12.15% per 14.12% rise in water content and 35% per 0.518 increase in C_c. An improved foundation bearing capacity model based on the Prandtl–Reissner theory is proposed by integrating particle gradation and water content, tailored for beach foundations in Quanzhou. Model validation demonstrates an average error of approximately 15%, outperforming traditional models. These findings provide valuable theoretical support for assessing foundation stability in building construction projects in Quanzhou and similar coastal regions. Full article

(This article belongs to the Topic Resilient Civil Infrastructure, 2nd Edition)

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25 pages, 8084 KB

Open AccessArticle

Neural Network-Based Prediction of Compression Behaviour in Steel–Concrete Composite Adapter for CFDST Lattice Turbine Tower

by Shi-Chao Wei, Hao Wen, Ji-Zhi Zhao, Yu-Sen Liu, Yong-Jun Duan and Cheng-Po Wang

Buildings 2025, 15(17), 3103; https://doi.org/10.3390/buildings15173103 - 29 Aug 2025

Abstract

The prestressed concrete-filled double skin steel tube (CFDST) lattice tower has emerged as a promising structural solution for large-capacity wind turbine systems due to its superior load-bearing capacity and economic efficiency. The steel–concrete composite adapter (SCCA) is a key component that connects the [...] Read more.

The prestressed concrete-filled double skin steel tube (CFDST) lattice tower has emerged as a promising structural solution for large-capacity wind turbine systems due to its superior load-bearing capacity and economic efficiency. The steel–concrete composite adapter (SCCA) is a key component that connects the upper tubular steel tower to the lower lattice segment, transferring axial loads. However, the compressive behaviour of the SCCA remains underexplored due to its complex multi-shell configuration and steel–concrete interaction. This study investigates the axial compression behaviour of SCCAs through refined finite element simulations, identifying diagonal extrusion as the typical failure mode. The analysis clarifies the distinct roles of the outer and inner shells in confinement, highlighting the dominant influence of outer shell thickness and concrete strength. A sensitivity-based parametric study highlights the significant roles of outer shell thickness and concrete strength. To address the high cost of FE simulations, a 400-sample database was built using Latin Hypercube Sampling and engineering-grade material inputs. Using this dataset, five neural networks were trained to predict SCCA capacity. The Dropout model exhibited the best accuracy and generalization, confirming the feasibility of physics-informed, data-driven prediction for SCCAs and outperforming traditional empirical approaches. A graphical prediction tool was also developed, enabling rapid capacity estimation and design optimization for wind turbine structures. This tool supports real-time prediction and multi-objective optimization, offering practical value for the early-stage design of composite adapters in lattice turbine towers. Full article

(This article belongs to the Section Building Structures)

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17 pages, 3054 KB

Open AccessArticle

Building Instance Extraction via Multi-Scale Hybrid Dual-Attention Network

by Qingqing Hu, Yiran Peng, Chi Zhang, Yunqi Lin, KinTak U and Junming Chen

Buildings 2025, 15(17), 3102; https://doi.org/10.3390/buildings15173102 - 29 Aug 2025

Abstract

Accurate building instance segmentation from high-resolution remote sensing images remains challenging due to complex urban scenes featuring occlusions, irregular building shapes, and heterogeneous textures. To address these issues, we propose a novel Multi-Scale Hybrid Dual-Attention Network (MS-HDAN), which integrates a dual-stream encoder, multi-scale [...] Read more.

Accurate building instance segmentation from high-resolution remote sensing images remains challenging due to complex urban scenes featuring occlusions, irregular building shapes, and heterogeneous textures. To address these issues, we propose a novel Multi-Scale Hybrid Dual-Attention Network (MS-HDAN), which integrates a dual-stream encoder, multi-scale feature extraction, and a hybrid attention mechanism. Specifically, the encoder is designed with a Local Feature Extraction Pathway (LFEP) and a Global Context Modeling Pathway (GCMP), enabling simultaneous capture of structural details and long-range semantic dependencies. A Local-Global Collaborative Perception Enhancement Module (LG-CPEM) is introduced to fuse the outputs from both streams, enhancing contextual representation. The decoder adopts a hierarchical up-sampling structure with skip connections and incorporates a dual-attention module to refine boundary-level details and suppress background noise. Extensive experiments on benchmark urban building datasets demonstrate that MS-HDAN significantly outperforms existing state-of-the-art methods, particularly in handling densely distributed and structurally complex buildings. The proposed framework offers a robust and scalable solution for real-world applications, such as urban planning, where precise building segmentation is crucial. Full article

(This article belongs to the Special Issue Practice and Application of Artificial Intelligence in Urban Decision-Making)

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23 pages, 6161 KB

Open AccessArticle

Investigation of Screw Layout and Hole Geometry on Cold-Formed Steel Bending Performance Using Finite Element Model and Statistical Methods

by Zeynep Yaman, Mahyar Maali, Ekin Abanoz, Elif Ağcakoca, Mohammad Saber Sadid and Türker Fedai Çavuş

Buildings 2025, 15(17), 3101; https://doi.org/10.3390/buildings15173101 - 29 Aug 2025

Abstract

The affordability, ease of manufacturing, and assembly efficiency of cold-formed steel profiles have contributed to their widespread use in structural applications. However, the presence of holes in these profile webs is likely to reduce their mechanical resistance. This study explores the bending behavior [...] Read more.

The affordability, ease of manufacturing, and assembly efficiency of cold-formed steel profiles have contributed to their widespread use in structural applications. However, the presence of holes in these profile webs is likely to reduce their mechanical resistance. This study explores the bending behavior of a built-up box section constructed using lipped and unlipped C-profiles, which are commonly utilized in the construction industry. The investigation focuses on the influence of self-drilling screw layout density and hole distribution within the section. A total of 30 different models were analyzed, considering three primary variables: the spacing of self-drilling screws, hole diameter, and the number of holes. The steel profiles were connected using self-drilling screws with spacing intervals of 100, 200, and 400 mm. Key parameters, such as moment capacity, effects on elastic zones, shear forces on screws, and ductility, were examined in relation to these variables. The findings indicate that reducing screw spacing and increasing the number of holes are crucial design factors for improving joint strength. However, while greater screw spacing enhances ductility, it leads to lower plastic deformation rates. Additionally, optimizing the number of holes in the section proved to be an effective strategy for improving ductility in the analyzed models. Mathematical evaluation confirmed that hole number and screw spacing significantly affect moment capacity and estimation stability, highlighting the need for their joint optimization in structural design. Full article

(This article belongs to the Special Issue Cold-Formed Steel Structures)

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26 pages, 17806 KB

Open AccessArticle

Cross-Material Damage Detection and Analysis for Architectural Heritage Images

by Qingman Yu, Xin Yuan and Lingyu Xu

Buildings 2025, 15(17), 3100; https://doi.org/10.3390/buildings15173100 - 28 Aug 2025

Abstract

This study addresses the strategic requirements for cultural heritage preservation as specified, alongside the needs of high-quality urban-rural development. It highlights the inefficiency, subjectivity, and lack of intelligence in traditional manual detection methods used in architectural heritage preservation. Consequently, this research explores intelligent [...] Read more.

This study addresses the strategic requirements for cultural heritage preservation as specified, alongside the needs of high-quality urban-rural development. It highlights the inefficiency, subjectivity, and lack of intelligence in traditional manual detection methods used in architectural heritage preservation. Consequently, this research explores intelligent damage detection and quantitative analysis through image detection technology based on artificial intelligence. Firstly, a cross-material classification standard for architectural remnants is developed to facilitate data annotation in image detection techniques. Secondly, a dense object detection algorithm specifically designed for architectural images is proposed to address challenges such as boundary ambiguity and high-density damage in architectural heritage. This algorithm effectively facilitates intelligent detection and quantitative analysis of architectural heritage damage. On this basis, multiple datasets for architectural heritage damage detection are compiled and constructed on-site. Experimental results obtained from these datasets demonstrate that the proposed method surpasses comparative approaches across various metrics, including average precision, thus confirming its feasibility and effectiveness. Additionally, a software application for intelligent damage detection and quantitative analysis of architectural heritage images is developed, providing novel insights and support for the field of architectural heritage preservation. Full article

(This article belongs to the Special Issue Analysis, Conservation, and Refurbishment Methods of Heritage Architecture Based on Modern Technology)

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51 pages, 4639 KB

Open AccessReview

Opportunities for Supplementary Cementitious Materials from Natural Sources and Industrial Byproducts: Literature Insights and Supply Assessment

by Somayeh Nassiri, Ali Azhar Butt, Ali Zarei, Souvik Roy, Iyanuoluwa Filani, Gandhar Abhay Pandit, Angel Mateos, Md Mostofa Haider and John T. Harvey

Buildings 2025, 15(17), 3099; https://doi.org/10.3390/buildings15173099 - 28 Aug 2025

Abstract

This paper reviews various emerging alternative SCMs derived from minerals and biomass sources, industrial byproducts, and underutilized waste streams. The paper compiles and evaluates physicochemical properties, reaction mechanisms in cementitious systems, resource availability, supply chain dynamics, technology readiness, the impact on concrete performance, [...] Read more.

This paper reviews various emerging alternative SCMs derived from minerals and biomass sources, industrial byproducts, and underutilized waste streams. The paper compiles and evaluates physicochemical properties, reaction mechanisms in cementitious systems, resource availability, supply chain dynamics, technology readiness, the impact on concrete performance, and environmental and cost factors for each candidate SCM. Specifically, the review examines wood ash from bioenergy plants, volcanic and sedimentary natural pozzolans, and construction and demolition waste. This includes recycled concrete fines, asphalt plants’ rock dust (baghouse fines), aggregate production fines, and post-consumer waste, particularly municipal solid waste incinerator ash and wastewater sludge ash. Additionally, the paper explores innovative additives such as cellulose and chitin nanomaterials and calcium–silicate–hydrate nanoseeds to address challenges of slower strength development and rheological changes. The key contribution of this review is a multifactor framework for assessing alternative SCMs, emphasizing availability, supply chain, market readiness, and environmental performance, combined with an engineering performance review. Full article

(This article belongs to the Special Issue Innovative Composite Materials in Construction)

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21 pages, 5332 KB

Open AccessArticle

Experimental and Numerical Simulation Study on Shear Performance of RC Corbel Under Synergistic Change in Inclination Angle

by Hao Huang, Chengfeng Xue and Zhangdong Wang

Buildings 2025, 15(17), 3098; https://doi.org/10.3390/buildings15173098 - 28 Aug 2025

Abstract

The purpose of this paper is to study the shear performance of reinforced concrete corbels under a synergistic change in the main stirrup inclination angle to explore the synergistic mechanism of the main reinforcement and the stirrup inclination angle, and to evaluate the [...] Read more.

The purpose of this paper is to study the shear performance of reinforced concrete corbels under a synergistic change in the main stirrup inclination angle to explore the synergistic mechanism of the main reinforcement and the stirrup inclination angle, and to evaluate the applicability of existing design specifications. The shear performance test was carried out by designing RC corbel specimens with an inclination angle of the main reinforcement and stirrup. The test results show that a 15° inclination scheme significantly improves the shear performance: the yield load is increased by 28.3%, the ultimate load is increased by 23.6%, the strain of the main reinforcement of the 15° specimen is reduced by 51.3%, the stirrup shows a delayed yield (the yield load is increased by 11.6%) and lower strain level (250 kN is reduced by 23.7%), and the oblique reinforcement optimizes the internal force transfer path and delays the reinforcement yield. A CDP finite element model was established for verification, and the failure mode and crack propagation process of the corbel were accurately reproduced. The prediction error of ultimate load was less than 2.27%. Based on the test data, the existing standard method is tested and a modified formula of the triangular truss model based on the horizontal inclination angle of the tie rod is proposed. The prediction ratio of the bearing capacity is highly consistent with the test value. A function correlation model between the inclination angle of the steel bar and the bearing capacity is constructed, which provides a quantitative theoretical tool for the optimal design of RC corbel inclination parameters. Full article

(This article belongs to the Special Issue Safety Assessment and Structural Analysis of Reinforced Concrete Buildings)

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