Dynamics Of Thin-walled Structures Research Articles

Data-driven prediction and analysis of chaotic origami dynamics

Advances in machine learning have revolutionized capabilities in applications ranging from natural language processing to marketing to health care. Recently, machine learning techniques have also been employed to learn physics, but one of the formidable challenges is to predict complex dynamics, particularly chaos. Here, we demonstrate the efficacy of quasi-recurrent neural networks in predicting extremely chaotic behavior in multistable origami structures. While machine learning is often viewed as a “black box”, we conduct hidden layer analysis to understand how the neural network can process not only periodic, but also chaotic data in an accurate manner. Our approach shows its effectiveness in characterizing and predicting chaotic dynamics in a noisy environment of vibrations without relying on a mathematical model of origami systems. Therefore, our method is fully data-driven and has the potential to be used for complex scenarios, such as the nonlinear dynamics of thin-walled structures and biological membrane systems.

Modeling the Varying Dynamics of Thin-Walled Aerospace Structures for Fixture Design Using Genetic Algorithms

Fixture design for milling of aerospace thin-walled structures is a challenging process due to the high flexibility of the structure and the nonlinear interaction between the forces and the system dynamics. At the same time, the industry is aiming at achieving tight tolerances while maintaining a high level of productivity. Numerical models based on FEM have been developed to simulate the dynamics of thin-walled structures and the effect of the fixture layout. These models require an extensive computational effort, which makes their use for optimization very unpractical. In this research work, a new concept is introduced by using a multi-span plate with torsional and translational springs to simulate the varying dynamics of thin-walled structure during machining. A formulation, based on holonomic constraints, was developed and implemented to take into account the effect of rigid fixture supports. The developed model, which reduces the computational time by one to two orders of magnitude as compared to FE models, is used to predict the dynamic response of complex aerospace structural elements including pockets and ribs while taking into account different fixture layouts. The model predictions are validated numerically. The developed model meets the conflicting requirements of prediction accuracy and computational efficiency.

The Dynamics of Thin-Walled Structures Under Nonstationary Loads

Studies are reviewed in which nonstationary loads determining the dynamics of thin-walled structures are found and the initial concepts are formulated for the theory and methods of stress–strain analysis of shells with holes and different discrete reinforcements, as well as for coupled problems of hydro- and aeroelasticity. Special attention is drawn to the design and strength and dynamic analyses of thin-walled blasting chambers. The basic investigations conducted at the S. P. Timoshenko Institute of Mechanics of the National Academy of Sciences of Ukraine are outlined