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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. / 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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

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