Buildings

22 pages, 6206 KB

Open AccessArticle

Parameter Estimation and Interval Assessment of the Collapse Capacity of Viscous-Damped Structures Under Degradation and Partial Failure Scenarios

by Xi Zhao and Wen Pan

Buildings 2026, 16(6), 1271; https://doi.org/10.3390/buildings16061271 - 23 Mar 2026

Viewed by 262

Abstract

In-service deviations of viscous dampers can reduce the collapse safety margin of viscous-damped structures under strong earthquakes. This study examines two representative mechanisms: global degradation of the damper group and local failure of a subset of dampers. Incremental dynamic analyses are conducted for [...] Read more.

In-service deviations of viscous dampers can reduce the collapse safety margin of viscous-damped structures under strong earthquakes. This study examines two representative mechanisms: global degradation of the damper group and local failure of a subset of dampers. Incremental dynamic analyses are conducted for five damper-state scenarios using the 22 far-field ground-motion records recommended by ATC-63. To support reliability-oriented, uncertainty-aware collapse-capacity comparison with limited records, three complementary probabilistic inference frameworks are developed: an event-based fragility model using binary collapse indicators, a drift-margin model leveraging continuous deformation information from non-collapse responses, and a fusion model that combines both sources via a weighted composite likelihood with fusion strength governed by the weight w. For each scenario, the capacity scale parameter μ_m is reported as IM_50,m, and record-level bootstrap resampling is used to construct interval estimates. Multi-scenario effects are further summarized by the ensemble mean reduction b and inter-path dispersion σ_damper, offering compact measures of systematic shift and pathway-to-pathway variability. Results indicate a dominant systematic downward shift in median collapse capacity, with IM_50,m reduced by approximately 2.4–2.9% overall, whereas differences among degradation pathways are secondary and bounded by the intervals. Scenario rankings remain consistent across the three frameworks; fusion outputs show weak sensitivity to w and yield tighter interval constraints on σ_damper than the event-only baseline. The resulting interval-based parameters enable risk- and reliability-informed interpretation of degradation effects and provide a consistent basis for uncertainty quantification in probabilistic performance comparisons across scenarios. Full article

(This article belongs to the Special Issue Reliability and Risk Assessment of Building Structures)

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36 pages, 3021 KB

Open AccessReview

Fatigue Damage in Cement-Based Materials: A Critical Multiscale Review

by Chuan Kuang, Tao Liu, Henrik Stang and Alexander Michel

Buildings 2026, 16(6), 1270; https://doi.org/10.3390/buildings16061270 - 23 Mar 2026

Viewed by 334

Abstract

This review examines fatigue damage in cement-based materials across the micro-, meso-, and macroscales, with emphasis on how damage initiates, transfers, and becomes structurally observable under cyclic loading. At the microscale, capillary pores, unhydrated cement particles, and the calcium–silicate–hydrate (C-S-H) phase govern local [...] Read more.

This review examines fatigue damage in cement-based materials across the micro-, meso-, and macroscales, with emphasis on how damage initiates, transfers, and becomes structurally observable under cyclic loading. At the microscale, capillary pores, unhydrated cement particles, and the calcium–silicate–hydrate (C-S-H) phase govern local stress concentration, bond rupture, limited healing, and microcrack development. At the mesoscale, the interfacial transition zone (ITZ), cement paste, aggregates, and fiber reinforcement effects control crack initiation, deflection, bridging, and coalescence. At the macroscale, specimen size, boundary conditions, loading regime, and environmental exposure shape stiffness degradation, residual strain accumulation, crack growth, and fatigue life. Beyond summarizing existing studies, this review synthesizes a causal damage transfer interpretation that links microscale deterioration, mesoscale crack interaction, and macroscale response. Current gaps include the limited quantitative link between microstructure-informed models and three-dimensional experimental observations, the still-incomplete validation of multiscale predictive frameworks, and the insufficient treatment of coupled fatigue–environment effects. Addressing these gaps is essential for more reliable fatigue life prediction and for developing durable, resource-efficient concrete infrastructure. Full article

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28 pages, 7144 KB

Open AccessArticle

Optimization of an MPC Controller Based on a Hybrid Cooling Load Prediction Model and Experimental Validation in HVAC Systems

by Shen Zhang, Xuelian Lei, Xiaofang Shan, Ting Li and Wenyu Wu

Buildings 2026, 16(6), 1269; https://doi.org/10.3390/buildings16061269 - 23 Mar 2026

Viewed by 227

Abstract

The high energy intensity of public buildings, especially those with HVAC systems, calls for advanced control strategies such as Model Predictive Control (MPC) to balance energy efficiency and thermal comfort. However, the performance of MPC relies critically on the accuracy and robustness of [...] Read more.

The high energy intensity of public buildings, especially those with HVAC systems, calls for advanced control strategies such as Model Predictive Control (MPC) to balance energy efficiency and thermal comfort. However, the performance of MPC relies critically on the accuracy and robustness of building cooling and heating load calculations, which remain challenging, particularly for buildings with complex dynamic characteristics. This study proposes a simplified modeling-based MPC approach and investigates the influence of three different load calculation methods on controller performance: a physics-driven white-box model, a data-driven black-box model, and a novel Closed-Loop Load Grey Model (CLLGM). Under identical outdoor conditions during summer cooling operation, the three controllers exhibit distinct performance disparities: although the proposed CLLGM-based controller only reduces the load prediction MAPE by 0.63% compared with the black-box model, it improves the temperature control stability index (TDI) by 80.43% and increases the comprehensive score from the MPC multi-objective optimization function by 16.55%. Its key advantage is that it can use on-site temperature measurements as feedback to correct the cooling load, making it better suited for simulation and computation in MPC. Full article

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

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Graphical abstract

27 pages, 7661 KB

Open AccessArticle

Seismic Resilience Assessment of High-Rise RC Frame–Shear Wall Structure Under Long-Period Ground Motions

by Bo Wang, Mingchao Tian, Aofei Jia and Xingli Pi

Buildings 2026, 16(6), 1268; https://doi.org/10.3390/buildings16061268 - 23 Mar 2026

Viewed by 254

Abstract

Long-period ground motions (LPGMs), rich in low-frequency content, can resonate with long-period structures like high-rise buildings, leading to severe damage. As seismic design shifts from safety toward resilience, limited attention to LPGMs makes it difficult to ensure the seismic resilience of long-period structures. [...] Read more.

Long-period ground motions (LPGMs), rich in low-frequency content, can resonate with long-period structures like high-rise buildings, leading to severe damage. As seismic design shifts from safety toward resilience, limited attention to LPGMs makes it difficult to ensure the seismic resilience of long-period structures. This study used Perform-3D software to model three high-rise reinforced concrete (RC) frame–shear wall structures with varying periods and one with infill walls for resilience assessment. The resilience indicators and seismic resilience grades under LPGMs and ordinary ground motions (OGMs) were compared using the Standard for Seismic Resilience Assessment of Buildings (GB/T38591-2020) and the Guideline for Evaluation of Seismic Resilience Assessment of Urban Engineering Systems (RISN-TG041-2022), which are national standards in China. The results show that the structural response under LPGMs is significantly different from that under OGMs. In particular, the influence of LPGMs on displacement-sensitive non-structural components is much greater than OGMs. Resilience indicators were higher under LPGMs. The presence of infill walls notably reduced resilience indicators, with a stronger effect under OGMs. Based on GB/T38591-2020, the seismic resilience of each structure generally decreases by 1–2 grades under LPGMs, while evaluations based on RISN-TG041-2022 show similar ratings under both LPGMs and OGMs. Full article

(This article belongs to the Special Issue Seismic Analysis and Design of Building Structures—2nd Edition)

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68 pages, 5341 KB

Open AccessSystematic Review

Utilizing Building Automation Systems for Indoor Environmental Quality Optimization: A Review of the Current Literature, Challenges, and Opportunities

by Qinghao Zeng, Marwan Shagar, Kamyar Fatemifar, Pardis Pishdad and Eunhwa Yang

Buildings 2026, 16(6), 1267; https://doi.org/10.3390/buildings16061267 - 23 Mar 2026

Viewed by 400

Abstract

Indoor Environmental Quality (IEQ) plays a vital role in occupant health and productivity. However, current Building Management Systems (BMS) often struggle in sustaining optimal IEQ levels due to limitations in data management and lack of occupant-centric feedback loops. To address these gaps, this [...] Read more.

Indoor Environmental Quality (IEQ) plays a vital role in occupant health and productivity. However, current Building Management Systems (BMS) often struggle in sustaining optimal IEQ levels due to limitations in data management and lack of occupant-centric feedback loops. To address these gaps, this research synthesizes the state-of-the-art methods for IEQ monitoring, assessment, and control within Building Automation Systems (BAS), identifying both technological and methodological advancements, as well as highlighting the challenges and potential opportunities for future innovations. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, this multi-stage literature review analyzes 176 publications from 1997 to 2024, with a focus on the decade of rapid technological evolution from 2014 to 2024. The review focuses on high-impact journals indexed in Scopus to ensure quality while acknowledging the potential bias inherent in a single-database search. The synthesis reveals a methodological shift in monitoring from sparse, zone-level sensing towards dense, multi-modal systems that incorporate physiological data via wearables and behavioral recognition through computer vision. Assessment techniques are evolving from static models such as the Predicted Mean Vote (PMV) towards adaptive, personalized frameworks supported by Digital Twins and integrated simulations. Furthermore, control logic is transitioning toward Reinforcement Learning and Model Predictive Control to proactively manage occupancy surges and environmental variables. This evolution of monitoring approaches, assessment techniques, and control strategies is represented within the study’s Three-Tiered Developmental Trajectory, providing a novel Body of Knowledge (BOK) for mapping the transition of building systems from reactive tools to autonomous, occupant-centric agents. This study also introduces a Cross-Modal Interaction Matrix to systematically analyze the systemic trade-offs between IEQ domains. Furthermore, by establishing the “Implementation Frontier,” this work identifies the specific technical and ethical bottlenecks, such as “false vacancy” sensing errors, fragmented data silos, and the ethical complexities of high-resolution data collection that prevent academic innovations from becoming industry standards. To bridge these gaps, we conclude that the next generation of “cognitive buildings” must prioritize three pillars: resolving binary sensing limitations, harmonizing data via vendor-neutral APIs, and adopting privacy-preserving architectures to ensure scalable, interoperable, and occupant-centric optimization. Full article

(This article belongs to the Special Issue Advancements in Super-Low-Energy Buildings: Innovations for Extreme Climate Conditions)

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18 pages, 1528 KB

Open AccessArticle

Unlocking Success: Overcoming the Impact of Variation Orders on SMEs Using Modern Methods of Construction

by Hafiz Muhammad Mubashar, Anushika Ekanayake, David J. Edwards, Akila Rathnasinghe and Agana Parameswaran

Buildings 2026, 16(6), 1266; https://doi.org/10.3390/buildings16061266 - 23 Mar 2026

Viewed by 301

Abstract

Construction project delays remain a persistent issue, often exacerbated by variation orders that adversely affect both financial and environmental performance, even in the UK. Although Modern Methods of Construction (MMC) have been increasingly employed to mitigate delays and improve efficiency, limited research has [...] Read more.

Construction project delays remain a persistent issue, often exacerbated by variation orders that adversely affect both financial and environmental performance, even in the UK. Although Modern Methods of Construction (MMC) have been increasingly employed to mitigate delays and improve efficiency, limited research has examined how variations affect small- and medium-sized enterprises (SMEs) adopting MMC in the UK construction sector. Given the pivotal role of SMEs and their financial vulnerability, this study examines the key challenges posed by variation orders for SMEs adopting MMC, with the broader aim of enhancing future project performance. Employing a two-stage iterative methodology, the research first identifies challenges through a comprehensive literature review, followed by a questionnaire survey and expert interviews. The resulting data were analysed thematically and statistically using SPSS and subsequently validated through a detailed case study involving interviews and document analysis. The findings highlight three principal clusters of challenges: operational, contractual, and module alteration-related, of which operational issues, particularly cost discrepancies, client approval delays, and rework, exert the most significant influence. The study provides a structured understanding of these interlinked challenges and underscores the need for targeted mitigation strategies to improve productivity and performance among UK construction SMEs engaged in MMC projects. Full article

(This article belongs to the Section Construction Management, and Computers & Digitization)

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36 pages, 5956 KB

Open AccessArticle

A Knowledge-Augmented Two-Stage Workflow for Architectural Concept-to-Massing Generation and Evaluation

by Shangci Sun and Yao Fu

Buildings 2026, 16(6), 1265; https://doi.org/10.3390/buildings16061265 - 23 Mar 2026

Viewed by 304

Abstract

Large language models (LLMs) and diffusion-based image generators can rapidly produce architectural ideas and imagery, yet translating conceptual narratives into massing composition is often implicit and difficult to reproduce. In this paper, we present a knowledge-augmented two-stage workflow for architectural concept-to-massing generation and [...] Read more.

Large language models (LLMs) and diffusion-based image generators can rapidly produce architectural ideas and imagery, yet translating conceptual narratives into massing composition is often implicit and difficult to reproduce. In this paper, we present a knowledge-augmented two-stage workflow for architectural concept-to-massing generation and evaluation. The outputs are represented as axonometric massing proxy images, which serve as 2D visual proxies for early-stage massing refinement rather than editable 3D models. The workflow integrates a prototype library and Knowledge Graph (KG) routing to map narrative cues into executable strategy and operation tokens and compile stage-specific prompts. Stage 1 produces structural concept sketches emphasizing legible composition, while Stage 2 generates axonometric massing proxy images conditioned on Stage 1 sketches to stabilize composition across candidates. Under a fixed sampling budget, candidates are ranked using a rubric-based scoring protocol with Top-K selection, and evaluation signals can be written back to update prompt compilation iteratively. Across diverse project briefs, ablation studies demonstrate that knowledge augmentation improves constraint compliance and composition readability while maintaining controlled diversity for early exploration. We report expert ratings together with paired statistical tests to support reproducible comparisons. Full article

(This article belongs to the Special Issue From Theory to Practice: Artificial Intelligence Applications in the Built Environment)

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43 pages, 5027 KB

Open AccessReview

A Review of the Rheological Properties of 3D-Printed Concrete: Raw Materials, Printing Parameters, and Evolution Mechanisms

by Jianfen Luo, Qidong Wang, Lijia Wang and Mingyue Fang

Buildings 2026, 16(6), 1264; https://doi.org/10.3390/buildings16061264 - 23 Mar 2026

Viewed by 435

Abstract

As a representative digital additive construction material, three-dimensional printed concrete (3DPC) imposes a synergistic rheological requirement on fresh cementitious mixtures, namely “pumpability–extrudability–buildability,” throughout the forming process. Rheological parameters and their temporal evolution not only govern the stability of the material during pumping, nozzle [...] Read more.

As a representative digital additive construction material, three-dimensional printed concrete (3DPC) imposes a synergistic rheological requirement on fresh cementitious mixtures, namely “pumpability–extrudability–buildability,” throughout the forming process. Rheological parameters and their temporal evolution not only govern the stability of the material during pumping, nozzle extrusion, and layer-by-layer deposition, but also directly determine interlayer interfacial integrity, geometric fidelity, and the development of macroscopic mechanical performance. This paper provides a systematic review of the regulation strategies and evolutionary characteristics of 3DPC rheology, with particular emphasis on how raw material composition, printing parameters, and multiscale evolution mechanisms influence yield stress, plastic viscosity, and thixotropic behavior. The time-dependent evolution of rheological properties is elucidated across multiple length scales, encompassing microscopic particle interactions and hydration-induced bridging, mesoscopic aggregate force-chain networks and particle migration, and macroscopic shear stimulation coupled with temperature–humidity effects. On this basis, it is further highlighted that existing models and characterization frameworks remain insufficient to capture the time-dependent structural evolution under realistic printing conditions. Therefore, the establishment of unified characterization standards, together with in situ rheological measurements and multiscale simulations, is urgently required to enable the coordinated optimization of material design and printing processes and to facilitate engineering-scale implementation. Full article

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

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32 pages, 8627 KB

Open AccessArticle

A Social Dimension Study of Post-Occupancy Evaluation for Old Residential Communities: A Case Study of Baoshengli North Community in Beijing

by Jianming Yang, Yanglu Shi, Wenying Ding, Yang Liu, Mingli Wang, Chenxiao Liu and Mo Han

Buildings 2026, 16(6), 1263; https://doi.org/10.3390/buildings16061263 - 23 Mar 2026

Viewed by 253

Abstract

Against the background of high-quality development and urban renewal in China, old residential communities have become key areas for improving spatial quality and quality of life. We used the entrance pavilion of Baoshengli North Community as a case study to explore how spatial [...] Read more.

Against the background of high-quality development and urban renewal in China, old residential communities have become key areas for improving spatial quality and quality of life. We used the entrance pavilion of Baoshengli North Community as a case study to explore how spatial design and layout can meet residents’ psychological and social needs. Adopting a mixed-methods approach, combining field observation, behavioral mapping, a questionnaire (Total = 105), in-depth interviews, and statistical analysis, a post-occupancy evaluation (POE) was conducted on spatial effectiveness and social functions. The results show that user-oriented spatial design, safety, esthetic quality, and inclusive functions significantly enhance residents’ spatial perception, willingness to use the space, and social interaction. Differentiated spatial preferences and potential conflicts among diverse resident groups were also identified. Targeted design interventions can effectively strengthen the connection between spatial use and subjective perception, and participatory and equitable strategies help promote social harmony and justice. This study enriches the post-occupancy evaluation system for the renewal of old communities from psychological and social dimensions, and provides practical references for user-centered, inclusive, and sustainable public space design in urban renewal practices. One limitation of this study is that data were collected over a single period, which restricts the analysis of seasonal impacts on spatial usage. Full article

(This article belongs to the Special Issue Community Resilience and Urban Sustainability: A Global Perspective)

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25 pages, 5491 KB

Open AccessArticle

Assessing Spatiotemporal Accessibility of Fire Services to Key Units of Fire Safety in Shanghai: Dynamics, Disparities, and Policy Implications

by Yiqi Zhang, Xiao Wang, Shizhen Cao, Yuheng He and Xiang Li

Buildings 2026, 16(6), 1262; https://doi.org/10.3390/buildings16061262 - 23 Mar 2026

Viewed by 258

Abstract

Accurately assessing the accessibility of fire services is critical for enhancing urban safety and the resilience of the built environment. However, existing studies often lack a systematic analysis of spatiotemporal dynamics across an entire municipality. To address this gap, this study develops a [...] Read more.

Accurately assessing the accessibility of fire services is critical for enhancing urban safety and the resilience of the built environment. However, existing studies often lack a systematic analysis of spatiotemporal dynamics across an entire municipality. To address this gap, this study develops a citywide dynamic assessment framework for Shanghai, integrating GIS with real-time traffic data across 240 consecutive intervals to assess the service accessibility of 195 fire stations in relation to 7973 key units of fire safety. The principal findings are threefold. First, the results reveal significant urban–suburban heterogeneity in emergency response times. Notably, the proximity advantage of fire stations in central urban areas is offset by traffic congestion, and the marginal benefit of traffic speed improvement exhibits a sharp decline once the average speed exceeds a critical threshold of 13.7–21.0 km/h. Second, the accessibility ratio demonstrates a clear temporal pattern, being highest on holidays and lowest during weekday peak hours, and follows a nonlinear spatial decline from the urban centre to the periphery. This pattern is influenced more critically by the matching of supply and demand than by fire station density alone. Third, the analysis identifies dynamic vulnerability hotspots, which display a ‘bimodal (M-shaped)’ pattern on weekdays and a ‘unimodal (A-shaped)’ pattern on weekends and holidays. This spatiotemporal mismatch shows that central urban areas, despite higher station density, can suffer from both high fire risk and low accessibility, revealing structural patterns consistent with the ‘Inverse Care Law’ in emergency service provision. This study concludes that merely improving traffic conditions is insufficient; optimising the spatial matching of resources is paramount for effective urban disaster prevention. By developing a refined dynamic assessment framework, this study advances current knowledge by focusing on demand locations consistent with actual fire regulatory priorities and examining spatiotemporal patterns across both urban and suburban areas, thereby providing quantitative, evidence-based support for the strategic planning of fire stations and the enhancement of infrastructure resilience. Full article

(This article belongs to the Topic Advances in Urban Resilience for Sustainable Futures)

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24 pages, 7126 KB

Open AccessArticle

3D Printing of Earth-Based Mixtures: Linking Material Design, Printability, and Structural Performance

by Daiquiri Zozaya, Hamideh Shojaeian, Francisco Uviña-Contreras and Maryam Hojati

Buildings 2026, 16(6), 1261; https://doi.org/10.3390/buildings16061261 - 23 Mar 2026

Viewed by 560

Abstract

The advancement of sustainable construction requires the development of earthen materials compatible with 3D printing (additive manufacturing), along with specified engineering standards. Many existing studies improve workability and early strength using chemical stabilizers such as cement; however, these additives increase embodied carbon and [...] Read more.

The advancement of sustainable construction requires the development of earthen materials compatible with 3D printing (additive manufacturing), along with specified engineering standards. Many existing studies improve workability and early strength using chemical stabilizers such as cement; however, these additives increase embodied carbon and undermine sustainability objectives. Challenges remain in the formulation of an earthen mixture that satisfies both printability and structural requirements for large-scale construction. Previous earth-based mixes have reported excessive shrinkage and inadequate compressive strength. This study presents the systematic optimization of a low-carbon, 3D-printable earthen mixture using locally sourced clay-loam soil from Belén, New Mexico (NM). The soil was modified with graded concrete sand and rice hull fiber to improve printing parameters such as buildability, extrudability, and printability while meeting the NM Earthen Building Code requirements for compressive and flexural strength. Soil characterization tests (particle size distribution, consistency, optimal water content) guided iterative refinement to enhance dimensional stability and mechanical performance. A baseline 2:1 soil-to-sand ratio (max aggregate size No. 4) was established. Incorporating

2 %

rice hull fiber and reducing max aggregate size to No. 16 (S67F2) early-age shrinkage was reduced from

12.33 %

to

3.48 %

(

72 %

reduction) while maintaining a 28-day compressive strength exceeding 660 psi, more than twice the code minimum. The optimized mixture supported 24 printed layers without deformation, achieved 189 psi flexural strength (three times the code minimum), and produced a stable 2-ft-diameter dome with minimal cracking. Full article

(This article belongs to the Special Issue 3D-Printed Technology in Buildings)

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27 pages, 3031 KB

Open AccessArticle

Spatial Justice Evaluation of Psychological Therapeutic Landscapes in High-Density Residential Areas

by Xin Zhang, Xiangyu Liu and Runzhe Shi

Buildings 2026, 16(6), 1260; https://doi.org/10.3390/buildings16061260 - 23 Mar 2026

Viewed by 263

Abstract

The global mental health issue is becoming increasingly prominent. The fair supply of psychological therapeutic landscape spaces in urban high-density residential areas is a core path to ensuring the physical and mental health of residents and maintaining social health equity. This study takes [...] Read more.

The global mental health issue is becoming increasingly prominent. The fair supply of psychological therapeutic landscape spaces in urban high-density residential areas is a core path to ensuring the physical and mental health of residents and maintaining social health equity. This study takes the theory of spatial justice as the core framework, selects 20 typical high-density residential areas in Shijiazhuang City as empirical samples, and collects basic data through structured questionnaire surveys and on-site observations to explore the justice dilemma, evaluation system, and group demand differentiation characteristics of psychological therapeutic landscape spaces in high-density residential areas. The research results show that there are three core injustice problems in the psychological therapeutic landscape spaces of high-density residential areas: insufficient spatial inclusiveness, lack of ecological space justice, and incomplete facilities and management systems. Residents’ evaluations of the spatial justice of therapeutic landscapes can be divided into four dimensions: practical, ecological, social, and management. Among them, the ecological dimension is the core dimension that residents pay the most attention to. Individual characteristics such as gender, age, identity category, community activity duration, and governance participation willingness have a significant impact on residents’ evaluations of spatial justice. This study constructs an evaluation system for the spatial justice of therapeutic landscape spaces suitable for high-density residential areas, providing theoretical support and practical guidance for the planning, design, and optimization and renewal of fair and inclusive psychological therapeutic landscapes in high-density residential areas in northern China. At the same time, it provides a scientific basis for the construction of healthy cities and the practical application of spatial justice in the field of human settlements. Full article

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

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30 pages, 4202 KB

Open AccessArticle

Study on Post-Use Evaluation and Optimization Strategies for the Cultural Tourism Landscape of Xidajie Street in Baoding from the Perspective of Immersive Experience

by Ke Ni, Ji Feng, Chenyu Wang, Yanwei Zhou and Heng Wang

Buildings 2026, 16(6), 1259; https://doi.org/10.3390/buildings16061259 - 23 Mar 2026

Viewed by 497

Abstract

In the context of immersive technologies deeply integrated into the cultural tourism industry, immersive cultural tourism has become an important means of heritage revitalization. Immersive experience is both a crucial consumer element and a key indicator for evaluating the attractiveness of cultural tourism [...] Read more.

In the context of immersive technologies deeply integrated into the cultural tourism industry, immersive cultural tourism has become an important means of heritage revitalization. Immersive experience is both a crucial consumer element and a key indicator for evaluating the attractiveness of cultural tourism landscapes. This study evaluates the post-use experience of the cultural tourism landscape of Xidajie Street in Baoding from the perspective of tourist immersion. Through a literature review, investigation of typical immersive districts, and expert interviews, we extract immersive cultural tourism landscape evaluation criteria based on a depth model of immersion, focusing on three dimensions: narrative, enclosure, and interaction. Subjective perception data from tourists is then collected through a survey, and IPA (Importance–Performance Analysis) is employed to identify the strengths and weaknesses of Xidajie’s cultural tourism landscape. The results show that Xidajie excels in spatial environment shaping and historical preservation, but has room for improvement in cultural narrative extension, contextual immersion, and interactive experiences. Therefore, strategies are proposed to enhance the cultural IP, establish a complete narrative structure, create authentic enveloping environments, and enrich interactive games to build a high-quality online and offline immersive cultural tourism landscape. This aims to promote the renewal of Xidajie and the dynamic transmission of Baoding’s local culture. Full article

(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)

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24 pages, 19961 KB

Open AccessArticle

Spatial Distribution and Influencing Factors of Speech Intelligibility in Round-Table Conversation Scenarios

by Lingling Liu, Linda Liang, Kangying Huang, Miao Ren and Yang Song

Buildings 2026, 16(6), 1258; https://doi.org/10.3390/buildings16061258 - 23 Mar 2026

Viewed by 224

Abstract

Round-table conversations, as common social environments, greatly depend on effective verbal communication to enrich the interactive experience. However, considerable variations in speech intelligibility (SI) occur among listeners at different positions under negative factors. This study employed numerical simulations, in situ measurements, and subjective [...] Read more.

Round-table conversations, as common social environments, greatly depend on effective verbal communication to enrich the interactive experience. However, considerable variations in speech intelligibility (SI) occur among listeners at different positions under negative factors. This study employed numerical simulations, in situ measurements, and subjective listening tests to evaluate the main factors affecting SI, and quantified SI using the Speech Transmission Index (STI) and Speech Reception Threshold (SRT). The results demonstrate that SI varies with listener position, with the extent of these variations surpassing expectations. The listeners closer to the speaker have a significantly greater SI than those across the table, with STI variations reaching 0.55 in the free field and 0.23 (SRT variations up to 3.1 dB) in the actual room. Both speaker orientation and listener head orientation greatly influence SI distribution and its positional sensitivity. Furthermore, the overall STI among listeners decreases by no more than 0.2 for each increase in table diameter. Overall, the trend of the change in SI in the actual room is essentially consistent with those in the free field, but reflections improve SI for listeners in less favorable positions. These findings reveal SI distribution patterns in round-table scenarios, providing evidence and insights for future research. Full article

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

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33 pages, 5861 KB

Open AccessArticle

User-Centered Energy Management System for a University Laboratory Based on Intelligent Sensors and Fuzzy Logic

by Cosmin-Florin Fudulu, Mihaela-Gabriela Boicu, Mihaela Vasluianu, Giorgian Neculoiu and Marius-Alexandru Dobrea

Buildings 2026, 16(6), 1257; https://doi.org/10.3390/buildings16061257 - 22 Mar 2026

Viewed by 277

Abstract

The paper proposes an intelligent energy management system designed for a university laboratory room, centered on the user and based on the integration of smart sensors and fuzzy logic for the simultaneous optimization of thermal comfort and energy efficiency. The system architecture integrates [...] Read more.

The paper proposes an intelligent energy management system designed for a university laboratory room, centered on the user and based on the integration of smart sensors and fuzzy logic for the simultaneous optimization of thermal comfort and energy efficiency. The system architecture integrates three control methods, On/Off controller, Proportional Integral Derivative (PID) controller, and Fuzzy Logic, within a hybrid structure capable of managing multiple factors such as thermal comfort, energy consumption, and the availability of renewable energy sources. The system is implemented and tested using Zigbee 3.0 sensors, smart relays, and photovoltaic panels, while variables such as temperature, humidity, energy consumption, and user feedback are monitored. The simulation results, obtained in the MATLAB/Simulink development environment, demonstrate that the fuzzy algorithm reduces thermal oscillations, optimizes energy costs, and maintains perceived comfort within an optimal range. The main contribution of the study lies in the development of a user-centered, interpretable, and scalable architecture, along with a PowerApps application that records occupants’ feedback in real time, which can be implemented in smart buildings with limited computational resources. Two operating scenarios with different time periods were developed for the proposed system. The fuzzy controller maintained a mean temperature deviation below ±0.2 °C, reduced oscillatory behavior compared to PID controller, and enabled photovoltaic coverage of up to 29.97% during peak intervals, with an average daily contribution of 8.77%. The total simulated energy cost was 8.49 RON for the one-day scenario and 48.12 RON for the five-day interval. Full article

(This article belongs to the Special Issue AI-Driven Distributed Optimization for Building Energy Management)

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22 pages, 993 KB

Open AccessArticle

How Music Alleviates Job Burnout: Uncovering the Mediating Mechanism of Leisure Crafting Among Construction Workers

by Sihui Li, Siqin Wang, Haohao Yang and Ken Nah

Buildings 2026, 16(6), 1256; https://doi.org/10.3390/buildings16061256 - 22 Mar 2026

Viewed by 245

Abstract

With the continuous development of the construction industry, work pressure faced by construction workers has been increasing, leading to a growing prominence of job burnout that adversely affects workers’ physical and mental health as well as work efficiency. Constantly exposed to high-pressure environments, [...] Read more.

With the continuous development of the construction industry, work pressure faced by construction workers has been increasing, leading to a growing prominence of job burnout that adversely affects workers’ physical and mental health as well as work efficiency. Constantly exposed to high-pressure environments, construction workers are prone to symptoms such as emotional exhaustion, depersonalization, and diminished personal accomplishment, which in turn impair their work performance and quality of life. However, existing literature has largely overlooked the potential role of leisure activities such as music in alleviating job burnout. Although music is widely recognized as an effective tool for emotional regulation, its application and impact among construction workers remain underexplored. Based on a sample of 1086 construction workers (71.09% male, 48.99% aged 36–45), this study examines four dimensions of music engagement, including Time Commitment (TC), Economic Spending (ES), Emotional Investment (EI), and Personal Participation (PP), and investigates how these dimensions, through the mediating role of leisure crafting (LC), negatively influence job burnout (JB) among this population. This study employed covariance-based structural equation modeling (CB-SEM) with a sample of 1086 construction workers (71.09% male, 48.99% aged 36–45) to examine how four dimensions of music engagement, namely Time Commitment (TC), Economic Spending (ES), Emotional Investment (EI), and Personal Participation (PP), influence job burnout through leisure crafting. The results show that: (1) time commitment, economic spending, emotional investment and personal participation all have a negative influence on job burnout; and (2) leisure crafting mediates the effect of music engagement by construction workers on job burnout. This study emphasizes the necessity of incorporating mental health interventions into high-pressure work environments, providing guidance for companies to develop more flexible and effective employee care and welfare policies. This research therefore holds significant theoretical and practical value, as it promotes sustainable development in the construction industry, improves workers’ well-being and enhances the design of related work environments. Full article

(This article belongs to the Section Construction Management, and Computers & Digitization)

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22 pages, 2755 KB

Open AccessArticle

A General Framework for Determining a Target Failure Mechanism in Frame Structures

by Yue Wei and Congzhen Xiao

Buildings 2026, 16(6), 1255; https://doi.org/10.3390/buildings16061255 - 22 Mar 2026

Viewed by 253

Abstract

Guiding structural failure toward a prescribed failure mechanism can significantly mitigate the risk of collapse under extreme seismic action. However, quantitative criteria for identifying the target failure mechanism remain underdeveloped. To fill the gap, this work proposes a general framework for determining a [...] Read more.

Guiding structural failure toward a prescribed failure mechanism can significantly mitigate the risk of collapse under extreme seismic action. However, quantitative criteria for identifying the target failure mechanism remain underdeveloped. To fill the gap, this work proposes a general framework for determining a target failure mechanism in frame structures. First, a generalized lateral failure mechanism is introduced and rigorously defined. Second, a topology-based search algorithm is developed to identify the minimal cut sets of failure mechanisms. On this basis, a two-stage evaluation procedure is proposed to identify the governing failure mechanism via the upper-bound theorem and subsequently determine the target failure mechanism through a max–min capacity criterion. Finally, 36 case studies covering three frame topologies are investigated. Results indicate that: (1) the selection of the target mechanism should be case-specific rather than determined solely by engineering intuition; (2) the target mechanism is controlled by structural topology, design constraints, and inter-story height distribution; and (3) across all topologies, increasing γ⁽⁰⁾ consistently shifts the selected target failure mechanisms toward configurations with a lower proportion of column hinges. Numerical pushover validation further confirms the mechanical consistency of the proposed framework, with the ultimate capacities obtained from the proposed method agreeing well with nonlinear simulation results. The proposed framework provides a theoretical basis and practical tools for failure-mechanism-based seismic design, with implications for improving structural safety and reliability. Full article

(This article belongs to the Section Building Structures)

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19 pages, 2252 KB

Open AccessArticle

Research on Cable Force Optimization for the Construction of Reinforced Concrete Arch Bridges Based on Improved Whale Optimization Algorithm and Support Vector Machine

by Hongping Ye, Jianjun Liu, Jian Yang, Jinbo Zhu, Jijin Zhang, Zhimei Jiang and Zhongya Zhang

Buildings 2026, 16(6), 1254; https://doi.org/10.3390/buildings16061254 - 22 Mar 2026

Viewed by 194

Abstract

To address the issue of cable force optimization during the cantilever casting stage of reinforced concrete arch bridge construction, this study proposes a cable force optimization method based on an Improved Whale Optimization Algorithm (IWOA) combined with a Support Vector Machine (SVM) model. [...] Read more.

To address the issue of cable force optimization during the cantilever casting stage of reinforced concrete arch bridge construction, this study proposes a cable force optimization method based on an Improved Whale Optimization Algorithm (IWOA) combined with a Support Vector Machine (SVM) model. First, the standard Whale Optimization Algorithm is enhanced through Tent chaotic mapping, a nonlinear iterative control parameter, adaptive weight factors, and adaptive threshold strategies. The improved algorithm is then used to optimize key parameters (C, g) in the SVM model, constructing a parameter-optimized cable force combination-structure response prediction model for the arch bridge. Next, with the average tensile stress of the arch ring’s top and bottom slabs during construction and the bending strain energy after bridge completion as target variables, a multi-objective optimization mathematical model for cable forces during the construction stage of reinforced concrete arch bridges based on IWOA-SVM was established. Finally, the feasibility of the method was validated using the Shatuo Bridge project as a case study. The results indicate that compared to the finite element optimization method, the IWOA-SVM cable force optimization method significantly improved computational efficiency while ensuring optimization effectiveness. After optimization, the peak tensile stress and vertical displacement of each arch segment were significantly reduced, leading to improved internal force distribution and alignment, thereby enhancing the overall structural safety and reliability of reinforced concrete arch bridges. Full article

(This article belongs to the Topic New Developments in Intelligent Construction and Operation of Infrastructures)

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28 pages, 4396 KB

Open AccessArticle

Optimization of Low-Heat Cementitious Materials Based on Construction Spoil Using Response Surface Methodology

by Xiangsai Guo, Qiang Zeng, Desheng Jin, Hao Wu, Chao Wang and Zhiwei Song

Buildings 2026, 16(6), 1253; https://doi.org/10.3390/buildings16061253 - 22 Mar 2026

Cited by 1 | Viewed by 220 | Correction

Abstract

To address the problem of temperature cracking caused by the concentrated release of hydration heat in mass concrete, this study developed a low-heat composite cementitious material (CWCM) by partially replacing conventional mineral admixtures with construction spoil. A multi-factor synergistic optimization design based on [...] Read more.

To address the problem of temperature cracking caused by the concentrated release of hydration heat in mass concrete, this study developed a low-heat composite cementitious material (CWCM) by partially replacing conventional mineral admixtures with construction spoil. A multi-factor synergistic optimization design based on response surface methodology (RSM) was conducted. The water–binder ratio, spoil replacement ratio, curing temperature, and ball-milling time were selected as influencing factors, while the 28-day flexural strength, 28-day compressive strength, and 72 h cumulative hydration heat were used as response variables. A four-factor, three-level Box–Behnken model was established. The results show that the regression model exhibits good fitting performance, and the prediction errors between the predicted and experimental values of all response variables are within a reasonable range. Under the optimized mixture proportion (15% spoil replacement), the system achieves a 28-day compressive strength of 61.03 MPa, while the 72 h cumulative hydration heat is reduced by approximately 15%, meeting the requirements for low-heat cement. Microstructural analyses using XRD, SEM, and TG/DTG indicate that a decrease in the Ca/Si ratio and an increase in the Al/Si ratio promote the formation of a denser C-(A)-S-H gel structure, enhancing the pozzolanic reaction. This mechanism plays a key role in achieving the synergistic regulation of strength enhancement and hydration heat reduction. Compared with conventional fly ash or slag systems, this study innovatively utilizes construction spoil as a partial substitute for traditional mineral admixtures. While maintaining satisfactory mechanical performance, the proposed system effectively reduces hydration heat release, providing a new pathway for temperature control design in mass concrete engineering and high-value resource utilization of construction waste. Full article

(This article belongs to the Special Issue A Circular Economy Paradigm for Construction Waste Management)

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27 pages, 3445 KB

Open AccessArticle

Artificial Neural Network-Based Prediction of Compressive Strength for Mix Design Evaluation in Sustainable Expanded Polystyrene-Infused Concrete

by Kavin John O. Castillanes and Gilford B. Estores

Buildings 2026, 16(6), 1252; https://doi.org/10.3390/buildings16061252 - 21 Mar 2026

Viewed by 261

Abstract

Lightweight concrete incorporating expanded polystyrene (EPS) remains an active area of research due to its potential to produce more sustainable resource-efficient construction materials. However, identifying the optimal mix design for EPS-infused concrete typically requires extensive experimental trials, resulting in significant time, cost, and [...] Read more.

Lightweight concrete incorporating expanded polystyrene (EPS) remains an active area of research due to its potential to produce more sustainable resource-efficient construction materials. However, identifying the optimal mix design for EPS-infused concrete typically requires extensive experimental trials, resulting in significant time, cost, and material consumption. To address this challenge, this study proposes an artificial neural network (ANN) predictive model with 5-fold cross-validation to estimate compressive strength performance and to develop mix design recommendations based on actual and predicted results. A total of 55 experimental samples were prepared and grouped into 11 batches, with the EPS volume replacement levels ranging from 0% to 50% at 5% increments. Model performance was evaluated using mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), coefficient of determination (R²), and scatter index (SI), with graphical representations like predicted vs. actual plots, response plots, and residual plots, and the results were benchmarked against a multiple linear regression (MLR) model. Among the tested configurations, the 4-5-1 ANN model demonstrated the highest predictive accuracy. Furthermore, a Shapley (SHAP) analysis was conducted to interpret the model behavior and determine the relative importance of the input variables. The findings reveal that EPS content had the greatest influence on compressive strength prediction, followed by slump value, then gravel content, and finally concrete density. Full article

(This article belongs to the Special Issue Artificial Intelligence in Material and Structural Optimization for Sustainable Infrastructure)

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17 pages, 6264 KB

Open AccessArticle

Mechanism of the EICP Centrifugal Cementation Method for Short-Term Brick Crack Rehabilitation

by Zhongyuan Chen, Xiaolong Xu, Jianping Wei, Xueyan Guo and Xinyi Ke

Buildings 2026, 16(6), 1251; https://doi.org/10.3390/buildings16061251 - 21 Mar 2026

Viewed by 206

Abstract

Traditional enzyme-induced carbonate precipitation (EICP) technology for brick crack rehabilitation is commonly plagued by solution clogging and low repair efficiency. To overcome these technical limitations, a novel centrifugal cementation method was proposed in this study, with its core innovation lying in decoupling the [...] Read more.

Traditional enzyme-induced carbonate precipitation (EICP) technology for brick crack rehabilitation is commonly plagued by solution clogging and low repair efficiency. To overcome these technical limitations, a novel centrifugal cementation method was proposed in this study, with its core innovation lying in decoupling the EICP reaction from the masonry reinforcement process. After the complete reaction of urease with the cementation solution, a high-concentration calcium carbonate colloid was extracted via centrifugation, which was then mixed with fine sand to prepare a repair mortar for direct injection into brick cracks. The experimental results, based on a single-factor design with a fixed soybean powder concentration (180 g/L, peak urease activity), showed that the maximum flexural strength of the repaired bricks reached 2.31 MPa, recovering as much as 122.9% of that of the cracked unrepaired bricks. Furthermore, the flexural strength of the repaired bricks exhibited a significant positive correlation with the calcium carbonate content (20–100%) and curing time (3–28 days). Phase analysis indicated that the repair mortar was primarily composed of calcite and quartz. The high shear force generated by centrifugation triggered explosive nucleation of calcium carbonate, and spherical calcite particles were formed through Ostwald ripening, exhibiting a distinct characteristic of decoupling between the spherical morphology and calcite crystal phase. The centrifugal cementation method proposed in this study achieves excellent short-term repair effects for masonry structures under laboratory conditions, thus providing a novel technical approach for the crack rehabilitation of masonry structures. Full article

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

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15 pages, 3274 KB

Open AccessArticle

Stochastic Fatigue Damage Behavior and Modeling of Seawater Sea-Sand Concrete Under Uniaxial Compression

by Lijuan Li, Mengyang Li, Haoquan Zhu and Yanpeng Wang

Buildings 2026, 16(6), 1250; https://doi.org/10.3390/buildings16061250 - 21 Mar 2026

Viewed by 155

Abstract

This paper presents the first study on the fatigue damage behavior of seawater sea-sand concrete (SSC) and its modeling. Experimental tests were conducted on cylindrical specimens subjected to uniaxial compression, investigating the effects of maximum stress level and material variability. The results indicate [...] Read more.

This paper presents the first study on the fatigue damage behavior of seawater sea-sand concrete (SSC) and its modeling. Experimental tests were conducted on cylindrical specimens subjected to uniaxial compression, investigating the effects of maximum stress level and material variability. The results indicate that the maximum stress-fatigue life curve for SSC can be well represented by a straight line, while the secant stiffness of SSC degrades in a two-phase process: initially in a decelerating manner, followed by an accelerating degradation until failure. Compared to ordinary concrete, SSC exhibits a significantly longer fatigue life. Due to material variability, the fatigue life of SSC shows considerable randomness, which can be effectively modeled using a Weibull distribution. A modification was made to a recently proposed damage model by the author and Li to capture the stochastic fatigue damage evolution behavior of SSC. The modified model successfully simulates both the maximum stress-fatigue life curve and the secant stiffness degradation curve, including their inherent randomness. Future research should explore the underlying specific factors contributing to the significantly longer fatigue life of SSC compared to ordinary concrete. Full article

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

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24 pages, 3300 KB

Open AccessArticle

Design-Oriented Phenomenological Modelling Approach for Seismic Analyses of Multi-Storey CLT Buildings

by Valentino Nicolussi, Andrea Polastri, Diego Alejandro Talledo, Stefano Pacchioli and Luca Pozza

Buildings 2026, 16(6), 1249; https://doi.org/10.3390/buildings16061249 - 21 Mar 2026

Viewed by 251

Abstract

This work proposes a design-oriented numerical modelling approach for predicting the seismic response of multi-storey Cross-Laminated Timber (CLT) buildings. The model is based on a phenomenological approach and is capable of accurately replicating the seismic behaviour of multi-storey CLT wall systems by means [...] Read more.

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

(This article belongs to the Section Building Structures)

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24 pages, 3485 KB

Open AccessArticle

A Hybrid Deep Learning Framework with CEEMDAN, Multi-Scale CNN, and Multi-Head Attention for Building Load Forecasting

by Limin Wang, Dezheng Wei, Jumin Zhao, Wei Gao and Dengao Li

Buildings 2026, 16(6), 1248; https://doi.org/10.3390/buildings16061248 - 21 Mar 2026

Viewed by 222

Abstract

Accurate building load forecasting is essential for smart grid and energy management, yet nonlinearity, non-stationarity, and multi-scale characteristics of load data challenge traditional methods. To address these issues, we propose a hybrid deep learning framework, CEEMDAN-MultiScale-CNN-BiLSTM-MultiAttention. First, Complete Ensemble Empirical Mode Decomposition with [...] Read more.

Accurate building load forecasting is essential for smart grid and energy management, yet nonlinearity, non-stationarity, and multi-scale characteristics of load data challenge traditional methods. To address these issues, we propose a hybrid deep learning framework, CEEMDAN-MultiScale-CNN-BiLSTM-MultiAttention. First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) decomposes the load sequence into intrinsic mode functions (IMFs), mitigating mode mixing and complexity. Then, a MultiScale Convolutional Neural Network extracts multi-scale local features from each IMF. A Bidirectional Long Short-Term Memory network captures bidirectional temporal dependencies, and a Multi-Attention mechanism dynamically emphasizes critical time steps and feature channels, enhancing interpretability and prediction. The framework is validated on the Building Data Genome Project 2 dataset, achieving a Mean Absolute Percentage Error (MAPE) of 2.6464% and a coefficient of determination R² of 0.8999, outperforming mainstream methods across multiple metrics. The main contributions are: (1) a hybrid framework integrating CEEMDAN, multi-scale feature extraction, and attention mechanisms to handle nonlinearity and non-stationarity; (2) a MultiScale-CNN to capture multi-scale temporal features and adapt to multi-frequency components; (3) a Multi-Attention mechanism to dynamically focus on key time steps and channels, improving accuracy and robustness. This work provides an effective solution for building load forecasting in complex energy systems. Full article

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21 pages, 4925 KB

Open AccessArticle

Modeling and Prediction of Mechanical Properties of MFRC Based on Fiber Distribution Characteristics

by Kuan Lu, Jianjian Wu, Yajing Guan, Kaixing Liao, Deming Zeng and Mingli Cao

Buildings 2026, 16(6), 1247; https://doi.org/10.3390/buildings16061247 - 21 Mar 2026

Viewed by 174

Abstract

This study develops a multi-scale fiber-reinforced cementitious composite (MFRC) by hybridizing calcium carbonate whisker (CW), polyvinyl alcohol (PVA) fiber, and steel fiber. The interfacial micromechanical properties between steel fiber/matrix and PVA fiber/matrix under the influence of CW were systematically examined through single-fiber pull-out [...] Read more.

This study develops a multi-scale fiber-reinforced cementitious composite (MFRC) by hybridizing calcium carbonate whisker (CW), polyvinyl alcohol (PVA) fiber, and steel fiber. The interfacial micromechanical properties between steel fiber/matrix and PVA fiber/matrix under the influence of CW were systematically examined through single-fiber pull-out tests. The two-dimensional and three-dimensional distribution characteristics of fibers in the MFRC were analyzed using backscattered electron imaging (BSE) and X-ray computed tomography (X-CT), respectively. Based on the fiber distribution characteristics, flexural strength prediction models were developed with R² values of 0.79 (2D) and 0.82 (3D). Experimental validation via splitting tensile tests and three-point bending tests confirmed the model’s effectiveness in simultaneously predicting splitting tensile strength (R² = 0.89) and flexural strength (R² = 0.93). These findings demonstrate the reliability and universality of the proposed model for predicting flexural–tensile strength in an MFRC. Full article

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

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21 pages, 4493 KB

Open AccessArticle

Direct Shear Rheological Tests on Clays and Model Analysis

by Yingguang Fang, Kang Gao, Zhenfeng Ou and Renguo Gu

Buildings 2026, 16(6), 1246; https://doi.org/10.3390/buildings16061246 - 21 Mar 2026

Viewed by 201

Abstract

This study aims to investigate the influence of clay mineral content on the rheological properties and long-term deformation stability of clays, and to establish a unified model capable of quantitatively describing the nonlinear rheological behavior of clays with different mineral compositions. Direct shear [...] Read more.

This study aims to investigate the influence of clay mineral content on the rheological properties and long-term deformation stability of clays, and to establish a unified model capable of quantitatively describing the nonlinear rheological behavior of clays with different mineral compositions. Direct shear rheological tests were conducted on specimens prepared with different mixing ratios of bentonite, kaolin, and quartz. Combined with micro-mechanism analysis, the controlling factors of clay rheological behavior were explored. The experimental results show that the creep stress threshold, elastic viscosity, and average plastic viscosity decrease significantly with increasing clay mineral content. The rheological deformation exhibits distinct nonlinear characteristics, and clay mineral content plays a controlling role in the rheological behavior. Based on experimental and mechanistic analysis, a unified rheological model was established, which reflects the material origin of rheology and captures nonlinear rheological characteristics. This model can predict the entire time-history mechanical behavior of clays with different mineral compositions across the three stages of instantaneous deformation, decay rheology, and steady-state rheology under different shear stress levels using a single set of parameters. Validation was performed through direct shear rheological tests under 50 working conditions for five types of clay specimens, demonstrating good consistency between the model calculations and experimental results. The unified rheological model reveals the material origin and physical essence of clay rheology, demonstrates high universality, and advances the understanding of the influence of mineral composition on rheology from the current phenomenological qualitative description to quantitative calculation for the first time, significantly enhancing its engineering application value. This provides a more reliable tool for predicting long-term deformation and assessing the stability of clay foundations. Full article

(This article belongs to the Section Building Structures)

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25 pages, 3479 KB

Open AccessArticle

Generalization of Machine Learning Surrogates Across Building Orientation and Roof Solar Absorptance in Naturally Ventilated Dwellings

by Cintia Monreal Jiménez, Angel Jiménez-Godoy, Guillermo Barrios, Robert Jäckel, Alberto Ramos Blanco and Geydy Gutiérrez-Urueta

Buildings 2026, 16(6), 1245; https://doi.org/10.3390/buildings16061245 - 21 Mar 2026

Viewed by 433

Abstract

This study develops an interpretable machine learning (ML) surrogate to predict hourly indoor air temperature and discomfort indicators for a representative Mexican social-housing prototype in San Luis Potosí (cold semi-arid, Köppen–Geiger BSk). A four-zone EnergyPlus model with constant window opening (50%) and no [...] Read more.

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

T_{n}

, ML predictions preserved the main cold and hot discomfort degree-hour patterns across the full design space. The proposed surrogate enables rapid, physically consistent comfort-oriented screening of roof finishes and orientation choices in naturally ventilated social housing. Full article

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

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26 pages, 887 KB

Open AccessArticle

Using Safety Accountability to Enhance Construction Safety Performance: The Mediating Roles of Safety Monitoring and Safety Learning Under Inclusive Leadership

by Mohamed Mohamed and Benard Vetbuje

Buildings 2026, 16(6), 1244; https://doi.org/10.3390/buildings16061244 - 21 Mar 2026

Viewed by 216

Abstract

Safety performance remains a persistent challenge in the construction industry due to hazardous working conditions, dynamic site environments, and complex organizational structures. Despite regulatory advances and technical safety controls, accident rates remain high, suggesting that formal mechanisms alone are insufficient. Addressing this gap, [...] Read more.

Safety performance remains a persistent challenge in the construction industry due to hazardous working conditions, dynamic site environments, and complex organizational structures. Despite regulatory advances and technical safety controls, accident rates remain high, suggesting that formal mechanisms alone are insufficient. Addressing this gap, this study examines safety accountability as a central organizational mechanism and investigates how it influences construction workers’ safety performance through behavioral processes and leadership conditions. Drawing on accountability theory and social learning theory, we propose a moderated parallel mediation model in which safety monitoring and safety learning function as mediators, while inclusive leadership behavior serves as a contextual moderator. Data were collected from 629 construction workers employed in large-scale projects in Istanbul and Ankara, Türkiye, using a two-wave survey design to mitigate common method bias. Hypotheses were tested using confirmatory factor analysis and Hayes’ PROCESS macro. The results indicate that safety accountability does not exert a significant direct effect on safety performance; rather, its influence is fully transmitted through safety monitoring and safety learning, with monitoring emerging as the stronger mediating mechanism. Moreover, inclusive leadership behavior significantly strengthens the accountability-driven pathways leading to improved safety outcomes. By integrating accountability structures, behavioral processes, and leadership context, this study advances construction safety research and provides evidence-based guidance for enhancing occupational safety performance in high-risk construction environments. Full article

(This article belongs to the Special Issue Safety Management and Occupational Health in Construction)

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26 pages, 1035 KB

Open AccessArticle

Time-Aware Construction Site Risk Prediction Based on Sentence-BERT and 7-Day Window Aggregation with Unlabeled Data

by Shu Liu, Weidong Yan, Guoqi Liu and Rui Zhang

Buildings 2026, 16(6), 1243; https://doi.org/10.3390/buildings16061243 - 21 Mar 2026

Viewed by 179

Abstract

Construction safety texts are commonly used only for descriptive statistical analysis, and systematic approaches for uncovering latent semantic risk correlations remain limited. In particular, risk identification and prioritization under unlabeled conditions remain challenging. To address this issue, this study proposes a semantic risk [...] Read more.

Construction safety texts are commonly used only for descriptive statistical analysis, and systematic approaches for uncovering latent semantic risk correlations remain limited. In particular, risk identification and prioritization under unlabeled conditions remain challenging. To address this issue, this study proposes a semantic risk association and ranking framework based on Sentence-BERT (SBERT). First, a domain-specific keyword library is constructed, and representative risk terms are extracted through tokenization, stop-word removal, and TF-IDF weighting. A fine-tuned SBERT model is then employed to generate sentence embeddings. FAISS-based similarity search is applied to match safety inspection records with historical accident reports, enabling automatic identification and ranking of the most relevant accident types. In addition, a seven-day inspection window is introduced to capture the temporal accumulation effect of hazards and support risk assessment without explicit labels. Experiments conducted on 1368 accident reports and 484 inspection records show that the proposed framework achieves an accuracy of 0.75, a recall of 1.00, and an F1-score of 0.8571. Cross-project validation yields an F1-score of 0.5607, and the performance remains stable under 10% noise interference. The results demonstrate that the proposed semantic risk association and ranking framework is effective and robust for practical construction safety management. Full article

(This article belongs to the Topic Advancing Construction Safety and Health: Innovations and Strategies)

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24 pages, 3108 KB

Open AccessArticle

Field Measurement and Data-Driven Modeling of a Photovoltaic/Thermal and Air-Source Dual-Source Heat Pump System in Dalian, China

by Xin Jia, He Wang, Shuangshuang Li, Shuang Jiang, Ye Ning, Hu Chen, M. Hasanuzzaman and Shugang Wang

Buildings 2026, 16(6), 1242; https://doi.org/10.3390/buildings16061242 - 21 Mar 2026

Viewed by 180

Abstract

Dual-source heat pump systems combining photovoltaic-thermal (PVT) and air-source technologies have attracted considerable research interest due to their energy complementarity. Based on the climatic characteristics of the Dalian region, this study conducted field measurements and data analysis on a developed dual-source heat pump [...] Read more.

Dual-source heat pump systems combining photovoltaic-thermal (PVT) and air-source technologies have attracted considerable research interest due to their energy complementarity. Based on the climatic characteristics of the Dalian region, this study conducted field measurements and data analysis on a developed dual-source heat pump system incorporating three adaptive operational modes: (1) PVT mode, (2) PVT/air dual-source mode, and (3) photovoltaic (PV)/air-source mode. Compared to Mode (3), Mode (1) achieves a 5.76% higher heating capacity and an 11.56% greater electrical efficiency. Meanwhile, Mode (2) demonstrates a 12.23% increase in heating capacity, and a 9.14% improvement in electrical efficiency relative to Mode (3). A data-driven methodology is provided to quantify the system’s evaporation temperature, the thermal efficiency of PVT mode, and the coefficient of performance (COP) of the PVT heat pump. The economic assessment demonstrates that the proposed dual-source heat pump system achieves a heating cost as low as RMB 0.1125/kWh and a payback period of 6.4 years, indicating favorable economic benefits. This study provides fundamental data and computational methods for the optimized operation of the PVT/air dual-source heat pump. Full article

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

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