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        <title>Frontiers in Built Environment | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/built-environment</link>
        <description>RSS Feed for Frontiers in Built Environment | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-07-08T12:27:52.357+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1837617</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1837617</link>
        <title><![CDATA[A governance-calibrated machine learning pipeline for predicting change order ratio under extreme data scarcity in public construction]]></title>
        <pubdate>2026-07-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mohammed A. KA. Al-Btoush</author><author>Hashem Khaled Almashaqbeh</author><author>Imad Al Shalout</author><author>Ja’far A. Aldiabat Al-Btoosh</author><author>Taiseer Mustafa Rawashdeh</author><author>Amani Ismail Alsmadi</author>
        <description><![CDATA[IntroductionPredicting change order magnitude in fragmented public construction systems remains methodologically unreliable, particularly under extreme data scarcity and correlated project attributes. This study develops a governance-calibrated predictive architecture for estimating the Change Order Ratio (COR) using objective contractual and design records from 21 public projects in Jordan, and is therefore framed as preliminary, proof-of-concept evidence from a small, single-context sample rather than externally generalizable inference.MethodsTo prevent overfitting and validation bias, a leakage-free nested Leave-One-Out Cross-Validation (LOOCV) framework integrates regularized regression and nonlinear Support Vector Regression (SVR).ResultsThe unregularized baseline achieves strong in-sample fit (R2 of 0.84) but deteriorates under cross-validation (R2 of 0.54), suggesting instability in small datasets. Regularization enhances robustness (LASSO LOOCV R2 of 0.70), while nonlinear SVR delivers the strongest generalization (LOOCV R2 of 0.76; RMSE of 1.25), suggesting curvature and interaction structures beyond linear shrinkage in this sample. Sensitivity analysis identifies nonlinear amplification of design completeness and positions Requests for Information as leading instability indicators.DiscussionThe findings suggest that change-order volatility is more closely associated with tender-stage information and documentation conditions than with project scale or contractual strictness in the studied context. The study contributes a defensible small-sample modeling framework and highlights upstream documentation maturity as the primary leverage point for enhancing predictability in data-scarce public-sector project delivery environments.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1883353</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1883353</link>
        <title><![CDATA[Lightweight deep learning for sustainable adobe construction: a block-level baseline aligned with circular economy principles and sustainable development goals]]></title>
        <pubdate>2026-07-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Carlos Damián Pinto Almeida</author><author>Nancy Jordán Buenaño</author>
        <description><![CDATA[IntroductionThe construction sector accounts for nearly 37% of global energy-related CO2 emissions, motivating renewed interest in low-carbon vernacular materials such as stabilized adobe. The integration of recycled inputs into adobe formulations advances circular-economy principles in the built environment, yet large-scale adoption is constrained by the absence of objective, scalable quality-control methods.MethodsWe present a methodologically rigorous baseline for AI-driven visual quality control in stabilized adobe construction. A dataset of 330 images was constructed from 55 physical adobe blocks fabricated under controlled laboratory conditions with three circular-economy stabilization mixtures: recycled polyethylene terephthalate (1.5%), sugarcane bagasse fiber (8%), and Portland cement (10%). Each block was photographed from six standardized angles. To eliminate data leakage, we implemented strict block-level data splitting. A MobileNetV2 transfer learning pipeline with frozen ImageNet weights, aggressive data augmentation, L2 regularization, and balanced class weights was developed. Performance was characterized through accuracy with bootstrap 95% confidence intervals, per-class metrics, ROC AUC and Average Precision, five-fold block-level cross-validation, ablation study, and Grad-CAM interpretability.ResultsThe model achieved 80.95% test accuracy (95% CI: 69.0%–92.9%) on a held-out set of seven physical blocks (42 images). AUC = 0.858 and Average Precision = 0.944. Per-class F1-scores were 0.692 (sound) and 0.862 (defective). Block-level five-fold cross-validation confirmed stability at 70.0% (95% CI: 60.7%–79.2%). Ablation showed: simple CNN 71.43%, MobileNetV2 without augmentation 71.43%, complete pipeline 80.95% (+9.5 pp). Grad-CAM confirmed attention to physically meaningful surface features. The 9.24 MB model footprint enables offline deployment on commodity smartphones.ConclusionThis work establishes a methodologically rigorous baseline for AI-driven quality control in stabilized adobe construction. By demonstrating meaningful performance with modest datasets and edge-deployable architectures, this study supports broader adoption of circular-economy adobe construction and contributes to Sustainable Development Goals 9, 11, 12, and 13. Future work should expand the dataset, evaluate hierarchical classification, and assess field deployment.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1856289</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1856289</link>
        <title><![CDATA[Overview of blowout preventers systems and predictive analytics using machine learning: a review]]></title>
        <pubdate>2026-07-08T00:00:00Z</pubdate>
        <category>Review</category>
        <author>B. Naveen Kumar</author><author>M. Aslam Abdullah</author>
        <description><![CDATA[Blowout Preventers (BOPs) are vital safety devices used in oil and gas drilling to control sudden pressure surges and prevent accidents that can cause severe environmental and economic damage. However, past disasters, such as the deepwater horizon incident, show that even modern BOPs can fail due to equipment issues, human error, or poor maintenance. This review paper explains how combining traditional engineering approaches with Machine Learning (ML) can make BOPs more dependable and efficient. It covers common BOP designs, failure causes, and lessons from real-world blowout incidents. Various risk analysis methods such as Failure Mode, Effects, and Criticality Analysis (FMECA), Fault Tree Analysis (FTA), Reliability Block Diagram (RBD), and Dynamic Bayesian Networks (DBN) are compared, with DBN identified as the best choice for real-time monitoring and predicting failures. The paper also explores how ML can detect gas kicks early, predict underground pressure, and monitor BOP health, helping drilling companies act before problems become disasters. By utilising these smart technologies, the industry can enhance safety, minimise downtime, and drill in a more sustainable manner. By integrating artificial intelligence and ML techniques with traditional engineering methods, the oil and gas industry can improve and enhance drilling efficiency, minimise non-productive time, and reduce environmental risks for further exploration of energy.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1883823</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1883823</link>
        <title><![CDATA[Building the future through the wisdom of the past: water management and hydraulic resilience in the Byzantine aqueduct system of the Holy Monastery of Dochiariou, Mount Athos]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>G.-Fivos Sargentis</author><author>Nikolaos Papadodimas</author>
        <description><![CDATA[Monastic communities established in isolated and environmentally demanding landscapes historically developed sophisticated hydraulic infrastructures to ensure long-term self-sufficiency and resilience. This study investigates the historical water management system of the Holy Monastery of Dochiariou on Mount Athos, Greece, a Byzantine monastic complex founded in the late 10th century. Combining in situ field observations with historical and architectural analysis, the study reconstructs an integrated gravity-driven hydraulic network consisting of subterranean qanat-type galleries, open channels, watermills, cascading reservoirs, concealed conduits, and inverted siphons. The analysis positions the system comparatively within Ancient Greek, Roman, Ancient Persian, and Byzantine hydraulic traditions using criteria related to water capture, conveyance, storage, energy use, and organizational logic. An approximate water balance assessment based on the identified storage infrastructure is also introduced to evaluate the functional capacity and self-sufficiency potential of the monastic complex. The results indicate that the system combined source diversification, distributed storage, passive operation, and adaptation to topographic constraints to sustain monastic activities over long periods. Rather than proposing direct technological replication, the study identifies transferable principles relevant to contemporary discussions on decentralized, resilient, and resource-efficient water infrastructure.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1837367</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1837367</link>
        <title><![CDATA[Engineering-integrated robotic timber diagrids: co-located analysis-to-fabrication workflow and rapid assembly]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Aryan Rezaei Rad</author><author>AnnaLisa Meyboom</author><author>Nicholas Hoban</author>
        <description><![CDATA[Advanced design, engineering, and manufacturing tools linked through a common digital workflow are enabling a new approach to timber construction based on parametric, component-based systems that preserve data coherence across disciplines. This is especially important for bespoke timber structures, where fragmented exchange-file workflows often separate geometric design, structural verification, fabrication, and assembly. This paper presents a new structural system as a double-curved box-beam diagrid timber wall assembled through a robotically fabricated, self-locating wood-to-wood cross-lap grammar that can be mapped onto complex curved surfaces. Assembly intent is encoded directly into the parts through embedded positional constraints, enabling measurement-free erection and reducing tolerance stacking. A co-located computer-aided design, engineering, and manufacturing workflow is implemented to reduce drift between analyzed, fabricated, and assembled states. Validation through a 1:1 prototype includes 116 structural web elements, 624 cross-lap joints, and 200 non-structural flanges assembled in 4 hours using nominal zero-gap joints. Fabrication results show 78% average sheet utilization from 2.0 m × 4.0 m stock, with joint openings within ±0.5 to 1.0 mm of nominal. The study demonstrates a reproducible pathway for engineering-integrated design for manufacture and assembly of complex timber structures.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1863309</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1863309</link>
        <title><![CDATA[Model test study on high-clay-content bauxite slime under the synergistic action of drainage body layout and cement modification]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhiqiang Wu</author><author>Chunyang Yin</author><author>Jiqun Dai</author><author>Kai Xu</author><author>Yinkun Li</author>
        <description><![CDATA[High-clay-content bauxite slime possesses extremely low permeability and high plasticity, which severely limits its large-scale geotechnical reuse. To improve its drainage consolidation efficiency, this study conducted staged vacuum loading model tests to investigate the effects of drainage body layout (vertical vs. horizontal) and cement modification (0% vs. 2%) on the dewatering and strength development of the slime. The results show that the horizontal drainage layout consistently outperforms the vertical layout under both non-cemented and cemented conditions. Under the non-cemented condition, the horizontal layout increases final settlement by 14.9%, total drainage volume by 8.1%, and shortens treatment duration by 17.7%, compared with the vertical layout. Under the cemented condition, the horizontal layout increases final settlement by 16.5%, total drainage volume by 6.2%, and shortens treatment duration by 21.4%, compared with the vertical layout. Cement addition further improves the absolute drainage performance: for the vertical layout, it boosts total drainage volume by 29.8% and reduces consolidation time by 12.5%; for the horizontal layout, it boosts total drainage volume by 27.6% and reduces consolidation time by 16.5%. This improvement is mainly attributed to the formation of a skeletal structure by cement hydration products, which enhances permeability and vacuum transmission. Moreover, compared with the vertical layout, the horizontal layout produces a more uniform distribution of density, water content, and penetration strength along the drainage distance and depth, which is particularly beneficial for large-area treatment. Microstructural analyses (mercury intrusion porosimetry and SEM) reveal that cement hydration products preferentially fill micropores, while the horizontal drainage path promotes a multimodal pore size distribution with larger inter-platelet pores. The combination of horizontal drainage and cement modification exhibits a complementary enhancement effect, jointly optimizing the consolidation of high-clay, high-moisture bauxite slime. This work provides a practical approach for efficient volume reduction and resource utilization of industrial clay-rich waste slurries.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1827874</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1827874</link>
        <title><![CDATA[Influence of sand gradation and binder-to-sand ratio on the development of 3D printable cementitious mix with partial replacement of cement by waste marble powder]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>P. Janani</author><author>G. Mohan Ganesh</author>
        <description><![CDATA[This study presents the particle size influence of sand and binder to sand ratio for better extrusion in three-dimensional (3D) printing concrete mix. It also addresses the shape stability tests associated with subsequent layer weight holding capacity for 3D printing. Concrete mixes with aggregate size passing through 2.36-mm and 1.18-mm sieves were evaluated with different binder-to-sand ratios of 1:2, 1:1.6, and 1:1.2. The flow table and extrusion test were investigated to determine the most effective printing material mix. Results show that the 1:1.2 ratio exhibited better extrusion compared with 1:2 and 1:1.6. The flow table value is around 165 mm. Subsequently, the compressive strength test of waste marble powder replacement to cement from 5% to 20% was evaluated with the finalized ratio of 3D printable material mix. The optimized mix proportion and replacement was subjected to printer-based assessment for extrusion test and buildability.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1804487</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1804487</link>
        <title><![CDATA[Establishment of bearing formula and numerical study of mechanical behavior of multi-parameter coupled spiral pile]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zeng Fanxing</author><author>Jiang Wen</author><author>Yang Guang</author><author>Hu Wenbo</author><author>Chen Yin</author><author>Xiao Yun</author><author>Liu Liyun</author><author>Pan Deng</author><author>Xia Yuanyou</author>
        <description><![CDATA[This research optimizes the bearing performance of solid-waste recycled spiral composite reinforcements in soft-soil foundation treatment, using theoretical analysis, numerical simulation, and engineering verification to investigate spiral piles’ mechanical behavior under multi-parameter coupling. Based on pile-soil compaction principle, shear resistance mechanisms, and limit equilibrium theory from JGJ94-2008 and JGJ79-2012 codes, an engineering formula for spiral pile bearing capacity is established, incorporating soil shear-strength parameters (c′, ϕ′) and pile geometric characteristics (D/d ratio, l/d ratio). A 3D pile-soil interaction model via Abaqus analyzes load-displacement response, axial force distribution, and soil stress-deformation under vertical load. Results show pile-side friction contributes ∼93% of ultimate bearing capacity, enhanced by spiral blade extrusion-shearing. Increasing blade width improves friction resistance, boosting capacity by ∼29%, while excessive pitch reduces it by 18%. A “sparse-top-dense-bottom” variable-pitch arrangement is proposed to balance shallow friction/deep end resistance, optimizing capacity and economic efficiency. Engineering verification shows <5% error between theoretical formula and simulation, validating model reliability, providing theoretical/practical references for solid waste utilization and soft-soil reinforcement in power engineering.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1879853</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1879853</link>
        <title><![CDATA[Digital twin systems for whole-life carbon assessment in net-zero building retrofit in the United Kingdom: a systematic literature review and policy analysis]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Adiba Shafique</author><author>Mohammad Tahir</author>
        <description><![CDATA[IntroductionBuildings and construction contribute substantially to global and United Kingdom carbon emissions, and achieving net-zero targets requires accelerated retrofit of the existing building stock. Digital Twin (DT) systems are increasingly promoted for real-time monitoring, predictive analytics and lifecycle performance optimisation, yet their ability to support whole-life carbon (WLC) assessment in United Kingdom retrofit contexts remains unclear.MethodsThis study conducted a PRISMA-guided systematic literature review and policy analysis of 62 sources, comprising 42 peer-reviewed academic papers and 20 United Kingdom government, parliamentary and industry documents. Sources were drawn from Scopus, Web of Science, ScienceDirect and Google Scholar. The review used quality appraisal and thematic analysis to examine DT capabilities across EN 15978 lifecycle modules, RICS Whole Life Carbon Assessment requirements and United Kingdom retrofit policy instruments.ResultsThe findings show that current DT research is strongly weighted towards operational carbon, while embodied carbon and full WLC integration remain underdeveloped. Many systems described as digital twins function more closely as digital shadows with limited or one-way data flows. Reported energy-saving claims are often based on well-instrumented commercial buildings and are not always transferable to the heterogeneous domestic retrofit stock that dominates the United Kingdom's net-zero challenge. Retrofit-specific DT applications remain limited despite the importance of existing buildings in the 2050 stock.DiscussionFour main gaps are identified: the absence of integrated DT-WLC frameworks across all EN 15978 modules, the underrepresentation of retrofit-focused DT research, limited alignment with United Kingdom policy and standards, and weak integration between static lifecycle assessment databases and dynamic DT systems. The paper proposes a conceptual five-layer DT-WLC integration framework and a policy-aligned research agenda to support future validation, interoperability and retrofit-scale implementation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1883191</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1883191</link>
        <title><![CDATA[GIS-based assessment of climate-zone shifts in Spain under RCP scenarios: ESG-oriented urban regeneration and real estate valuation]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Carmen Díaz-López</author><author>Carmen M. Muñoz-González</author><author>Alejandro Morales-Ruíz</author><author>María Dolores Joyanes-Díaz</author><author>Cristián Salazar-Concha</author><author>Konstantin Verichev</author>
        <description><![CDATA[IntroductionClimate change is modifying the climatic assumptions embedded in building regulation, urban regeneration policy and real estate valuation. In Spain, building-code climate zones combine winter and summer climatic severity, which are directly linked to heating demand, cooling demand, thermal comfort and envelope-performance requirements.MethodsThis study develops a GIS-based scenario assessment of projected climatezone shifts in Spain under RCP4.5 and RCP8.5. The empirical database integrates 7,966 valid municipal observations and 77 AEMET/AdapteCCa climate-station observations, including recalculated present classifications and projected classes for 2055 and 2085. The analysis measures municipal class change, winterseverity shifts, summer-severity shifts, A4/B4 high-summer-severity concentration and valuation-materiality channels for ESG-oriented urban regeneration.ResultsResults show a substantial reconfiguration of Spain’s building-climate geography. Relative to the recalculated present classification, 84.2% of municipalities change class under RCP4.5-2055, 85.0% under RCP4.5-2085, 93.2% under RCP8.5-2055 and 93.2% under RCP8.5-2085. Under RCP8.5-2085, 88.9% of municipalities move toward lower winter severity, while 66.1% move toward higher summer severity. The dominant future classes become B4 and A4, representing 41.7% and 39.8% of valid observations, respectively.DiscussionThese findings indicate that chronic warming may reduce winter severity while intensifying summer stress, shifting building-performance priorities from heating-dominated assumptions toward cooling resilience, overheating prevention and adaptation-oriented retrofitting. The study provides a reproducible pathway for linking climatezone transition intensity with building vulnerability, socioeconomic sensitivity, ESG regeneration priorities and real estate valuation materiality.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1847444</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1847444</link>
        <title><![CDATA[Deep learning-based early warning for pantograph slider faults in straddle-type monorails]]></title>
        <pubdate>2026-07-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chuang Wu</author><author>Hongli Gao</author><author>Jun Song</author>
        <description><![CDATA[Wear of the pantograph slider on straddle-type monorail systems is a primary failure source affecting operational safety, and achieving accurate early warning of such wear is of great significance for intelligent maintenance. Given the temporal evolution characteristics and local abnormal features of the slider wear contour profile, this paper comparatively evaluates the warning performance of four deep learning models: BiLSTM, CNN-BiLSTM, CNN-BiLSTM-Attention, and HFOA-CNN-BiLSTM-Attention. Experimental results show that the BiLSTM model achieves an accuracy of 64.17% on the test set, indicating insufficient sensitivity to local features. With the introduction of local feature extraction, the CNN-BiLSTM model improves accuracy to 78.33%, demonstrating that integrating local pattern recognition with temporal modeling is key to enhancing diagnostic precision. The CNN-BiLSTM-Attention model without fine hyperparameter tuning exhibits performance fluctuations, achieving 74.17% accuracy. In contrast, the HFOA-CNN-BiLSTM-Attention model, optimized via global search using the HawkFish Optimization Algorithm, attains a test accuracy of 96.67% and a recall of 96.89%, achieving optimal synergy among feature extraction, temporal modeling, and dynamic weighting. The results indicate that the HFOA-CNN-BiLSTM-Attention model can not only accurately identify progressive normal wear of the pantograph slider but also effectively classify sudden fault patterns such as abnormal U-shaped wear, shifting fault warning from post-event diagnosis to pre-event prediction. This provides key technical support for predictive maintenance of pantograph sliders and operational safety.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1807837</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1807837</link>
        <title><![CDATA[Enhancing seismic resilience of buildings using prefabricated foamed concrete infill walls in earthquake-prone Indonesia]]></title>
        <pubdate>2026-07-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Miswar Tumpu</author><author> Mansyur</author><author>M. W. Tjaronge</author><author>Azlan Abas</author><author>Andung Yunianta</author><author>Fatmawaty Rachim</author><author>Hoong-Pin Lee</author>
        <description><![CDATA[Indonesia is highly exposed to seismic hazards, requiring building systems that can improve structural safety while remaining feasible for widespread application. This study investigates the effectiveness of prefabricated foamed concrete infill walls in enhancing the seismic resilience of buildings in earthquake-prone regions of Indonesia. The research integrates material characterization, structural performance assessment, and seismic response analysis to evaluate the role of lightweight prefabricated infill systems in reducing seismic demand on structural frames. Experimental testing and numerical simulations were conducted to analyze load–displacement behavior, energy dissipation capacity, and damage patterns under earthquake loading scenarios representative of Indonesian seismic conditions. The results demonstrate that the use of prefabricated foamed concrete infill walls significantly improves lateral stiffness and energy dissipation while reducing structural damage and overall seismic vulnerability. Compared to conventional infill systems, the proposed approach offers improved constructability, reduced structural mass, and enhanced post-earthquake functionality. This study provides evidence that integrating prefabricated foamed concrete infill walls into building design can serve as an effective and scalable strategy to enhance seismic resilience in developing, high-risk seismic regions, supporting safer and more sustainable built environments in Indonesia.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1778822</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1778822</link>
        <title><![CDATA[Transition toward sustainable building design to approach sustainability]]></title>
        <pubdate>2026-06-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Berhane Gebreslassie</author><author>Akhtar Kalam</author><author>Aladin Zayegh</author>
        <description><![CDATA[Sustainable construction practices are evolving from traditional designs to innovative approaches referred to as “Green, intelligent.” This evolution is attracting considerable attention amid the ongoing energy crisis, which highlights the limitations of conventional building methods. Recent studies indicate that the construction sector accounts for 30%-40% of global annual energy consumption, exacerbating the challenges posed by rising fossil fuel prices and increasing CO2 emissions. Consequently, sustainable construction techniques aim to improve environmental responsibility, conserve resources, develop alternative energy sources, and reduce pollution without causing significant harm to ecosystems. However, recent research indicates that current levels of CO2 emissions could lead to higher temperatures in future centuries, in addition to solar panels installed in “built-in environment” producing heat that leads cooling devices to consume extra loads. Therefore, it is crucial to investigate sustainable construction methods that can significantly contribute to a circular economy—an economic model focused on the continuous reuse of materials to minimize waste. Additionally, technologies such as Building Information Modelling (BIM) and Digital Twin enable real-time virtual simulations that replicate physical entities, enhancing project collaboration, transparency, and engineering efficiency. Thus, this study presents three case studies of conceptual building simulation aiming to reduce energy consumption, CO2 emissions, and promote environmental comfort. The design emphasizes sustainability through structural integrity, efficient resource use, and the reduction of indoor air pollutants within the building industry. Numerical values for the case studies were estimated. Case study one, focused on the built environment, yielded a basic rooftop photovoltaic (PV) cell capacity of 85,881.61 kWh/year. Case study two examined building solar radiation absorption in the non-built environment, with optimal generation accounting for 55.13% of the consumed load. A mathematical equation was developed to estimate the output of renewable energy. Case study three evaluated energy-efficient packages and operational selectivity, resulting in load-level reductions. In this case, electrical loads increased by 8.7%, while fuel consumption decreased by 50%. The results from these three case studies were subsequently used to examine the building’s energy self-sufficient approach using a mathematical equation. The projected timeframes required for the case studies' approaches were 402, 90, and 70 years, respectively.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1854031</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1854031</link>
        <title><![CDATA[3D concrete printing, material characterization, capacity prediction, and strength testing of a sub-scale concrete dome structure]]></title>
        <pubdate>2026-06-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Keunhyoung Park</author><author>Ali M. Memari</author><author>Maryam Hojati</author><author>José P. Duarte</author><author>Shadi Nazarian</author><author>Aleksandra Radlińska</author><author>Sven G. Bilén</author>
        <description><![CDATA[This paper presents the results of printing, structural modeling and analysis, and testing a sub-scale geopolymer concrete dome structure as a preliminary step toward constructing a full-scale building. A broader objective of the study was to explore the potential of the printing method as an autonomous construction technique, including its possible use in space exploration as envisioned by NASA's 3D-Printed Habitat Challenge. The paper initially discusses a method developed for 3D printing (or additive manufacturing) of concrete, and then it presents the results of material characterization in the form of mechanical properties of printed concrete. This is then followed by developing a preliminary finite element modeling of a dome-shaped structure and estimating the failure mode and capacity under gravity loading. The prediction of the structural capacity of the dome was necessary prior to actual testing of the dome structure. Initial tests were carried out based on compressive strength and simple bending tests of printed geopolymer specimens. The test results were used in the finite element modeling to predict the failure load that can collapse the scale dome structure. The actual failure mode of the tested scaled dome structure under top-side loading was then compared with the predicted failure mode and capacity from the simulation. The observed discrepancies between the simulation and real-world test results highlight critical limitations in 3D concrete printing for complex shapes. The reduced structural performance revealed the shortcomings of conventional approaches in determining the structural behavior of printed components, emphasizing the need for more in-depth testing and research.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1821031</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1821031</link>
        <title><![CDATA[Field monitoring and numerical simulation study on the long-term response of rainfall and groundwater in collapsible loess areas]]></title>
        <pubdate>2026-06-26T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chen Quanjie</author><author>Wang Yuchen</author><author>Liu Gen</author><author>Xia Min</author>
        <description><![CDATA[Long-term rainfall–groundwater response in deep collapsible loess remains insufficiently understood, particularly under extreme rainfall conditions. This study investigates rainfall infiltration, soil-water response, wetting-front migration, and groundwater dynamics in a deep loess area of Zhengning County, China. A 100 m observation well was used for continuous monitoring of meteorological conditions, soil moisture, and groundwater levels from 2015 to 2020, and targeted observations during an extreme rainfall event in 2021 were also analyzed. The physical properties of a 175 m thick loess profile were examined, and rainfall infiltration processes were simulated using HYDRUS-1D. The loess is classified as low-plasticity silty clay, with silt accounting for 60%–80%. Rainfall was concentrated from May to October, representing 81.9%–90.2% of annual precipitation. Soil moisture in the upper 0-2.0 m was strongly controlled by atmospheric conditions, especially above 1.0 m. A rainfall intensity threshold of 12.4 mm/d caused a >5% increase in water content at 0.2 m, while deeper layers showed increasing response lag. Wetting-front depth followed a power-law relationship with rainfall duration (R2 = 0.95) and a logarithmic relationship with cumulative rainfall (R2 = 0.97). Single short-term heavy rainfall produced limited infiltration, whereas multi-stage sustained rainfall increased infiltration depth to 7 m during the extreme event. Groundwater levels declined slowly by 0.5 m over five years, with no rapid rainfall recharge observed. Simulations showed that when the rainfall intensity/saturated hydraulic conductivity ratio was <1, infiltration depth and wetted-zone water content increased markedly; under equal cumulative rainfall, longer-duration, lower-intensity rainfall promoted deeper infiltration. These results indicate that rainfall duration, intensity, and temporal pattern strongly control infiltration and wetting-front migration in deep loess, whereas groundwater responds slowly because of the thick vadose zone and lack of preferential flow pathways. The findings provide useful data for water-cycle simulation, groundwater assessment, and geological hazard early warning in deep loess regions of the Loess Plateau.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1810085</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1810085</link>
        <title><![CDATA[Comparative study on spatial morphology of Lou Lim Ioc Park in Macau based on space syntax]]></title>
        <pubdate>2026-06-26T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Junling Zhou</author><author>Shuojia Wang</author><author>Xusheng Xie</author><author>Xiaowei Chen</author><author>Linhui Hu</author><author>Kuan Liu</author><author>Ling Feng Xie</author>
        <description><![CDATA[In 2022, the Macao SAR Government proposed in the “Macao Special Administrative Region Urban Master Plan (2020-2040)” that it would protect Macao’s historical and cultural heritage as a goal to build a “world tourism and leisure center” and a “beautiful home”. Parks are a combination of natural scenic tourism resources and cultural tourism resources. They are an important part of Macao’s tourism resources and an important condition for supporting the development of Macao’s tourism. This study mainly discusses the spatial changes of the same garden under two different attributes in the process of transforming the original private garden in Macao into a public garden in the process of urban development. Therefore, this study takes Lou Lim Ioc Park as the research object, uses the theoretical framework of spatial syntax, restores and draws the garden map through field research and historical research, and then builds a spatial syntactic model on this basis to systematically analyze the spatial composition characteristics of the park as a public garden and a private garden. By analyzing the evolution process of its spatial form, the change law of the spatial logic of Lou Lim Ioc Park is revealed. At the same time, with the change of service objects, the garden space also highlights its own adaptability, in the process of urban modernization, the “publicity“ of such important historical and cultural heritage has begun to awaken, and this study also optimizes the strategy for such historical and cultural heritage. Corresponding protection strategies such as improving cultural readability and protecting the integrity and authenticity of cultural heritage itself are proposed.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1904217</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1904217</link>
        <title><![CDATA[Editorial: Technologies for cleaner and resilient transportation and transit systems]]></title>
        <pubdate>2026-06-25T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Sakdirat Kaewunruen</author><author>Cholachat Rujikiatkamjorn</author><author>Dan Li</author><author>Kong Fah Tee</author><author>Lapyote Prasittisopin</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1851806</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1851806</link>
        <title><![CDATA[Predicting civil engineering project success with machine learning: benchmarking models on one million projects]]></title>
        <pubdate>2026-06-25T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mirvat Abdallah</author><author>Chady El Hachem</author>
        <description><![CDATA[Civil engineering projects involve complex interdependencies among financial, technical, and organizational factors and directly influence the performance of the built environment. Accurate prediction of project success can support earlier risk identification, more effective resource allocation, and better planning decisions, particularly for large-scale infrastructure programs. This study evaluates several machine-learning classifiers using the Civil Engineering Global Project Dataset (Kaggle), which contains one million project records described by eleven input variables, including project cost, proximity, certification level, years of experience, company score, overtime hours, and salary bracket. The outcome variable is_good is used as a binary indicator of project performance (high-performing versus needs improvement), reflecting overall project delivery quality and operational effectiveness. A Logistic Regression model provided as a baseline was replicated to verify reproducibility, yielding 0.7975 accuracy and 0.7976 ROC–AUC. Model evaluation was further supported using precision, recall, and F1-score metrics to provide a more comprehensive assessment of classification performance. Random Forest and XGBoost models were then compared, along with Random Forest variants using polynomial feature expansion (degrees 2 and 3) and extensive hyperparameter tuning. Across the full dataset, accuracy and ROC–AUC values remained tightly clustered around 0.79–0.80, indicating a performance plateau and suggesting that algorithmic complexity alone provides limited incremental benefit with the current feature set. A cost-stratified analysis, motivated by the bimodal cost distribution, revealed distinct regime-dependent error profiles, highlighting the importance of threshold calibration and cost-aware decision rules for practical deployment. Overall, the findings emphasize that future gains are more likely to come from domain-driven feature engineering, richer project descriptors, and cost-sensitive evaluation, supporting more reliable decision-making for infrastructure delivery and resilience in the built environment.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1806678</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1806678</link>
        <title><![CDATA[Experimental study on physical model of pile-soil mechanical behavior of spiral piles regenerated from phosphogypsum-based solid waste]]></title>
        <pubdate>2026-06-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zeng Fanxing</author><author>Jiang Wen</author><author>Yang Guang</author><author>Hu Wenbo</author><author>Chen Yin</author><author>Pan Jun</author><author>Pan Deng</author><author>Xia Yuanyou</author>
        <description><![CDATA[Curved spiral piles, as a type of high-efficiency compression-resistant pile, have been widely applied in highway and construction engineering for their unique spiral structure, which effectively enlarges the pile-soil contact area, enhances lateral friction resistance, and improves compressive bearing capacity. In recent years, phosphogypsum-based recycled materials with adjustable cementitious activity have provided an innovative green manufacturing route for spiral piles, while their engineering application in pile foundations is still in the exploratory stage. There is a lack of systematic research on the stress distribution mechanism of spiral piles with internal and external composite reinforcement under loading, especially the quantitative relationship between the geometric parameters of spiral ribs and the bearing capacity of piles. To reveal the compression-bearing mechanism of phosphogypsum-based solid waste recycled spiral piles, laboratory model tests were carried out on four model piles with different spiral configurations (width and thickness) and structural forms (with or without internal reinforcement). The vertical compressive static load test of a single pile was conducted by the slow maintained load method, and key parameters including pile top displacement, pile axial force, lateral friction resistance, and surrounding soil pressure under different compression loads were synchronously monitored. On this basis, the influence of spiral width, thickness, and internal-external composite reinforcement structure on the load-bearing performance of spiral piles was systematically analyzed. The test results show that: (1) Spiral width is the core parameter regulating the compressive bearing performance of spiral piles. When the spiral width increased from 1.0 cm to 1.5 cm, the ultimate compressive bearing capacity of the pile increased by 18.29%, the pile top displacement under the same load of 2400 N decreased by 25.87%, and the ultimate lateral friction resistance increased by 22.54%. (2) Within the test range of 0.15 cm–0.3 cm, the change of spiral thickness had no statistically significant effect on the ultimate compressive bearing capacity, pile top displacement and lateral friction resistance of spiral piles, with a relative difference of only 4.40% in ultimate bearing capacity. (3) The internal-external composite reinforcement structure can effectively optimize the load transfer path and disperse the axial force of the pile body. Under the load of 2400 N, the axial force of the pile with internal reinforcement was 19.90% lower than that of the pile without internal reinforcement, and the ultimate soil pressure around the pile increased by 14.2%, with a more concentrated soil pressure distribution and better compaction and consolidation effect on the surrounding soil. This study systematically clarifies the compression-bearing mechanism of phosphogypsum-based solid waste recycled spiral piles, and quantifies the regulation effect of key spiral geometric parameters and composite reinforcement structure on its mechanical behavior, which can provide critical experimental support and theoretical basis for the geometric parameter optimization, design method construction and engineering application of this type of green spiral piles.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fbuil.2026.1831309</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fbuil.2026.1831309</link>
        <title><![CDATA[Hybrid paving and brick blocks: plastic and wood waste for cooler and safer buildings]]></title>
        <pubdate>2026-06-24T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Arif Nuryawan</author><author>Rahmi Karolina</author><author>Muhammad Andhika Ramadhan</author>
        <description><![CDATA[Idea of this perspective is to modify the conventional paving block which is usually made of mixture of sands and cement into addition of plastics and wood particles. Plastics, which are traditionally resistant to natural degradation, can be effectively utilized as a component of paving block raw materials. Wood particles will store the carbon while being used. This action will mitigate the climate in the long term. Previous works and studies related to the development of sustainable construction materials made of plastics, wood particles, and the mixture of the two were presented in order to compare the possibility to mix among these materials. Study here proposed that plastic, wood particle, cement, and sand are capable to be mixed with different proportion to make paving block. The evaluation included physical and mechanical properties. Beyond their conventional application as paving materials, the incorporation of plastic and wood particle suggests that these hybrid blocks may also function as alternative brick materials for lightweight wall construction. Such bricks could help to reduce heat transfer into buildings, thereby improving thermal comfort and lowering indoor temperatures. Moreover, due to their reduced weight, these hybrid bricks offer additional benefits in earthquake-prone regions by minimizing structural load and enhancing safety. Overall, the integration of plastic and wood into paving or wall materials presents a promising strategy for sustainable construction by reducing waste, storing carbon, and improving building performance.]]></description>
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