Hang Deng, Jimin Ye^*, Wei Li^*, Dongmei Huang

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1731-1747, 2023, DOI:10.32604/cmes.2023.028334

Abstract In this paper, the response properties of galloping energy harvesters under bounded random parameter excitation are studied theoretically. The first-order approximate solution of the galloping energy harvester is derived by applying the multi-scales method. The expression for the largest Lyapunov exponent that determines the trivial solution is derived, and the corresponding simulation diagrams, including the largest Lyapunov exponent diagrams and time domain diagrams, verify our results. Then the steady-state response moments of the nontrivial solution are studied using the moment method, and the analytical expressions for the first-order and second-order moments of the voltage amplitude are obtained, respectively. The corresponding… More >

Saqlain Abbas^1,2, Zulkarnain Abbas^3,4,*, Yanping Zhu², Waqas Tariq Toor⁵, Xiaotong Tu⁶

Structural Durability & Health Monitoring, Vol.16, No.4, pp. 307-321, 2022, DOI:10.32604/sdhm.2022.015266

Abstract In the previous couple of decades, techniques to reap energy and empower low voltage electronic devices have received outstanding attention. Most of the methods based on the piezoelectric effect to harvest the energy from ambient vibrations have been revolutionized. There’s an absence of experiment-based investigation which incorporates the microstructure analysis and crystal morphology of those energy harvest home materials. Moreover, the impact of variable mechanical and thermal load conditions has seldom been studied within the previous literature to utilize the effectiveness of those materials in several practical applications like structural health monitoring (SHM), etc. In the proposed research work, scanning… More >

Hao Li^1,2, Zhixia Wang^1,2, Wei Wang^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 765-782, 2020, DOI:10.32604/cmes.2020.010061

Abstract Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors. Despite researchers follow the sparse identification nonlinear dynamics algorithm (SINDy) rule to restore nonlinear equations, there also exist obstacles. One is the excessive dependence on empirical parameters, which increases the difficulty of data pre-processing. Another one is the coexistence of multiple coefficient vectors, which causes the optimal solution to be drowned in multiple solutions. The third one is the composition of basic function, which is exclusively applicable to specific equations. In this article, a local sparse screening identification algorithm (LSSI) is proposed… More >