Liste des publications de "Snaiki, Reda"

Allard, Laurent et Snaiki, Reda. 2024. « Buffeting response of a long-suspension bridge considering the effects of a changing climate ». In Proceedings of the Canadian Society for Civil Engineering Annual Conference 2023, Volume 10 : Structures Track (Moncton, NB, Canada, May 24-27, 2023) Coll. « Lecture Notes in Civil Engineering », vol. 504. pp. 225-236. Springer Science and Business Media Deutschland GmbH.

Allard, Laurent et Snaiki, Reda. 2025. « Buffeting-induced fatigue damage assessment of a long-span bridge under a changing climate scenario ». Journal of Bridge Engineering, vol. 30, nº 3.

Jard, Timothé et Snaiki, Reda. 2025. « Real-time dynamic layout optimization for floating offshore wind farm control ». Ocean Engineering, vol. 316.

Jard, Timothé et Snaiki, Reda. 2023. « Real-time repositioning of floating wind turbines using model predictive control for position and power regulation ». Wind, vol. 3, nº 2. pp. 131-150.
Compte des citations dans Scopus : 10.

Kijewski-Correa, Tracy, Taflanidis, Alexandros, Vardeman, Charles II, Sweet, James, Zhang, Jize, Snaiki, Reda, Wu, Teng, Silver, Zachariah et Kennedy, Andrew. 2020. « Geospatial environments for hurricane risk assessment : Applications to situational awareness and resilience planning in New Jersey ». Frontiers in Built Environment, vol. 6.
Compte des citations dans Scopus : 28.

Li, S., Snaiki, Reda et Wu, Teng. 2020. « Active simulation of transient wind field in a multiple-fan wind tunnel via deep reinforcement learning ». Communication lors de la conférence : Engineering Mechanics Institute Conference (New York City, NY, USA, May 26-29, 2020).

Li, Shaopeng, Snaiki, Reda et Wu, Teng. 2021. « A knowledge-enhanced deep reinforcement learning-based shape optimizer for aerodynamic mitigation of wind-sensitive structures ». Computer-Aided Civil and Infrastructure Engineering, vol. 36, nº 6. pp. 733-746.
Compte des citations dans Scopus : 53.

Li, Shaopeng, Snaiki, Reda et Wu, Teng. 2021. « Active simulation of transient wind field in a multiple-fan wind tunnel via deep reinforcement learning ». Journal of Engineering Mechanics, vol. 147, nº 9.
Compte des citations dans Scopus : 21.

Naeini, Saeed Saviz et Snaiki, Reda. 2023. « Machine learning approximation for rapid prediction of high-dimensional storm surge and wave responses ». In Proceedings of the Canadian Society of Civil Engineering Annual Conference (Whistler, BC, Canada, May 25-28, 2022) Coll. « Lecture Notes in Civil Engineering », vol. 363. pp. 701-710. Springer.
Compte des citations dans Scopus : 1.

Naeini, Saeed Saviz et Snaiki, Reda. 2024. « Rapid prediction of storm wave run-up using a hybrid physics-informed machine learning ». In Proceedings of the Canadian Society for Civil Engineering Annual Conference 2023, Volume 9, Hydrotechnical Track (Moncton, NB, Canada, May 24-27, 2023) Coll. « Lecture notes in civil engineering », vol. 503. pp. 179-190. Springer.

Saviz Naeini, Saeed et Snaiki, Reda. 2024. « A novel hybrid machine learning model for rapid assessment of wave and storm surge responses over an extended coastal region ». Coastal Engineering, vol. 190.
Compte des citations dans Scopus : 6.

Saviz Naeini, Saeed et Snaiki, Reda. 2024. « A physics-informed machine learning model for time-dependent wave runup prediction ». Ocean Engineering, vol. 295.
Compte des citations dans Scopus : 4.

Shabani, Mehdi, Jamali, Abdeslam, Snaiki, Reda et Rahem, Ahmed. 2022. « Prediction of ice accretion on transmission lines using hybrid particle swarm optimization-based artificial neural networks ». In Proceedings of the International Workshop on Atmospheric Icing of Structures (IWAIS) (Montreal, QC, Canada - En ligne, June 20-23, 2022)

Snaiki, Reda. 2024. « Performance-based ice engineering framework: A data-driven multi-scale approach ». Cold Regions Science and Technology, vol. 224.
Compte des citations dans Scopus : 3.

Snaiki, Reda, Jamali, Abdeslam, Rahem, Ahmed, Shabani, Mehdi et Barjenbruch, Brian L.. 2024. « A metaheuristic-optimization-based neural network for icing prediction on transmission lines ». Cold Regions Science and Technology, vol. 224.
Compte des citations dans Scopus : 2.

Snaiki, Reda et Makki, Seyedali. 2024. « A new analytical wind turbine wake model considering the effects of coriolis force and yawed conditions ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 250.
Compte des citations dans Scopus : 3.

Snaiki, Reda et Mirfakhar, Seyedeh Fatemeh. 2024. « Multiresolution dynamic mode decomposition approach for wind pressure analysis and reconstruction around buildings ». Computer-Aided Civil and Infrastructure Engineering.
Compte des citations dans Scopus : 1. (Sous presse)

Snaiki, Reda et Parida, Siddharth S.. 2023. « A data-driven physics-informed stochastic framework for hurricane-induced risk estimation of transmission tower-line systems under a changing climate ». Engineering Structures, vol. 280.
Compte des citations dans Scopus : 13.

Snaiki, Reda et Parida, Siddharth S.. 2023. « Climate change effects on loss assessment and mitigation of residential buildings due to hurricane wind ». Journal of Building Engineering, vol. 69.
Compte des citations dans Scopus : 9.

Snaiki, Reda et Wu, Teng. 2019. « A knowledge-enhanced deep learning for simulation of idealized storm surge ». Communication lors de la conférence : Engineering Mechanics Institute Conference (EMI) (Pasadena, CA, USA, Sept. 01-06, 2019).

Snaiki, Reda et Wu, Teng. 2017. « A linear height-resolving wind field model for tropical cyclone boundary layer ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 171. pp. 248-260.
Compte des citations dans Scopus : 46.

Snaiki, Reda et Wu, Teng. 2018. « A new boundary layer wind field model for landfalling hurricanes ». Affiche présentée lors de la conférence : 10th International Conference on Urban Climate / 14th Symposium on the Urban Environment (New York City, NY, USA, Aug. 06-10, 2018).

Snaiki, Reda et Wu, Teng. 2018. « A semi-empirical model for mean wind velocity profile of landfalling hurricane boundary layers ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 180. pp. 249-261.
Compte des citations dans Scopus : 39.

Snaiki, Reda et Wu, Teng. 2016. « A simplified analytical wind‐field model for hurricane boundary layer ». Communication lors de la conférence : Engineering Mechanics Institute Conference (EMI) and the Probabilistic Mechanics & Reliability Conference (PMC) (Nashville, TN, USA, May 22-25, 2016).

Snaiki, Reda et Wu, Teng. 2019. « A simplified dynamic system for estimating hurricane supergradient winds ». In Proceedings of 15th International Conference on Wind Engineering (ICWE15) (Beijing, China, Sept. 01-06, 2019) International Association for Wind Engineering.

Snaiki, Reda et Wu, Teng. 2017. « A theoretical model for rapid estimates of rainfall during tropical cyclones ». In 13th Americas Conference on Wind Engineering (ACWE) (Gainesville, FL, USA, May 21-24, 2017) Americas Conference on Wind Engineering.

Snaiki, Reda et Wu, Teng. 2018. « An analytical framework for rapid estimate of rain rate during tropical cyclones ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 174. pp. 50-60.
Compte des citations dans Scopus : 12.

Snaiki, Reda et Wu, Teng. 2020. « An analytical model for rapid estimation of hurricane supergradient winds ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 201.
Compte des citations dans Scopus : 13.

Snaiki, Reda et Wu, Teng. 2018. « An improved methodology for risk assessment of tropical cyclones under changing climate ». In 33rd Conference on Hurricanes and Tropical Meteorology (Ponte Vedra, FL, USA, Apr. 16-20, 2018) American Meteorological Society.

Snaiki, Reda et Wu, Teng. 2017. « Dynamic interaction of wind and rain fields in the boundary layer of a tropical cyclone ». Communication lors de la conférence : Engineering Mechanics Institute Conference (EMI) (San Diego, CA, USA, June 04-07, 2017).

Snaiki, Reda et Wu, Teng. 2020. « Hurricane hazard assessment along the United States northeastern coast : Surface wind and rain fields under changing climate ». Frontiers in Built Environment, vol. 6.
Compte des citations dans Scopus : 12.

Snaiki, Reda et Wu, Teng. 2021. « Hurricane risk assessment of offshore wind turbines under changing climate ». In IABSE Congress : Structural Engineering for Future Societal Needs (Ghent, Belgium, Sept. 22-24, 2021) pp. 241-248. International Association for Bridge and Structural Engineering.

Snaiki, Reda et Wu, Teng. 2020. « Hurricane wind and storm surge effects on coastal bridges under a changing climate ». Affiche numéro 20-04086 présentée lors de la conférence : Transportation Research Board (TRB) 99th Annual Meeting (Washington D.C., USA, Jan. 12-16, 2020).

Snaiki, Reda et Wu, Teng. 2019. « Knowledge-enhanced deep learning for simulation of extratropical cyclone wind risk ». In 15th International Conference on Wind Engineering (ICWE15) (Beijing, China, Sept. 01-06, 2019) International Association for Wind Engineering.

Snaiki, Reda et Wu, Teng. 2022. « Knowledge-enhanced deep learning for simulation of extratropical cyclone wind risk ». Atmosphere, vol. 13, nº 5.
Compte des citations dans Scopus : 8.

Snaiki, Reda et Wu, Teng. 2019. « Knowledge-enhanced deep learning for simulation of tropical cyclone boundary layer winds ». In Proceedings of 15th International Conference on Wind Engineering (ICWE15) (Beijing, China, Sept. 01-06, 2019) International Association for Wind Engineering.
Compte des citations dans Scopus : 52.

Snaiki, Reda et Wu, Teng. 2019. « Knowledge-enhanced deep learning for simulation of tropical cyclone boundary-layer winds ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 194.
Compte des citations dans Scopus : 52.

Snaiki, Reda et Wu, Teng. 2019. « Modeling rain-induced effects on boundary-layer wind field of tropical cyclones ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 194.
Compte des citations dans Scopus : 4.

Snaiki, Reda et Wu, Teng. 2017. « Modeling tropical cyclone boundary layer: Height-resolving pressure and wind fields ». Journal of Wind Engineering and Industrial Aerodynamics, vol. 170. pp. 18-27.
Compte des citations dans Scopus : 37.

Snaiki, Reda et Wu, Teng. 2020. « Revisiting hurricane track model for wind risk assessment ». Structural Safety, vol. 87.
Compte des citations dans Scopus : 36.

Snaiki, Reda et Wu, Teng. 2016. « Temperature and moisture effects on the hurricane wind field based on a simplified model ». Communication lors de la conférence : Engineering Mechanics Institute Conference (EMI) and the Probabilistic Mechanics & Reliability Conference (PMC) (Nashville, TN, USA, May 22-25, 2016).

Snaiki, Reda et Wu, Teng. 2016. « Temperature and moisture effects on the tropical cyclone boundary layer: Pressure and wind fields ». In Proceedings of 8th International Colloquium on Bluff-Body Aerodynamics and its Application (BBAAVIII) (Boston, MA, USA, June 07-11, 2016) International Association for Wind Engineering ; Northeastern University.

Snaiki, Reda, Wu, Teng, Whittaker, Andrew S. et Atkinson, Joseph F.. 2020. « Hurricane wind and storm surge effects on coastal bridges under a changing climate ». Transportation Research Record, vol. 2674, nº 6. pp. 23-32.
Compte des citations dans Scopus : 31.

Wu, Teng et Snaiki, Reda. 2022. « Applications of machine learning to wind engineering ». Frontiers in Built Environment, vol. 8.
Compte des citations dans Scopus : 40.