Abstract in English:

Abstract Tensegrity structures are geometric nonlinear systems and statically and kinematically indeterminate structures that require an initial shape-finding procedure to establish a self-equilibrium state. This paper presents a shape-finding algorithm requiring structure topology, strut force, cable force density, and a random initial estimate of node coordinates as input. The equilibrium of the structure is achieved by zeroing the nonlinear static equilibrium in which the generalized nodal coordinates are chosen as variables. The modified Newton-Raphson method is used to solve the nonlinear equilibrium system by decreasing the nonlinear least square function to ensure global convergence. The stability of the self-balancing structure was evaluated using the properties of the geometric and tangent stiffness matrix. Various numerical examples are presented to illustrate the method's effectiveness for 2-d and 3-d tensegrity structures with multiple states of self-stress.

Abstract in English:

Abstract This study aims to refine orthogonal cutting analysis using numerical methodology of limit analysis, focusing on predicting cutting forces and contact stresses more accurately. Unlike prior models, it incorporates frictional dissipation and considers sticking or sliding as part of the solution. It is shown that shear stress in sticking contact cannot be equated to shear yield stress, as typically imposed, leading to stress overestimation. The workpiece is treated as a deformable body, discretized with finite elements, while the tool is rigid. Interaction between them follows contact conditions in normal and tangential directions. Inputs include cutting conditions, friction coefficient, and material properties. Results encompass cutting forces, velocity and stress fields, and shear regions. Discrepancy between the shear angle predicted by Merchant and those ones obtained numerically is discussed. Finally, results are compared with experimental data found in literature. This approach provides a more accurate cutting model for determining cutting forces and contact stresses, which is crucial for estimating tool wear and life.

Abstract in English:

Abstract A number of techniques have been proposed for the detection of damage to structures. Some of these techniques are based on vibrational data, whereby changes in physical properties can be identified through alterations in vibrational characteristics. The majority of techniques are based on variations of modal parameters. The direct utilization of accelerations offers considerable advantages in damage detection, making the process more rapid and more straightforward by eliminating the necessity for an identification stage. The paucity of research into raw dynamic data (accelerations) can be attributed to the considerable volume of data that must be stored and manipulated. Some authors suggest Symbolic Data Analysis (SDA) and Principal Components Analysis (PCA) as techniques for reducing the volume of data without compromising its fundamental characteristics. The objective of this study is to examine the number of categories utilized in SDA and the number of principal components in PCA that yielded the optimal damage state classification results when applied to experimental data from a simply supported beam and numerical data from a four-story Benchmark. Two techniques for determining the number of SDA categories are put forth for consideration.