Manufacturing-oriented topology optimization has been extensively studied the past two
decades, in particular for the conventional manufacturing methods, for example, machining …

Data-driven models are rising as an auspicious method for the geometrical design of
materials and structural systems. Nevertheless, existing data-driven models customarily …

Deep learning (DL) and the collocation method are merged and used to solve partial
differential equations (PDEs) describing structures' deformation. We have considered …

In this paper, we develop a convolutional neural network model to predict the mechanical
properties of a two-dimensional checkerboard composite quantitatively. The checkerboard …

The paper is devoted to a review of recent achievements in the field of dynamic analysis of
structures and structural elements, such as beams and plates, with embedded viscoelastic …

This paper presents a unified modeling approach for cylindrical shells with partial
constrained layer damping (CLD) treatment under general boundary conditions, followed by …

The dynamics of engineering structures are of great importance for topology optimization
problems in both academia and industry. However, for design problems where broadband …

In this paper infinitesimal elasto-plastic based topology optimization is extended to finite
strains. The employed model is based on rate-independent isotropic hardening plasticity …

An adjoint sensitivity analysis framework to evaluate path‐dependent design sensitivities for
problems involving inelastic materials and dynamic effects is presented and shown in the …

Damping and natural frequency are the most important characteristics for evaluating the
performance of dynamic structures. This paper proposes a topology optimization algorithm …