Open Access
Issue
E3S Web Conf.
Volume 336, 2022
The International Conference on Energy and Green Computing (ICEGC’2021)
Article Number 00004
Number of page(s) 7
DOI https://doi.org/10.1051/e3sconf/202233600004
Published online 17 January 2022
  1. A. Lakhdar, A. Moumen, L. Zahiri, M. Jammoukh, Kh Mansouri, Experimental and Numerical Study of the Mechanical Behavior of Bio-Loaded PVC Subjected to Aging, Adv. Sci. Technol. Eng. Syst. J, ASTESJ, 5, pp. 607–612, (2020). [Google Scholar]
  2. A. Lakhdar, A. Moumen, Kh. Mansouri, Study of The Mechanical Behavior of Bio Loaded Flexible Pvc by Coconut and Horn Fibers Subjected to Aging, International Journal on Technical and Physical Problems of Engineering, (IJTPE), Iss. 46, 13, No. 1, Mar. (2021) [Google Scholar]
  3. A. Moumen, M. Jammoukh, L. Zahiri, K. Mansouri, Numerical modeling of the thermo mechanical behavior of a polymer reinforced by horn fibers, International Journal of Advanced Trends in Computer Science and Engineering, ASTESJ, 9, 6541–6548, (2020) [Google Scholar]
  4. P. Marimuthu, C. Kumar, Finite element modelling to predict machining induced residual stresses in the end milling of hard to machine Ti6Al4V alloy, Periodicals of Engineering and Natural Sciences, 7, 1–11, (2019) [Google Scholar]
  5. Z. Cao, Y. Dan, Z. Xiong, C. Niu, X. Li, S. Qianand, J. Hu, Convolutional Neural Networks for Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix and Magpie Descriptors, Crystals, 9, 191, (2019) [Google Scholar]
  6. D.J. Scott, P.V. Coveney, J.A. Kilner, J.C.H. Rossiny, N.Mc N. Alford, Prediction of the functional properties of ceramic materials from composition using artificial neural networks, Journal of the European Ceramic Society, 27, 4425–4435, (2007) [Google Scholar]
  7. C. Yang, Y. Kimb, S. Ryu, G. X. Gua, Prediction of composite microstructure stress-strain curves using convolutional neural networks, Materials and Design, 189, (2020) [Google Scholar]
  8. Q. Sun, T. Ertekin, Screening and optimization of polymer flooding projects using artificial-neural-network (ANN) based proxies, J. Pet. Sci. Eng., 185, p. 106617, (2020) [Google Scholar]
  9. J. S. Chohan, Mechanical Strength Enhancement of 3D Printed Acrylonitrile Butadiene Styrene Polymer Components Using Neural Network Optimization Algorithm, Polymers, BASEL, 12, no. 10, p. 2250, (2020) [Google Scholar]
  10. A. Lakhdar, A. Moumen, K. Mansouri, Recycled PVC with chicken feathers as bio-load, IOP Conference Series Materials Science and Engineering, India, March (2021) [Google Scholar]
  11. A. Ansarullah, R. Ramli, A. Kusno, B. Baharuddin, N. Jamala, Utilization of waste of chicken feathers and waste of cardboard as the material of acoustic panel maker, Earth and Environmental Science, 1-8, (2018) [Google Scholar]
  12. I. Aranberri, S. Montes, I. Azcune, A. Rekondo, H-J. Grande, Fully Biodegradable Biocomposites with High Chicken Feather Content, Polymers, 9, 593, (2017) [Google Scholar]
  13. W.F. Schmidt, Innovative Feather Utilization Strategies, in Poultry Waste Management Conference, Springdale, Arkansas (1998) [Google Scholar]
  14. A. Lakhdar, M. Jammoukh, L. Zahiri, K. Mansouri, A. Moumen, B. Salhi, Numerical and Experimental Study of the Behavior of PVC Material Subjected to Aging, 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), IEEE: 1–6, (2020) [Google Scholar]
  15. A., Moumen, A., Lakhdar, A., Mansouri, K. Numerical study of the mechanical behavior of polyamide 66 reinforced by argan nut shell particles with the finite element method and the mori-tanaka model, Int. J. Adv. Trends Comput. Sci. Eng., 9, no. 5, pp. 7723–7730, (2020) [Google Scholar]
  16. J. Naveen, M. Jawaid, A. Vasanthanathan, M. Chandrasekar, Finite element analysis of natural fiber-reinforced polymer composites. in Modelling of Damage Processes in Biocomposites, Fibre-Reinforced Composites and Hybrid Composites, Elsevier, pp. 153–170, (2019) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.