arXiv · 2610.29451
A high-order multi-scale method and its error analysis for nonlocal-in-time fractionally damped wave problems in composite materials
Abstract
Significant spatial heterogeneity and nonlocal history-dependent attenuation jointly govern wave propagation in composite materials, making full-scale direct numerical simulation (DNS) computationally prohibitive. This study proposed a high-order multi-scale (HOMS) method for nonlocal-in-time fractionally damped wave problems with highly oscillatory and discontinuous material coefficients. Using a multi-scale asymptotic expansion approach, the macroscopic homogenized equation, and first- and second-order correction terms are derived to construct the high-accuracy HOMS solution. Moreover, a local pointwise error analysis identifies the leading residual eliminated by this HOMS solution and validates its local physical balance preservation. Then, a global energy-norm error estimate establishes the $O(\varepsilon)$-order convergence rate for the HOMS solution. Subsequently, an efficient spatiotemporal multi-scale algorithm integrating the finite element and finite difference methods is designed, which employs a novel fully discrete $L2\text{-}1_σ$-Newmark scheme, and corresponding unconditional shifted-energy stability and explicit convergence rates are also obtained for the macroscopic homogenized displacement and velocity, respectively. Both two- and three-dimensional examples are presented to demonstrate the accuracy, efficiency, reduced cost, and robustness of the proposed HOMS method. This work provides an effective multi-scale tool for nonlocal-in-time wave simulation in engineering applications.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Gehao Wang, Hao Dong, Yufeng Nie, Junzhi Cui. 2026-10-21. A high-order multi-scale method and its error analysis for nonlocal-in-time fractionally damped wave problems in composite materials. https://arxiv.org/abs/2610.29451
Cite the original work for its findings. Save a collection to share your selection of sources.