Developments in the Built Environment最新文献

{"title":"Micro-mechanisms and performance of high plasticity clay stabilized with a modified fly ash-based geopolymer","authors":"Lu Li ,&nbsp;Xiuyan Yin ,&nbsp;Huizhi Wang ,&nbsp;Rui Zhang ,&nbsp;Kang Chen ,&nbsp;Yingli Gao ,&nbsp;Yafei Zhang","doi":"10.1016/j.dibe.2026.100911","DOIUrl":"10.1016/j.dibe.2026.100911","url":null,"abstract":"<div><div>High-plasticity clay (HPC) poses significant challenges for transportation infrastructure due to its pronounced water sensitivity and associated strength loss. This study develops a multi-precursor fly ash-based geopolymer incorporating calcium carbide residue, desulfurization gypsum, and steel slag to stabilize HPC, with the optimal binder formulation of 6.34%, 1.60%, and 29.47%, respectively, determined using response surface methodology. The performance of geopolymer stabilize HPC (GHPC) prepared with the optimal binder formulation was evaluated through Atterberg limits, California Bearing Ratio, linear shrinkage, and wet-dry cycles tests, with comparisons to cement-treated HPC (CHPC). Results show that GHPC significantly enhances strength and volume stability. A proposed damage-potential framework quantified GHPC's superior resistance to wet-dry degradation compared to CHPC and HPC. Leaching tests confirmed effective immobilization of heavy metals by the geopolymer matrix. Multiscale analyses using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and mercury intrusion porosimetry (MIP) revealed that the continuous formation of dense C(N)-A-S-H gel networks and gel pores promotes particle agglomeration and fabric densification, governing the enhanced engineering performance.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100911"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147709841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanism of shrinkage and cracking in high-strength concrete regulated by internal humidity under extreme drying environments","authors":"Jun Qin ,&nbsp;Li Gong ,&nbsp;Chunling Jin ,&nbsp;Dandan Dang ,&nbsp;Tengteng Yang","doi":"10.1016/j.dibe.2026.100902","DOIUrl":"10.1016/j.dibe.2026.100902","url":null,"abstract":"<div><div>Extreme climates characterized by coupled drying, large diurnal temperature variations, and wind are widespread in regions such as northwestern China, significantly aggravating the deterioration of volumetric stability and cracking risk of high-strength concrete (HSC) during curing. Under extreme drying coupled environments, multiscale experiments were conducted to investigate the regulation of SAP-based internal curing in HSC with different water-to-binder ratios (W/B) (0.36–0.20). Drying shrinkage and restrained deformation, the evolution of internal relative humidity (RH) and temperature, and pore structure characteristics were systematically examined, and a drying shrinkage prediction model based on internal RH was established. The results show that diurnal temperature cycling induces pronounced asymmetric periodic strain responses during the shrinkage and expansion stages of HSC, which continuously accumulate under restrained conditions, with this effect becoming significantly more pronounced as the W/B decreases. Internal RH exhibits synchronous periodic fluctuations with environmental temperature, and temperature-driven RH oscillations repeatedly disturb the pore water–vapor equilibrium, triggering cyclic loading and unloading of capillary tension and thereby driving irreversible deformation accumulation; HSC with lower W/B is more sensitive to this process. SAP-based internal curing effectively reduces the deformation sensitivity of HSC to diurnal temperature cycling by mitigating RH reduction, optimizing mesopore structure, and weakening capillary-tension-driven effects. For HSC with a W/B of 0.20, the incorporation of 0.3% SAP reduced the average shrinkage peak value and strain fluctuation amplitude by approximately 34% and 35%, respectively, significantly suppressing drying shrinkage, restrained deformation accumulation, and cracking. The proposed model shows good agreement with experimental results (R² &gt; 0.90), with prediction errors below 10%. This study provides a theoretical basis for mix design optimization and shrinkage–cracking risk assessment of HSC in arid regions with pronounced diurnal temperature variations.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100902"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147709894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proactive health oriented residential floor plan generation via controllable multi agent deep reinforcement learning","authors":"Yi Man,&nbsp;Hanhan Zhang,&nbsp;Ping Shu","doi":"10.1016/j.dibe.2026.100934","DOIUrl":"10.1016/j.dibe.2026.100934","url":null,"abstract":"<div><div>With the growing demand for healthy residential environments, Proactive Health which emphasizes guiding occupants’ behaviors and physiological perceptions through spatial design, has become an important direction in residential design. However, existing floor plan design approaches remain limited in the systematic representation and controllable realization of explicit design objectives. To address this issue, a multi-agent deep reinforcement learning model Rein2Plan is developed. By analyzing the interaction mechanisms between Proactive Health factors and key spatial parameters, health-oriented reward formulations are constructed to enable goal driven residential layout generation. Experimental results show that Rein2Plan outperforms benchmark generative models in geometric compliance and room connectivity, while the generated layouts also achieve superior performance in health oriented habitability compared with real world residential plans and existing deep learning methods. An integrated workflow encompassing pre parameter analysis, controllable layout generation, and result evaluation is established, providing a methodological foundation for green, healthy, and sustainable generative residential design.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100934"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148184325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Commercializing big data as an asset in the construction and built environment: A conceptual framework","authors":"S. Thomas Ng ,&nbsp;Lawrence Martin Mankata ,&nbsp;Joshua Amo Larbi ,&nbsp;Prince Antwi-Afari","doi":"10.1016/j.dibe.2026.100923","DOIUrl":"10.1016/j.dibe.2026.100923","url":null,"abstract":"<div><div>The construction and built environment (CBE) sector generates vast amounts of data from Internet of Things (IoT) devices, BIM models, and project records with untapped potential as a monetizable and strategic asset. This paper develops a conceptual framework for commercializing big data as an asset in the CBE. With a grounding in data assetization theory and resource-based view, a systematic evidence synthesis (SES) of 52 studies identified from Scopus and Web of Science databases is undertaken to identify foundational concepts, thematic gaps, and opportunities for applying data-as-an-asset (DaaA) concept to CBE big data assets. The proposed conceptual framework structures the commercialization logic on three main pillars of integrated value chain processes, ecosystem actors and stakeholders, and enabling infrastructure. The integrated value chain process encompasses data governance, acquisition, processing, monetization, and utilization. Within this integrated value chain the key stakeholders include data regulators, producers, aggregators, brokers, and consumers. At its core, the pathways to monetization are realized through the sale and licensing of data products, services, solutions, and platform-sharing arrangements. All value chain processes and stakeholder interactions are supported by critical enabling infrastructure which include modelling and monitoring tools, secure storage and sharing systems, analytics and intelligence tools, and data exchanges and marketplaces. To demonstrate the operationalization of the framework, a proof-of-concept prototype is developed to simulate CBE scenarios through which big data assets are transformed from acquisition to utilization. The implications these hold for theory, industry practice, and policy are addressed together with future research directions for piloting and experimenting with the framework at scale.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100923"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147858164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable soundscape empowered by environmentally friendly meta-barrier","authors":"Yuwei Xu,&nbsp;Zhongming Gu,&nbsp;Jie Liu,&nbsp;Yinjie Su,&nbsp;Wei Zhong,&nbsp;Fangshuo Mo,&nbsp;Yong Li,&nbsp;Jie Zhu","doi":"10.1016/j.dibe.2026.100941","DOIUrl":"10.1016/j.dibe.2026.100941","url":null,"abstract":"<div><div>Noise pollution has posed persistent challenges to the sustainable development of urban and built environments. Prior efforts have been mainly devoted to enhancing the performance of sound insulation, with comparatively less attention paid to fostering pleasant soundscapes. Here, we propose a multi-functional meta-barrier engineered for broadband sound reduction with ecological integration, while also enabling modulation of environmental conditions. By recycling the rainwater, the volumes of the acoustic cavities can be adjusted to block over 90% of sound energy in the range from 300 to 1600 Hz, following an optimization mechanism based on hybrid resonances. Meanwhile, the hydroponic plants can be set up in the cavities and further absorb more acoustic energy as porous materials. Besides the mitigation of unwanted sound, this environmentally friendly design also exhibits the characteristics of ventilation and thermal insulation, thereby creating a restorative urban space. The verification consisting of simulations and experiments is conducted to demonstrate the validity of a full-size sample across diverse conditions. By merging sound insulation with other ecological benefits, our design provides a versatile solution for noise challenges with potential applications in urban environmental infrastructure.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100941"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147945089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From street-view sensing to maintenance decisions: A knowledge-based engineering informatics framework for urban pavement defect assessment","authors":"Linchao Li ,&nbsp;Bangxing Li ,&nbsp;Jiazhen Liu ,&nbsp;Bowen Du","doi":"10.1016/j.dibe.2026.100920","DOIUrl":"10.1016/j.dibe.2026.100920","url":null,"abstract":"<div><div>Urban pavement defects, such as cracks and potholes, pose significant challenges to road safety and maintenance. Traditional pavement defect detection methods rely heavily on manual inspection, which is labor-intensive and time-consuming. Recent advances in deep learning have opened new opportunities for automating this process, particularly through the use of convolutional neural networks (CNNs). This paper presents an improved deep learning-based approach for detecting pavement defects using street view imagery. The proposed method leverages a customized dataset constructed from high-resolution street view images, incorporating both common and hazardous defects. The detection algorithm is based on an enhanced YOLOv8 model, optimized for handling low-resolution images and small defect targets. The model improvements include the introduction of a spatial-depth convolutional layer to preserve fine-grained information, a generalized feature pyramid network for better feature fusion, and a dynamic head with multi-task awareness for improved detection accuracy in complex urban environments. Experimental results demonstrate that the proposed model achieves superior performance in detecting pavement defects, with a mean Average Precision (mAP) improvement of 4.7% over the baseline model, while maintaining high inference speed. These findings suggest that the enhanced YOLOv8 model can be effectively applied to urban pavement maintenance, providing a reliable and efficient solution for large-scale defect detection.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100920"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147709840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation on the high-temperature thermal damage mechanism of hybrid steel-polypropylene fiber reinforced UHPC using X-ray computed tomography","authors":"Yajun Lv ,&nbsp;Juzheng Liu ,&nbsp;Heng Yang ,&nbsp;Leigao Zuo ,&nbsp;Peng Lu ,&nbsp;Weizhun Jin","doi":"10.1016/j.dibe.2026.100939","DOIUrl":"10.1016/j.dibe.2026.100939","url":null,"abstract":"<div><div>To investigate the influence mechanism of hybrid fibers on the high temperature damage of ultra-high performance concrete (UHPC), this study employed micro-scale X-ray computed tomography (X-CT) to evaluate the high temperature damage process of UHPC reinforced by steel fiber (SF) alone and hybrid SF and polypropylene fiber (PPF). The results show that the hybrid fibers (1.6% SF + 0.6% PPF) can significantly enhance the crack resistance and thermal damage resistance of UHPC at high temperature. Compared to the porosity at 25 °C, the porosity of UHPC at 600 °C increases by 0.68% for the control group, 1.14% for the SF-reinforced group, and only 0.26% for the hybrid fiber-reinforced group. The hybrid fiber-reinforced UHPC exhibits a smaller increase in porosity, a slower degree of crack propagation, and a higher retention of compressive strength after high temperature damage compared to UHPC without fiber and SF-only reinforced UHPC.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100939"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147858161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evacuation performance of occupants at different smoke layer height based on mixed reality","authors":"Zhen Xu ,&nbsp;Xiyan Tang ,&nbsp;Yajun Yang ,&nbsp;Yuan Tian ,&nbsp;Donglian Gu","doi":"10.1016/j.dibe.2026.100945","DOIUrl":"10.1016/j.dibe.2026.100945","url":null,"abstract":"<div><div>Changing smoke layer heights in building fires force evacuees to adapt their postures, thereby significantly affecting evacuation speed. However, existing studies often lack realistic experimental scenarios and reliable data. To this end, this study investigates the evacuation performance of occupants under different smoke layer heights using mixed reality (MR). A highly immersive smoke environment was developed by integrating Fire Dynamics Simulator (FDS) with Unity on HoloLens. Experiments were carried out at four smoke layer heights, comprising 240 trials, where precise three-dimensional (3D) movement data were collected. The effects of smoke layer height on evacuation posture and speed were analyzed both qualitatively and quantitatively. A novel parameter, Dynamic Height Ratio (DHR), was introduced to quantify postural adaptation. A formula for calculating speed incorporating this parameter was developed, with a coefficient of determination (<em>R</em>² = 0.98). This study provides valuable theoretical insights and empirical data to enhance the understanding of evacuation behavior in smoke environments.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100945"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148000958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-informed neural network surrogate for predicting hydration heat evolution profiles of Portland limestone cement (PLC)","authors":"Sangyoung Han ,&nbsp;Yerim Byun ,&nbsp;Hyeyun Lee ,&nbsp;Hyeon-Ji Kim ,&nbsp;Taemin Heo ,&nbsp;Hansol Jang ,&nbsp;Tangwei Mi ,&nbsp;Gyuyong Kim ,&nbsp;Hyun-Do Yun ,&nbsp;Otim Kelvin Kennedy ,&nbsp;Dongho Jeon","doi":"10.1016/j.dibe.2026.100949","DOIUrl":"10.1016/j.dibe.2026.100949","url":null,"abstract":"<div><div>Accurate prediction of the heat-evolution profile is particularly important for Portland-limestone cement (PLC) because limestone does not simply dilute the binder but fundamentally alters the hydration kinetics and reaction pathways. Therefore, relying solely on the final cumulative heat is insufficient; instead, the full time-resolved heat-flow curve is essential for understanding and modeling PLC behavior. This study introduces a data-assisted physics-informed neural network (DA-PINN) that fuses calorimetry with mechanistic kinetics to learn continuous cumulative heat of hydration <em>Q</em>(<em>t</em>, <em>α</em>). The model encodes rate, capacity, and onset as smooth <em>α</em>-dependent functions. Across eight PLC mixtures (0–40% limestone), DA-PINN closely tracks both induction and acceleration stages and shows strong interpolation performance under leave-one-out cross-validation (LOOCV). Additional comparisons with both physics-free multiple layer perceptron (pure MLP) and Knudsen-type kinetic baseline further clarify the benefit of embedding physically constrained kinetics into the learning process. The scope of the present study is deliberately restricted to PLC systems; transfer to chemically distinct binder systems is left for future work and would require separate governing assumptions and independent validation. Within this calibrated PLC domain, DA-PINN provides a practical, interpretable surrogate for reconstructing full hydration-heat curves from sparse calorimetry data and for accelerating low-carbon PLC mixture screening, which is urgently needed.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100949"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148000959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward interactive crowd dynamics in virtual built environment: A BIM-driven and macro–micro integrated crowd simulation framework","authors":"Haoyang Liang ,&nbsp;Jian Sun ,&nbsp;S.C. Wong ,&nbsp;Xiaoqian Liu ,&nbsp;Chi Chiu Lam ,&nbsp;Mun On Wong","doi":"10.1016/j.dibe.2026.100937","DOIUrl":"10.1016/j.dibe.2026.100937","url":null,"abstract":"<div><div>Interactive crowd dynamics are crucial for achieving high-fidelity pedestrian behavior in virtual built environments. This study presents IntCrowd, a novel framework for enhancing interactive crowd simulation within immersive virtual environments. The framework comprises a BIM-driven navigational graph, a macro—micro integrated crowd simulation model comprising multidirectional potential fields and modified social force model, and a human—agent information fusion system. Simulation experiments show IntCrowd is more efficient than agent-based models, achieving an 85.6% reduction in additional computational time for generating more agents. A human-in-the-loop experiment conducted on a CAVE platform further demonstrates that IntCrowd can produce realistic pedestrian behavior closely aligned with real-world characteristics on the pedestrian fundamental diagram. The experiment also indicates IntCrowd significantly increases pedestrians’ perceived presence. The findings underscore the importance of high-fidelity and interactive crowd simulation for experiencing virtual built environments. Moreover, IntCrowd offers a more reliable testbed for studying pedestrian behavior in virtual built environments.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"26 ","pages":"Article 100937"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147945091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}