The nature of soil varies horizontally as well as vertically, owing to the process of the formation of soil. Thus, ensuring the safe design of geotechnical structures has been a major challenge. In shallow foundations, conducting field tests is expensive and time-consuming and often conducted on significantly scaled-down models. Empirical models, too, have been found to be the least reliable in the literature. The study proposes AI-based techniques to predict the bearing capacity of a shallow foundation, simulated using the datasets obtained in experiments conducted in different laboratories in the literature. The results of the ELM-EO and ELM-PSO hybrid models are compared with that of the ELM and MARS models. The performance of the models is analyzed and compared with each other using various performance parameters. The models are graded to each other using rank analysis and the visual interpretations are provided using error matrices and REC curves. ELM-EO is concluded to be the best performing model (R² and RMSE equal to 0.995 and 0.01, respectively, in the testing phase), closely followed by ELM-PSO, MARS, and ELM. The performance of MARS is better than ELM (R² equals 0.97 and 0.5, respectively, in the testing phase); however, hybridization greatly enhances the performance of the ELM and the hybrid models perform better than MARS. The paper concludes that AI-based models are robust and hybridization of regression models with optimization techniques should be encouraged in further research. Sensitivity analysis suggests that all the input parameters have a significant influence on the output, with friction angle being the highest.

This study aims to investigate the two-way shear strength of concrete slabs with FRP reinforcements. Twenty-one strength models were briefly outlined and compared. In addition, information on a total of 248 concrete slabs with FRP reinforcements were collected from 50 different research studies. Moreover, behavior trends and correlations between their strength and various parameters were identified and discussed. Strength models were compared to each other with respect to the experimentally measured strength, which were conducted by comparing overall performance versus selected basic variables. Areas of future research were identified. Concluding remarks were outlined and discussed, which could help further the development of future design codes. The ACI is the least consistent model because it does not include the effects of size, dowel action, and depth-to-control perimeter ratio. While the EE-b is the most consistent model with respect to the size effect, concrete compressive strength, depth to control perimeter ratio, and the shear span-to-depth ratio. This is because of it using experimentally observed behavior as well as being based on mechanical bases.

The construction industry is one of the most complex industries, and it involves numerous change orders. Change orders often occur in all or some phases of industrial construction work and have a significant impact on the success of the project, its on‐time completion, or ultimately, an increase in the estimated cost of the project. Change orders are one of the most frequently common problems facing construction projects in Saudi Arabia. The purpose of this study is to examine the impacts of change orders on construction projects in Saudi Arabia and identify preventive solutions to mitigate these impacts. To achieve this objective, the effects of change orders on construction projects in general were identified through a comprehensive literature review. Then, an analytical study was conducted on five construction projects in diverse universities in Saudi Arabia. Following that, interviews were conducted with some experts in these projects. Finally, a survey was conducted by distributing questionnaires to the parties involved in the projects, and the responses were analyzed by using the relative index method. A triangulation technique involving collecting data from the analytical study, the interviews, and the survey was used to improve the validity of the findings. The results showed that the major impacts of change orders on construction projects in Saudi Arabia were on meeting the needs of the project, disputes among parties of the project, and the development of project specifications. A set of preventive solutions were suggested to mitigate these impacts, such as having all parties study the project and coordinate between them before starting the project and hiring a specialized consultant with experience in similar projects.

Unreinforced masonry (URM) is one of the most popular construction materials around the world, but vulnerable during earthquakes. Due to its brittle nature, the URM structures may lead to a possible collapse of the wall of a building during earthquake events causing casualties. In the current research, an attempt is made to enhance the seismic capacity of URM structures by proposing a new innovative composite material that can improve the shear strength and deformation capacity of the URM wall systems. The results revealed that the fiber-reinforced plastic having high tensile and shear stiffness can significantly increase in-plane as well as out-of-plane bending strength of the URM wall. It was recorded that the bending moment of the prism increased up to 549.5% by increasing the bending moment from 490 N*mm to 3183 N*mm per mm deflection of prism upon using glass fibers. Moreover, the ductility ratio amplified up to 5.73 times while the stiffness ratio increased up to 4.16 times with the aid of glass fibers. Since the material used in this research work is low cost, easily available, and no need for any skilled labor, which is economically good. Therefore, the URM walls retrofitted with fiber-reinforced plastic is an economical solution.

This study evaluates the readiness of Egypt’s construction sector to integrate Circular Economy (CE) principles by identifying and analyzing the main barriers to effective Construction and Demolition Waste (CDW) management. A comprehensive survey-based methodology (n = 384) was employed to gather data from industry stakeholders, demonstrating excellent sampling adequacy (KMO = 0.961). Initially, 41 potential barriers were identified via literature review and expert consultation. Exploratory Factor Analysis (EFA) subsequently refined these to 10 critical barriers, whose interrelationships were validated using Structural Equation Modeling (SEM), exhibiting a strong model fit (RMSEA = 0.065; CFI = 0.974). The analysis revealed persistent economic, technological, and social barriers impeding CE adoption. Notable challenges include high implementation costs, inadequate technical expertise, low stakeholder awareness, and weak policy enforcement. Based on these findings, prioritized, time-phased recommendations are proposed to provide an evidence-based framework for policy and practice. This research contributes an early empirical assessment of CE adoption in Egypt’s construction sector, offering a robust roadmap for a more sustainable, resource-efficient industry aligned with national environmental and economic objectives.