Yao, Z., J. Tong, J. Jiang, A. Mohamed Abdel Sattar, J. Constantino Gomes da Silva, S. Kumar, X. Wang, M. S. Abd-Elhady, J. Liu, M. Jin, et al., "Pyrolysis-gasification conversion of waste pharmaceutical blisters: Thermo-kinetic and thermodynamic study, fuel gas analysis and machine learning modeling", Chemical Engineering Science, vol. 300, pp. 120583, 2024. AbstractWebsite

It delved into the pyrolysis-gasification behavior of waste pharmaceutical blisters (WPBs), exploring both kinetics and thermodynamics, and employing machine learning modeling. The decomposition of WPBs occurred in three stages, with temperature intervals of 140–350, 350–500, and 500–900 °C, respectively. Cyclization/aromatization reactions were hindered, as indicated by mass spectrometric analysis, which revealed the main evolved products, including CxHy, CH3OH, CH4, and H2. Apparent activation energy values obtained from FWO, KAS, Friedman, Cai & Chen models were comparable, showing a decreasing trend ranging from 264.9 to 48.4 kJ mol−1 at α ≤ 0.70, followed by a subsequent increase to 283.1 kJ mol−1 at a conversion of 0.80. The D1 model was more reliable in describing the pyrolysis-gasification process of WPBs. Machine learning modeling results indicated that the ANN19 with a topology structure of 5 ∗ 15 ∗ 1 and genetic programming models showed superior performance in predicting TG data.

Wang, B., Z. Yao, S. Kumar, M. Salama Abdelhady Mohamed, A. Mohamed Abdel Sattar, N. Ortuño, X. Wang, and W. Qi, "Pyrolysis conversion of multi-layer packaging waste under a CO2 atmosphere: Thermo-kinetic study, evolved products analysis and artificial neural networks modeling", Chemical Engineering Science, vol. 300, pp. 120584, 2024. AbstractWebsite

Packaging waste such as beverage carton forms a significant part of municipal solid waste and its pyrolysis behavior, kinetics, and thermodynamics were studied. A four-stage decomposition process was revealed: dehydration below 200 ℃, paperboard degradation at 200–400 ℃, polyethylene devolatilization at 400–550 ℃, and inorganic decomposition at 550–900 ℃. The evolved products included furans and acetic acid during stage II, followed by the presence of 2-butene and 1-pentene in the subsequent stage. Apparent activation energy (Ea) were determined using model-free models, revealing a notable level of comparability among these results. The average Ea was 123.6 kJ/mol within α range of 0.10–0.60, increasing to 233.3 kJ/mol beyond that range. The most probable reaction mechanism was determined, with the one-dimensional model proving more reliable. An artificial neural network model was developed to predict the thermal degradation. The selected topology of 5*15*1 displayed a robust ability to predict the thermal data.

Sattar, A. M. A., A. N. Ghazal, M. Elhakeem, A. E. S. Ansary, and B. Gharabaghi, "Application of Machine Learning Coupled with Stochastic Numerical Analyses for Sizing Hybrid Surge Vessels on Low-Head Pumping Mains", water, vol. 15, issue 19, pp. 3525, 2023.
application/pdf iconwater-15-03525-v3.pdf
Sattar, A. M. A., A. N. Ghazal, M. Elhakeem, A. E. S. Ansary, and B. Gharabaghi, "Application of Machine Learning Coupled with Stochastic Numerical Analyses for Sizing Hybrid Surge Vessels on Low-Head Pumping Mains", water, vol. 15, issue 19, pp. 3525, 2023.
application/pdf iconwater-15-03525-v3.pdf
Aredah, A. S., O. F. Ertugrul, A. A. Sattar, H. Bonakdari, and B. Gharabaghi, "Extreme Learning Machine model for assessment of stream health using the Qualitative Habitat Evaluation Index", Water Supply, vol. 22, issue 5, pp. 5355 - 5375, 2022. Abstract
n/a
Diab, G., M. Elhakeem, and A. M. A. Sattar, "Performance assessment of lift-based turbine for small-scale power generation in water pipelines using OpenFOAM", Engineering Applications of Computational Fluid Mechanics, vol. 16, issue 1, pp. 536 - 550, 2022. Abstract
n/a
Kazemian-Kale-Kale, A., A. Gholami, M. Rezaie-Balf, A. Mosavi, A. A. Sattar, A. H. Azimi, B. Gharabaghi, and H. Bonakdari, "Uncertainty assessment of entropy-based circular channel shear stress prediction models using a novel method", Geosciences (Switzerland), vol. 11, issue 8, 2021. Abstract
n/a
Azari, A., M. Zeynoddin, I. Ebtehaj, A. M. A. Sattar, B. Gharabaghi, and H. Bonakdari, "Integrated preprocessing techniques with linear stochastic approaches in groundwater level forecasting", Acta Geophysica, vol. 69, issue 4, pp. 1395 - 1411, 2021. Abstract
n/a
Bonakdari, H., I. Ebtehaj, A. H. Azimi, P. Samui, A. A. Sattar, A. Jamali, S. H. A. Talesh, A. Mosavi, and B. Gharabaghi, "Pareto design of multiobjective evolutionary neuro-fuzzy system for predicting scour depth around bridge piers", Water Engineering Modeling and Mathematic Tools, pp. 491 - 517, 2021. Abstract
n/a
Bonakdari, H., F. Moradi, I. Ebtehaj, B. Gharabaghi, A. A. Sattar, A. H. Azimi, and A. Radecki-Pawlik, "A non-tuned machine learning technique for abutment scour depth in clear water condition", Water (Switzerland), vol. 12, no. 1, 2020. AbstractWebsite
n/a
Tourism