Christina El Sawda

This study investigates the effect of mass-based replacement of natural coarse aggregate with electric arc furnace (EAF) slag on the performance of ordinary Portland cement (OPC) concrete. Replacement levels of 0%, 30%, 50%, and 100% were examined, with particular attention to the volumetric changes induced by the higher density of EAF slag, which leads to an increase in paste volume. Fresh, mechanical, durability-related, and microstructural properties were evaluated. Results show a continuous reduction in workability with increasing slag content, despite the increase in paste volume, indicating the dominant influence of aggregate morphology on rheological behavior. Mechanical performance exhibited a non-linear response. Within the tested series, the 50% replacement mixture showed the highest mean compressive and splitting tensile strengths; however, the compressive strength difference relative to the control mixture remained small and within typical experimental scatter. In contrast, water absorption decreased progressively, reflecting improved matrix densification. However, this densification did not translate into enhanced mechanical performance, highlighting a decoupling between durability-related indicators and strength. A screening-level CO₂ assessment further showed that reductions in aggregate-related emissions were offset by increased cement content associated with mass-based replacement. The results emphasize the importance of considering volumetric effects when interpreting the behavior and sustainability of slag-based concrete. Note: all strength comparisons are based on mean values from three-specimen sets without formal statistical testing and should be regarded as exploratory observations.

Background: Cement production is a significant source of global CO ₂ emissions, driving the need for sustainable alternatives in construction. Ground granulated blast-furnace slag (GGBS) has emerged as a promising supplementary cementitious material; however, its performance across wide replacement ranges and its combined environmental and economic implications remain insufficiently characterised, particularly in hot and arid climatic contexts such as the Gulf region. Methods: Nine mortar mixes incorporating GGBS as a partial replacement for ordinary Portland cement (OPC) were prepared at replacement levels ranging from 5% to 100%. Compressive and flexural strength were assessed at 7, 14, and 28 days of curing. Life cycle assessment (LCA) and life cycle cost (LCC) analyses were conducted to evaluate the environmental and economic performance of each mix over its service life. Results: Replacement levels between 20% and 30% yielded optimal compressive strength, surpassing the OPC control at 28 days. Higher replacement levels enhanced flexural strength, though the highest recorded values require further validation. LCA results confirmed a progressive reduction in CO ₂ emissions with increasing GGBS content, while LCC analysis demonstrated improved cost efficiency relative to the OPC reference. Discussion: A 30% GGBS replacement level is identified as the optimal balance between mechanical performance, environmental benefit, and economic efficiency. These findings support the adoption of GGBS-blended mortars as viable, sustainable alternatives to conventional OPC-based construction materials in the Gulf region and comparable climatic environments.

This study aims to utilize principal component analysis (PCA) to analyze the effects of various chemical components on the behavior of cementitious composites containing cellulose nanomater...

Les propriétés mécaniques d'un enrobé bitumineux dépendent souvent des caractéristiques de son mastic. Ce dernier comprend le bitume et de petites particules appelées fines. Une analyse des différentes échelles bitumineuses (mastic ou mortier) permet de prédire le comportement de l'enrobé. Cette thèse se concentre sur le calcul numérique et l'évaluation des propriétés mécaniques des matériaux bitumineux, à savoir le module complexe et la fatigue. L'objectif de cette étude est de valider une méthode numérique capable d'évaluer l'endommagement par fatigue via une approche multi-échelle hétérogène. La modélisation a été réalisée en utilisant la méthode des éléments finis (EF). Les modèles sont constitués d'un squelette granulaire élastique et d'une matrice viscoélastique. Le squelette granulaire a été généré dans le logiciel MOA (acronyme français pour random object modeler) en respectant une courbe granulométrique propre aux matériaux étudiés. Sous ABAQUS, un logiciel d'éléments finis, l'équation de fatigue a été appliquée aux modèles. Ensuite, l'endommagement par fatigue a été calculé et présenté sous forme de cartographies visuelles. En appliquant l'approche multi-échelle hétérogène, il a été possible de développer une nouvelle méthode numérique pour définir l'endommagement des mélanges bitumineux. Cette approche s'est avérée assez précise. Elle est basée sur l'analyse de l'accumulation du pourcentage de dommages dans le modèle. Les résultats ont montré que les valeurs obtenues numériquement sont similaires aux données expérimentales. Une erreur de moins de dix pour cent a été calculée en ce qui concerne l'endommagement par fatigue à l'échelle du mastic. Cependant, à l'échelle de l'asphalte, cette différence est plus importante en raison de nombreux phénomènes tels que l’enchevêtrement granulaire et la dissipation visqueuse.

Accurate prediction of the mechanical performance of fiber-reinforced cement mortars (FRCM) is challenging because fiber geometry and properties vary widely and interact with the cement matrix in a non-trivial way. In this study, we propose an interpretable, computationally light framework that combines principal component analysis (PCA) with multiple linear regression (MLR) to predict compressive strength (Cs) and flexural strength (Fs) from mix proportions and fiber parameters. The literature-based dataset of 52 mortar mixes reinforced with polypropylene, steel, coconut, date palm, and hemp fibers was compiled and analyzed, covering Cs = 4.4–78.6 MPa and Fs = 0.75–16.7 MPa, with fiber volume fraction V_f = 0–15% and fiber length F_l = 4.48–60 mm. PCA performed on the full dataset showed that PC1–PC2 explain 53.4% of the total variance; a targeted variable-selection strategy increased the captured variance to 73.0% for the subset used for regression model development. MLR models built using PC1 and PC2 achieved good accuracy in the low-to-mid strength range, while prediction errors increased for higher-strength mixes (approximately Cs ≳ 60 MPa and Fs ≳ 10 MPa). On an independent validation dataset (n = 10), the refined model achieved mean absolute percentage errors of 11.3% for Fs and 18.5% for Cs. The proposed PCA-MLR approach provides a transparent alternative to more complex data-driven predictors, and it can support preliminary screening and optimization of fiber-reinforced mortar designs for durable structural and repair applications.

Understanding how soil organic matter (SOM) responds to agricultural management at the molecular scale remains a central challenge, particularly in semi-arid Mediterranean systems where long-term monitoring is limited, and soils face marked seasonal fluctuations, salinity constraints, and sustained cultivation pressure. In this study, lignin and lipid biomarkers were combined to provide complementary views of SOM dynamics in the agricultural soils of Oued Rhiou (Algeria), enabling the simultaneous assessment of plant-derived inputs, microbial processing, and stabilization pathways under cultivation and subsequent rest periods. Depth-dependent patterns showed that lignin indicators responded strongly to shifts between crop residue inputs and root-derived material, while lipid proxies captured changes in microbial activity, biosynthesis, and OM stabilization. Surface soils exhibited enhanced microbial turnover during cultivation, whereas deeper layers were characterized by selective preservation of recalcitrant compounds. Principal Component Analysis (PCA) further highlighted these processes by distinguishing vegetation-driven variability from microbial reworking patterns, with subset analyses (lignin-only and lipid-only) providing clearer explanatory power than the combined dataset. Collectively, the findings underscore the importance of integrating rest periods into agricultural cycles to promote SOM stabilization, highlight the complementarity of lignin and lipid proxies for deciphering SOM transformation pathways, and offer molecular-level insights that can guide sustainable soil management strategies aimed at balancing productivity, soil resilience, and long-term carbon sequestration.

The demand for sustainable energy storage solutions has led to increased interest in biomass-derived carbon aerogels as electrode materials for supercapacitors. These materials offer a high surface area, tunable porosity, and excellent electrochemical properties while utilizing renewable and waste biomass sources. This study evaluates the electrochemical performance of various biomass-based carbon aerogels, including those derived from cellulose, lignin, chitosan, and biomass waste, to identify key factors influencing supercapacitor efficiency. Principal Component Analysis (PCA) is employed to systematically analyze the relationships between structural and electrochemical properties, such as the specific surface area, specific capacitance, capacity retention, rate capability, energy density, and power density. The PCA results indicate that the first two principal components (PC1 and PC2) explain 58.20% of the total variance, with capacity retention (26.22%), energy density (19.55%), and specific capacitance (18.48%) identified as the most critical quantitative factors influencing supercapacitor performance. Chitosan-derived carbon aerogels exhibit superior capacitance and energy density, with a specific capacitance reaching up to 1074 F/g and energy density of 40.18 Wh/kg, whereas lignin-based aerogels demonstrate a high structural stability and capacity retention (up to 97.4%). Biomass waste-derived aerogels, despite their lower performance (176–298.6 F/g capacitance, 81.6–91.7% retention), provide cost-effective and environmentally sustainable alternatives. This quantitative analysis offers valuable insights into the rational design of high-performance, biomass-based aerogels, contributing significantly to the development of sustainable energy storage technologies.