Mohamed Mortagi

Facility management (FM) requires priorities that distinguish important operational risks from perceived weaknesses in their management. This study develops a perception-based framework linking Building Information Modeling (BIM) and the Saudi Building Code (SBC). Thirty-two literature-derived FM risk factors were rated by 47 professionals for importance, perceived BIM mitigation potential, and perceived SBC adequacy. Analyses combined Relative Importance Index (RII) summaries, internal consistency, and paired Wilcoxon tests with Benjamini–Hochberg adjustment. Ten factors showed positive importance–adequacy contrasts with q < 0.05. External contractor quality had the largest contrast (0.094), followed by life-cycle cost underestimation (0.081). A complementary importance–adequacy analysis separated the ten candidates into five factors combining high importance with adequacy below the scale’s good-adequacy benchmark, four safety factors combining high importance with good perceived adequacy, and one asset-renewal factor below both benchmarks. No factor had mean perceived adequacy below the scale midpoint. Alternative sample-mean crosshairs changed quadrant membership, demonstrating threshold sensitivity. The proposed framework therefore distinguishes targeted improvement, continuing safety assurance, and longer-term asset planning. It also maps the candidates to operational information needs, with BIM positioned as a conditional support mechanism requiring complementary management controls and, where justified, operational systems and analytics. The findings identify professional perceptions and guidance topics rather than legal deficiencies, demonstrated risk reduction, or quantified economic benefits.

The structural performance of reinforced concrete (RC) columns can be substantially improved by using advanced confinement systems and sustainable cementitious materials. This study presents an integrated experimental, numerical, and analytical investigation of RC columns strengthened with self-compacting geopolymer concrete (SCGC) and carbon fiber-reinforced polymer (CFRP) under axial compression. Twelve column specimens were tested across four groups: conventional RC columns, unconfined SCGC columns, SCGC-jacketed columns (CONF. SCGC), and CFRP-wrapped columns (CONF. FRP), in three cross-sectional geometries: square (177 × 177 mm), rectangular (265 × 177 mm), and circular (Ø200 mm). Experimental results demonstrated that replacing conventional concrete with SCGC improved deformation capacity, increasing the ultimate axial displacement from 2.07 mm in the reference square RC column (RC C1) to 3.21 mm in the corresponding square SCGC specimen (SCGC C1). On a normalized stress basis, the unconfined SCGC specimens achieved ultimate axial stress values of 56–64 MPa compared to 41–49 MPa for the RC reference columns of the same geometry, representing material-level strength gains of 1.30–1.49×. The application of external confinement further enhanced column behaviour. The CFRP-wrapped specimens achieved the highest material-level strength efficiency, with normalized ultimate axial stress values of 98–108 MPa for the square and rectangular geometries, representing gains of 2.01–2.41× over the corresponding unconfined RC columns of identical cross-section. The SCGC-jacketed specimens achieved the highest absolute load capacities, with CONF. SCGC C2 reaching 8270 kN and a maximum stiffness of 5531 kN/mm and energy absorption of 19,740 kN·mm. However, on a normalized stress basis, the SCGC-jacketed square and rectangular specimens achieved 45–47 MPa, comparable to the RC reference columns, confirming that their absolute load gains are primarily attributable to section enlargement rather than intrinsic material strength enhancement. The circular SCGC-jacketed specimen achieved a normalized stress of 43 MPa, consistent with the same trend. A three-dimensional nonlinear finite element model developed in ABAQUS using the Concrete Damaged Plasticity model and cohesive zone interactions showed close agreement with experimental results, with mean prediction ratios of 1.03 for ultimate load and 0.96 for displacement. An analytical model provided conservative estimates of axial capacity. The findings demonstrate that CFRP wrapping offers superior material-level confinement efficiency, while SCGC jacketing provides the highest absolute load capacity through combined section enlargement and passive confinement, representing a potentially more environmentally friendly strengthening strategy for existing RC columns.

Accurate prediction of the unconfined compressive strength (UCS) of geopolymer-stabilized clayey soil is critical for geotechnical engineering. Conventional regression algorithms and even advanced machine learning approaches such as artificial neural networks often struggle to fully capture the highly non-linear interactions among soil properties and geopolymer mix parameters while maintaining computational efficiency and interpretability on limited datasets. To address these challenges, this investigation proposes a novel hybrid predictive framework based on a sector fruit fly optimization algorithm–enhanced extreme learning machine (SFOA-ELM) for improved UCS estimation. The model used 270 experimental records with 8 input variables (i.e., liquid limit, plasticity index, GGBS content, molarity). The baseline ELM achieved moderate performance (training R² = 0.9432, testing R² = 0.9054; RMSE = 1.55 MPa and 1.91 MPa, respectively). The predictive accuracy of the standard FOA-ELM improved to an R² of 0.9768 (training) and 0.9318 (testing), with RMSE values of 0.99 MPa (training) and 1.62 MPa (testing). The performance of the SFOA-ELM model improved to have excellent predictive performance with an R² value of 0.9775 (training) and 0.9446 (testing), and an RMSE value of 0.98 MPa (training) and 1.462 MPa (testing), respectively. The SFOA-ELM model reduced the testing MSE by 42% compared to ELM and by 19% compared to FOA-ELM. A SHAP analysis suggested that GGBS content, plasticity index and liquid limit were the most important for prediction. The statistical validations and residual analysis confirmed SFOA-ELM’s ability to generalize effectively and exhibit a tight distribution of errors. These findings show that the SFOA-ELM framework offers a robust, computationally efficient, and interpretable tool for geopolymer mix design and UCS prediction, providing practical decision-support for geotechnical engineering applications.

This study presents a comprehensive experimental and numerical investigation into the flexural behavior of sustainable self-compacting geopolymer concrete ( SCGC ) beams incorporating granite waste and slag powder. While the environmental benefits of geopolymer concrete are widely studied, its structural performance, particularly when utilizing industrial wastes, remains underexplored. To address this gap, six reinforced concrete beams (100 × 150 × 1500 mm), including five SCGC beams and one Portland cement concrete ( PCC ) control beam, were tested under four-point bending. The investigation systematically evaluated the influence of key parameters: the longitudinal reinforcement ratio (0.85%, 1.34% and 2.0%) and the shear span-to-depth ratio (4.27, 4.48 and 4.7). Experimental results demonstrate that the cracking load, yield load, and ultimate flexural capacity of the SCGC beams increased with a higher reinforcement ratio and a lower shear span-to-depth ratio. Notably, the SCGC beams exhibited a higher moment capacity compared to the conventional PCC beam. A nonlinear finite element model, validated against the experimental data, provided accurate predictions of the load–deflection response and ultimate strength. The findings confirm that SCGC incorporating granite waste is a structurally viable and superior alternative to conventional concrete, with the developed model serving as a reliable tool for future design and analysis.

This research investigates the shear performance of sustainable self-compacting reinforced geopolymer concrete (GPC) beams incorporating granite waste powder (GWP) and ground granulated blast-furnace slag (GGBFS) as eco-friendly binding agents through experimental and numerical analyses. Five geopolymer reinforced concrete beam specimens (100 mm × 150 mm × 1500 mm) were tested under two-point loading conditions to evaluate the influence of longitudinal reinforcement ratio (0.85% to 2.0%) and shear span-to-effective depth ratio on the structural shear performance. The experimental investigation revealed that geopolymer reinforced concrete beams exhibit shear behavior characteristics similar to conventional Portland cement concrete beams, with the 2.0% reinforcement ratio achieving 18.3% higher shear strength compared to the 0.85% reinforcement ratio, while shear capacity increased proportionally with increasing shear span-to-depth ratio. Experimental data, including load–displacement response, shear strength measurements, strain distributions, failure modes, and crack patterns, were studied. Finite element nonlinear analysis was conducted by modifying the concrete modulus and stress–strain relationships to reflect the properties of geopolymer concrete using ABAQUS software integrated with the concrete damaged plasticity model. The results demonstrated that for the tested geopolymer reinforced concrete beams, first cracking load, steel yielding load, and ultimate load capacity increased systematically with increasing tension steel reinforcement ratio and proportionally with higher shear span-to-depth ratios.

The rising environmental burden of Portland cement production has intensified the demand for eco-friendly binders that support sustainable construction. This study investigates the development and performance of eco-friendly self-compacting geopolymer concrete (SCGC) produced from industrial by-products, including fly ash (FA), ground granulated blast furnace slag (GGBFS), silica fume (SF), metakaolin (MK), and glass waste powder (GWP). Twenty-one binder formulations were evaluated for fresh-state workability, mechanical performance, durability, and microstructural characteristics under different curing regimes. Fresh properties were assessed using slump flow, V-funnel, L-box, and J-ring tests, while hardened-state evaluations included compressive and flexural strength, Young’s modulus, and water absorption. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were performed on selected mixes to examine microstructural features and crystalline phase development. Results highlight a strong dependency of SCGC performance on binder composition and curing conditions. Mixes rich in GGBFS and SF demonstrated superior mechanical and durability performance, achieving compressive strengths of up to 102.4 MPa under water curing and 107.6 MPa under heat curing, along with negligible water absorption, reflecting a dense and well-developed gel matrix. SEM micrographs confirmed homogeneous, compact microstructures in high-performing mixes, while XRD analysis revealed broad amorphous humps indicative of well-formed N-A-S-H and C-A-S-H gel phases with minimal crystalline residues. In contrast, FA-dominant mixes displayed delayed strength development, and MK-GWP-rich systems exhibited higher porosity and reduced strength. This study underscores the significance of precursor synergy, optimized curing strategies, and microstructural refinement in tailoring SCGC for high-performance, durable, and low-carbon applications in sustainable construction with values ranged from 38.64 GPa (Mix 21) to 25.04 GPa (Mix 19) at 28 days. Stiffer mixes corresponded to denser matrices containing GGBFS and silica fume, whereas lower values were linked to weaker bonding and higher porosity.

To address the demands of the low-carbon era, this study proposed a solution by using eggshell powder (ESP), fly ash, and ground granulated blast furnace slag together with alkaline solution in the preparation of lightweight geopolymer foam concrete (LWGFC). The aim of this study is to investigate the influence of replacing precursor materials with 5–20% ESP on the expansion behavior, physical, mechanical characteristics, and thermal conductivity of LWGFC. Additionally, the study examines the effect of varying the silicate modulus (SiO₂/Na₂O ratios of 1.0, 1.25, and 1.5) on the properties of LWGFC. Incorporating ESP from 5% to 20% with a constant SiO₂/Na₂O ratio reduced the initial setting time, while a high SiO₂/Na₂O ratio controlled the setting time and expansion volume. The high SiO₂/Na₂O ratio decreased the porosity and enhanced the compressive strength of the LWGFC but increased the thermal conductivity. The inclusion of more than 10% ESP content negatively affected compressive strength; however, a high SiO₂/Na₂O ratio can mitigate this detrimental effect. The thermal conductivity of optimal-content ESP mixtures with a SiO₂/Na₂O ratio of 1.0 was about 0.84 W/m·K, which is 2.1% lower than mixtures with a ratio of 1.25 and 18.6% lower than those with a ratio of 1.5. High-content ESP mixtures had a density of 1707 kg/m³, 0.97 W/m·K, and a compressive strength of 18.9 MPa at a low SiO₂/Na₂O ratio. Finally, the inclusion of ESP in the LWGFC, along with the use of an appropriate silicate modulus, resulted in improved strength development while decreasing porosity.

Structural lightweight concrete is preferred over traditional concrete due to its ability to reduce the dead load, minimize the size of load-bearing structural members, and provide more economical solutions for foundation deteriorations. This research sheds light on sustainable lightweight concrete using waste crushed clay bricks (CCB) as a lightweight aggregate. To reduce micro-crack propagation of the developed concrete, two types of fiber were implemented and investigated. Steel fibers (SF) with amounts of 0.5% and 1.0% by volume of concrete, and polypropylene fibers (PPF) with amounts of 0.1% and 0.2% by volume of concrete, were employed. Five reinforced concrete beams were made and tested in order to precisely evaluate the structural behavior of the proposed lightweight CCB concrete. Additionally, ABAQUS software for nonlinear finite element analysis has been utilized to simulate the tested beams and compare the numerical model predictions with the experimental findings. The findings revealed that the addition of SF and PPF exhibited a notable influence on enhancing the mechanical characteristics of lightweight CCB concrete. Adding 0.2% PPF increased the ultimate load and deformation capacity at failure by approximately 16% and 24%, respectively. Furthermore, after 28 days, the addition of 0.5% and 1.0% SF enhanced the compressive strength by around 11.7% and 17.6%, respectively. Moreover, a significant level of consistency between the results obtained from the numerical model and the experimental findings was observed. In general, the use of SF and PPF in CCB concrete successfully produced high-quality lightweight concrete with interesting results for use in reinforced concrete beams.

In recent years, the presence of progressive collapse in tall buildings induced a catastrophic event which attracted the majority of the community’s attention. The purpose of this paper is to develop a 3D numerical analysis of tall building under column loss. A composite steel frame building with 25 stories with five spans in both directions is proposed. The building has 3 m story height and 8 m span in both directions. The building is designed through the commercial software SAP2000 software against wind loads based on Eurocode 1-2005. The focus here is to investigate various parametric studies under abrupt column loss of multi-story composite building. The effect of composite slab is considered with full composite action between beam and slab. The findings of a parametric formulation incorporating important parameters for the progressive collapse design technique are given and confirmed using nonlinear dynamic time history analyses. The assessment of results has been introduced based on deformation, axial force in columns, equivalent plastic strain, major moment and axial force in the considered beams above the column loss. Next, a probabilistic analysis has been performed to assess the behavior of composite steel buildings against column loss. The study investigates the critical column loss and pinpoints the location of the next critical column. The results show that the concrete grade, position of the removed column, beams cross-section, and place of bracings have a significant effect in the response of the building rather than the steel grade and bottom reinforcement density. The removal of exterior column has the significant increase of the axial force percentage by 111.4% for the corner column. The corner column removal gives the maximum equivalent plastic strain with a value of 0.00449. Furthermore, the results reveal the potential impact of uncertainty on the structural elements of the considered buildings through the progressive collapse analysis. The vertical displacement above the column is fitted with mean value of 0.0251387 m and with a coefficient of variation 0.01664.