We present NeuralMag, a flexible and high-performance open-source Python library for micromagnetic simulations. NeuralMag leverages modern machine learning frameworks, such as PyTorch and JAX, to ...

Tibial periprosthetic fracture (TPF) is a severe complication of cementless Oxford Unicompartmental Knee Replacement (OUKR) with patient risk factors including small tibial size and tibia vara with an ...

Electrochemiluminescence (ECL) is a vital analytical technique widely used in immunosensing and emerging applications in biological imaging. Traditional ECL simulations rely on finite element methods, ...

Abstract: In this paper, Python programming is employed to study the electromagnetic finite element method (FEM) and Bayesian deep learning. Rectangular cavity and folded waveguide (FWG) slow-wave ...

Fibre-reinforced composite materials have become indispensable in numerous applications in various industries such as automotive, aerospace, and construction, due to their exceptional mechanical ...

Mechanical engineering has long been at the forefront of technological advancements, driving innovation and transforming industries. In recent years, there has been a significant rise in the use of ...

Abstract: As an important part of transmission lines, preformed helical fitting plays an indispensable role in the safe and stable operation of electronic circuits. However, due to the poor service ...

This repository includes the work done within the course TRA105 - GPU-accelerated Computational Methods using Python and CUDA, held at Chalmers University. The main contributions are given by Stefano ...

Finite Element Method (FEM) codes in Matlab and Python for beam, plane frame, and plane truss structures static and modal analysis. Functions for the determination of stiffness and mass matrices are ...

PLAXIS is a Finite Element modelling software that geotechnical engineers will definitely come across at certain point of their career. Modelling complex geotechnical problems in a PLAXIS can be ...

Physical scientists and engineering research and development (R&D) teams are embracing neural networks in attempts to accelerate their simulations. From quantum mechanics to the prediction of blood ...