Results 131 to 140 of about 32,424,344 (291)
Mesh and Model Adaptivity for Multiscale Elastoplastic Models With Prandtl‐Reuss Type Material Laws
ABSTRACT Homogenization methods simulate heterogeneous materials like composites effectively, but high computational demands can offset their benefits. This work balances accuracy and efficiency by assessing model and discretization errors of the finite element method (FEM) through an adaptive numerical scheme.
Arnold Tchomgue Simeu +2 more
wiley +1 more source
In this paper, we investigate how adaptive time-integration strategies can be effectively combined with parallel-in-time numerical methods for solving systems of ordinary differential equations.
Imre Fekete +3 more
doaj +1 more source
Discrete Variational Methods and Symplectic Generalized Additive Runge--Kutta Methods [PDF]
Antonella Zanna
openalex +1 more source
This study elucidates the mechanism of compressible flow exfoliation for producing 2D hexagonal boron nitride (h‐BN). Fluid dynamics analysis reveals that acceleration‐driven aerodynamic shear forces, rather than shock waves alone, drive effective layer separation.
Md Farhadul Islam +3 more
wiley +1 more source
ABSTRACT This work presents novel structure‐preserving formulations for stable model order reduction in the context of time‐domain room acoustics simulations. A solution to address the instability in conventional model order reduction formulations based on the Linearized Euler Equations is derived and validated through numerical experiments.
Satish Bonthu +4 more
wiley +1 more source
PLA and strontium‐substituted hydroxyapatite filaments were used in 3D printing to fabricate a trabecular‐inspired scaffold. The scaffold was functionalized with a polydopamine coating. Characterization revealed enhanced surface properties and mechanical performance, supporting its potential application in bone tissue engineering.
Adones Almeida Rocha +4 more
wiley +1 more source
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source
Rib‐Reinforced Ultralight and Ultra‐Strong Shell Lattices
This study thoroughly reveals the relation between the curvature and stress direction of triply periodic minimal surface (TPMS) thin shell lattices and proposes a novel rib reinforcement design strategy to incorporate ribs along the line of asymptotes (LOA) and the line of principal curvatures (LOC) to enhance the strength of ultralight TPMS shell ...
Winston Wai Shing Ma +6 more
wiley +1 more source
This work demonstrates the application of neural ordinary differential equations (neural ODEs) for learning hydrocracking reaction kinetics directly from data, achieving robust predictions under noise and sparsity while preserving mechanistic interpretability through gradient‐based analysis of temperature‐ and concentration‐dependent reaction rates ...
Souvik Ta +2 more
wiley +1 more source
Considered physical model and effect of Nuav(τ = 0.1) for Re and ϕ at τ = 0.1. ABSTRACT Although open cavity configurations are common in modern electronic and solar applications, limited attention has been given to thick‐walled hollow cavity designs, particularly in the context of comprehensive sensitivity analysis.
Murad Hossen +5 more
wiley +1 more source

