Wave responses in seismic FGM concrete nanobeam using deep neural network

Yong Huang, Bo Zhang, Chunwang Sun, Mostafa Habibi, Nejib Ghazouani and Mohamed Hechmi El Ouni

Abstract

In the current study, we investigate the vibration of a nano-scale beam structure composed of bi-directionally functionally graded concrete. We employ a dual approach, combining mathematical structural modeling with deep neural network analysis, to determine the natural frequency of the nanobeam. The concrete is assumed to be graded along the beam's axis and transverse direction, following a power-law model. We utilize Timoshenko beam theory (TBT) and nonlocal stress-strain gradient relations to describe the nanobeam's displacement field. Hamilton's principle is used to account for external forces and boundary conditions. A deep neural network is trained to predict the natural frequency with varying error margins. The governing equations are solved using the differential quadrature numerical method, and the results are validated against existing literature. This work introduces novelties in three key areas: 1) a model for bi-FG concrete nanobeams under in-plane loading, 2).

Key Words

bi-directional FG concrete nanobeam; differential quadrature method; nonlocal strain gradient theory; physics-informed neural networks; vibrational analysis

Address

Yong Huang: State Key Laboratory of Chemistry and Utilization of Carbon Based Energy Resources; College of Chemistry, Xinjiang University, Urumqi 830017, Xinjiang, PR China/ College of Ecology and Environment, Xinjiang University, Urumqi 830017, Xinjiang, PR China/ College of Civil Engineering and Architecture, Xinjiang University, Urumqi 830017, Xinjiang, PR China/ Xinjiang production and Construction Corps Construction Engineering (Group) Co., Ltd., Urumqi 830000, Xinjiang, PR China/ Chengdu University of Technology, Chengdu 610000, Sichuan, PR China/ Transpotation Industry Highway Maintenance Collaborative Innovation Platform under Complicated Conditions of Western China, Urumqi 830000, Xinjiang, PR China/ Road Maintenance Professional Committee of Zhongguancun Zhongke Highway Maintenance Technology Innovation Alliance, Urumqi 830000, Xinjiang, PR China Bo Zhang: School of computer science, Wuhan Donghu College, Wuhan 430212, Hubei, China Chunwang Sun: College of Ecology and Environment, Xinjiang University, Urumqi 830017, Xinjiang, PR China/ College of Civil Engineering and Architecture, Xinjiang University, Urumqi 830017, Xinjiang, PR China/ Xinjiang production and Construction Corps Construction Engineering (Group) Co., Ltd., Urumqi 830000, Xinjiang, PR China Mostafa Habibi: Facultad de Arquitectura y Urbanismo, Universidad UTE, Calle Rumipamba S/N y Bourgeois, 170147, Quito, Ecuador/ Department of Biomaterials, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, 600077, India/ Department of Mechanical Engineering, Faculty of Engineering, Haliç University, Istanbul, Turkey Nejib Ghazouani: Mining Research Center, Northern Border university, Arar 73222, Arar, Saudi Arabia Mohamed Hechmi El Ouni: Department of Civil Engineering, College of Engineering, King Khalid University, PO Box 394, Abha 61411 Kingdom of Saudi Arabia/ Center for Engineering and Technology Innovations, King Khalid University, Abha 61421, Saudi Arabia

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