LSTM-based aerodynamic force modeling for unsteady flows around structures

Shijie Liu, Zhen Zhang, Xue Zhou and Qingkuan Liu

Abstract

The aerodynamic force is a significant component that influences the stability and safety of structures. It has unstable properties and depends on computer precision, making its long-term prediction challenging. Accurately estimating the aerodynamic traits of structures is critical for structural design and vibration control. This paper establishes an unsteady aerodynamic time series prediction model using Long Short-Term Memory (LSTM) network. The unsteady aerodynamic force under varied Reynolds number and angles of attack is predicted by the LSTM model. The input of the model is the aerodynamic coefficients of the 1 to n sample points and output is the aerodynamic coefficients of the n+1 sample point. The model is predicted by interpolation and extrapolation utilizing Unsteady Reynolds-average Navier-Stokes (URANS) simulation data of flow around a circular cylinder, square cylinder and airfoil. The results illustrate that the trajectories of the LSTM prediction results and URANS outcomes are largely consistent with time. The mean relative error between the forecast results and the original results is less than 6%. Therefore, our technique has a prospective application in unsteady aerodynamic force prediction of structures and can give technical assistance for engineering applications.

Key Words

angles of attack; deep learning; engineering structures; long short-term memory; Reynolds number; unsteady aerodynamic force

Address

Shijie Liu:School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China Zhen Zhang:1)School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China 2)State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures, Shijiazhuang Tiedao University, Shijiazhuang 050043, China 3)Innovation Center for Wind Engineering and Wind Energy Technology of Hebei Province, Shijiazhuang 050043, China Xue Zhou:School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China Qingkuan Liu:1)School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China 2)State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures, Shijiazhuang Tiedao University, Shijiazhuang 050043, China 3)Innovation Center for Wind Engineering and Wind Energy Technology of Hebei Province, Shijiazhuang 050043, China

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