CivilEng

This research used the SWARA approach to analyze risk assessment criteria for public–private partnership (PPP) projects in Iran’s water and sewage sectors to identify and prioritize the most significant elements influencing project success from public and private viewpoints. Key results show that the public sector considers “risk probability” to be the most important aspect, highlighting the requirement for stability and predictability in project outcomes. In contrast, the private sector prioritizes the “ability to predict and discover risk”, emphasizing efficiently anticipating and managing uncertainty. Furthermore, this study revealed five common major risk characteristics, including “risk manageability” and “uncertainty of risk”; however, their rankings differ per industry, demonstrating various risk prioritizing methodologies. This study is unique in that it focuses only on Iran’s water and sewage infrastructure, an area historically neglected in PPP research, providing a rare investigation of sector-specific hazards as well as the interaction between public and private interests in a developing country environment. The paper makes specific suggestions, calling for more openness, improved communication, and the use of sophisticated risk management techniques to bridge the gap across sectors. These findings not only add to the scholarly knowledge of PPP dynamics in emerging countries but also provide practical recommendations for governments and private investors navigating Iran’s infrastructure issues. Full article

Fragility curves are fundamental tools in seismic risk assessments, providing insights into the vulnerability of structures to earthquake-induced damages. These curves, which plot the probability of a structure reaching or exceeding various damage states against earthquake intensity, are critical for developing effective modification strategies. This review aims to present the characteristics between building- and site-specific fragility curves, which incorporate detailed local characteristics, and generic fragility curves that apply broader, more generalized parameters. We utilize the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology to systematically review the literature to address key research questions about the methodological differences, applications, and implications of these curve types in assessing seismic risks. The methods involved a comprehensive search and combination of existing studies on the topic, focusing on how these curves are developed and applied in real-world scenarios. The results from this review show that building- and site-specific curves, while more precise, require extensive data and are therefore more complex and costly to develop. In contrast, generic curves, though less accurate, offer a cost-effective solution for preliminary risk assessments over large areas. The conclusions drawn from this review suggest that while each type has its merits, the choice between building- and site-specific and generic fragility curves should be guided by the specific requirements of the seismic risk assessment task, including available resources and the need for precision in the vulnerability estimations. Full article

Generative Artificial Intelligence (AI) holds significant potential for revolutionizing the Architecture, Engineering, and Construction (AEC) industry by automating complex tasks such as construction scheduling, hazard recognition, resource leveling, information retrieval from BIM, etc. However, realizing this potential requires a strategic approach to ensure effective utilization and maximum benefit. This paper presents guidelines for prompt design and engineering to elicit desired responses from ChatGPT, a Generative AI tool, in AEC applications. Key steps include understanding user intent, leveraging model capabilities, and optimizing prompt structures. By following these guidelines, stakeholders in the AEC industry can harness the power of Generative AI to improve construction scheduling processes, increase project efficiency, and ultimately drive innovation and growth in the industry. Several illustrative examples on construction scheduling and hazard recognition are provided to demonstrate the methodology proposed in this research. It is concluded that Generative AI, when effectively utilized, significantly enhances project scheduling and hazard recognition capability in the AEC industry with minimal error. Full article

This study proposes a novel framework for determining variables’ weights in transportation assets condition indices calculations using statistical and machine learning techniques. The methodology leverages subjective ratings alongside objective measurements to derive data-driven weights. The motivation for this study lies in addressing the limitations of existing expert-based weighting methods for condition indices, which often lack transparency and consistency; this research aims to provide a data-driven framework that enhances accuracy and reliability in infrastructure asset management. A case study was performed as a proof of concept of the proposed framework by applying the framework to obtain data-driven weights for pavement condition index (PCI) calculations using data for the city of West Des Moines, Iowa. Random forest models performed effectively in modeling the relationship between the overall condition index (OCI) and the objective measures and provided feature importance scores that were converted into weights. The data-driven weights showed strong correlation with existing expert-based weights, validating their accuracy while capturing contextual variations between pavement types. The results indicate that the proposed framework achieved high model accuracy, demonstrated by R-squared values of 0.83 and 0.91 for rigid and composite pavements, respectively. Additionally, the data-driven weights showed strong correlations (R-squared values of 0.85 and 0.98) with existing expert-based weights, validating their effectiveness. This advanceIRIment offers transportation agencies an enhanced tool for prioritizing maintenance and resource allocation, ultimately leading to improved infrastructure longevity. Additionally, this approach shows promise for application across various transportation assets based on the yielded results. Full article

Concrete columns with hollow-core sections find widespread application owing to their excellent structural efficiency and efficient material utilization. However, corrosion poses a challenge in concrete buildings with steel reinforcement. This paper explores the possibility of using glass fiber-reinforced polymer (GFRP) reinforcement as a non-corrosive and economically viable substitute for steel reinforcement in short square hollow concrete columns. Twelve hollow short columns were meticulously prepared in the laboratory experiments and subjected to pure axial compressive loads until failure. All columns featured a hollow square section with exterior dimensions of (180 × 180) mm and 900 mm height. The columns were categorized into four separate groups with different variables: steel and GFRP longitudinal reinforcement ratio, hollow ratio, spacing between ties, and reinforcement type. The experimental findings point to the compressive participation of longitudinal GFRP bars, estimated to be approximately 35% of the tensile strength of GFRP bars. Notably, increasing GFRP longitudinal reinforcement significantly improved the ultimate load capability of hollow square GFRP column specimens. Specifically, elevating the ratio of GFRP reinforcement from 1.46% to 2.9%, 3.29%, 4.9%, and 5.85% resulted in axial load capacity improvements of 32.3%, 43.9%, 60.5%, and 71.7%, respectively. Specifically, the GFRP specimens showed a decrease in capacity of 13.1%, 9.2%, and 9.4%, respectively. Notably, the load contribution of steel reinforcement to GFRP reinforcement (with similar sectional areas) was from approximately three to four times the axial peak load, highlighting the greater load participation of steel reinforcement due to its higher elastic modulus. In addition, the numerical modeling and analysis conducted using ABAQUS/CAE 2019 software exhibited strong concordance with experimental findings concerning failure modes and capacity to carry axial loads. Full article

The increase in cement production has had a noteworthy impact on the emission of greenhouse gases. As a result, it is essential to develop geopolymer concrete innovations to mitigate the environmental consequences. However, conventional geopolymer concrete not only requires heavy machinery and an increase in the cross-sectional area of structural supports, but it also endangers the operating safety of workers. Therefore, in recent times, lightweight concrete has gained significant attention due to its many advantages and benefits to the structure and construction sectors. Thus, the aim of this study is to carry out a bibliometric analysis of the lightweight geopolymer concrete and assess its fundamental characteristics to determine the research gap in this area. This review paper will benefit researchers in identifying the ongoing trend in lightweight aggregate geopolymer concrete, identifying more areas for additional study. It will also act as a knowledge source for policymakers, journal editors, professionals, and research organizations. Full article

To understand changes in bedrock motion at the ground surface, frequency effects, and spatial distribution within the soil, it is important to look at how a site responds to earthquakes. This is important for soil–structure interaction in structural and geotechnical earthquake engineering. This study deals with the effect of classifying clays according to shear wave velocity (stiff/medium/soft) and nonlinearity in behavior (linear/nonlinear) on the analysis of the site response. A 3D soil model with a combination of free fields and quiet boundaries and advanced constitutive models for soil to obtain accurate results was used to conduct this study. A strong TABAS earthquake was used to excite the compliant base of the model after converting the velocity record of TABAS to an equivalent surface traction force using a horizontal force–time history proportional to the velocity–time history. This study reveals that the site response analysis is affected by the type of clay soil and the soil material behavior, with soft clay soil causing higher PGV and PGV values in the linear case and lower values in the nonlinear case due to soil yielding, which causes soil response attenuation. This results in extremely conservative and expensive building designs when linear soil behavior is adopted. On the other hand, the applied earthquake exhibits greater attenuation at longer frequencies and greater amplification at mid and short frequencies. However, at frequencies near the applied earthquake frequency, neither attenuation nor amplification occurs. Furthermore, nonlinear soil behavior is crucial for soil evaluation and foundation design due to higher octahedral shear strain and settlement values, especially in softer soils, resulting from extensive plastic deformation. Full article

Sandstone has poor mechanical properties. To facilitate the application of sandstone into asphalt mixtures, sandstone was treated by immersion in sodium silicate solution, and the dynamic modulus after reinforcement was used as a criterion. The results showed that the mechanical properties of the sandstone aggregate treated with sodium silicate were improved, and the dynamic modulus was increased by 18.2%, which will help to reduce rutting. The dynamic modulus and phase angle can be effectively predicted over a wide frequency range using the sigma function and the Kramers–Kronig relationship. Sandstone asphalt mixtures basically conform to linear viscoelasticity, but the phase angle changes are more complicated at high temperatures and do not vary monotonically with frequency. By calculating the rutting coefficient, fatigue coefficient, and DSRFn parameters for performance prediction, it was found that an increase in dynamic modulus resulted in a significant increase in the rutting coefficient but a decrease in the cracking resistance. Full article

This research, with its potential to revolutionise the construction industry, aims to develop quaternary-blended composites (QBC) by replacing 80% of ordinary Portland cement (OPC) with metakaolin, rice husk ash, and wood ash combined with discrete hybrid natural fibres at a volume fraction of 0.5%. This study investigates the mechanical properties, including compressive strength, split tensile strength, and impact strength of the QBC at various curing ages of 7, 28, and 56 days. Scanning electron microscopy (SEM) analysis was performed to assess the microstructural characteristics. This research aimed to formulate a novel quaternary binder that may minimise our reliance on cement. The experimental results indicate that the mix labelled M4L2 exhibited superior compressive and split tensile strength performance, with percentage increases of approximately 51.03% and 29.19%, respectively. Meanwhile, the M5L1 mix demonstrated enhanced impact energy, with a percentage increase of about 36.40% in 56 days. SEM observations revealed that the MC4 mix contained unhydrated portions and larger cracks. In contrast, the presence of fibres in the M4L2 mix contributed to crack resistance, resulting in a denser matrix and improved microstructural properties. This study also employed an artificial neural network (ANN) model to predict the compressive, tensile, and impact strength characteristics of the QBC, with the predictions aligning closely with the experimental results. An investigation was conducted to determine the ideal number of hidden layers and neurons in each layer. The model’s effectiveness was evaluated using statistical metrics such as correlation coefficient (R), coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MEA), and mean absolute percentage error (MAPE). The findings suggest that the developed QBCs can effectively reduce reliance on conventional cement while offering improved mechanical properties suitable for sustainable construction practices. Full article

The asphalt industry has long been challenged with finding sustainable solutions to enhance the performance of asphalt mixtures while mitigating their environmental impact. One promising avenue is the incorporation of waste filler materials into asphalt mixtures. This review explores the feasibility and effectiveness of utilizing waste filler in asphalt mixtures, focusing on its effects on the mechanical characteristics, durability, and sustainability of asphalt pavements. Various waste filler materials, such as rice husk ash, fly ash, and construction and demolition wastes, have been examined in terms of their potential as substitutes for traditional filler materials such as limestone and mineral powders. This review synthesizes literature to assess the impact of waste fillers on the performance of asphalt mixtures, including rutting resistance, fatigue behavior, moisture susceptibility, and aging characteristics. This work begins by examining the interaction of the asphalt fillers to provide clarification. The usage of various waste fillers is then examined. With fewer harmful environmental consequences than traditional cement manufacturing has, waste filler materials improve the strength and durability of asphalt mixtures. This research underscores the promising future of waste filler materials as environmentally friendly and innovative materials. To fully capitalize on their benefits, further research, standardization, and widespread use of waste filler-based products are necessary. Full article

To minimize the impact on nearby structures during deep excavations, choosing an appropriate soil constitutive model for analysis holds significant importance. This study aims to conduct a comparative analysis of various constitutive soil models—namely, the Mohr–Coulomb (MC) model, the hardening soil (HS) model, the hardening soil small strain (HSS) model, and the soft soil (SS) model—to identify the most suitable model for the lacustrine deposit. To implement these models, the soil’s index properties and mechanical behavior were evaluated from undisturbed soil samples. The numerical simulation and verification of these properties were carried out by comparing the laboratory test results with the outcome of the finite element method; the most suitable constitutive soil model for the soil was identified as the HSS model. Upon analyzing the wall deflection and ground settlement profiles obtained from respective constitutive models, it was observed that the HS and HSS models exhibit similar characteristics and are well-suited for analyzing typical lacustrine soil. In contrast, the MC and SS models yield overly optimistic results with lower wall deflection and ground settlement and fail to predict realistic soil behavior. As a result, this research highlights the significance of selecting the appropriate constitutive soil model and refining the parameters. This optimization process contributes significantly to the design of support systems, enhancing construction efficiency and ensuring overall safety in deep excavation projects. Full article

Construction work and regular inspection work at nuclear power plants involve many special tasks, unlike general on-site work. In addition, the opportunity to transfer knowledge from skilled workers to unskilled workers is limited due to the inability to easily enter the plant and various security and radiation exposure issues. Therefore, in this study, we considered the application of virtual reality (VR) as a method to increase opportunities to learn anytime and anywhere and to transfer knowledge more effectively. In addition, as an interactive learning method to improve comprehension, we devised a system that uses hand tracking and eye tracking to allow participants to experience movements and postures that are closer to the real work in a virtual space. For hand-based work, three actions, “pinch”, “grab”, and “hold”, were reproduced depending on the sizes of the parts and tools, and visual confirmation work was reproduced by the movement of the gaze point of the eyes, faithfully reproducing the special actions of the inspection work. We confirmed that a hybrid learning process that appropriately combines the developed active learning method, using experiential VR, with conventional passive learning methods, using paper and video, can improve the comprehension and retention of special work at nuclear power plants. Full article

The realm of green energy is in constant flux, drawing considerable attention from stakeholders dedicated to minimizing environmental impact, reducing costs, and developing structures that align with stringent standards. This study introduces an innovative approach aimed at improving onshore wind tower foundation systems, emphasizing both engineering and financial feasibility. The approach involves a comprehensive analysis of design load cases, particularly emphasizing resistance against overturn, while ensuring compliance with Eurocode guidelines. The foundation system is conceptualized as a beam slab with voids filled by soil material. High reduction in concrete quantity is achieved by reaching 30%, while the steel reduction reaches 90%. It is worth mentioning that the total cost is reduced by up to 70%. Furthermore, as a future trend, this study aims to integrate the new foundation system with steel 3D printing technology in the manufacturing process of the wind tower’s structural elements. This integration is expected to enhance the precision and customization of the superstructure-foundation system, thereby improving overall performance and efficiency. The optimized design not only significantly reduces construction costs but also streamlines installation, saving time. Simultaneously, this study enhances the structural behavior of the wind tower foundation by focusing on elements crucial to its efficiency. Full article

This study investigated the geotechnical and geophysical properties of the soil layers at the Missan combined-cycle power plant in Iraq. The data from 69 boreholes, including physical and chemical soil properties, were analyzed. The soil is primarily classified as silty clay with moderate to high plasticity, with some sandy layers. Since the Missan governorate is located in a seismically active region represented by the Iraq–Iran border, a study on the seismic properties of the site is also performed. Seismic downhole tests were conducted to determine wave velocities and dynamic moduli. The site was classified as soft clay soil according to FEMA and Eurocode 8 standards. Correlations for the physical and dynamic soil properties were evaluated. The correlations were executed via regression statistical analysis via Microsoft Excel software (2013). The results of the correlation equations and the coefficient of correlation R² show that the physical correlations were considered medium to good correlations, whereas the dynamic soil correlations were perfectly correlated such that the R² values were close to 1. This paper provides comprehensive data and soil property correlations, which can be valuable for future construction projects in the Missan area and similar geological formations. Full article

The rise in early-age temperature concrete structures, driven by the exothermic reactions during cement hydration, significantly increases the risk of thermal cracking. To address this issue, the construction industry employs several strategies, including the partial substitution of cement with ground granulated blast furnace slag (GGBS) due to its lower heat of hydration. Accurately predicting the hydration temperature of concrete is critical for preventing thermal cracking. This task becomes more complex, with fluctuating ambient temperatures influencing hydration kinetics and heat dissipation. Previous studies often assume adiabatic or isothermal conditions, thus overlooking the impact of ambient temperature variations. This paper presents an innovative finite element modelling (FEM) approach to simulate the hydration temperature progression in in situ concrete slabs, incorporating the effects of ambient temperature fluctuations. Isothermal calorimetry curves were adjusted using the Arrhenius-based approach to express the cement hydration rate as a function of ambient temperature. The FEM outcomes, validated with semi-adiabatic calorimetry tests, demonstrate the model’s capability to forecast temperature development in in situ concrete under varying ambient conditions. Additionally, the study examines the influence of partial cement replacement with GGBS on thermal behaviour, revealing that while GGBS effectively reduces thermal reactions at higher contents, its efficacy diminishes with rising ambient temperatures. Full article

This study investigates the seismic behavior of moment-resistant composite frames with concrete-filled steel tube (CFT) columns and composite steel beams under multiple earthquakes, considering soil–structure interaction (SSI) effects. Nonlinear time history analyses were performed on 2-, 4-, and 6-storey frames under five real seismic sequences and various soil conditions. The key response parameters included interstorey drift ratios, floor displacements, accelerations, and residual deformations. The results indicate that consecutive ground motions generally increase displacement demands and residual deformations compared to single-event scenarios. Incorporating SSI typically reduces drift ratios and accelerations but increases periods and displacements. Contrary to conventional assumptions, taller buildings exhibited lower maximum interstorey drift ratios, with the second storey consistently experiencing the highest drift across all building heights. Peak floor accelerations varied with building height; low-rise structures showed higher accelerations from earthquake sequences, while mid-rise buildings experienced higher accelerations from single events. These findings challenge traditional assumptions in seismic engineering and underscore the importance of considering multiple earthquake scenarios, building-specific factors, and SSI effects in the seismic design of CFT–steel composite frames. The results suggest a need for revising current design approaches to better account for these complex interactions. Full article

This paper presents experimental investigations on buried Glass Reinforced Plastic (GRP) pipes with a diameter of 1400 mm. The tested pipes were buried in dense, gravelly sand and subjected to traffic loads to study the effects of backfill cover on pipe deflection. The experimental program included tests on three GRP pipes with backfill covers of 100 cm, 75 cm, and 50 cm. The maximum traffic loads applied to the pipe–soil system corresponded to Iraqi Truck Type 3 (AASHTO H type). Vertical deflections of the pipes were monitored during the application of these loads. The experimental results showed that, as the backfill cover increased, the maximum vertical deflection of the pipe decreased. Deflection reductions were 38.0% and 33.3% when the backfill increased from 50 cm to 100 cm and from 50 cm to 75 cm, respectively. A 500 mm compacted backfill cover was found to be sufficient to resist traffic loads, with the vertical deflection percentage remaining below the allowable limit. Additionally, the behavior of the GRP pipes under different traffic load configurations was analyzed using finite element (FE) analysis with Plaxis 3D. The model was validated using field data. The study investigated numerous variables impacting the behavior of embedded pipes, including pipe material, pipe thickness, backfill properties, backfill depth, and the properties of the soil beneath the GRP pipe. The deflections of the steel pipe were lower than those of the GRP pipe when using different thicknesses. Full article

Presently, the application of big data in the construction industry encounters numerous obstacles and involves diverse stakeholders, with the intricate network of relationships between these factors and stakeholders remaining unclear. Investigating stakeholders’ management priorities and collaborative patterns can facilitate the development of BDAC. Therefore, this study employs a two-mode social network analysis to explore stakeholders’ power and attitudes toward the factors of BDAC. Firstly, the initial list of stakeholders and factors is identified based on the literature and expert interviews, followed by a questionnaire to establish stakeholder–factor relationships and construct the network. Subsequently, the adjacency matrix, centrality, core–periphery structure, and hierarchical cluster are adopted to analyze the network. The results found that (1) technical factors need to be addressed by all stakeholders due to complexity; (2) due to the low resource similarity of factors and low power similarity of stakeholders, all stakeholders should be involved in the collaboration; and (3) government, developers, and consultants, as core stakeholders, exhibit a proactive inclination towards collaborative efforts in addressing central factors, and can coordinate with peripheral stakeholders. Consequently, this study establishes a stakeholder collaboration model centered on the government–developer–consultant trio, which provides clear responsibility allocation and strategic guidance for fostering long-term, effective collaboration in BDAC. Full article

We remember and comment on the research scenario of the theory of elastic stability that accompanied all the course of studies, carried out with enthusiasm and passion, of Prof. Marcello Pignataro, who we still miss and to whom our affectionate memory goes. Marcello was in continuous contact with Professor Koiter in Delft, to study, with a new approach, the many and still open problems of the nonlinear theory of elastic stability. In those times, the entire approach used in the study of the equilibrium stability of elastic structures was in question and its basis seemed to need to be reformulated. The central theme was the definition of the stability criterion of the second variation of the potential energy and how it being definite positive could effectively imply stability. Full article