Recent Developments in Numerical Methods for Partial Differential Equations

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "C1: Difference and Differential Equations".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 800

Special Issue Editor


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Guest Editor
Laboratoire Jacques-Louis Lions, Sorbonne Université, 75005 Paris, France
Interests: applied mathematics; numerical methods; partial differential equations; finite element methods; high performance computing; computational fluid dynamics; financial engineering

Special Issue Information

Dear Colleagues,

The time has come to survey the recent developments in the mathematical and practical aspects of analytical and scientific computing for partial differential equations.  As such, we welcome your publications for this Special Issue, “Recent Developments in Numerical Methods for Partial Differential Equations”.

The Issue focuses on the numerical analysis of PDEs, numerical methods for nonlinear or large-scale problems and systems, and computational techniques, including sparse linear solvers, hierarchical methods, and domain decomposition methods. We are also interested in contributions on implementation tools, programming languages, and libraries. etc.  Finally,  artificial intelligence is rapidly becoming an impressive acceleration tool for PDE solvers.

Applications are numerous in physics, engineering, and quantitative finance, amongst other areas. However, applications without algorithmic innovation are not the primary focus of this Special Issue, as other Special Issues already address areas like fluid dynamics and computational physics.

Thank you for your support and interest in contributing to this Special Issue.

Prof. Dr. Olivier Pironneau
Guest Editor

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Keywords

  • numerical analysis
  • scientific computing
  • numerical methods
  • high-performance computing
  • partial differential equations

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Published Papers (1 paper)

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Research

20 pages, 4194 KiB  
Article
Algorithm for Acoustic Wavefield in Space-Wavenumber Domain of Vertically Heterogeneous Media Using NUFFT
by Ying Zhang and Shikun Dai
Mathematics 2025, 13(4), 571; https://doi.org/10.3390/math13040571 - 9 Feb 2025
Viewed by 540
Abstract
Balancing efficiency and accuracy is often challenging in the numerical solution of three-dimensional (3D) point source acoustic wave equations for layered media. To overcome this, an efficient solution method in the spatial-wavenumber domain is proposed, utilizing the Non-Uniform Fast Fourier Transform (NUFFT) to [...] Read more.
Balancing efficiency and accuracy is often challenging in the numerical solution of three-dimensional (3D) point source acoustic wave equations for layered media. To overcome this, an efficient solution method in the spatial-wavenumber domain is proposed, utilizing the Non-Uniform Fast Fourier Transform (NUFFT) to achieve arbitrary non-uniform sampling. By performing a two-dimensional (2D) Fourier transform on the 3D acoustic wave equation in the horizontal direction, the 3D equation is transformed into a one-dimensional (1D) space-wavenumber-domain ordinary differential equation, effectively simplifying significant 3D problems into one-dimensional problems and significantly reducing the demand for memory. The one-dimensional finite-element method is applied to solve the boundary value problem, resulting in a pentadiagonal system of equations. The Thomas algorithm then efficiently solves the system, yielding the layered wavefield distribution in the space-wavenumber domain. Finally, the wavefield distribution in the spatial domain is reconstructed through a 2D inverse Fourier transform. The correctness of the algorithm was verified by comparing it with the finite-element method. The analysis of the half-space model shows that this method can accurately calculate the wavefield distribution in the air layer considering the air layer while exhibiting high efficiency and computational stability in ultra-large-scale models. The three-layer medium model test further verified the adaptability and accuracy of the algorithm in calculating the distribution of acoustic waves in layered media. Through a sensitivity analysis, it is shown that the denser the mesh node partitioning, the higher the medium velocity, and the lower the point source frequency, the higher the accuracy of the algorithm. An algorithm efficiency analysis shows that this method has extremely low memory usage and high computational efficiency and can quickly solve large-scale models even on personal computers. Compared with traditional FEM, the algorithm has much higher advantages in terms of memory usage and efficiency. This method provides a new approach to the numerical solution of partial differential equations. It lays an essential foundation for background field calculation in the scattering seismic numerical simulation and full-waveform inversion of acoustic waves, with strong theoretical significance and practical application value. Full article
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