0
  • DE
  • EN
  • FR
  • Internationale Datenbank und Galerie für Ingenieurbauwerke

Anzeige

M. Z. Naser ORCID

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Naser, M. Z. / Kodur, V. K. R. (2017): Comparative fire behavior of composite girders under flexural and shear loading. In: Thin-Walled Structures, v. 116 (Juli 2017).

    https://doi.org/10.1016/j.tws.2017.03.003

  2. Naser, M. Z. (2024): Causal diagrams for civil and structural engineers. In: Structures, v. 63 (Mai 2024).

    https://doi.org/10.1016/j.istruc.2024.106398

  3. Naser, M. Z. / Ross, Brandon / Ogle, Jennifer / Kodur, Venkatesh / Hawileh, Rami / Abdalla, Jamal / Thai, Huu-Tai (2024): Evaluating the Performance of Artificial Intelligence Chatbots and Large Language Models in the FE and PE Structural Exams. In: Practice Periodical on Structural Design and Construction, v. 29, n. 2 (Mai 2024).

    https://doi.org/10.1061/ppscfx.sceng-1369

  4. Hostetter, Haley / Naser, M. Z. / Randall, Kristina / Murray-Tuite, Pamela (2024): Evacuation preparedness and intellectual disability: Insights from a university fire drill. In: Journal of Building Engineering, v. 84 (Mai 2024).

    https://doi.org/10.1016/j.jobe.2024.108578

  5. Assad, Maha / Hawileh, Rami / Karaki, Ghada / Abdalla, Jamal / Naser, M. Z.: Assessment of critical parameters affecting the behaviour of bearing reinforced concrete walls under fire exposure. In: Journal of Structural Fire Engineering.

    https://doi.org/10.1108/jsfe-07-2023-0029

  6. Hostetter, Haley / Naser, M. Z. (2023): Architectural and Structural Engineering of Nineteenth- and Twentieth-Century Mental Health Institutions and Psychiatric Hospitals with Respect to Fire Causes and Mitigation Strategies. In: Journal of Architectural Engineering (ASCE), v. 29, n. 4 (Dezember 2023).

    https://doi.org/10.1061/jaeied.aeeng-1643

  7. Naser, M. Z. / Ozyuksel Ciftcioglu, Aybike (2023): Causal discovery and inference for evaluating fire resistance of structural members through causal learning and domain knowledge. In: Structural Concrete, v. 24, n. 3 (April 2023).

    https://doi.org/10.1002/suco.202200525

  8. Guzmán-Torres, J. A. / Domínguez-Mota, F. J. / Martinez-Molina, W. / Naser, M. Z. / Tinoco-Guerrero, G. / Tinoco-Ruíz, J. G. (2023): Damage detection on steel-reinforced concrete produced by corrosion via YOLOv3: A detailed guide. In: Frontiers in Built Environment, v. 9 (Februar 2023).

    https://doi.org/10.3389/fbuil.2023.1144606

  9. Zhou, Huanting / Li, Huaidong / Qin, Han / Liang, Tianfu / Naser, M. Z. (2023): Examining fire response of unilaterally concrete-reinforced web prestressed composite beams with corrugated webs. In: Engineering Structures, v. 274 (Januar 2023).

    https://doi.org/10.1016/j.engstruct.2022.115194

  10. Naser, M. Z. (2022): CLEMSON: An Automated Machine-Learning Virtual Assistant for Accelerated, Simulation-Free, Transparent, Reduced-Order, and Inference-Based Reconstruction of Fire Response of Structural Members. In: Journal of Structural Engineering (ASCE), v. 148, n. 9 (September 2022).

    https://doi.org/10.1061/(asce)st.1943-541x.0003399

  11. Hostetter, Haley / Naser, M. Z. (2022): Characterizing disability in fire evacuation: A progressive review. In: Journal of Building Engineering, v. 53 (August 2022).

    https://doi.org/10.1016/j.jobe.2022.104573

  12. Diana Andrushia, A. / Anand, N. / Neebha, T. Mary / Naser, M. Z. / Lublóy, Éva (2022): Autonomous detection of concrete damage under fire conditions. In: Automation in Construction, v. 140 (August 2022).

    https://doi.org/10.1016/j.autcon.2022.104364

  13. Mathews, Mervin Ealiyas / Kiran, Tattukolla / Anand, N. / Lublóy, Éva / Naser, M. Z. / Prince Arulraj, G. (2022): Effect of protective coating on axial resistance and residual capacity of self-compacting concrete columns exposed to standard fire. In: Engineering Structures, v. 264 (August 2022).

    https://doi.org/10.1016/j.engstruct.2022.114444

  14. Naser, M. Z. (2022): A Faculty’s Perspective on Infusing Artificial Intelligence into Civil Engineering Education. In: Journal of Civil Engineering Education, v. 148, n. 4 (Oktober 2022).

    https://doi.org/10.1061/(asce)ei.2643-9115.0000065

  15. Guzmán-Torres, José A. / Naser, M. Z. / Domínguez-Mota, Francisco J. (2022): Effective medium crack classification on laboratory concrete specimens via competitive machine learning. In: Structures, v. 37 (März 2022).

    https://doi.org/10.1016/j.istruc.2022.01.061

  16. Naser, M. Z. / Kodur, V. K. (2022): Explainable machine learning using real, synthetic and augmented fire tests to predict fire resistance and spalling of RC columns. In: Engineering Structures, v. 253 (Februar 2022).

    https://doi.org/10.1016/j.engstruct.2021.113824

  17. Degtyarev, V. V. / Naser, M. Z. (2021): Boosting machines for predicting shear strength of CFS channels with staggered web perforations. In: Structures, v. 34 (Dezember 2021).

    https://doi.org/10.1016/j.istruc.2021.09.060

  18. Zarringol, Mohammadreza / Thai, Huu-Tai / Naser, M. Z. (2021): Application of machine learning models for designing CFCFST columns. In: Journal of Constructional Steel Research, v. 185 (Oktober 2021).

    https://doi.org/10.1016/j.jcsr.2021.106856

  19. Naser, M. Z. (2021): An engineer's guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating causality, forced goodness, and the false perception of inference. In: Automation in Construction, v. 129 (September 2021).

    https://doi.org/10.1016/j.autcon.2021.103821

  20. Naser, M. Z. / Thai, Son / Thai, Huu-Tai (2021): Evaluating structural response of concrete-filled steel tubular columns through machine learning. In: Journal of Building Engineering, v. 34 (Februar 2021).

    https://doi.org/10.1016/j.jobe.2020.101888

  21. Mhanna, Haya H. / Hawileh, Rami A. / Abuzaid, Wael / Naser, M. Z. / Abdalla, Jamal A. (2020): Experimental Investigation and Modeling of the Thermal Effect on the Mechanical Properties of Polyethylene-Terephthalate FRP Laminates. In: Journal of Materials in Civil Engineering (ASCE), v. 32, n. 10 (Oktober 2020).

    https://doi.org/10.1061/(asce)mt.1943-5533.0003389

  22. Naser, M. Z. (2020): Autonomous Fire Resistance Evaluation. In: Journal of Structural Engineering (ASCE), v. 146, n. 6 (Juni 2020).

    https://doi.org/10.1061/(asce)st.1943-541x.0002641

  23. Naser, M. Z. / Kodur, V. K. R. (2016): Factors governing onset of local instabilities in fire exposed steel beams. In: Thin-Walled Structures, v. 98 (Januar 2016).

    https://doi.org/10.1016/j.tws.2015.04.005

  24. Kodur, V. K. R. / Naser, M. Z. (2015): Effect of local instability on capacity of steel beams exposed to fire. In: Journal of Constructional Steel Research, v. 111 (August 2015).

    https://doi.org/10.1016/j.jcsr.2015.03.015

  25. Kodur, V. K. R. / Naser, M. Z. (2014): Effect of shear on fire response of steel beams. In: Journal of Constructional Steel Research, v. 97 (Juni 2014).

    https://doi.org/10.1016/j.jcsr.2014.01.018

  26. Kodur, V. K. R. / Naser, M. Z. (2019): Designing steel bridges for fire safety. In: Journal of Constructional Steel Research, v. 156 (Mai 2019).

    https://doi.org/10.1016/j.jcsr.2019.01.020

  27. Kodur, V. K. R. / Naser, M. Z. (2018): Approach for shear capacity evaluation of fire exposed steel and composite beams. In: Journal of Constructional Steel Research, v. 141 (Februar 2018).

    https://doi.org/10.1016/j.jcsr.2017.11.011

  28. Naser, M. Z. (2019): Autonomous and resilient infrastructure with cognitive and self-deployable load-bearing structural components. In: Automation in Construction, v. 99 (März 2019).

    https://doi.org/10.1016/j.autcon.2018.11.032

  29. Naser, M. Z. / Kodur, V. K. R. (2018): Cognitive infrastructure - a modern concept for resilient performance under extreme events. In: Automation in Construction, v. 90 (Juni 2018).

    https://doi.org/10.1016/j.autcon.2018.03.004

  30. Naser, M. Z. (2018): Deriving temperature-dependent material models for structural steel through artificial intelligence. In: Construction and Building Materials, v. 191 (Dezember 2018).

    https://doi.org/10.1016/j.conbuildmat.2018.09.186

Eine Veröffentlichung suchen...

Nur verfügbar mit
Mein Structurae

Volltext
Structurae kooperiert mit
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine