Results 81 to 90 of about 29,946 (302)
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Robust Variational Physics-Informed Neural Networks
Computer Methods in Applied Mechanics and EngineeringWe introduce a Robust version of the Variational Physics-Informed Neural Networks method (RVPINNs). As in VPINNs, we define the quadratic loss functional in terms of a Petrov-Galerkin-type variational formulation of the PDE problem: the trial space is a (Deep) Neural Network (DNN) manifold, while the test space is a finite-dimensional vector space ...
Rojas, Sergio +4 more
openaire +3 more sources
Inverse Physics-Informed Neural Networks for transport models in porous materials
Physics-Informed Neural Networks (PINN) are a machine learning tool that can be used to solve direct and inverse problems related to models described by Partial Differential Equations by including in the cost function to minimise during training the ...
Icardi, Matteo +2 more
core +1 more source
Physics Informed Neural Networks for Engineering Systems
, 2020 This thesis explores the application of deep learning techniques to problems in fluid mechanics, with particular focus on physics informed neural networks.
Sukirt, None
core
Magnetostatics and micromagnetics with physics informed neural networks
, 2022 Partial differential equations and variational problems can be solved with physics informed neural networks (PINNs). The unknown field is approximated with neural networks.
Breth, Leoni +10 more
core +1 more source
Advanced Engineering Materials, EarlyView.A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
Within the present study, a framework for Physics Informed Neural Networks (PINN) is formulated for the analysis of frame structures in two dimensions.
Most, Thomas +3 more
core +1 more source
MathematicsThis work introduces a new initialization scheme for complex-valued layers in physics-informed neural networks that use holomorphic activation functions.
Andrei-Ionuț Mohuț, Călin-Adrian Popa
doaj +1 more source
Advanced Engineering Materials, EarlyView.Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
Модели, системы, сети в экономике, технике, природе и обществеBackground. An analysis of physics-informed neural networks for solving partial differential equations has been conducted, and the advantages of physics-informed radial basis function networks have been demonstrated.
Dmitry A. Stenkin
doaj +1 more source