Internal forces within a closed system, such as a ship, cannot generate net motion, as the action and reaction forces cancel out. External interactions are required to propel a ship forward.
The authors analyze a dislocation model for simulating ground motion during earthquakes, where the fault region is represented as a surface rather than a thin volume. This allows for efficient numerical approximation by avoiding the need to resolve large deformations in the fault.
This paper presents a comparative study of mixed finite element and two-point stress approximation finite volume methods for the numerical simulation of linearized elasticity and Cosserat materials. The methods are assessed for their accuracy, robustness, and computational efficiency.
The Deep Ritz Method can be used to model strain localization in elastoplastic solids as sharp discontinuities in the displacement field.
The authors present an approach to coupling mixed-dimensional continua by employing the mathematically enriched linear Cosserat micropolar model, where the kinematical reduction to lower dimensional domains leaves the fundamental degrees of freedom intact, enabling intrinsic agreement of the degrees of freedom at the interface.
A novel multi-grid graph neural network model with self-attention layers achieves significant improvements in computational fluid dynamics simulations, outperforming state-of-the-art models by up to 75% on challenging datasets.
The proposed clustering adaptive Gaussian process regression (CAG) method can accurately and efficiently predict the nonlinear deformation of hyperelastic cylinders under axial stretching and compression, outperforming traditional Gaussian process regression with uniform sampling.
The node-based uniform strain virtual element method (NVEM) enables linearly-precise virtual elements to accurately model elastoplastic solids while avoiding volumetric locking.
This work presents a detailed numerical analysis and applications of a stabilized finite element method for solving the Biot's poroelasticity equations in the frequency domain, with a focus on ensuring stability and robustness for a wide range of permeabilities.
DIC2CAE, a MATLAB-based tool, automates the conversion of Digital Image Correlation (DIC) data into a format compatible with Computer-Aided Engineering (CAE) software like ABAQUS, enabling accurate simulations and reliable calculations of stress intensity factors (SIFs) and the J-integral.