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Fly ash-based geopolymer concrete is studied in this research work for its compressive strength, life cycle and environmental impact assessment contribution to the construction environment. This is in line with the United Nations’ sustainable development goals SDG9 and SDG11. However, the focus of this research paper is on the sustainability of geopolymer concrete and its overall environmental impact. The metaheuristic machine learning approaches have been deployed to predict the compressive strength (CS) of the GPC based on environmental impact considerations of the concrete constituent materials, which included fly ash, sodium silicate, sodium hydroxide, fine and coarse aggregates. The metaheuristic techniques include the k-Nearest Neighbour (kNN), support vector regression (SVR), and random forest regression (RFR), where all are optimized with the particle swarm (PSO). These metaheuristic techniques have been modified for this research work with new codes to enhance innovation in terms of run time and efficiency. The results of the life cycle assessment (LCA) evaluation of the GPC mixes based on the Ecoinvent 3 available in SimaPro and Eco-indicator 99 and CML 2001 modified in the framework of ReCiPe 2016 recent development show reduced potential of environmental acidification due to increased fly ash (FA) in the GPC mixes compared to previous results. The decisive CS and LCA predictive models, RFR-PSO and SVR-PSO respectively performed optimally above 90% and better than previous models from the literature. Overall, they present an innovative metaheuristic smart technology for the prediction of the GPC infrastructure behavior and performance integrity.

This paper provides a comprehensive review of the current state of 3D printing technology in the construction industry, highlighting the potential applications, benefits, and future directions of this emerging field. The review indicates that 3D printing technology has the potential to revolutionize the construction industry by offering more efficient, precise, and sustainable methods of construction. The technology offers numerous advantages, including the ability to create complex geometries and custom components, improved precision and accuracy, reduction in waste materials, improved worker safety, and potential for use in remote or inaccessible locations. Furthermore, the advent of additive manufacturing, colloquially known as 3D printing, presents prospects for the advancement of novel material compositions, printing methodologies, and cybernetic systems that have the potential to optimize the efficiency and effectiveness of the construction domain. Future research should focus on developing larger printers with more efficient support structures, improving the accuracy and speed of printing, and exploring the potential of using new and innovative materials in the construction process. Additionally, the environmental impact of 3D printing technology should be further examined, particularly in terms of its potential for reducing waste and energy consumption in the construction industry. Overall, the potential utilizations and advantageous outcomes stemming from the implementation of 3D printing technology within the construction sector are momentous. Persistent exploration and innovation within this realm hold the capacity to engender noteworthy strides in construction technology and foster heightened sustainability within building methodologies.

The flow of Bingham non-Newtonian incompressible fluids like concrete is associated with the large deformation of materials. The modeling and simulation of these fluids’ flow behavior by using conventional numerical methods. suffer problem-formulation setbacks due to mesh distortion. In order to compensate for the mathematical inefficiencies encountered in the process, particle-based methods have evolved and been applied. Also, the use of some particle-based methods produces a stretch of unreliability due to the Eulerian algorithmic trail, which visits every particle edge allowing for revisiting vertices during its operation. This makes the model path cumbersome and time-consuming. Concrete flow is an important element of sustainable infrastructural development, and its understanding strengthens the efficiency of concrete handling and placement during construction activities. In this paper, a mesh-free method of modeling the flowability of self-compacting concrete (SCC) known as the smoothed particle hydrodynamics (SPH) has been reviewed. It derives its advantage from the Lagrangian algorithmic trail. This explores its merits and demerits in the concrete construction industry to propose the best practices for the passing ability, filling ability, and dynamic stability of the flowing fresh concrete (FFC)

In this paper, selected materials that influence the viscosity of the self-consolidating concrete (SCC) are introduced like the Limestone Powder (LSP), the High Range Water Reducing Admixture (HRWRA), which reduce the interparticle force between concrete constituents like the aggregates, and other superplasticizers. Moreover, in serious attempts to design the SCC for different infrastructure requirements, there have been repeated laboratory visits, which need to be reduced. In this research paper, the artificial intelligence (AI) methods: Artificial Neural Network (ANN), Evolutionary Polynomial Regression (EPR), and Genetic programming (GP) have been deployed to predict the slump flow (SF), V-funnel flow time (VFFT), L-box ratio (LBR) or passing ratio, and Orimet flow time (OFT) of LSP-admixed SCC. The independent variables of the predictive model were cement, LSP, water, water-binder ratio, HRWRA, sand, and coarse aggregates of 4/8 mm and 8/16 mm sizes. The flow tests were conducted after 5 minutes of waiting time after mixing. The model results showed ANN with superior intelligent learning ability over previous models in terms of overall performance.

The effect of Pond Ash (PA) activated with sodium chloride (NaCl) solution and reinforced with glass powder on the mechanical properties of soft clay soil, which comprise of the California bearing ratio (CBR) and the unconfined compressive strength (UCS) has been studied in this research work. The PA requires pozzolanic improvements to meet the ASTM C618 requirements for pozzolanas. In the present research paper, further emphasis has been on the machine learning prediction of CBR and UCS of the soft clay soil stabilized with a composite of PA. Generally, the studied soft clay soil properties, which were the microstructure, microspecter/micrograph, oxide composition, Atterberg limits, compaction behavior, free swell index (FSI), CBR and UCS significantly improved due to the enhanced cementitious ability of the activated and reinforced PA. The multiple data collected from this general stabilization result were used to predict the soil’s CBR and UCS by the artificial neural network (ANN) technique. The results showed high performance of the model in terms of the sum of squares error (SSE) of 1.5% and 2.0% and the coefficient of determination (R2) of 0.9979 and 0.9973 for the CBR and UCS models, respectively. The models also outclassed the performances of other models from the literature.

In response to the critical need for enhanced resource management in the construction industry, this research develops an innovative, integrated methodology that synergistically combines Agent-Based Modeling (ABM), Building Information Modeling (BIM), and Bluetooth Low Energy (BLE) technologies. Central to our approach is a sophisticated technological framework that incorporates a Client Early Warning System (CEWS) and a Decision Support System (DSS). These systems facilitate real-time monitoring and management of construction resources, ensuring operational efficiency and optimal resource utilization. Our methodology was empirically validated through a comprehensive case study at Helwan University's College of Engineering. The results demonstrated a significant enhancement in operational efficiency, particularly in resource allocation and progress tracking. Key practical outcomes include the development of a CEWS master dashboard that provides in-depth, real-time insights into project metrics. This dashboard was crucial for managing compliance with health protocols during the COVID-19 pandemic, showcasing the framework's adaptability to critical health standards. Further, the integration of indoor tracking technology revolutionized attendance tracking by replacing outdated manual methods with automated processes. This capability not only underscores the practical applicability of our research but also establishes a new benchmark for future technological advancements in construction project management. Our study sets the stage for subsequent innovations, paving the way for a more connected, efficient, and data-driven approach in the construction industry. [ABSTRACT FROM AUTHOR]

Investigating the impact of near-field ground motions on the fragility curves of multi-span simply supported concrete girder bridges is the main goal of this paper. Fragility curves are valuable tools for evaluating seismic risks and vulnerabilities of bridges. Numerous studies have investigated the impact of ground motions on the fragility curves of bridges. Ground motions are commonly categorized into two sets, based on the distance of the recorded station from the seismic source: far-field and near-field. Studies examining the influence of near-field records on bridge fragility curves vary depending on the specific bridge type and type of fragility curve being analyzed. Due to the widespread use of multi-span simply supported concrete girder bridges in the Central and Southeastern United States, this study makes use of this bridge type. This research investigates the component fragility curves for column curvatures, bearing deformations, and abutment displacements by employing 3-D analytical models and conducting nonlinear time history analysis. These curves illustrate the impact of near-field ground motions on different components. The component fragility curves for two sets of records, 91 near-field ground motions and 78 far-field ground motions, were obtained and compared. These findings demonstrate that near-field ground motions have a greater damaging effect on columns and abutments than far-field earthquakes. When it comes to bearing deformations, the far-field earthquake impact is more severe at lower intensities, whereas the impact of the near-field ground motion is stronger at higher intensities. [ABSTRACT FROM AUTHOR]

Filling ability is one of the prominent rheological properties of the self-compacting concrete (SCC), which has been studied in this research work deploying the functional behavior of the concrete through the Orimet apparatus using the coupled ANSYS-SPH interface. Seven (7) model cases: Case 1: 0% coarse particles and 100% fine particles, Case 2: 60% coarse particles and 40% fine particles, Case 3: 55% coarse particles and 45% fine particles, Case 4: 50% coarse particles and 50% fine particles, Case 5: 45% coarse particles and 55% fine particles, Case 6: 40% coarse particles and 60% fine particles and Case 7: 100% coarse particles and 0% fine particles were studied and optimized. The maximum size of the coarse aggregates considered is 20 mm and that of the fine aggregates is below 4 mm. The Bingham model properties for the multiphysics (SPH)-ANSYS models' simulation are; Viscosity = 20 ≤ μ ≤ 100 and the Yield stress = 50 ≤ τ0 ≤ 200, standard flow time, t (s) ranges; 0 ≤ t ≤ 6, and the Orimet volume is 10 l. The minimum boundary flow time, which represents the time (0 ≤ t ≤ 6) it takes for the SCC to completely flow through a specified distance, typically measured in seconds was modeled for in the seven (7) model cases. The first case; 0%C mixed with 100%F flowed out completely in 6 s, second case; 40%C mixed with 60%F completely flowed out in 5 s, third case; 45%C mixed with 55%F completely flowed out in 9 s, fourth case; 50%C mixed with 50%F completely flowed out in 12 s, fifth case; 55%C mixed with 45%F completely flowed out in 11 s, sixth case; 60%C mixed with 40%F completely flowed out in 12 s, and lastly, the 7th case; 100%C mixed with 0%F completely flowed out in 20 s. The minimum flow time was considered alongside other relevant parameters and tests, such as slump flow, passing ability, segregation resistance, and rheological properties (stresses), to comprehensively assess the filling ability of SCC in this model. By considering these factors and the optimized mix (40%C + 60%F:5 s), engineers and researchers can optimize the SCC mix design to achieve the desired flowability and filling performance for their specific construction applications. The multiphase optimized mix (40%C + 60%F:5 s) was further simulated using the coupled interface of the ANSYS-SPH platform operating with the CFX command at air temperature of 25 °C, which incorporated the studied density of 2400 kg/m³, plastic viscosity boundary, yield stress, and aggregate sampling. The model simulation operated on total number of nodes = 143,083, total number of elements = 753,292, total number of tetrahedrons = 753,292, and total number of faces = 68,488, and produced Dynamic Viscosity = 1.831E-05 kg m-1 s-1, Thermal Conductivity = 2.61E-02 W m-1 K-1, Absorption Coefficient = 0.01 m-1, Thermal Conductivity = 2.61E-02 W m-1 K-1, Refractive Index = 1.0 m m-1, Molar Mass = 1 kg kmol-1, Specific Heat Capacity = 8.80E + 02 J kg-1 K-1, Normal Speed = 165 mm s-1, Pressure Profile Blend = 0.05, and Maximum Partition Smoothing Sweeps = 100. Also, the Global Length = 1.9144E-01, Minimum Extent = 1.1800E-01, Maximum Extent = 6.5976E-01, Density = 1.1850E + 00, Velocity = 1.6500E-01, Advection Time = 1.1602E + 00, and Reynolds Number = 2.0443E + 03. The simulation also produced wall forces and moments on the wall of the Orimet for the optimized mix containing 40%C + 60%F:5 s flow mix as follows; pressure force on wall; -3.0996E-08, -2.0863E-07, and -3.5048E-04 for x-component, y-component, and z-component, respectively, viscous force on wall; -5.5332E-10, -9.2298E-10, and -2.7250E-05 for the x-, y-, and z-components, respectively, pressure moment on wall; -5.0051E-05, 3.1362E-06, and 2.2774E-09 for the x-, y-, and z-components, respectively and viscous moment on wall; -3.8925E-06, 2.4396E-07, and -7.2693E-11 for the x-, y-, and z-components, respectively. Also, the maximum residuals were located at node 110413 for the pressure, node 76766 for the K-TurbKE, and node 110724 for the E-Diss.K. Ideally, the mix, 40%C + 60%F:5 s has been proposed as the mix with the most efficient flow to achieve the filling ability for sustainable structural concrete construction. [ABSTRACT FROM AUTHOR]

Non-destructive testing (NDT) is a crucial method for detecting damages in concrete structures. Structural damage can lead to functional changes, necessitating a range of damage detection techniques. Non-destructive methods enable the pinpointing of the location of the damage without causing harm to the structure, thus saving both time and money. Damaged structures exhibit alterations in their static and dynamic properties, primarily stemming from a reduction in stiffness. Monitoring these changes allows for the determination of the failure location and severity, facilitating timely repairs and reinforcement before further deterioration occurs. A systematic approach to damage detection and assessment is pivotal for fortifying structures and preventing structural collapse, which can result in both financial and human losses. In this study, we employ image processing to categorize damaged beams based on their crack growth and propagation patterns. We also utilize support vector machine (SVM) and k-nearest neighbor (KNN) methods to detect the type, location, and extent of failures in reinforced concrete beams. To provide context and relevance for the laboratory specimens, we will compare our findings to the results from controlled experiments in a controlled laboratory setting. [ABSTRACT FROM AUTHOR]

Much research has been conducted and published on the examination of the behavior of reinforced steel and concrete structures with a FRP system. Nevertheless, the performance of FRP differs from that of FRCM, particularly at high temperature and ultimate strength. The present study provides a review of previous research on structural elements (viz. beams, columns, arches, slabs, and walls) retrofitted with FRCM systems, taking account of various parameters, such as layers, composite types, configurations, and anchors for controlling or delaying failure modes (FMs). Additionally, this paper discussed the details of different FMs observed during experimental tests, such as crushed concrete or bricks, fiber debonding from substrate materials, slippage, fiber rupture, and telescopic failure for strengthened specimens. Moreover, this paper investigated where and how fractures may develop in structural elements retrofitted with the FRCM system under various retrofit scenarios. To this end, in addition to the review of the relevant literature, a large dataset has been compiled from different (RC) structural elements and masonry members. Next, a relationship is developed between failure modes (FMS) and influential parameters, i.e., the number of layers and the type of composite, based on this dataset. This can be used as a benchmark example in future studies, as there is no such basis available in the literature, to the best of the authors' knowledge. [ABSTRACT FROM AUTHOR]

Various cases of two adjacent multi-story buildings with different numbers of floors and equal or unequal foundation levels under earthquake loading and considering soil-structure interaction (SSI) are investigated. A two-dimensional model for each case of the two adjacent unequal buildings without separation distance is used and a special arrangement of contact elements in the contact zone is employed to fulfil all possible deformation contact modes which take place under seismic loading. The soil is modelled by two-dimensional 4-node elements which are in contact with the foundations of the two adjacent buildings. This paper studies the earthquake-induced double pounding that takes place between the two adjacent unequal height buildings in some upper points at superstructure in the contact zone and also at foundation level, considering soil-structure interaction (SSI). The double pounding and the soil-structure interaction (SSI) effects should be taken into consideration in the seismic analysis of adjacent buildings especially those with different heights and different foundation levels. [ABSTRACT FROM AUTHOR]

An existing riverine platform in Egypt, together with its pile group foundation, is analyzed under environmental loads using 3D FEM structural analysis software incorporating soil-pile interaction. The interaction between the transfer plate and the piles supporting the platform is investigated. Two connection conditions were studied assuming fixed or hinged connection between the piles and the reinforced concrete platform for the purpose of comparison of the structural behavior. The analysis showed that the fixed or hinged connection condition between the piles and the platform altered the values and distribution of displacements, normal force, bending moments, and shear forces along the length of each pile. The distribution of piles in the pile group affects the stress distribution on both the soil and platform. The piles were found to suffer from displacement failure rather than force failure. Moreover, the resulting bending stresses on the reinforced concrete plate in the case of a fixed connection between the piles and the platform were almost doubled and much higher than the allowable reinforced concrete stress and even exceeded the ultimate design strength and thus the environmental loads acting on a pile-supported riverine offshore platform may cause collapse if they are not properly considered in the structural analysis and design. [ABSTRACT FROM AUTHOR]

Soil-structure interaction (SSI) could affect the seismic response of structures. Since liquid storage tanks are vital structures and must continue their operation under severe earthquakes, their seismic behavior should be studied. Accordingly, the seismic response of two types of steel liquid storage tanks (namely, broad and slender, with aspect ratios of height to radius equal to 0.6 and 1.85) founded on half-space soil is scrutinized under different earthquake ground motions. For a better comparison, the six considered ground motions are classified, based on their pulse-like characteristics, into two groups, named far and near fault ground motions. To model the liquid storage tanks, the simplified mass-spring model is used and the liquid is modeled as two lumped masses known as sloshing and impulsive, and the interaction of fluid and structure is considered using two coupled springs and dashpots. The SSI effect, also, is considered using a coupled spring and dashpot. Additionally, four types of soils are used to consider a wide variety of soil properties. To this end, after deriving the equations of motion, MATLAB programming is employed to obtain the time history responses. Results show that although the SSI effect leads to a decrease in the impulsive displacement, overturning moment, and normalized base shear, the sloshing (or convective) displacement is not affected by such effects due to its long period. [ABSTRACT FROM AUTHOR]