Search Results (424)

The integration of artificial intelligence (AI) and machine learning (ML) has revolutionised civil engineering, enhancing predictive accuracy, decision-making, and sustainability across domains such as structural health monitoring, geotechnical analysis, transportation systems, water management, and sustainable construction. This paper presents a detailed review of peer-reviewed publications from the past decade, employing bibliometric mapping and critical evaluation to analyse methodological advances, practical applications, and limitations. A novel taxonomy is introduced, classifying AI/ML approaches by civil engineering domain, learning paradigm, and adoption maturity to guide future development. Key applications include pavement condition assessment, slope stability prediction, traffic flow forecasting, smart water management, and flood forecasting, leveraging techniques such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Support Vector Machines (SVMs), and hybrid physics-informed neural networks (PINNs). The review highlights challenges, including limited high-quality datasets, absence of AI provisions in design codes, integration barriers with IoT-based infrastructure, and computational complexity. While explainable AI tools like SHAP and LIME improve interpretability, their practical feasibility in safety-critical contexts remains constrained. Ethical considerations, including bias in training datasets and regulatory compliance, are also addressed. Promising directions include federated learning for data privacy, transfer learning for data-scarce regions, digital twins, and adherence to FAIR data principles. This study underscores AI as a complementary tool, not a replacement, for traditional methods, fostering a data-driven, resilient, and sustainable built environment through interdisciplinary collaboration and transparent, explainable systems. Full article

High-permeability emulsified asphalt has emerged as a promising prime coat for enhancing interlayer bonding in semi-rigid pavement structures. However, its widespread adoption remains limited by insufficient permeability and inconsistent mechanical properties. This study systematically investigated the effects of emulsifier ionic type (cationic or anionic), kerosene dosage (0–20%), and diluted asphalt content (corresponding to oil-water ratios of 5:5 and 4:6) on the comprehensive performance of high-permeability emulsified asphalt. Fundamental physical tests (sieve residue, evaporation residue, penetration, softening point, ductility), permeability evaluation, rotational viscosity measurements, and adhesion performance tests were conducted. Grey relational analysis (GRA) was employed to quantify the influence of each factor and their interactions on key performance metrics. The results reveal that anionic emulsifiers significantly improved low-temperature ductility and permeability. A low kerosene dosage (<10%) enhanced permeability and viscosity but compromised thermal stability at higher levels. Reducing the diluted asphalt content partially offset these adverse effects. GRA identified kerosene dosage as the dominant factor influencing permeability, softening point, and adhesion performance while emulsifier ionic type primarily affected ductility, and oil-water ratio strongly governed emulsification quality and viscosity. These findings provide quantitative insights for optimizing the composition of high-permeability emulsified asphalt and serve as a theoretical foundation for its engineering application in durable prime coats. Full article

This study compiled a dataset of published works relating to fatigue testing in asphalt mixes, covering 2020–2025. The dataset was subjected to bibliometric and textual analyses, including a systematic review, to explore emerging trends and patterns in experimental protocols. Bibliometrix, VOSviewer, and IRaMuTeQ were employed to map the scientific landscape of 368 articles. Following PRISMA guidelines, the 100 most-cited articles were reviewed to identify prevailing test setups and parameters. The results showed a growing scientific production (9.1% per year), concentrated in a few high-impact journals and dominated by China, with emphasis on sustainability. A comparison between scientific output and a road quality index revealed a disconnect between academic research and field implementation. Five thematic clusters emerged: sustainable pavement management, mechanical characterization, binder modification, performance modeling, and evaluation of innovative materials. Indirect tensile and four-point bending tests were the most common loading modes. Considerable variability in protocols, frequent omissions of methodological details, and limited statistical treatment were also observed. The study highlighted the importance of standardized reporting and robust analysis, offering a reproducible framework to understand fatigue behavior and support future research. Full article

Improving air quality is a significant environmental challenge. This research explored the potential of asphalt mixtures functionalized with a chitosan–TiO₂ composite (CS-TiO₂) to reduce high NO₂ concentrations and improve durability. For the assessment of the photocatalytic efficiency of the new CS-TiO₂ composite, a low-cost reactor adapted to accommodate asphalt Marshall-type specimens and high pollutant concentrations encompassing a passive sampling module was developed. The CS-TiO₂ was synthesized using a wet impregnation method at a concentration of 2%, and asphalt mixtures were treated with aqueous solutions of the photocatalysts at 2.5 g/m² and 5.0 g/m². Laboratory tests using the photocatalytic reactor and passive sampling of NO₂ revealed pollutant reductions of 21% with TiO₂ and 28% with CS-TiO₂. CS-TiO₂ achieved 15% efficiency in visible light, reducing NO₂ levels and offering UV protection to the asphalt mixtures. Additionally, the chitosan improved the photocatalyst’s adhesion by about 18%, as confirmed by tape test results, suggesting enhanced durability on pavement surfaces. The results achieved showcase the relevance of the proposed methodological improvements for supporting further research. Full article

This study evaluated the benefits of pavement preservation treatments across two climatic zones using data from the National Center for Asphalt Technology (NCAT) Pavement Preservation Group Study. Longitudinal data analysis was conducted to quantify pavement performance over time. Results indicate that in the freeze zone, treatments significantly improved pavement smoothness, as evidenced by reductions in the progression of the International Roughness Index (IRI), whereas similar trends were not observed in the no-freeze region, highlighting the need for further research to quantify the benefits in these zones. Life cycle cost analysis (LCCA) showed that selected preservation treatments reduced user costs by 54–57% due to lower excess fuel consumption, particularly in high-traffic corridors. These treatments also contributed to reductions in greenhouse gas (GHG) emissions by decreasing fuel use. Despite these findings, comprehensive, high-quality data are needed to fully evaluate the economic and environmental benefits of preservation treatments at the project level and to improve decision-making in pavement management strategies. Full article

Each layer of the constructed asphalt pavement is evaluated by measuring its quality indicators, as specified in the construction regulations ĮT ASFALTAS 08, and comparing the obtained values with the corresponding design or threshold values. Due to inherent variability in material properties and systematic or random errors during the production, transport, and installation of the asphalt mixture, the quality indicators of the asphalt layers often deviate from their optimal values. When deviations exceed permissible deviations (PD) or limit values (LV), monetary deductions (MDs) are applied. This study presents normalised values and variation dynamics for 10 quality indicators of the asphalt layer subject to MDs in Lithuania. Using the expertise of 71 road construction professionals and multi-criteria decision-making (MCDM) methods, the influence of these deviations on road quality was assessed. The experts ranked all indicators using percentage weights and the Analytic Hierarchy Process (AHP) method. Expert consensus was verified using concordance coefficients and consistency ratios. After eight statistical outliers were excluded, adjusted weights were calculated based on responses from 63 experts. The proposed method, termed CIBRO (Criteria Importance But Rejected Outliers), enables the objective prioritisation of asphalt quality indicators. The CIBRO method enhances expert concordance and results reliability by aligning criterion ranks with the normal distribution, complementing the Kendall rank correlation approach. The findings highlight that insufficient compaction, inadequate layer thickness, and binder content deviations are the most influential factors that affect layer quality. In contrast, deviations in pavement width, friction coefficient, and surface evenness (measured with a 3 m straight edge) were found to have a lesser impact. The CIBRO method offers a robust approach to assessing the importance of the quality of the asphalt layer, supporting improvements in construction standards and pavement assessment systems. Full article

Latent stripping has become increasingly apparent in asphalt pavements, particularly in highway rehabilitation and international construction projects supported by Official Development Assistance (ODA) from the Government of Japan. Stripping accelerates structural deterioration, making countermeasures essential. However, in ODA projects, securing high-quality aggregates or evaluating local materials is often difficult due to environmental and budgetary constraints. This study focused on Surface Free Energy (SFE) as a small-sample evaluation method and developed ten types of styrene–butadiene–styrene (SBS) polymers to enhance interfacial adhesion by targeting aggregate surface functional groups. The SFE of each Polymer-Modified Bitumen (PMB) and thirteen aggregates was measured, and the work of adhesion and moisture sensitivity index (MSI) were calculated for all combinations. Twenty-one Hot-Mix Asphalts (HMA) were then prepared and evaluated using the Hamburg Wheel Tracking Test (HWTT) based on load cycles to stripping initiation (LC_SN) and to 12.5 mm rut depth (LC_ST). The developed PMBs showed a higher work of adhesion, a lower MSI, and substantially increased LC_SN and LC_ST values. Strong negative correlations were observed between MSI and both HWTT indicators, confirming the utility of SFE-based MSI for material screening. This study demonstrates that interface-targeted PMBs can improve stripping resistance, thereby promoting the use of lower-quality aggregates in durable pavements. Full article

To facilitate the high-value utilization of reclaimed asphalt pavement (RAP), this study investigated the efficacy of fine separation technology as a pre-treatment method. This technology significantly reduced the variability of RAP, controlling the coefficients of variation for asphalt content and aggregate gradation within 5% and 10%, respectively, and minimized false particle content (agglomerates of fines and aged asphalt). Response Surface Methodology (RSM) was employed to optimize the mix design for ultra-high-RAP- content mixtures (50–70%). A predictive regression model was developed to determine the Optimal Binder Content (OBC) based on RAP and rejuvenator dosage. The road performance of the resulting mixtures was comprehensively evaluated. Results showed that the technology markedly enhanced the overall performance of recycled asphalt mixtures. While high-temperature rutting resistance improved with increasing RAP content, low-temperature performance declined. The mixture with 70% RAP failed to meet low-temperature cracking requirements. Consequently, an optimal RAP content of 60% is recommended. Furthermore, the generalized sigmoidal model effectively constructed dynamic modulus master curves, accurately predicting the viscoelastic behavior of these ultra-high-RAP mixtures. This study demonstrates that fine separation is a critical pre-processing step for reliably producing high-quality, sustainable asphalt mixtures with RAP content far exceeding conventional limits. Full article

The use of Reclaimed Asphalt Pavement (RAP) in asphalt mixtures offers environmental and economic advantages by reducing reliance on virgin aggregates and minimizing construction waste. However, the aged binder in RAP increases mixture stiffness, which can compromise fatigue resistance. This systematic review evaluates the influence of RAP content on fatigue performance compared to conventional mixtures, with a focus on the Indirect Tensile Test (IDT) as the primary assessment method. Following the parameters of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, five studies published between 2014 and 2024 were identified through searches in Web of Science, ScienceDirect, ASCE, and Scopus. Study quality was assessed using the Cochrane Risk of Bias tool. The results indicate that although RAP enhances rutting resistance, higher contents (>30%) often lead to reduced fatigue performance due to binder hardening and reduced mixture flexibility. The incorporation of rejuvenators—such as heavy paraffinic extracts—and modifiers, including high-modulus agents, polymers, and epoxy binders, can partially restore aged binder properties and improve performance. Sustainable innovations, such as lignin-based industrial by-products and warm-mix asphalt technologies, show promise in balancing mechanical performance with reduced environmental impact. Variability in material sources, modification strategies, and test protocols limits direct comparability among studies, underscoring the need for standardized evaluation frameworks. Overall, this review highlights that optimizing RAP content and selecting effective rejuvenation or modification strategies are essential for achieving durable, cost-effective, and environmentally responsible asphalt pavements. Future research should integrate advanced laboratory methods with performance-based design to enable high RAP utilization without compromising fatigue resistance. Full article

This research addresses the challenge of predicting operating vehicles’ speeds (V85) on single-carriageway road tangents. While most previous models rely on preceding segment speeds or focus on curves, this research develops an independent prediction model specifically for road tangents, based on empirical data collected in Croatia. A total of 46 locations across 23 road cross-sections were analysed, with operating speeds measured using field radar surveys and fixed traffic counters. Following a comprehensive correlation and multicollinearity analysis of 24 geometric, environmental, and traffic-related variables, a multiple linear regression model was developed using a training dataset (36 locations) and validated on a separate test set (10 locations). The model includes nine statistically significant predictors: shoulder type (gravel), edge line quality (excellent and satisfactory), pavement quality (excellent), average summer daily traffic (ASDT), crash ratio, edge lane presence, overtaking allowed, and heavy goods vehicle share. The model demonstrated strong predictive performance (R² = 0.89, RMSE = 5.24), with validation results showing an average absolute deviation of 2.43%. These results confirm the model’s reliability and practical applicability in road design and traffic safety assessments. Full article

Foreign Object Debris (FOD) on airport pavements poses a serious threat to aviation safety, making accurate detection and interpretable scene understanding crucial for operational risk management. This paper presents an integrated multi-modal framework that combines an enhanced YOLOv7-X detector, a cascaded YOLO-SAM segmentation module, and a structured prompt engineering mechanism to generate detailed semantic descriptions of detected FOD. Detection performance is improved through the integration of Coordinate Attention, Spatial–Depth Conversion (SPD-Conv), and a Gaussian Similarity IoU (GSIoU) loss, leading to a 3.9% gain in mAP@0.5 for small objects with only a 1.7% increase in inference latency. The YOLO-SAM cascade leverages high-quality masks to guide structured prompt generation, which incorporates spatial encoding, material attributes, and operational risk cues, resulting in a substantial improvement in description accuracy from 76.0% to 91.3%. Extensive experiments on a dataset of 12,000 real airport images demonstrate competitive detection and segmentation performance compared to recent CNN- and transformer-based baselines while achieving robust semantic generalization in challenging scenarios, such as complete darkness, low-light, high-glare nighttime conditions, and rainy weather. A runtime breakdown shows that the enhanced YOLOv7-X requires 40.2 ms per image, SAM segmentation takes 142.5 ms, structured prompt construction adds 23.5 ms, and BLIP-2 description generation requires 178.6 ms, resulting in an end-to-end latency of 384.8 ms per image. Although this does not meet strict real-time video requirements, it is suitable for semi-real-time or edge-assisted asynchronous deployment, where detection robustness and semantic interpretability are prioritized over ultra-low latency. The proposed framework offers a practical, deployable solution for airport FOD monitoring, combining high-precision detection with context-aware description generation to support intelligent runway inspection and maintenance decision-making. Full article

Diamond grinding is a key concrete pavement restoration technique for concrete pavements. Traffic degrades the serviceability of the concrete pavements, resulting in unsatisfactory skid levels and noise concerns. Diamond grinding is known to enhance longevity and performance by improving smoothness and friction. By removing flaws with a cutting head equipped with diamond blades, the procedure produces a “corduroy” texture that enhances braking and stability. Diamond grinding typically results in a 20–80% reduction in the International Roughness Index, significantly enhancing pavement smoothness. It also improves macrotexture and creates longitudinal drainage channels, which collectively increase skid resistance and lower the chance of hydroplaning. The paper aims to highlight the need for diamond grinding for concrete pavements, which, despite their longevity, have decreased serviceability from traffic. The review further explores emerging innovations and identifies the gaps in long-term performance tracking and life-cycle environmental assessment. This paper reviews the effectiveness of diamond grinding as a pavement rehabilitation technique, with emphasis on ride quality, surface friction, noise reduction, and durability. Field applications and evaluation metrics are discussed to assess their contribution to pavement performance. This review aims to support researchers, pavement engineers, and agencies by providing a comprehensive understanding of diamond grinding’s applications, performance metrics, and potential for sustainable pavement management. Full article

Temporary architecture, as an expression of the concept of impermanence, offers adaptable and time-sensitive spatial interventions that promote community engagement and encourage experimentation within the urban environment. Beyond its physical and functional qualities, this architectural approach acts as a social mediator, fostering dialogue, networking, and the exchange of ideas between local communities and professionals, while contributing to the development of a socio-cultural common ground. This paper explores the Greenfeel Architecture wooden pavilion as a case study of small-scale architecture embedded within a landscape dedicated to urban agriculture and community-driven activities. The design process was guided by the need to balance functional requirements—providing shelter from the sun and rain and facilitating social interactions—with the protection of the existing vegetation and the enhancement of local biodiversity, with particular emphasis on supporting bee populations. In line with sustainable construction principles, the pavilion was built through the reuse of recovered materials, including used bricks for pavement, wooden slabs for the facade and roof, and several structural components sourced from previous building projects. Since its completion, the pavilion has acted as an urban acupuncture point within the surrounding area and has become a host for various outdoor activities and educational workshops aimed at diverse groups, including children, adults, professionals, and laypersons alike. The duality between the scale of the pavilion and the scale of its social, cultural, or ecological influence highlights the potential of temporary architecture to become a tool for both physical and socio-cultural sustainability in an urban environment. Full article

This research aimed to develop a comprehensive decision-making model for road rehabilitation, with the goals of extending pavement service life, minimizing major repairs, and improving the efficiency of investment and resource planning. The proposed methodology integrates structural condition, functional performance, and total economic value across the pavement lifecycle. It enables engineers and road managers to make informed decisions based on structural capacity, functional performance, asset value, and optimized rehabilitation strategies. The model was validated through case studies using data from Central European roads and accelerated pavement testing. It compared conventional and high-modulus asphalt overlays of equal thickness, demonstrating that a 3000 MPa increase in modulus extended residual life by over 30% and raised structural value by EUR 5.8/m². This approach enhances planning and prioritization of rehabilitation activities, supports the use of higher-quality materials, reduces lifecycle costs and CO₂ emissions, and facilitates integration with asset management systems. By linking pavement design, performance prediction, and asset management, the model supports strategic decision-making under performance and budget constraints. Full article

Quality requirements for mineral aggregate for concrete used to construct pavement for busy highways are high because of the fatigue traffic loads and environmental exposure. The use of local aggregate for infrastructure projects could result in important sustainability improvements, provided that the concrete’s durability is assured. The objective of this study was to identify the potential alkaline reactivity of local greywacke aggregate and select appropriate mitigation measures against the alkali–silica reaction. Experimental tests on concrete specimens were performed using the miniature concrete prism test at 60 °C. Mixtures of coarse greywacke aggregate up to 12.5 mm with natural fine aggregate of different potential reactivity were evaluated in respect to the expansion, compressive strength, and elastic modulus of the concrete. Two preventive measures were studied—the use of metakaolin and slag-blended cement. A moderate reactivity potential of the greywacke aggregate was found, and the influence of reactive quartz sand on the expansion and instability of the mechanical properties of concrete was evaluated. Both crystalline and amorphous alkali–silica reaction products were detected in the cracks of the greywacke aggregate. Efficient expansion mitigation was obtained for the replacement of 15% of Portland cement by metakaolin or the use of CEM III/A cement with the slag content of 52%, even if greywacke aggregate was blended with moderately reactive quartz sand. It resulted in a relative reduction in expansion by 85–96%. The elastic modulus deterioration was less than 10%, confirming an increased stability of the elastic properties of concrete. Full article