A neural network-assisted 3D theoretical thermoelastic solution for laminated liquid crystal elastomer plate used in restoring cardiac mechanical function. (December 2022)

• Record Type: Journal Article
• Authors: Wang, Jue; Yuan, Weiyi; Li, Zichuan; Trofimov, Yuri; Lishik, Sergey; Fan, Jiajie
• Is Part Of: Journal of the mechanical behavior of biomedical materials. Volume 136(2022)
• Publication Date: 2022-12
• Subjects: Liquid crystal elastomer -- Laminated plate -- Thermoelastic theory -- Exact solution -- Neural network; Biomedical materials -- Periodicals; Biomedical materials -- Mechanical properties -- Periodicals; Biomedical materials; Biomedical materials -- Mechanical properties; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.jmbbm.2022.105478
• Languages: English
• ISSNs: 1751-6161

Abstract

Abstract: Some atrial contractile assist devices applied on the heart surface can be regarded as a laminated Liquid crystal elastomer (LCE) plate under steady temperature loads and a contact mechanical force. An exact solution for the deformation of the laminated LCE plate under combined thermal and mechanical loads is derived by solving the three-dimensional (3D) equilibrium equations including heat conduction and thermoelastic theory. The validity of mathematical formula and computer programming is proved by convergence and comparison examples with finite element method (FEM). In order to simplify the complex calculation of exact solution, a back propagation neural network (BPNN) is further trained with a database containing 9504 sets of thermo-mechanical load conditions and their corresponding deformation which is solved by the exact solutions. Then the deformations of LCE plate subject to combined thermo-mechanical load can be predicted by this BP neural network instead of complex numerical calculation. Moreover, it is also applied to inverse the contact mechanical force at the bottom surface of LCE plate with a given deformation and temperature conditions. The results show that: (1) The results from the exact theoretical solution are in consistence with that from FEM but have a higher computational efficiency and stability; (2) The deformation of the laminated plate is more sensitive to the layered thickness of LCE than the variation of the temperature; (3) 3-D elasticity solutions of a laminated LCE plate under the combined thermos-mechanical load can be effectively predicted by a trained BP neural network. Highlights: Exact deformation of simply supported laminated LCE plate under thermo-mechanical loads are presented. BP neural network technique is used to predict the mechanical solutions of a laminated LCE plate. Effects of layer thickness and temperature on deformation of the LCE plate are analyzed. Highly accurate prediction of deformation or inversing mechanical load can be achieved.