Infrastructures

Structural health monitoring (SHM) is critical for ensuring the safety and longevity of structures, yet existing methodologies often face challenges such as high data dimensionality, lack of interpretability, and reliance on extensive label datasets. Current research in SHM has primarily focused on supervised approaches, which require significant manual effort for data labeling and are less adaptable to new environments. Additionally, the large volume of data generated from dynamic structural monitoring campaigns often includes irrelevant or redundant features, further complicating the analysis and reducing computational efficiency. This study addresses these issues by introducing an unsupervised learning approach for SHM, employing an agglomerative clustering model alongside an unsupervised feature selection technique utilizing box-plot statistics. The proposed method is assessed through raw acceleration signals obtained from four dynamic structural monitoring campaigns, including 44 features with temporal, statistical, and spectral information. In addition, these features are also evaluated in terms of their relevance, and the most important ones are selected for a new execution of the computational procedure. The proposed feature selection not only reduces data dimensionality but also enhances model interpretability, improving the clustering performance in terms of homogeneity, completeness, V-measure, and adjusted Rand score. The results obtained for the four analyzed cases provide clear insights into the patterns of behavior and structural anomalies. Full article

Rollover crashes are among the most prevalent types of accidents in developing countries. Various factors may contribute to the occurrence of rollover crashes. However, limited studies have simultaneously investigated both traffic stream and road-related variables. For instance, the effects of T-intersection density, U-turns, roadside parking lots, the entry and exit ramps of side roads, as well as traffic stream characteristics (e.g., standard deviation of vehicle speeds, speed violations, presence or absence of speed cameras, and road surface deterioration) have not been thoroughly explored in previous research. Additionally, the simultaneous modeling of crash frequency and intensity remains underexplored. This study examines single-vehicle rollover crashes in Yazd Province, located in central Iran, as a case study and simultaneously evaluates all the variables. A dataset comprising three years of crash data (2015–2017) was collected and analyzed. A crash index was developed based on the weight of crash intensity, road type, road length (as dependent variables), and road infrastructure and traffic stream properties (as independent variables). Initially, the dataset was refined to determine the significance of explanatory variables on the crash index. Correlation analysis was conducted to assess the linear independence between variable pairs using the variance inflation factor (VIF). Subsequently, various models were compared based on goodness of fit (GOF) indicators and odds ratio (OR) calculations. The results indicated that among ten crash modeling techniques, namely, Poisson, negative binomial (NB), zero-truncated Poisson (ZTP), zero-truncated negative binomial (ZTNB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), fixed-effect Poisson (FEP), fixed-effect negative binomial (FENB), random-effect Poisson (REP), and random-effect negative binomial (RENB), the FENB model outperformed the others. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) values for the FENB model were 1305.7 and 1393.6, respectively, demonstrating its superior performance. The findings revealed a declining trend in the frequency and severity of rollover crashes. Full article

Analytical models to predict distresses and service conditions of road pavements can greatly contribute to the development of an effective pavement management system. These models allow the transportation agencies to monitor and track the deterioration of pavements and consequently determine the needed maintenance operations to preserve the performance of the network. In this research, the pavement distresses and service conditions of the Indus Highway N-55 located in Karak district, Pakistan were examined. Distresses were identified by visual observation, and then their severity and extent were measured individually by using a Vernier caliper and a measuring scale. For each distress type, the corresponding PCR was calculated. The compaction densities of the base and wearing courses were considered as input parameters to develop an ordinal logistic regression model for two dominant distresses, namely rutting and potholes. Rutting severity and extent were divided into three levels, while pothole severity was divided into four levels. Bulk and maximum specific gravity were found to have a significant impact on the models of both distresses. The model can be used to predict their development in terms of severity and extent. The proposed formulation provides valuable insights into monitoring and predicting pavement distresses by assessing the densities of road construction materials. Full article

The use of precast concrete pipes for water and sewage transportation systems is a very important element of a country’s infrastructure. The main aim of this study was to investigate the effects of concrete’s compressive strength and reinforcement levels on the mechanical performance of spun-cast full-scale precast concrete pipes in the local construction industries of developing countries. A test matrix was adopted using a full 3² factorial design. The studied concrete’s compressive strength was 20, 30, and 40 MPa, and reinforcement levels were 60%, 80%, and 100%, representing low, medium, and high levels, respectively. The medium level of reinforcement represented the reinforcement requirement of ASTM C76 in concrete pipes. A total of eighteen full-scale pipes of 450 mm diameter were cast in an industrial precast pipe unit using a spin-casting technique and were tested under a three-edge bearing load. The experimental results showed that the crack load and ultimate load of the tested pipes increased with higher levels of concrete strength and reinforcement levels. For example, an approximately 35% increase in the 0.30 mm crack load was observed when the concrete strength increased from 20 MPa to 30 MPa for all tested levels of reinforcement. Similarly, around a 19% increase in ultimate load was observed for pipes with 80% reinforcement compared to identical pipes with 60% reinforcement. It was found that the pipe class, as per ASTM C76, is highly dependent on the concrete strength and reinforcement levels. All of the pipes exhibited the development of flexural cracks at critical locations (crown, invert, and springlines). Moreover, concrete pipes cast with low-level strength and reinforcement also showed signs of crushing at the crown location near to the pipe failure. The analysis of variance (ANOVA) results showed that the main factors (compressive strength and reinforcement levels) were significantly affected by the cracking loads of precast pipes. No significant effect of the interaction of factors was observed on the crack load response. However, interaction factors, along with main factors, have significant effects on the ultimate load capacity of the concrete pipes, as indicated by the F-value, p-value, and Pareto charts. This study made an effort to illustrate and optimize the mechanical performance of pipes cast with various concrete strengths and reinforcement levels to facilitate the efficient use of materials for more resilient pipe infrastructure. Moreover, the exact optimization of concrete strength and reinforcement level for the desired pipe class will make the pipe design economical, leading to an increased profit margin for local spin-cast pipe fabricators without compromising the pipe’s quality. Full article

The widespread adoption of wood in construction is driven by its sustainability, cost-effectiveness, and esthetic appeal. The construction of wood buildings often requires minimal specialized equipment, contributing to affordability and higher demand for wood-frame structures. Wood is considered more sustainable than other building materials, such as steel or concrete, for several reasons, including its renewable nature, low embodied energy, carbon sequestration, energy efficiency, and biodegradability, among others. In the United States, wood is the most common material used in building construction. While many of the structures are single-family homes, wood framing is also prevalent in larger apartment complexes, as well as commercial and industrial buildings. Timber has also been traditionally used for bridge construction, and recently, it has been considered again for the construction of new bridges. Over time, wood-frame construction has developed from a basic method for primitive shelters into a sophisticated field of structural design. As an eco-friendly resource, wood is crucial for promoting sustainable building practices. However, ensuring the long-term performance and safety of timber structures is essential. Regular inspections and testing of wooden structures are important to identify signs of wear, damage, or decay. One type of testing which is gaining popularity is nondestructive testing (NDT). NDT techniques have become invaluable for assessing the condition of timber components because such techniques are non-invasive in nature and do not cause damage, ensuring that structures remain functional with minimal disruptions. These methods provide critical insights into the structural integrity and operational efficiency of wood under sustained loads and in inclement environments. This article examines various NDT techniques used to evaluate timber structures, highlighting their capabilities, as well as advantages and limitations. It also discusses the importance of wood in advancing sustainability within the construction industry and emphasizes the need for accurate and reliable assessment methods to enhance the use of timber as an environmentally friendly building material. By incorporating NDT practices into regular inspection and maintenance protocols for buildings, bridges, and other structures, various stakeholders can ensure the durability, longevity, and safety of timber structures, thereby contributing to the progress and advancement of sustainable construction practices worldwide. Full article

Belite calcium sulfoaluminate cement (CSAB), an alternative to Portland cement, exhibits excellent strength at both early and later ages. However, due to its high belite content, the carbon reduction from this type of cement is not sufficient when compared to other alternative cements. To further enhance CSAB’s sustainability, this study investigates the performance of CSAB when partially replaced by low-carbon mineral additives (i.e., limestone and gypsum). The primary objective is to identify the optimal mixture design by incorporating gypsum and limestone to formulate a sustainable binder that maintains high compressive strength. The CSAB is replaced (with both additives) by up to 51% at two different liquid-to-solid ratios of 0.4 and 0.5. gypsum replacements ranging from 0% to 27%, resulting in three unique gypsum-to-ye’elimite molar ratios (M). Limestone replacements range from 0% to 30% in 10% increments. The investigation focuses on the development of hydrates, hydration kinetics, and compressive strength of the sustainable binders after 3 days. The results indicate that a higher replacement level of limestone provides more free water to react with ye’elimite and belite, thereby enhancing the hydration kinetics, but decreasing the compressive strength. It also shows that the addition of gypsum enhances the formation of ettringite, enabling the maintenance of great compressive strength within the binder even at high limestone replacement levels. The binder containing 12% gypsum and 20% limestone was identified as the optimal mixture, yielding a compressive strength of 39 MPa. This performance, when compared to the plain CSAB (compressive strength of 49 MPa), demonstrates that the optimized binder achieves adequate sustainability while maintaining mechanical properties without significant compromise. Full article

Accurate estimation of concrete compressive strength is very important for the improvement of mix design, quality assurance, and compliance with engineering specifications. Most empirical traditional models have failed to capture the complex relationships inherent within varied constituents of concrete mixes. This paper develops a machine learning model for compressive strength prediction using mix design variables and curing age from a “Concrete Compressive Strength Dataset” obtained from the UCI Machine Learning Repository. After comprehensive data preprocessing and feature engineering, various regression and classification models were trained and evaluated, including gradient boosting, random forest, AdaBoost, k-nearest neighbors, linear regression, and neural networks. The gradient boosting regressor (GBR) achieved the highest predictive accuracy with an R² value of 0.94. Feature importance analysis showed that the water–cement ratio and age are the most crucial factors affecting compressive strength. Advanced methods such as SHapley Additive exPlanations (SHAP) values and partial dependence plots were used to attain deep insights about feature interaction with a view to enhancing interpretability and fostering trust in models. Results highlight the potential of machine learning models to improve concrete mix design with the aim of sustainable construction through the optimization of material usage and waste reduction. It is recommended that future research be undertaken with expanding datasets, more features, and richer feature engineering to enhance predictive power. Full article

The increasing global emphasis on sustainable construction practices has spurred significant international research into developing durable and eco-friendly concrete materials. This study investigates the potential of metakaolin and glass powder as supplementary aluminosilicate materials in slag- based geopolymer mortars, aiming to enhance their mechanical properties and durability. To further improve the performance, polypropylene fibers were incorporated at various dosages. Therefore, 13 mixtures of geopolymer mortar based on blast furnace slag have been developed. The control mix does not contain fibers or slag replacement materials, whereas in the other formulations, glass powder and metakaolin have been employed as substitutes for slag at weight percentages (relative to the weight of slag) of 5% and 10%, separately and in combination. Additionally, the fiber-containing samples are divided into two groups based on the volume percentage of polypropylene fibers, comprising 0.2% and 0.4%. The results of the investigation show that the use of glass powder, particularly at a replacement percentage of 10%, leads to an improvement in the 28-day compressive strength. Furthermore, the mixes containing glass powder demonstrated higher flexural strength compared to those containing metakaolin, irrespective of the volume percentage of fibers. The best performance in the rapid chloride permeability test is associated with the mix containing a combination of glass powder and metakaolin at a replacement percentage of 10%. Satisfactory results have been obtained when using fibers at volume percentages of 0.2% and 0.4%. Additionally, this study utilized a fuzzy inference system to predict compressive strength. The results indicate that, by considering uncertainties, the compressive strength of the mortar can be predicted with an error of less than 1% without the need for complex mathematical calculations. Full article

During the past decades, to minimize Greenhouse Gas (GHG) emissions and asphalt fumes during the asphalt mix production and construction process, various warm mix asphalt (WMA) additives have been developed and successfully applied. Currently, as production of WMA reaches close to that of Hot Mix Asphalt (HMA) in the US, the varied definition of WMA is questioned in this paper. Not only are the temperature reduction ranges from HMA defined by various studies too wide, but also the minimum threshold to be classified as WMA is often too small. In this paper, a new category of “Cool Mix Asphalt (CMA)” is proposed to distinguish it from the newly defined WMA based not on the reduction amount from HMA temperature but its actual production temperature. It is proposed that HMA should be defined as asphalt mixtures produced at temperatures between 140 and 160 °C (between 284 and 320 °F), WMA as production temperatures between 120 and 140 °C (between 248 and 284 °F), and CMA as production temperatures between 100 and 120 °C (212 to 248 °F). By defining their actual production temperatures rather than reduction temperatures from HMA, WMA and CMA will be clearly defined. This paper then presents a new Polymer Cool Mix Asphalt (PCMA) additive called “Zero-M”, which was developed to lower the mixing temperature to around 110 °C (203 °F). Recently, test sections using Zero-M were successfully constructed in Korea, Italy and Vietnam, and their laboratory test results of field cores and production and construction experiences are described in this paper. The chemistry and compositions of Zero-M are discussed along with its mechanism to significantly lower the production temperature of PCMA. All test sections constructed in three countries met the in-place compaction density requirements of their respective countries, which were close to or higher than those of the control HMA test sections. Full article

Existing models for predicting the international roughness index (IRI) of a road surface often lack adaptability, struggling to accurately reflect variations in climate, traffic, and pavement distresses—factors critical for effective and sustainable maintenance. This study presents a novel dual-model approach that integrates pavement condition index (PCI), pavement distress types, climatic, and traffic data to improve IRI prediction. Using data from the Long-Term Pavement Performance database, a dual-model approach was developed: pavements were classified into groups based on key factors, and tailored regression models were subsequently applied within each group. The model exhibits good predictive accuracy, with R² values of 0.62, 0.72, and 0.82 for the individual groups. Furthermore, the validation results (R² = 0.89) confirm that the combination of logistic regression and linear regression enhances the precision of IRI value predictions. This approach enhances adaptability and practicality, offering a versatile tool for estimating IRI under diverse conditions. The proposed methodology has the potential to support more effective, data-driven decisions in pavement maintenance, fostering sustainability and cost efficiency. Full article

Following the 1987 referendums, the Italian government stopped its nuclear energy production. Radioactive waste produced by existing nuclear facilities and the very-low- and low-level radioactive waste due to other activities (e.g., healthcare) require the construction of a National Repository. To this end, the National Map of Suitable Areas (CNAI), through which the optimal site to host the National Repository would be identified, was published on 23 December 2023. Over the years, the possible location of the National Repository has been repeatedly contested by the citizens of the territories concerned. However, the need to identify a site and build the National Repository is unavoidable. This study proposes an approach based on multi-criteria analysis. The approach represents an alternative model useful for enriching the public debate with additional information and criteria and is also consistent with the local needs of the communities involved. The proposed approach compares the sites proposed in the CNAI by analyzing their main short- and long-term risks, namely their seismic, transport-related and socio-economic risks. The obtained results show a possible different priority order of the CNAI sites. They highlight the possibility of identifying the optimal site mainly via using site safety criteria assessed throughout the entire service life of the infrastructures to be built and also consider the possible short-term economic advantages deriving from the construction of the National Repository. Full article

Carbon fiber-reinforced polymer (CFRP) is widely used in construction to extend the service life of building structures through the repair and rehabilitation of reinforced concrete (RC) columns. However, due to the difficulty of wrapping CFRP strips spirally around an RC spiral column, a flexible CFRP rope material has been developed as an alternative, which will be used as a spiral hoop for repairing circular columns. In this study, 12 RC spiral columns were constructed and tested under concentric load, considering slenderness ratio and spacing between CFRP rope and heat temperature, to investigate the RC spiral column’s behavior. These RC columns had three slenderness ratios with 17.75, 26.65, and 33.34 and were exposed to heat temperature of 600 °C for 3 h, then tested under compression. The results showed that as the slenderness ratio increases, the load capacity of RC spiral column decreases. The repaired specimens with a CFRP rope-with-slenderness ratio of 33.35 and 26.65 exhibited an increase in strength about (36% to 97%) and (30% to 88%), respectively. In all repaired specimens with a CFRP rope-of-slenderness ratio of 26.65 and 33.35, they showed a slight increase in ductility of about 2% compared with the heated specimen. However, they did not recover the ductility of the unheated specimen. Also, the specimens with a low slenderness ratio and repaired with CFRP at 300 mm showed a greater decrease in toughness and modulus of elasticity than in the specimens with a high slenderness ratio and repaired with CFRP at 150 mm. The repaired specimens with rope at 150 mm of spacing exhibited an increase in load capacity more than the repaired specimen with rope at 300 mm of spacing and reached a load capacity that was greater than what the unheated specimen reached in all groups. It can be shown that there is a significant effect of temperature on the behaviour of the RC spiral column. Adding rope at 300 mm of spacing restores the capacity and allows for a greater reach than the unheated load capacity of the specimens (about 4% to 11%). However, the specimens repaired with rope at 150 mm increased the load capacity by approximately 27.4% to 36.8% more than the unheated specimens in each group. Full article

The interface between old and new concrete is a critical component in many construction practices, including concrete pavements, bridge decks, hydraulic dams, and buildings undergoing rehabilitation. Despite various treatments to enhance bonding, this interface often remains a weak layer that compromises overall structural performance. Traditional design methods typically oversimplify the interface as a homogeneous or empirically adjusted factor, resulting in significant uncertainties. This paper introduces a novel framework for quantifying the anisotropic properties of old–new concrete interfaces using X-ray computed tomography (CT) and finite element-based numerical homogenization. The elastic coefficient matrix reveals that specimens away from the interface exhibit higher values in both normal and shear directions, with normal direction values averaging 33.15% higher and shear direction values 39.96% higher than those at the interface. A total of 10 sampling units along the interface were collected and analyzed to identify the “weakest vectors” in normal and shear directions. The “weakest vectors” at the interface show consistent orientations with an average cosine similarity of 0.62, compared with an average cosine similarity of 0.23 at the non-interface, which demonstrates directional features. Conversely, the result of average cosine similarity at the interface shows randomness that originates from the anisotropy of materials. The average angle between normal and shear stresses was found to be 88.64°, indicating a predominantly orthogonal relationship, though local stress distributions introduced slight deviations. These findings highlight the importance of understanding the anisotropic properties of old–new concrete interfaces to improve design and rehabilitation practices in concrete and structural engineering. Full article

To address the glare issues caused by highway ETC gantry monitoring and imaging illumination devices, this paper first investigates the mechanism of disability glare and derives the formula for the glare threshold increment. Subsequently, using the glare increment threshold as the evaluation metric and incorporating the current regulatory requirements for illumination devices, a simulation model for ETC gantry monitoring and imaging illumination devices was developed. A single-variable control method was applied to conduct simulation experiments on the glare problems from multiple perspectives (e.g., different standard illuminance levels, various luminous areas, varying installation heights, and different lateral offsets), and the glare level was analyzed using the glare increment threshold method. It was found that when the lateral offset of the illumination device reached 4 m, the glare increment threshold decreased by more than 50%. Additionally, it is recommended that the illuminance of the illumination device should be greater than 15 lx. Full article

Concrete is an essential construction material, and infrastructures, such as bridges, tunnels, and power plants, consume large quantities of it. Future infrastructure demands and sustainability issues necessitate the adoption of non-conventional supplementary cementitious materials (SCMs). At the same time, global labor shortages are compelling the conservative construction sector to implement autonomous and digital fabrication methods, such as 3D printing. This paper thus investigates the feasibility of using oil shale ash (OSA) as an SCM in concrete suitable for 3D printing, and collision milling is examined as a possible ash pretreatment. OSA from four different sources was collected and analyzed for its physical, chemical, and mineralogical composition. Concrete formulations containing ash were tested for mechanical performance, and the two best-performing formulations were assessed for printability. It was found that ash extracted from flue gases by the novel integrated desulfurizer has the greatest potential as an SCM due to globular particles that contain β-calcium silicate. The 56-day compression strength of concrete containing this type of ash is ~60 MPa, the same as in the reference composition. Overall, collision milling is effective in reducing the size of particles larger than 10 μm but does not seem beneficial for ash extracted from flue gasses. However, milling bottom ash may unlock its potential as an SCM, with the optimal milling frequency being ~100 Hz. Full article

Sustainability rating systems (SRSs) have emerged as indispensable frameworks for advancing the environmental, social, and economic sustainability of road infrastructure. Despite their growing adoption, their integration as authoritative tools within infrastructure planning and development remains limited. This study provides a comprehensive evaluation of eight leading SRSs—CEEQUAL, Greenroads, GreenLITES, GreenPave, I-LAST, INVEST, BE2ST-in-Highways, and Envision—focusing on their structural frameworks, criteria weightings, adherence to the three pillars of sustainability, and alignment with international benchmarks such as ISO, EN, and ASTM standards. By considering the three pillars of sustainability, the analysis of the eight SRSs reveals a disproportionate focus on environmental well-being (43%) and social well-being (42%), with economic well-being receiving minimal emphasis (15%). Furthermore, this study identifies notable deficiencies in the integration of critical international standards, including ISO, EN, and ASTM, which constrains the comprehensiveness and global applicability of these frameworks. Key findings suggest that the current SRSs inadequately address the principles of a circular economy, risk management, and social equity, highlighting areas for methodological enhancement. This review offers critical insights for researchers, policy makers, and practitioners seeking to refine sustainability rating systems for road infrastructure. By consolidating existing knowledge and proposing methodological advancements, this study contributes to the evolution of SRSs into comprehensive, globally relevant tools for sustainable infrastructure development. Full article

Urban multilane roundabouts and signalized intersections are two major roadway devices used for controlling and managing traffic flow. This paper presents a comparative analysis of the saturation flow rate between urban multilane roundabouts and multilane signalized intersections using field data from the Dammam Metropolitan Area (DMA) in Saudi Arabia. The data of this study were collected at four roundabouts and four signalized intersections in Dammam metropolitan area (DMA), Saudi Arabia. A total of 7028 saturation headways at the roundabouts and 2626 saturation headways at the signalized intersections were included. The results indicated that the signalized intersections had a higher saturation flow rate at the exit lane than the roundabouts at about 1046 vehicles per hour. These findings emphasize that signalized intersections outperform roundabouts in terms of the vehicular movement rate during green lights. Moreover, when the light is green, it takes 1.82 s for a car to move through the middle lane of a traffic light intersection. This study draws a unique connection between speed fluctuations in roundabouts with energy consumption, concluding how vehicles consume more energy this way. Thus, single-lane roundabouts are recommended for optimal traffic flow management in all directions. Full article

This study examined the impact of various foam concrete production techniques on pore size distribution and its water absorption properties. Techniques such as the use of a cavitation disintegrator and a turbulent mixer were employed to produce foam concrete. Six foam concrete compositions, with dry densities ranging from 820 to 1480 kg/m³ and compressive strength up to 47 MPa, were prepared. A novel method for digital image correlation was applied to analyse the pore size distribution within the foam concrete specimens. The manufactured foam concrete specimens’ porosity and water absorption indices were determined. The experimental results, including compression strength and water absorption, indicated that the production technique significantly affects the pore size distribution in foam concrete, impacting its mechanical and durability properties. Compressive strength was assessed at curing intervals of 7, 28, and 180 days. Cavitation technology was found to promote the formation of a finer porous structure in foam concrete, resulting in enhanced strength properties. Full article