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Teng Wu

Researcher at University at Buffalo

Publications -  89
Citations -  1864

Teng Wu is an academic researcher from University at Buffalo. The author has contributed to research in topics: Aerodynamics & Aeroelasticity. The author has an hindex of 19, co-authored 82 publications receiving 1102 citations. Previous affiliations of Teng Wu include Tongji University & State University of New York System.

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Recent developments of high-speed railway bridges in China

TL;DR: In this paper, the main technical standards of small-to medium-span HSR bridges are reviewed, where their comparison with the Japanese standard and International Union of Railway standards is highlighted.
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Modeling hysteretic nonlinear behavior of bridge aerodynamics via cellular automata nested neural network

TL;DR: In this paper, a new approach to model aerodynamic nonlinearities in the time domain utilizing an artificial neural network (ANN) framework with embedded cellular automata (CA) scheme has been developed.
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Measurements and analysis of non-stationary wind characteristics at Sutong Bridge in Typhoon Damrey

TL;DR: In this paper, the results of the data at the Sutong Bridge in the tropical storm reaffirm results from earlier studies and emphasize the need to incorporate non-stationary features of winds in the analysis and design of bridges from aerodynamic view point.
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Wind-induced effects on bluff bodies in turbulent flows: Nonstationary, non-Gaussian and nonlinear features

TL;DR: In this paper, the role of turbulence in bluff body aerodynamics and aeroelasticity is emphasized and its implications are delineated, as well as recent advances in analysis and identification tools, and modeling frameworks, which promise to offer better understanding of the underlying complexities associated with the aforementioned themes.
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Bridge aerodynamics and aeroelasticity: A comparison of modeling schemes

TL;DR: In this article, the authors compare and assess the efficacy of five analytical models available in the literature with a new model presented in this paper, and highlight the underlying role of each model in capturing the physics of bridge behavior under winds.