Pub Date : 2025-12-20DOI: 10.1016/j.dibe.2025.100832
Linchao Li , Zijian Huang , Junzhen Wang , Bowen Du , Linfabao Dai
This review synthesizes recent advancements in automated construction monitoring, focusing on key dimensions including equipment, methodologies, datasets, evaluation metrics, and practical applications. It examines diverse data collection setups including single camera, unmanned aerial vehicles (UAVs), mobile phones, and multi-cameras, along with a range of models such as deep learning models and simulation-based models. The analysis highlights the critical role of dataset scale, diversity, and realism in model robustness, and reviews commonly used metrics like accuracy, precision, mean Average Precision (mAP), and Frames per Second (FPS) to evaluate performance trade-offs. Applications span safety monitoring, equipment tracking, productivity analysis, and structural health assessment. The review identifies gaps in dataset generalizability, metric standardization, and real-world validation, offering recommendations such as developing hybrid models, large-scale construction-specific datasets, and integrated multi-functional platforms. This work aims to guide future research and support the practical adoption of intelligent monitoring systems for safer and more efficient construction management.
{"title":"Automated construction monitoring based on computer vision: A comprehensive review","authors":"Linchao Li , Zijian Huang , Junzhen Wang , Bowen Du , Linfabao Dai","doi":"10.1016/j.dibe.2025.100832","DOIUrl":"10.1016/j.dibe.2025.100832","url":null,"abstract":"<div><div>This review synthesizes recent advancements in automated construction monitoring, focusing on key dimensions including equipment, methodologies, datasets, evaluation metrics, and practical applications. It examines diverse data collection setups including single camera, unmanned aerial vehicles (UAVs), mobile phones, and multi-cameras, along with a range of models such as deep learning models and simulation-based models. The analysis highlights the critical role of dataset scale, diversity, and realism in model robustness, and reviews commonly used metrics like accuracy, precision, mean Average Precision (mAP), and Frames per Second (FPS) to evaluate performance trade-offs. Applications span safety monitoring, equipment tracking, productivity analysis, and structural health assessment. The review identifies gaps in dataset generalizability, metric standardization, and real-world validation, offering recommendations such as developing hybrid models, large-scale construction-specific datasets, and integrated multi-functional platforms. This work aims to guide future research and support the practical adoption of intelligent monitoring systems for safer and more efficient construction management.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100832"},"PeriodicalIF":8.2,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939634","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 : 2025-12-17DOI: 10.1016/j.dibe.2025.100831
Nina Chi Johansson , Johan Rootzén , Santiago Escudero Carmona
Cement, a crucial material in the construction industry, contributes about 8 % of global greenhouse gas emissions. While substituting clinker with supplementary cementitious materials (SCMs) is a key mitigation measure, SCM availability is expected to decline. In this work, a 2023–2050 scenario analysis predicts a decline in the supply of common SCMs in the EU, with fly ash supply decreasing from 8.5 Mt in 2025 to 1.9–2.7 Mt in 2035 and 0–1.1 Mt in 2045, and granulated blast furnace slag supply decreasing from 18 to 19 Mt in 2025 to 6.9–11.4 Mt in 2035 and 0–3.2 Mt in 2045. Thus, the supply of conventional SCMs will be insufficient to meet demand, even if demand for ordinary Portland cement is assumed to decline significantly in 2025–2045. Efforts to develop the production and logistics of alternatives in order to sustain a lower clinker-to-cement ratio are therefore needed.
{"title":"Concrete change: Exploring future scenarios for the supply of supplementary cementitious materials in the EU","authors":"Nina Chi Johansson , Johan Rootzén , Santiago Escudero Carmona","doi":"10.1016/j.dibe.2025.100831","DOIUrl":"10.1016/j.dibe.2025.100831","url":null,"abstract":"<div><div>Cement, a crucial material in the construction industry, contributes about 8 % of global greenhouse gas emissions. While substituting clinker with supplementary cementitious materials (SCMs) is a key mitigation measure, SCM availability is expected to decline. In this work, a 2023–2050 scenario analysis predicts a decline in the supply of common SCMs in the EU, with fly ash supply decreasing from 8.5 Mt in 2025 to 1.9–2.7 Mt in 2035 and 0–1.1 Mt in 2045, and granulated blast furnace slag supply decreasing from 18 to 19 Mt in 2025 to 6.9–11.4 Mt in 2035 and 0–3.2 Mt in 2045. Thus, the supply of conventional SCMs will be insufficient to meet demand, even if demand for ordinary Portland cement is assumed to decline significantly in 2025–2045. Efforts to develop the production and logistics of alternatives in order to sustain a lower clinker-to-cement ratio are therefore needed.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100831"},"PeriodicalIF":8.2,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939537","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}
For the European countries, the issue of combating climate change has become a matter of existence. Therefore, it is of extreme importance to present economic–based evidence for these countries' climate action. One emerging yet underexplored area is the environmental implications of the Economic Complexity Index (ECI), which reflects the knowledge intensity embedded in a country's production structure. Despite its relevance, studies examining the relationship between ECI and environmental degradation (ED) in the European context remain scarce. This paper aims to fill this gap by investigating the impact of ECI on ED between 1995 and 2021, focusing on the European Union countries recognized for their environmental sustainability efforts. For this purpose, the relationship between ECI and two of the pioneer indicators of ED—ecological footprint (EFP) and carbon emissions (CO2)—is assessed through two separate models. To address the dynamic and heterogeneous structure of the relationship, the novel Method of Moments Quantile Regression (MMQR) approach is employed. Empirical evidence suggests that ECI contributes to ED, with a stronger impact observed on CO2 emissions than on EFP. Another key finding is that higher levels of ED limit the negative environmental effects of ECI. However, the robustness of the findings is confirmed using the Driscoll–Kraay (D–K) standard error estimator and also, the symmetric causality test of Dumitrescu–Hurlin (D–H). As global leaders in environmental initiatives, EU countries must guarantee the availability and variety of green financing sources to expedite the transition to sustainable production methods in sectors impacting the ECI index via the European Investment Bank and the EU Innovation Fund.
Policymakers can provide favorable tax incentives to industries that implement eco-friendly production methods to lower their expenses, thereby rewarding these industries and fostering acceptance of this strategy among sectors beyond this framework. Achieving higher ECI scores through the integration of renewable energy and green technologies is therefore essential for EU countries striving for a greener and more resilient future.
{"title":"Shining the dynamics of the Economic Complexity Index on the European Union's climate change strategy: Evidence from the novel approach of MMQR","authors":"Ömer Faruk Kömürcüoğlu , Elif Duygu Kömürcüoğlu , Sinem Koçak , Dilek Çi̇l , Çiğdem Karış , Aykut Fatih Güven , Mohit Bajaj , Vojtech Blazek","doi":"10.1016/j.dibe.2025.100830","DOIUrl":"10.1016/j.dibe.2025.100830","url":null,"abstract":"<div><div>For the European countries, the issue of combating climate change has become a matter of existence. Therefore, it is of extreme importance to present economic–based evidence for these countries' climate action. One emerging yet underexplored area is the environmental implications of the Economic Complexity Index (ECI), which reflects the knowledge intensity embedded in a country's production structure. Despite its relevance, studies examining the relationship between ECI and environmental degradation (ED) in the European context remain scarce. This paper aims to fill this gap by investigating the impact of ECI on ED between 1995 and 2021, focusing on the European Union countries recognized for their environmental sustainability efforts. For this purpose, the relationship between ECI and two of the pioneer indicators of ED—ecological footprint (EFP) and carbon emissions (CO<sub>2</sub>)—is assessed through two separate models. To address the dynamic and heterogeneous structure of the relationship, the novel Method of Moments Quantile Regression (MMQR) approach is employed. Empirical evidence suggests that ECI contributes to ED, with a stronger impact observed on CO<sub>2</sub> emissions than on EFP. Another key finding is that higher levels of ED limit the negative environmental effects of ECI. However, the robustness of the findings is confirmed using the Driscoll–Kraay (D–K) standard error estimator and also, the symmetric causality test of Dumitrescu–Hurlin (D–H). As global leaders in environmental initiatives, EU countries must guarantee the availability and variety of green financing sources to expedite the transition to sustainable production methods in sectors impacting the ECI index via the European Investment Bank and the EU Innovation Fund.</div><div>Policymakers can provide favorable tax incentives to industries that implement eco-friendly production methods to lower their expenses, thereby rewarding these industries and fostering acceptance of this strategy among sectors beyond this framework. Achieving higher ECI scores through the integration of renewable energy and green technologies is therefore essential for EU countries striving for a greener and more resilient future.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100830"},"PeriodicalIF":8.2,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799059","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}
The growing need for sustainable materials in the built environment has intensified interest in upcycling biomass waste into high-performance construction products. This study introduces a novel approach to valorize peanut husks, which is an abundant but underutilized agricultural residue, by extracting cellulose and converting it into multifunctional aerogels. Peanut husk-derived cellulose was combined with sodium alginate/CaCl2 as a green gelation system, and aerogels with varying cellulose contents (2.5 %, 5 %, 7.5 %, and 10 %) were fabricated via freeze-drying. The samples were further surface-modified with methyltrichlorosilane (MTCS) using a chemical vapor deposition (CVD) method. The resulting aerogels exhibited low densities (0.047–0.130 g/cm3), excellent thermal insulation (0.017–0.029 W m−1 K−1), and high decomposition temperatures (∼336 °C). The MTCS-CVD treatment produced superhydrophobic surfaces (contact angle >150°) with high solvent adsorption capacity (up to 16 × their weight). These results demonstrate a technically feasible route for producing multifunctional cellulose aerogels from agricultural waste, emphasizing material design and process optimization for sustainable applications in energy-efficient and environmentally friendly building materials.
{"title":"Fabrication of superhydrophobic cellulose aerogel from peanut husk biomass for energy-efficient and environmental applications","authors":"Ubolluk Rattanasak , Thanaphat Thetpitak , Pumipat K. Pachana , Kamchai Nuithitikul , Peerapong Jitsangiam , Vanchai Sata , Chai Jaturapitakkul , Prinya Chindaprasirt","doi":"10.1016/j.dibe.2025.100829","DOIUrl":"10.1016/j.dibe.2025.100829","url":null,"abstract":"<div><div>The growing need for sustainable materials in the built environment has intensified interest in upcycling biomass waste into high-performance construction products. This study introduces a novel approach to valorize peanut husks, which is an abundant but underutilized agricultural residue, by extracting cellulose and converting it into multifunctional aerogels. Peanut husk-derived cellulose was combined with sodium alginate/CaCl<sub>2</sub> as a green gelation system, and aerogels with varying cellulose contents (2.5 %, 5 %, 7.5 %, and 10 %) were fabricated via freeze-drying. The samples were further surface-modified with methyltrichlorosilane (MTCS) using a chemical vapor deposition (CVD) method. The resulting aerogels exhibited low densities (0.047–0.130 g/cm<sup>3</sup>), excellent thermal insulation (0.017–0.029 W m<sup>−1</sup> K<sup>−1</sup>), and high decomposition temperatures (∼336 °C). The MTCS-CVD treatment produced superhydrophobic surfaces (contact angle >150°) with high solvent adsorption capacity (up to 16 × their weight). These results demonstrate a technically feasible route for producing multifunctional cellulose aerogels from agricultural waste, emphasizing material design and process optimization for sustainable applications in energy-efficient and environmentally friendly building materials.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100829"},"PeriodicalIF":8.2,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799061","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 : 2025-12-13DOI: 10.1016/j.dibe.2025.100826
Claudio Alanis Ruiz , Twan van Hooff , Bert Blocken , GertJan van Heijst
Unconditioned air infiltration through frequently used entrance doors can degrade building energy performance, indoor air quality, and thermal comfort. Air curtains mitigate these effects and are also critical in smoke and dust control, cleanrooms, and cold rooms. Their performance is commonly expressed as separation efficiency, which depends on jet dynamics and entrainment. While most studies consider single-jet air curtains, this work investigates secondary co-flowing jets as a design strategy to reduce entrainment and enhance separation efficiency. Large eddy simulations (LES), validated against a dedicated particle image velocimetry (PIV) dataset of plane turbulent impinging co-flowing jets, assess the influence of key jet parameters: velocity ratio (R), secondary-jet width (Ws), and inter-jet spacing (d). The results indicate that incorporating secondary jets under suitable discharge conditions increases infiltration-based separation efficiency by up to 5.4 % without compromising the combined infiltration–exfiltration metric; the latter can also improve by up to 3 %. Given baseline efficiencies of 86.2 % (infiltration) and 78.7 % (combined) for an optimized single-jet curtain, these gains are significant.
{"title":"Large eddy simulation of optimized air curtain separation via secondary co-flowing jets","authors":"Claudio Alanis Ruiz , Twan van Hooff , Bert Blocken , GertJan van Heijst","doi":"10.1016/j.dibe.2025.100826","DOIUrl":"10.1016/j.dibe.2025.100826","url":null,"abstract":"<div><div>Unconditioned air infiltration through frequently used entrance doors can degrade building energy performance, indoor air quality, and thermal comfort. Air curtains mitigate these effects and are also critical in smoke and dust control, cleanrooms, and cold rooms. Their performance is commonly expressed as separation efficiency, which depends on jet dynamics and entrainment. While most studies consider single-jet air curtains, this work investigates secondary co-flowing jets as a design strategy to reduce entrainment and enhance separation efficiency. Large eddy simulations (LES), validated against a dedicated particle image velocimetry (PIV) dataset of plane turbulent impinging co-flowing jets, assess the influence of key jet parameters: velocity ratio (<em>R</em>), secondary-jet width (<em>W</em><sub><em>s</em></sub>), and inter-jet spacing (<em>d</em>). The results indicate that incorporating secondary jets under suitable discharge conditions increases infiltration-based separation efficiency by up to 5.4 % without compromising the combined infiltration–exfiltration metric; the latter can also improve by up to 3 %. Given baseline efficiencies of 86.2 % (infiltration) and 78.7 % (combined) for an optimized single-jet curtain, these gains are significant.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100826"},"PeriodicalIF":8.2,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799060","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 presents the optimization of alginate-encapsulated bacterial spores (AEBS) for self-healing concrete. Bacillus sphaericus LMG 22257 spores were encapsulated in alginate microcapsules using ionotropic gelation, followed by freeze-drying. Response surface methodology was employed to determine the optimal conditions for bacterial spore microencapsulation, considering alginate concentration, calcium chloride concentration, and spore inoculum. The resulting AEBS were characterized in terms of encapsulation yield, capsule hardness, and swelling capacity. Statistical analysis revealed the significance and validity of the model. In addition, colorimetric urea analysis showed that AEBS decomposed urea more effectively than non-encapsulated bacterial spores. The self-healing performance was assessed via image processing and microstructural analysis. The mortar specimens treated with AEBS exhibited a complete crack-healing ratio (100 %) within 14 days, with the formation of CaCO3 confirmed as the healing product. These findings indicate that AEBS prepared under optimal conditions have a strong potential for crack repair in concrete structures.
{"title":"Enhancing self-healing concrete performance through optimized bacterial spore encapsulation using response surface methodology","authors":"Jirapa Intarasoontron , Pitcha Jongvivatsakul , Pattharaphon Chindasiriphan , Suched Likitlersuang , Pranee Rojsitthisak , Wiboonluk Pungrasmi","doi":"10.1016/j.dibe.2025.100828","DOIUrl":"10.1016/j.dibe.2025.100828","url":null,"abstract":"<div><div>This study presents the optimization of alginate-encapsulated bacterial spores (AEBS) for self-healing concrete. <em>Bacillus sphaericus</em> LMG 22257 spores were encapsulated in alginate microcapsules using ionotropic gelation, followed by freeze-drying. Response surface methodology was employed to determine the optimal conditions for bacterial spore microencapsulation, considering alginate concentration, calcium chloride concentration, and spore inoculum. The resulting AEBS were characterized in terms of encapsulation yield, capsule hardness, and swelling capacity. Statistical analysis revealed the significance and validity of the model. In addition, colorimetric urea analysis showed that AEBS decomposed urea more effectively than non-encapsulated bacterial spores. The self-healing performance was assessed via image processing and microstructural analysis. The mortar specimens treated with AEBS exhibited a complete crack-healing ratio (100 %) within 14 days, with the formation of CaCO<sub>3</sub> confirmed as the healing product. These findings indicate that AEBS prepared under optimal conditions have a strong potential for crack repair in concrete structures.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100828"},"PeriodicalIF":8.2,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798665","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 : 2025-12-13DOI: 10.1016/j.dibe.2025.100827
Yongdan Wang , Hainian Wang , Ziming Liu
The diffusion behavior between aged asphalt and rejuvenators is critical for designing effective pavement recycling strategies. This study investigated the diffusion behavior of three rejuvenators using experimental and molecular dynamics (MD) simulations. The interaction performance was assessed by wetting, anti-aging, and self-healing analysis. The micro-interface diffusion was characterized by optical parameters, while MD simulations illuminated the underlying mechanism. Comprehensive behavior was evaluated by a weighted sum model (WSM). Results showed that Industrial vegetable oil (IV) achieved a superior comprehensive performance with the strongest interfacial energy (increased at least by 28 %), attributed to polar bonds between its carboxyl groups and oxidized asphalt. Refined waste engine oil (RW) exhibited the highest diffusion coefficient indicating rapid diffusion, while Naphthenic oil (NO) showed slower diffusion and weaker integration (50 % difference). Increased time and elevated temperature (from 25 °C to 70 °C) significantly enhanced diffusion, with IV achieving the most uniform morphology at high temperatures. The WSM score ranked the overall performance as IV (0.82) > RW (0.75) > NO (0.58). MD-derived diffusion coefficients aligned with experimental data, providing multi-scale insights for rational rejuvenators selection in asphalt recycling.
{"title":"Enhancing durability of reclaimed asphalt through interface diffusion optimization: Experimental and molecular dynamics","authors":"Yongdan Wang , Hainian Wang , Ziming Liu","doi":"10.1016/j.dibe.2025.100827","DOIUrl":"10.1016/j.dibe.2025.100827","url":null,"abstract":"<div><div>The diffusion behavior between aged asphalt and rejuvenators is critical for designing effective pavement recycling strategies. This study investigated the diffusion behavior of three rejuvenators using experimental and molecular dynamics (MD) simulations. The interaction performance was assessed by wetting, anti-aging, and self-healing analysis. The micro-interface diffusion was characterized by optical parameters, while MD simulations illuminated the underlying mechanism. Comprehensive behavior was evaluated by a weighted sum model (WSM). Results showed that Industrial vegetable oil (IV) achieved a superior comprehensive performance with the strongest interfacial energy (increased at least by 28 %), attributed to polar bonds between its carboxyl groups and oxidized asphalt. Refined waste engine oil (RW) exhibited the highest diffusion coefficient indicating rapid diffusion, while Naphthenic oil (NO) showed slower diffusion and weaker integration (50 % difference). Increased time and elevated temperature (from 25 °C to 70 °C) significantly enhanced diffusion, with IV achieving the most uniform morphology at high temperatures. The WSM score ranked the overall performance as IV (0.82) > RW (0.75) > NO (0.58). MD-derived diffusion coefficients aligned with experimental data, providing multi-scale insights for rational rejuvenators selection in asphalt recycling.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100827"},"PeriodicalIF":8.2,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939632","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 : 2025-12-11DOI: 10.1016/j.dibe.2025.100825
Su Changwang , Shan Changxi , Hu Shaowei , Pan Fuqu , Zheng Zhichao , Ye Yuxiao , Zhang Haifen
Leakage detection and diagnosis of water supply pipe are crucial for ensuring urban water safety and reducing waste of water resources. Nowadays, pipe leakage is mainly detected using single-modal information (such as images, sound, etc.) combined with various numerical models or algorithms. However, there are many factors that affect pipe leakage in real environment. It is difficult for single-modal data to reflect the true information of pipe leakage accurately, and the collected data often have the problem of asymmetric information or partial missing. To address these challenges, an improved heterogeneous graph neural network model (p-HTGNN) with multi-modal information fusion is proposed, and the leakage monitoring experiment of the water supply pipe is carried out. The experimental and analytical results show that p-HTGNN achieves an F-score of 88.5 % for the classification of leakage defects and an F-score of 86.5 % for the diagnosis of leakage risk level. The recognition accuracy for different features all exceeds 95 %, with overall performance superior to other traditional detection algorithms. This work provides a novel method for accurately reflecting the actual situation of water supply pipe leakage and for carrying out leakage diagnosis intelligently and efficiently.
{"title":"Intelligent diagnosis of water supply pipe leakage based on multi-modal information fusion and improved heterogeneous temporal graph neural network","authors":"Su Changwang , Shan Changxi , Hu Shaowei , Pan Fuqu , Zheng Zhichao , Ye Yuxiao , Zhang Haifen","doi":"10.1016/j.dibe.2025.100825","DOIUrl":"10.1016/j.dibe.2025.100825","url":null,"abstract":"<div><div>Leakage detection and diagnosis of water supply pipe are crucial for ensuring urban water safety and reducing waste of water resources. Nowadays, pipe leakage is mainly detected using single-modal information (such as images, sound, etc.) combined with various numerical models or algorithms. However, there are many factors that affect pipe leakage in real environment. It is difficult for single-modal data to reflect the true information of pipe leakage accurately, and the collected data often have the problem of asymmetric information or partial missing. To address these challenges, an improved heterogeneous graph neural network model (p-HTGNN) with multi-modal information fusion is proposed, and the leakage monitoring experiment of the water supply pipe is carried out. The experimental and analytical results show that p-HTGNN achieves an F-score of 88.5 % for the classification of leakage defects and an F-score of 86.5 % for the diagnosis of leakage risk level. The recognition accuracy for different features all exceeds 95 %, with overall performance superior to other traditional detection algorithms. This work provides a novel method for accurately reflecting the actual situation of water supply pipe leakage and for carrying out leakage diagnosis intelligently and efficiently.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100825"},"PeriodicalIF":8.2,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798666","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 : 2025-12-11DOI: 10.1016/j.dibe.2025.100806
Jing Cao , Xiaojie Yang , Yaming Shi , Yi Yang , Yuan Qin , Junrui Chai , Zengguang Xu
3D-printed concrete has significant potential for applications in the construction industry. However, compatibility issues still exist when combining it with conventional steel reinforcement. Fiber-reinforced 3D-printed concrete is commonly used, but the fiber distribution affects the mechanical properties of the material. During the printing process, fiber agglomeration may occur, and currently, research on its influencing mechanism and microstructural analysis is relatively limited. To evaluate the influence of fiber agglomeration distribution characteristics on cement-based materials, this study established a two-dimensional finite element model of 3D-printed steel fiber-reinforced cement-based material (3DP-SFRCBM) using a parametric programming language. The model consists of steel fibers, cement mortar, and an interfacial transition zone (ITZ), and considers different fiber distribution widths (with β ratios of 20 %, 40 %, 60 %, 80 %, and 100 %) and orientations (horizontal, vertical, and random). At the same time, the Weibull distribution was applied to describe the uniformity of the ITZ (with homogeneity parameters m = 6 and 20), simulating the entire failure process of cement under uniaxial tensile loading. The results show that the direction and orientation of fiber agglomeration have a significant effect on the peak strength of the material. When the interfacial homogeneity parameter is m = 6, the influence of fiber orientation on peak stress follows the order: vertical (parallel to the loading direction) > random > horizontal (parallel to the direction perpendicular to loading). When the homogeneity increases, the results are opposite. For a constant fiber orientation, the horizontal fiber agglomeration direction exhibits a higher peak stress; improved homogeneity contributes to higher peak stress and more stable results. In addition, the directionality and concentration of fibers have an important influence on the formation of final cracks; fiber agglomeration leads to the formation of local stress concentration regions, which cause cracks in these regions to propagate rapidly. This study further reveals the mechanism of the fiber agglomeration phenomenon in 3D-printed fiber-reinforced composites and provides a theoretical basis for optimizing printing processes and material mix designs in future research.
{"title":"Numerical analysis of mechanical properties of steel fiber composite cement mortar considering non-uniformity in 3D printing","authors":"Jing Cao , Xiaojie Yang , Yaming Shi , Yi Yang , Yuan Qin , Junrui Chai , Zengguang Xu","doi":"10.1016/j.dibe.2025.100806","DOIUrl":"10.1016/j.dibe.2025.100806","url":null,"abstract":"<div><div>3D-printed concrete has significant potential for applications in the construction industry. However, compatibility issues still exist when combining it with conventional steel reinforcement. Fiber-reinforced 3D-printed concrete is commonly used, but the fiber distribution affects the mechanical properties of the material. During the printing process, fiber agglomeration may occur, and currently, research on its influencing mechanism and microstructural analysis is relatively limited. To evaluate the influence of fiber agglomeration distribution characteristics on cement-based materials, this study established a two-dimensional finite element model of 3D-printed steel fiber-reinforced cement-based material (3DP-SFRCBM) using a parametric programming language. The model consists of steel fibers, cement mortar, and an interfacial transition zone (ITZ), and considers different fiber distribution widths (with <em>β</em> ratios of 20 %, 40 %, 60 %, 80 %, and 100 %) and orientations (horizontal, vertical, and random). At the same time, the Weibull distribution was applied to describe the uniformity of the ITZ (with homogeneity parameters <em>m</em> = 6 and 20), simulating the entire failure process of cement under uniaxial tensile loading. The results show that the direction and orientation of fiber agglomeration have a significant effect on the peak strength of the material. When the interfacial homogeneity parameter is <em>m</em> = 6, the influence of fiber orientation on peak stress follows the order: vertical (parallel to the loading direction) > random > horizontal (parallel to the direction perpendicular to loading). When the homogeneity increases, the results are opposite. For a constant fiber orientation, the horizontal fiber agglomeration direction exhibits a higher peak stress; improved homogeneity contributes to higher peak stress and more stable results. In addition, the directionality and concentration of fibers have an important influence on the formation of final cracks; fiber agglomeration leads to the formation of local stress concentration regions, which cause cracks in these regions to propagate rapidly. This study further reveals the mechanism of the fiber agglomeration phenomenon in 3D-printed fiber-reinforced composites and provides a theoretical basis for optimizing printing processes and material mix designs in future research.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100806"},"PeriodicalIF":8.2,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939633","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 : 2025-12-11DOI: 10.1016/j.dibe.2025.100824
Li Ai , David Bianco , Vafa Soltangharaei , Rafal Anay , Mahmoud Bayat , Paul Ziehl
This research investigates different nondestructive evaluation (NDE) methods to assess concrete under alkali-silica reaction (ASR) development. Four methods including acoustic emission (AE), ultrasonic pulse velocity (UPV), crack width measurement, and strain measurement were applied to reactive and control specimens under accelerated ASR conditioning. The innovation lies in using NDE methods to monitor concrete with varying aggregate sizes, quantifying method sensitivity through measured indices, and highlighting the effectiveness of each method to capture ASR development. The results indicate that the unconfined reactive fine-aggregate sample exhibited isotropic expansion, while coarse-aggregate specimens showed around 50 % greater longitudinal expansion and AE cumulative signal strength up to 3.2 times higher. Furthermore, the reinforcing effect was more significant in the reactive coarse aggregate samples compared to the reactive fine aggregate ones. The ASR detection effectiveness for the four methods is 67 % for AE, 51 % for strain measurement, 12 % for crack width measurement, and 1 % for UPV.
{"title":"Evaluating the impact of aggregate size and reinforcement on alkali-silica reaction in concrete through nondestructive testing techniques","authors":"Li Ai , David Bianco , Vafa Soltangharaei , Rafal Anay , Mahmoud Bayat , Paul Ziehl","doi":"10.1016/j.dibe.2025.100824","DOIUrl":"10.1016/j.dibe.2025.100824","url":null,"abstract":"<div><div>This research investigates different nondestructive evaluation (NDE) methods to assess concrete under alkali-silica reaction (ASR) development. Four methods including acoustic emission (AE), ultrasonic pulse velocity (UPV), crack width measurement, and strain measurement were applied to reactive and control specimens under accelerated ASR conditioning. The innovation lies in using NDE methods to monitor concrete with varying aggregate sizes, quantifying method sensitivity through measured indices, and highlighting the effectiveness of each method to capture ASR development. The results indicate that the unconfined reactive fine-aggregate sample exhibited isotropic expansion, while coarse-aggregate specimens showed around 50 % greater longitudinal expansion and AE cumulative signal strength up to 3.2 times higher. Furthermore, the reinforcing effect was more significant in the reactive coarse aggregate samples compared to the reactive fine aggregate ones. The ASR detection effectiveness for the four methods is 67 % for AE, 51 % for strain measurement, 12 % for crack width measurement, and 1 % for UPV.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":"25 ","pages":"Article 100824"},"PeriodicalIF":8.2,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798726","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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