Afaf Chakir

This study investigates the physicomechanical, thermal, and structural behavior of polypropylene random copolymer (PPR) a new material reinforced with bamboo particles (BP) for potential use in PPR pipe formulations. Bamboo particles were incorporated at 2.5, 5, 7.5, and 10 wt.% after thermal drying and alkaline treatment using a 20 wt.% NaOH solution to improve compatibility with the polymer matrix. Mechanical testing, melt flow rate (MFR) and density measurements, differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR), and optical microscopy (OM) were conducted to evaluate the influence of particles addition and treatment. Treated particles significantly improved tensile strength and modulus while also affecting other characteristics, such as increasing viscosity (lower MFR) and decreasing the degree of crystallinity. FTIR and DSC confirmed chemical and thermal modifications following treatment, and OM revealed improved fiber dispersion. Overall, the incorporation of 10 wt.% treated bamboo particles led to a marked improvement in the mechanical performance of PPR, with increases of approximately 56.3% in tensile modulus, 24.3% in tensile strength, and 16.2% in elongation at break compared to virgin PPR, highlighting an effective reinforcement while preserving ductility.

This study presents an integrative experimental and statistical approach to investigate and predict cracking in CW617N brass inserts used in PPR fittings. Four production lots, including samples from customer complaints, were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy, optical microscopy, hardness testing, and X-ray fluorescence spectrometry to identify the metallurgical and mechanical factors driving intergranular fracture. Based on these analyses, a binary logistic regression model was developed using lead content, grain size, and hardness as explanatory variables. The model demonstrates statistically significant contributions of each factor and achieves high predictive performance, with an accuracy of 0.88, precision of 0.90, recall of 0.85, F1-score of 0.87, and a ROC-AUC of 0.90, highlighting its robustness. This framework effectively captures the complex interplay between lead segregation, grain coarsening, and hardness variations, enabling reliable quantitative prediction of crack formation. The combined methodology provides actionable insights for industrial quality control and process optimization while advancing the fundamental understanding of failure mechanisms in brass fittings.

Soil erosion is a major environmental concern, particularly in hydrologically unstable regions. Reliable prediction methods are essential for effective erosion risk assessment and mitigation. This study evaluates and compares two erosion prediction methodologies in the Beht watershed, Morocco:...

The alarming degradation of soils, particularly in the Moroccan Rif region, is the result of various forms of water erosion processes, leading to significant environmental and economic damage in the area. The Oued Lebene watershed is a sub-basin of the Sebou River, located in the central part of...

Intending to minimize the cost of production of pipes intended for construction and building activities and waste recycling, this research studies the physical and mechanical characteristics of high-performance polypropylene random (PPR), a new material extracted from a homopolymer polypropylene....