Pub Date : 2026-03-01Epub Date: 2026-02-04DOI: 10.1016/j.dibe.2026.100870
Fuyi Yao , Jialuo Du , Yingbo Ji , Wenjing Tong , Yangyang Leng
Research on high-rise building fire causal mechanisms remains limited. This study proposes a comprehensive fire cause analysis model for high-rise buildings by integrating text mining with the interpretive structural modelling (ISM) method. Based on text mining of a Chinese dataset containing 123 fire accident investigation reports from 2000 to 2024, 16 causes of high-rise building fire causes were objectively identified. Using UCINET analysis, 14 key causes were extracted, and the Apriori algorithm was applied to reveal 14 strong correlations among them. Subsequently, the ISM method was employed to structure these causes into six hierarchical levels. Results indicate that insufficient fire laws and policies, together with inadequate administrative management, are the fundamental root causes. At the uppermost level, direct causes include fire-related human activities, electrical malfunctions, and defects in fire protection facilities. The findings enhance the objectivity of fire cause identification and provide valuable insights for fire prevention and in high-rise buildings.
{"title":"Causal and correlation analysis of high-rise building fires using text mining and ISM: Evidence from China","authors":"Fuyi Yao , Jialuo Du , Yingbo Ji , Wenjing Tong , Yangyang Leng","doi":"10.1016/j.dibe.2026.100870","DOIUrl":"10.1016/j.dibe.2026.100870","url":null,"abstract":"<div><div>Research on high-rise building fire causal mechanisms remains limited. This study proposes a comprehensive fire cause analysis model for high-rise buildings by integrating text mining with the interpretive structural modelling (ISM) method. Based on text mining of a Chinese dataset containing 123 fire accident investigation reports from 2000 to 2024, 16 causes of high-rise building fire causes were objectively identified. Using UCINET analysis, 14 key causes were extracted, and the Apriori algorithm was applied to reveal 14 strong correlations among them. Subsequently, the ISM method was employed to structure these causes into six hierarchical levels. Results indicate that insufficient fire laws and policies, together with inadequate administrative management, are the fundamental root causes. At the uppermost level, direct causes include fire-related human activities, electrical malfunctions, and defects in fire protection facilities. The findings enhance the objectivity of fire cause identification and provide valuable insights for fire prevention and in high-rise buildings.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100870"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188951","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}
Pub Date : 2026-03-01Epub Date: 2026-02-05DOI: 10.1016/j.dibe.2026.100873
Jin-Yang Gui , Zhao-Hui Lu , Chun-Qing Li
Corrosion of reinforcing steel in concrete structures, especially in chloride-rich environments, remains a leading cause of structural degradation and presents significant challenges for maintenance. Traditional steel corrosion inspection techniques, both direct and indirect, often fall short in terms of accuracy, efficiency, and cost-effectiveness. In this paper, an interpretable machine learning (ML)-aided framework is developed for predicting steel corrosion degree in concrete, which integrates multi-scale feature selection (MSFS), optimal algorithm determination, and SHapley Additive exPlanations (SHAP) techniques, addressing key limitations of conventional ML models, such as limited feature selection, poor generalization, and black-box opacity. The learning capability of the computational model is verified through extensive comparisons with multiple baseline algorithms. A digital example is presented to demonstrate the accuracy and efficiency of the developed framework. From the example, it is found that the MSFS method can identify key features of steel corrosion, such as crack width (w), geometric ratios (cb/d, cl/d, cb/cl), and concrete properties (fc, W/C). This ensures an optimal balance between accuracy and generalization, as validated by 5-fold cross-validation and independent dataset testing, with the optimal model achieving a test set R2 of 0.94 and a 33.6% reduction in RMSE compared to the default model. It is also found that the SHAP technique can further vindicate w and cb/d as the most influential factors governing internal corrosion. This paper pioneers the ML computational models for the prediction of structural deterioration, e.g., steel corrosion in concrete, which can replace traditional mathematical model-based prediction. These innovations represent a significant step toward the future of digital-driven structural performance prediction.
{"title":"Interpretable machine learning-aided prediction of steel corrosion in concrete using advanced multi-scale feature selection and optimization techniques","authors":"Jin-Yang Gui , Zhao-Hui Lu , Chun-Qing Li","doi":"10.1016/j.dibe.2026.100873","DOIUrl":"10.1016/j.dibe.2026.100873","url":null,"abstract":"<div><div>Corrosion of reinforcing steel in concrete structures, especially in chloride-rich environments, remains a leading cause of structural degradation and presents significant challenges for maintenance. Traditional steel corrosion inspection techniques, both direct and indirect, often fall short in terms of accuracy, efficiency, and cost-effectiveness. In this paper, an interpretable machine learning (ML)-aided framework is developed for predicting steel corrosion degree in concrete, which integrates multi-scale feature selection (MSFS), optimal algorithm determination, and SHapley Additive exPlanations (SHAP) techniques, addressing key limitations of conventional ML models, such as limited feature selection, poor generalization, and black-box opacity. The learning capability of the computational model is verified through extensive comparisons with multiple baseline algorithms. A digital example is presented to demonstrate the accuracy and efficiency of the developed framework. From the example, it is found that the MSFS method can identify key features of steel corrosion, such as crack width (<em>w</em>), geometric ratios (<em>c</em><sub><em>b</em></sub>/<em>d</em>, <em>c</em><sub><em>l</em></sub>/<em>d</em>, <em>c</em><sub><em>b</em></sub>/<em>c</em><sub><em>l</em></sub>), and concrete properties (<em>f</em><sub><em>c</em></sub>, <em>W</em>/<em>C</em>). This ensures an optimal balance between accuracy and generalization, as validated by 5-fold cross-validation and independent dataset testing, with the optimal model achieving a test set <em>R</em><sup>2</sup> of 0.94 and a 33.6% reduction in RMSE compared to the default model. It is also found that the SHAP technique can further vindicate <em>w</em> and <em>c</em><sub><em>b</em></sub>/<em>d</em> as the most influential factors governing internal corrosion. This paper pioneers the ML computational models for the prediction of structural deterioration, e.g., steel corrosion in concrete, which can replace traditional mathematical model-based prediction. These innovations represent a significant step toward the future of digital-driven structural performance prediction.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100873"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189063","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}
Pub Date : 2026-03-01Epub Date: 2026-02-06DOI: 10.1016/j.dibe.2026.100876
Peddireddy Sreekanth Reddy, Amarnath Hegde
The study investigates the use of agricultural waste, i.e., Rice Husk Ash (RHA), in altering Bauxite Residue (BR) for pavement applications. Locally available natural soils (NS) was used for comparison. Samples were prepared with water and varying proportions of alkali activators, and their mechanical characteristics were examined through Unconfined Compressive Strength (UCS) and California Bearing Ratio (CBR) tests. Microstructural analyses were carried out using Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD). Heavy metal analysis was performed to assess environmental safety. Results showed that 95% BR with 5% RHA exhibited a remarkable UCS increase from 106.19 kPa (water) to 1247.78 kPa (alkali-activators). The CBR values confirmed superior strength under alkali activation. Both the UCS and CBR fulfilled the sub-base and subgrade requirements specified by standards. Morphological and mineralogical studies supported these improvements. The heavy metal concentrations in optimized samples were within the acceptable limit, further recommending it for field application.
{"title":"Assessing the efficacy of alkali-activated rice husk ash amended bauxite residue composites for pavement applications","authors":"Peddireddy Sreekanth Reddy, Amarnath Hegde","doi":"10.1016/j.dibe.2026.100876","DOIUrl":"10.1016/j.dibe.2026.100876","url":null,"abstract":"<div><div>The study investigates the use of agricultural waste, i.e., Rice Husk Ash (RHA), in altering Bauxite Residue (BR) for pavement applications. Locally available natural soils (NS) was used for comparison. Samples were prepared with water and varying proportions of alkali activators, and their mechanical characteristics were examined through Unconfined Compressive Strength (UCS) and California Bearing Ratio (CBR) tests. Microstructural analyses were carried out using Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD). Heavy metal analysis was performed to assess environmental safety. Results showed that 95% BR with 5% RHA exhibited a remarkable UCS increase from 106.19 kPa (water) to 1247.78 kPa (alkali-activators). The CBR values confirmed superior strength under alkali activation. Both the UCS and CBR fulfilled the sub-base and subgrade requirements specified by standards. Morphological and mineralogical studies supported these improvements. The heavy metal concentrations in optimized samples were within the acceptable limit, further recommending it for field application.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100876"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189061","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}
Pub Date : 2026-03-01Epub Date: 2026-01-14DOI: 10.1016/j.dibe.2026.100849
Daniel Tariku , H.M. Son , Daeik Jang , Solmoi Park
Microcrack formation in concrete poses a risk of durability degradation and ultimate failure of the structure. Calcium aluminate cements (CAC) are susceptible to significant early age microcrack formation due to their rapid setting behavior. Microbially-induced calcium carbonate precipitation (MICP) is a promising research frontier that delivers concrete self-healing capability upon the incorporation of specialized bacteria and nutrients into the cement mix. This study explored the applicability of bacteria-based self-healing technology to mitigate microcrack formation in CAC. The effect of self-healing nutrients such as urea, yeast extract and calcium lactate on the mechanical properties, phase assemblage and reaction kinetics of CAC were investigated. The results demonstrated that the incorporation of self-healing nutrients improved the compressive strength of the specimens by an order of magnitude, ranging from 21 to 97 %. However, the reaction kinetics of CAC was delayed by 25–65 h with the incorporation of yeast extract and calcium lactate.
{"title":"Assessing compatibility of self-healing nutrients for microbially induced calcium carbonate precipitation in calcium aluminate cement","authors":"Daniel Tariku , H.M. Son , Daeik Jang , Solmoi Park","doi":"10.1016/j.dibe.2026.100849","DOIUrl":"10.1016/j.dibe.2026.100849","url":null,"abstract":"<div><div>Microcrack formation in concrete poses a risk of durability degradation and ultimate failure of the structure. Calcium aluminate cements (CAC) are susceptible to significant early age microcrack formation due to their rapid setting behavior. Microbially-induced calcium carbonate precipitation (MICP) is a promising research frontier that delivers concrete self-healing capability upon the incorporation of specialized bacteria and nutrients into the cement mix. This study explored the applicability of bacteria-based self-healing technology to mitigate microcrack formation in CAC. The effect of self-healing nutrients such as urea, yeast extract and calcium lactate on the mechanical properties, phase assemblage and reaction kinetics of CAC were investigated. The results demonstrated that the incorporation of self-healing nutrients improved the compressive strength of the specimens by an order of magnitude, ranging from 21 to 97 %. However, the reaction kinetics of CAC was delayed by 25–65 h with the incorporation of yeast extract and calcium lactate.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100849"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189066","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}
Pub Date : 2026-03-01Epub Date: 2026-01-23DOI: 10.1016/j.dibe.2026.100863
Han-Saem Kim, Taek-Kyu Chung
This study proposes a decision-making framework for site-specific 3D geotechnical characterization to support Geo-BIM-based design in coastal smart cities. High-density geotechnical survey data and geostatistical modeling are integrated to assess site-specific geohazards, including settlement, liquefaction, and seismic amplification. The workflow incorporates preliminary and detailed surveys, remote sensing, and monitoring strategies tailored to vulnerable zones. Using nanozonation and regional-optimum spatial modeling, a high-resolution 3D ground model with a 5 m × 5 m × 1 m grid is constructed. The framework enables regional site characterization, consolidation-induced settlement prediction, and site response analysis, producing 2D/3D hazard zonation maps for early design support. These outputs are embedded into Geo-BIM applications to guide embankment design, ground improvement planning, and risk mitigation. A case study in a reclaimed coastal area demonstrates the model's utility in visualizing subsurface conditions and informing engineering decisions. The proposed framework facilitates geotechnical digitalization and promotes data-driven decision-making in smart city development and digital construction.
本研究提出了一个针对特定地点的三维岩土特征的决策框架，以支持沿海智慧城市中基于geo - bim的设计。高密度的地质技术调查数据和地质统计模型被整合到评估特定地点的地质灾害，包括沉降、液化和地震放大。该工作流程包括初步和详细的调查、遥感和针对脆弱地区的监测策略。利用纳米分区和区域优化空间建模技术，构建了5 m × 5 m × 1 m网格的高分辨率三维地面模型。该框架可以实现区域站点特征、固结引起的沉降预测和站点响应分析，为早期设计提供2D/3D危险分区图。这些输出嵌入到Geo-BIM应用程序中，以指导路堤设计、地面改善规划和风险缓解。在一个填海海岸地区的案例研究表明，该模型在可视化地下条件和为工程决策提供信息方面的实用性。提出的框架促进岩土工程数字化，促进智慧城市发展和数字化建设中的数据驱动决策。
{"title":"Integrating 3D geotechnical characterization and Geo-BIM for geohazard assessment in soft ground","authors":"Han-Saem Kim, Taek-Kyu Chung","doi":"10.1016/j.dibe.2026.100863","DOIUrl":"10.1016/j.dibe.2026.100863","url":null,"abstract":"<div><div>This study proposes a decision-making framework for site-specific 3D geotechnical characterization to support Geo-BIM-based design in coastal smart cities. High-density geotechnical survey data and geostatistical modeling are integrated to assess site-specific geohazards, including settlement, liquefaction, and seismic amplification. The workflow incorporates preliminary and detailed surveys, remote sensing, and monitoring strategies tailored to vulnerable zones. Using nanozonation and regional-optimum spatial modeling, a high-resolution 3D ground model with a 5 m × 5 m × 1 m grid is constructed. The framework enables regional site characterization, consolidation-induced settlement prediction, and site response analysis, producing 2D/3D hazard zonation maps for early design support. These outputs are embedded into Geo-BIM applications to guide embankment design, ground improvement planning, and risk mitigation. A case study in a reclaimed coastal area demonstrates the model's utility in visualizing subsurface conditions and informing engineering decisions. The proposed framework facilitates geotechnical digitalization and promotes data-driven decision-making in smart city development and digital construction.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100863"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077664","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}
Pub Date : 2026-03-01Epub Date: 2026-02-13DOI: 10.1016/j.dibe.2026.100882
Pengcong Du , Renyu Geng , Jinming Jiang , Huiliang Zhang , Jianwei Sun , Bin Du , Yanbo Zhang , Ruiyan Yu , Xuguang Wang , Weijun Gao
The ultra-fine fraction of gold tailings is difficult to utilize due to their tiny size, large surface area, and high clay content. This study proposes a novel and energy-efficient approach by directly utilizing the ultra-fine fraction of gold tailings (UGT, 300–12,000 mesh) as a siliceous raw material to replace quartz sand in autoclaved aerated concrete (AAC), thereby eliminating the energy-intensive ball milling process. The effects of key mix design parameters, including the lime-to-cement ratio, calcium-to-silicon molar ratio, water-to-solid ratio, and aluminum paste dosage, on slurry rheology, mechanical properties, and microstructure were systematically investigated. Under the optimal mix proportion, the prepared UGT-AAC achieved a compressive strength of 4.33 MPa and a dry density of 587 kg/m3, meeting the A3.5 and B06 requirements. Microstructural analyses indicate that strength development is governed by a dense pore-wall skeleton formed by tobermorite and calcium silicate hydrate gels, demonstrating the feasibility of high-value utilization of UGT.
{"title":"Utilization of ultra-fine fraction of gold tailings in autoclaved aerated concrete: Effects of mix design on mechanical properties and microstructure","authors":"Pengcong Du , Renyu Geng , Jinming Jiang , Huiliang Zhang , Jianwei Sun , Bin Du , Yanbo Zhang , Ruiyan Yu , Xuguang Wang , Weijun Gao","doi":"10.1016/j.dibe.2026.100882","DOIUrl":"10.1016/j.dibe.2026.100882","url":null,"abstract":"<div><div>The ultra-fine fraction of gold tailings is difficult to utilize due to their tiny size, large surface area, and high clay content. This study proposes a novel and energy-efficient approach by directly utilizing the ultra-fine fraction of gold tailings (UGT, 300–12,000 mesh) as a siliceous raw material to replace quartz sand in autoclaved aerated concrete (AAC), thereby eliminating the energy-intensive ball milling process. The effects of key mix design parameters, including the lime-to-cement ratio, calcium-to-silicon molar ratio, water-to-solid ratio, and aluminum paste dosage, on slurry rheology, mechanical properties, and microstructure were systematically investigated. Under the optimal mix proportion, the prepared UGT-AAC achieved a compressive strength of 4.33 MPa and a dry density of 587 kg/m<sup>3</sup>, meeting the A3.5 and B06 requirements. Microstructural analyses indicate that strength development is governed by a dense pore-wall skeleton formed by tobermorite and calcium silicate hydrate gels, demonstrating the feasibility of high-value utilization of UGT.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100882"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396714","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}
Pub Date : 2026-03-01Epub Date: 2025-12-11DOI: 10.1016/j.dibe.2025.100823
Jiheum Han , Jewoo Choi , Hyo Seon Park
Elastic metamaterials have emerged as a promising approach for addressing vibration problems in engineering structures, yet practical devices and automated or optimized design methodologies for their frequency tuning remain insufficiently explored in the literature. Motivated by this gap, this study proposes a grid-shaped metamaterial and an automated layout optimization method for frequency tuning. The structure, composed of intersecting grid lines, attenuates structural vibrations through its dynamic interaction and enables intuitive frequency tuning owing to its small set of design variables. Numerical and experimental results confirmed that the optimized layouts effectively matched the target frequency, with errors below 0.3 %. The best configuration achieved a 58.95 % reduction in vibration amplitude. A parameter study revealed the influence of the numbers of rows and columns and the line thickness on the frequency. Overall, the study provides an efficient and practical pathway for tuning metamaterials for vibration mitigation.
{"title":"Layout optimization of the grid-shaped metamaterial-based resonators for frequency tuning","authors":"Jiheum Han , Jewoo Choi , Hyo Seon Park","doi":"10.1016/j.dibe.2025.100823","DOIUrl":"10.1016/j.dibe.2025.100823","url":null,"abstract":"<div><div>Elastic metamaterials have emerged as a promising approach for addressing vibration problems in engineering structures, yet practical devices and automated or optimized design methodologies for their frequency tuning remain insufficiently explored in the literature. Motivated by this gap, this study proposes a grid-shaped metamaterial and an automated layout optimization method for frequency tuning. The structure, composed of intersecting grid lines, attenuates structural vibrations through its dynamic interaction and enables intuitive frequency tuning owing to its small set of design variables. Numerical and experimental results confirmed that the optimized layouts effectively matched the target frequency, with errors below 0.3 %. The best configuration achieved a 58.95 % reduction in vibration amplitude. A parameter study revealed the influence of the numbers of rows and columns and the line thickness on the frequency. Overall, the study provides an efficient and practical pathway for tuning metamaterials for vibration mitigation.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100823"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145750024","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}
Pub Date : 2026-03-01Epub Date: 2025-12-27DOI: 10.1016/j.dibe.2025.100838
Mariana Mateus Pinto , Rafaela Cardoso
Biocementation, or MICP (Microbiologically Induced Calcite Precipitation), has been used with success to repair cracks and consolidate porous stones and other construction materials. An experimental study was performed to investigate biocement adhesion to three different stone materials (limestone, shist and basalt) and to a poly methyl methacrylate (PMMA) control plate. Adhesion strength was quantified by pull-out tests performed under controlled conditions, this being the novel contribution of this paper. The mineralogical composition of the materials, roughness and contact angles with the treatment solutions were determined to better understand adhesion mechanisms. The thickness of the biocement coating on the different materials was measured and visualized under microscope, aiming to conclude that the biocement adheres to the porous and rough stone substrates, which serve as nucleation sites for the precipitation. Adhesion measurements were done after 2 and 4 treatments to understand biocement coating process and the influence of the thickness of the precipitated layer. The adhesion forces recorded, although affected by experimental error, allow understanding that detachment occurs between the precipitate and the substrate. The results suggest that time may affect this adhesion due to the creation of more bacterial attachment and because the thickness of the biocement layer has increased.
{"title":"Study on the adhesion of bacterially precipitated biocement to different stone substrates","authors":"Mariana Mateus Pinto , Rafaela Cardoso","doi":"10.1016/j.dibe.2025.100838","DOIUrl":"10.1016/j.dibe.2025.100838","url":null,"abstract":"<div><div>Biocementation, or MICP (Microbiologically Induced Calcite Precipitation), has been used with success to repair cracks and consolidate porous stones and other construction materials. An experimental study was performed to investigate biocement adhesion to three different stone materials (limestone, shist and basalt) and to a poly methyl methacrylate (PMMA) control plate. Adhesion strength was quantified by pull-out tests performed under controlled conditions, this being the novel contribution of this paper. The mineralogical composition of the materials, roughness and contact angles with the treatment solutions were determined to better understand adhesion mechanisms. The thickness of the biocement coating on the different materials was measured and visualized under microscope, aiming to conclude that the biocement adheres to the porous and rough stone substrates, which serve as nucleation sites for the precipitation. Adhesion measurements were done after 2 and 4 treatments to understand biocement coating process and the influence of the thickness of the precipitated layer. The adhesion forces recorded, although affected by experimental error, allow understanding that detachment occurs between the precipitate and the substrate. The results suggest that time may affect this adhesion due to the creation of more bacterial attachment and because the thickness of the biocement layer has increased.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100838"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939535","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}
Pub Date : 2026-03-01Epub Date: 2025-12-30DOI: 10.1016/j.dibe.2025.100839
Haifeng Jin , Zhen Xu , Ziheng Xu , Nan Li , Paul M. Goodrum
Falls from height (FFH) remain the leading cause of fatalities in construction, highlighting persistent challenges in personal fall protection system (PFPS) planning. Despite regulations, anchorage placements still rely on subjective judgment and static layouts, limiting adaptability to complex site risks. This study develops a computer vision-assisted optimization framework integrating hazard zone modeling and worker posture detection. Vision-based posture data and hazard zone models construct spatial risk fields, providing a basis for anchorage planning. A multi-objective model is formulated to enhance safety performance and reduce swing fall risk, while a simulation module based on genetic algorithms computes Pareto-optimal layouts. Computer vision posture detection is embedded into the iterative module, enabling adaptive adjustments to deviations between planned and observed postures. A high-rise piping construction case study demonstrates the framework's effectiveness in producing safety-resilient and efficient anchorage plans. The proposed method advances PFPS toward intelligent and data-driven safety management.
{"title":"Computer vision-assisted multi-objective spatial optimization of fall protection systems in construction: Integrating hazard zone modeling and posture detection","authors":"Haifeng Jin , Zhen Xu , Ziheng Xu , Nan Li , Paul M. Goodrum","doi":"10.1016/j.dibe.2025.100839","DOIUrl":"10.1016/j.dibe.2025.100839","url":null,"abstract":"<div><div>Falls from height (FFH) remain the leading cause of fatalities in construction, highlighting persistent challenges in personal fall protection system (PFPS) planning. Despite regulations, anchorage placements still rely on subjective judgment and static layouts, limiting adaptability to complex site risks. This study develops a computer vision-assisted optimization framework integrating hazard zone modeling and worker posture detection. Vision-based posture data and hazard zone models construct spatial risk fields, providing a basis for anchorage planning. A multi-objective model is formulated to enhance safety performance and reduce swing fall risk, while a simulation module based on genetic algorithms computes Pareto-optimal layouts. Computer vision posture detection is embedded into the iterative module, enabling adaptive adjustments to deviations between planned and observed postures. A high-rise piping construction case study demonstrates the framework's effectiveness in producing safety-resilient and efficient anchorage plans. The proposed method advances PFPS toward intelligent and data-driven safety management.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100839"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939530","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}
This study evaluates the durability of glass fiber-reinforced polymer (GFRP) bars under sustained loading combined with industrial wastewater. Towards this, twenty-four concrete beams (150 × 200 × 1800 mm) were cast, five with steel reinforcement and the rest with GFRP bars. The beam specimens were subjected to sustained loading at 40 % of ultimate flexural capacity and immersed in wastewater for 3, 6, and 12 months at 25 °C, 40 °C, and 60 °C. Subsequently, four-point bending tests were conducted to assess flexural behavior, including load-displacement response, ultimate capacity, deflection, cracking, and failure modes. Concurrently, bare GFRP bars exposed under identical conditions to assess degradation of the mechanical properties. Results showed up to 12 % capacity loss in steel-reinforced beams, whereas GFRP-reinforced beams maintained superior performance. Bare GFRP bars exhibited strength and stiffness reductions of 6 % and 9 %, respectively, after 12 months at 60 °C. Experimental findings were compared with analytical models available in design codes.
{"title":"Durability of GFRP bars subjected to the combined effect of high sustained load and industrial wastewater","authors":"Hamid Reza Shayegh , Mohsen Ali Shayanfar , Abolfazl Eslami , Sajjad Mirvalad","doi":"10.1016/j.dibe.2025.100840","DOIUrl":"10.1016/j.dibe.2025.100840","url":null,"abstract":"<div><div>This study evaluates the durability of glass fiber-reinforced polymer (GFRP) bars under sustained loading combined with industrial wastewater. Towards this, twenty-four concrete beams (150 × 200 × 1800 mm) were cast, five with steel reinforcement and the rest with GFRP bars. The beam specimens were subjected to sustained loading at 40 % of ultimate flexural capacity and immersed in wastewater for 3, 6, and 12 months at 25 °C, 40 °C, and 60 °C. Subsequently, four-point bending tests were conducted to assess flexural behavior, including load-displacement response, ultimate capacity, deflection, cracking, and failure modes. Concurrently, bare GFRP bars exposed under identical conditions to assess degradation of the mechanical properties. Results showed up to 12 % capacity loss in steel-reinforced beams, whereas GFRP-reinforced beams maintained superior performance. Bare GFRP bars exhibited strength and stiffness reductions of 6 % and 9 %, respectively, after 12 months at 60 °C. Experimental findings were compared with analytical models available in design codes.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100840"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939635","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}
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