Department of Mathematics

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Browsing Department of Mathematics by Author "Belaadi, Ahmed"

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    Forecasting the thermal degradation depending on the kinetics of dracaena Draco lignocellulosic fibers using an artificial neural network
    (Journal of Natural Fibers;Taylor &Francis, 2025-07-17) Hadou, Abdelwaheb; Belaadi, Ahmed; Ghernaout, Djamel; Mukalazi, Herbert
    In order to forecast the thermal degradation of Dracaena draco plant fibers (DDFs) using thermogravimetric analysis (TGA) at heating rates ranging from 5 to 30°C/min, this study employed artificial neural networks (ANNs). Hemicellulose, cellulose, and lignin break-down were represented by the three different degradation stages that were seen. The enhanced ANN27 model successfully captured pyrolysis behavior and degradation patterns, achieving a high prediction accuracy (R2 = 0.99966). The model performed well at lower heating rates (5 and 10°C/min), but because of bias and heteroscedasticity, adjustments are required at higher rates (15–30°C/min). In contrast to the experimental averages of 131.244 kJ/mol, 109.269 kJ/mol, and 131.694 kJ/mol, respectively, kinetic analysis showed that the ANN27-predicted activation energies (Ea) were 133.420 kJ/mol (KAS), 53.692 kJ/mol (FWO), and 133.784 kJ/mol (STR). Without requiring a lot of testing, our ANN method provides insights into DDF thermal behavior and optimizes processing settings by properly forecasting degradation curves
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    Quality evaluation and predictive analysis of drilled holes in jute/ palm/polyester hybrid bio-composites using CMM and ANN techniques
    (Journal of Natural Fibers, 2025-04-26) Amroune, Salah; Elhadi, Abdelmalek; Slamani, Mohamed; Arslane, Mustapha; Belaadi, Ahmed; Abdullah, Mahmood M. S.; Al-Lohedan, Hamad A.; Bidi, Tarek; Mukalazi, Herbert; Al-Khawlani, Amar
    In this study, the evaluation of 75 holes drilled in a hybrid bio-composite jute/palm/polyester plate and controlled by a coordinate measuring machine (CMM) is essential to ensure the quality, dimensional precision, and geometric conformity of the plate. This rigorous process is necessary to meet industrial standards for circularity and cylindricity, which are essential criteria for high-performance applications. Additionally, the integration of artificial neural network (ANN) techniques has revolutionized this approach by enabling precise predictions of key parameters such as delamination, circularity, and cylindricity. In this study, the ANN was trained with 52 samples (70%), while 8 samples (10%) were used for validation and 15 others (20%) for testing at different stages. The results show the influence of feed rate on the delamination factor (Fd) (R2 = 0.98), circularity error (R2 = 0.99), and cylindricity error (R2 = 0.98). This predictive approach significantly improves the reliability and efficiency of the evaluation process.
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    Sustainable renewable biofuel production toward pyrolysis of fibers biowaste Agave Americana L. and thermodynamics mechanisms kinetic parameters triplet assessment
    (Journal of Natural Fibres, 2025-07-26) Lalaymiaa, Imen; Belaadi, Ahmed; Alshahranib, Hassan; Ghernaoutc, Djamel; Mukalazie, Herbert
    derived from the flower stalk of Agave americana waste (FSSAW), aiming to assess their suitability for bioenergy applications. Non-isothermal thermogravimetric analysis (TGA) was conducted at heating rates of 30, 40, and 50 °C/min. Kinetic modeling using the Coats – Redfern method evaluated 36 solid-state reaction models to determine the activation energy-Ea and pre-exponential factor (lnA). The highest Ea was observed for Model M22, increasing from 218.87 kJ/mol at 30 °C/min to 252.73 kJ/mol at 50 °C/min, while the lowest Ea, 4.22 kJ/mol, was recorded for Model M19. These results indicate the presence of both complex and simple reaction mechanisms, with a general increase in Ea at higher heating rates, consistent with the kinetic compensation effect. Thermodynamic analysis revealed a maximum enthalpy change (ΔH) of 249.65 kJ/mol, a maximum Gibbs free energy change (ΔG) of 390.81 kJ/mol, and a minimum entropy change (ΔS) of −0.31 kJ/mol·K, confirming that the pyrolysis process is endothermic and non-spontaneous, leading to a more ordered transition state. Criado’s master plot technique further validated Model M16 (random nucleation and growth) as the most representative mechanism during early decomposition stages. However, deviations at higher conversions suggest the occurrence of multi-step processes, including diffusion and char formation.