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Tadesse G. Wakjira ORCID

La bibliographie suivante contient toutes les publications répertoriées dans la base de données qui sont reliées à ce nom en tant qu'auteur, éditeur ou collaborateur.

  1. Wakjira, Tadesse G. / Shahria Alam, M. (2024): Performance-based seismic design of Ultra-High-Performance Concrete (UHPC) bridge columns with design example – Powered by explainable machine learning model. Dans: Engineering Structures, v. 314 (septembre 2024).

    https://doi.org/10.1016/j.engstruct.2024.118346

  2. Wakjira, Tadesse G. / Abushanab, Abdelrahman / Shahria Alam, M. (2024): Hybrid machine learning model and predictive equations for compressive stress-strain constitutive modelling of confined ultra-high-performance concrete (UHPC) with normal-strength steel and high-strength steel spirals. Dans: Engineering Structures, v. 304 (avril 2024).

    https://doi.org/10.1016/j.engstruct.2024.117633

  3. Dey, Ashish / Rumman, Rubaiya / Wakjira, Tadesse G. / Jindal, Ashish / Bediwy, Ahmed G. / Islam, M. Shahidul / Shahria Alam, M. / Al Martini, Samer / Sabouni, Reem (2024): Towards net-zero emission: A case study investigating sustainability potential of geopolymer concrete with recycled glass powder and gold mine tailings. Dans: Journal of Building Engineering, v. 86 (juin 2024).

    https://doi.org/10.1016/j.jobe.2024.108683

  4. Wakjira, Tadesse G. / Kutty, Adeeb A. / Shahria Alam, M. (2024): A novel framework for developing environmentally sustainable and cost-effective ultra-high-performance concrete (UHPC) using advanced machine learning and multi-objective optimization techniques. Dans: Construction and Building Materials, v. 416 (février 2024).

    https://doi.org/10.1016/j.conbuildmat.2024.135114

  5. Wakjira, Tadesse G. / Abushanab, Abdelrahman / Shahria Alam, M. / Alnahhal, Wael / Plevris, Vagelis (2024): Explainable machine learning-aided efficient prediction model and software tool for bond strength of concrete with corroded reinforcement. Dans: Structures, v. 59 (janvier 2024).

    https://doi.org/10.1016/j.istruc.2023.105693

  6. Al Martini, Samer / Sabouni, Reem / Khartabil, Ahmad / Wakjira, Tadesse G. / Shahria Alam, M. (2023): Development and strength prediction of sustainable concrete having binary and ternary cementitious blends and incorporating recycled aggregates from demolished UAE buildings: Experimental and machine learning-based studies. Dans: Construction and Building Materials, v. 380 (mai 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.131278

  7. Al-Hamrani, Abathar / Wakjira, Tadesse G. / Alnahhal, Wael / Ebead, Usama (2023): Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars. Dans: Composite Structures, v. 305 (février 2023).

    https://doi.org/10.1016/j.compstruct.2022.116473

  8. Wakjira, Tadesse G. / Rahmzadeh, Ahmad / Shahria Alam, M. / Tremblay, Robert (2022): Explainable machine learning based efficient prediction tool for lateral cyclic response of post-tensioned base rocking steel bridge piers. Dans: Structures, v. 44 (octobre 2022).

    https://doi.org/10.1016/j.istruc.2022.08.023

  9. Kennedy-Kuiper, Remy C. S. / Wakjira, Tadesse G. / Shahria Alam, M. (2022): Repair and Retrofit of RC Bridge Piers with Steel-Reinforced Grout Jackets: An Experimental Investigation. Dans: Journal of Bridge Engineering (ASCE), v. 27, n. 8 (août 2022).

    https://doi.org/10.1061/(asce)be.1943-5592.0001903

  10. Wakjira, Tadesse G. / Al-Hamrani, Abathar / Ebead, Usama / Alnahhal, Wael (2022): Shear Capacity Prediction of FRP-RC Beams Using Single and Ensenble ExPlainable Machine Learning Models. Dans: Composite Structures, v. 287 (mai 2022).

    https://doi.org/10.1016/j.compstruct.2022.115381

  11. Wakjira, Tadesse G. / Ibrahim, Mohamed / Ebead, Usama / Shahria Alam, M. (2022): Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM. Dans: Engineering Structures, v. 255 (mars 2022).

    https://doi.org/10.1016/j.engstruct.2022.113903

  12. Wakjira, Tadesse G. / Shahria Alam, M. / Ebead, Usama (2021): Plastic hinge length of rectangular RC columns using ensemble machine learning model. Dans: Engineering Structures, v. 244 (octobre 2021).

    https://doi.org/10.1016/j.engstruct.2021.112808

  13. Wakjira, Tadesse G. / Ebead, Usama (2019): A shear design model for RC beams strengthened with fabric reinforced cementitious matrix. Dans: Engineering Structures, v. 200 (décembre 2019).

    https://doi.org/10.1016/j.engstruct.2019.109698

  14. Wakjira, Tadesse G. / Ebead, Usama (2021): Strengthening of reinforced concrete beams in shear using different steel reinforced grout techniques. Dans: Structural Concrete, v. 22, n. 2 (avril 2021).

    https://doi.org/10.1002/suco.202000354

  15. Wakjira, Tadesse G. / Ebead, Usama (2018): FRCM/internal transverse shear reinforcement interaction in shear strengthened RC beams. Dans: Composite Structures, v. 201 (octobre 2018).

    https://doi.org/10.1016/j.compstruct.2018.06.034

  16. Wakjira, Tadesse G. / Nehdi, Moncef L. / Ebead, Usama (2020): Fractional factorial design model for seismic performance of RC bridge piers retrofitted with steel-reinforced polymer composites. Dans: Engineering Structures, v. 221 (octobre 2020).

    https://doi.org/10.1016/j.engstruct.2020.111100

  17. Wakjira, Tadesse G. / Ebead, Usama (2020): Shear span-to-depth ratio effect on steel reinforced grout strengthened reinforced concrete beams. Dans: Engineering Structures, v. 216 (août 2020).

    https://doi.org/10.1016/j.engstruct.2020.110737

  18. El-Sherif, HossamEldin / Wakjira, Tadesse G. / Ebead, Usama (2020): Flexural strengthening of reinforced concrete beams using hybrid near-surface embedded/externally bonded fabric-reinforced cementitious matrix. Dans: Construction and Building Materials, v. 238 (mars 2020).

    https://doi.org/10.1016/j.conbuildmat.2019.117748

  19. Wakjira, Tadesse G. / Ebead, Usama (2018): Hybrid NSE/EB technique for shear strengthening of reinforced concrete beams using FRCM: Experimental study. Dans: Construction and Building Materials, v. 164 (mars 2018).

    https://doi.org/10.1016/j.conbuildmat.2017.12.224

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