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1. Discretisation of an Oldroyd-B viscoelastic fluid flow using a Lie derivative formulation NSTL国家科技图书文献中心

Ashby, Ben S. |  Pryer, Tristan -  《Advances in computational mathematics》 - 2025,51(1) - 共26页

摘要:In this article, we present a numerical method |  for the Stokes flow of an Oldroyd-B fluid. The |  viscoelastic stress evolves according to a constitutive law |  formulated in terms of the upper convected time derivative | . A finite difference method is used to discretise
关键词: Non-Newtonian fluid dynamics |  Upper convected time derivative |  Finite element methods |  Finite difference methods |  Lie derivative approximation

2. A reduced-order model for advection-dominated problems based on the Radon Cumulative Distribution Transform NSTL国家科技图书文献中心

Long, Tobias |  Barnett, Robert... -  《Advances in computational mathematics》 - 2025,51(1) - 共30页

摘要:Problems with dominant advection | , discontinuities, travelling features, or shape variations are |  widespread in computational mechanics. However, classical |  linear model reduction and interpolation methods |  typically fail to reproduce even relatively small
关键词: Reduced order model |  Non-linear transformations |  Advection-dominated problems |  Radon transform |  Cumulative distribution |  Proper orthogonal decomposition |  65-XX

3. On convergence of the generalized Lanczos trust-region method for trust-region subproblems NSTL国家科技图书文献中心

Feng, Bo |  Wu, Gang -  《Advances in computational mathematics》 - 2025,51(1) - 共29页

摘要:The generalized Lanczos trust-region (GLTR | ) method is one of the most popular approaches for |  solving large-scale trust-region subproblem (TRS). In |  Jia and Wang, SIAM J. Optim., 31, 887-914 2021. Z | . Jia et al. considered the convergence of this method
关键词: Trust-region subproblem |  Generalized Lanczos trust-region (GLTR) method |  Krylov subspace |  Cubic regularization |  Easy case

4. On the recovery of two function-valued coefficients in the Helmholtz equation for inverse scattering problems via neural networks NSTL国家科技图书文献中心

Zhou, Zehui -  《Advances in computational mathematics》 - 2025,51(1) - 共54页

摘要:Recently, deep neural networks (DNNs) have |  become powerful tools for solving inverse scattering |  problems. However, the approximation and generalization |  rates of DNNs for solving these problems remain |  largely under-explored. In this work, we introduce two
关键词: Inverse scattering problem |  Neural network |  Approximation |  Generalization |  Two function-valued coefficients

5. A nonsingular-kernel Dirichlet-to-Dirichlet mapping method for the exterior Stokes problem NSTL国家科技图书文献中心

Liu, Xiaojuan |  Li, Maojun... -  《Advances in computational mathematics》 - 2025,51(1) - 共24页

摘要:This paper studies the finite element method |  for solving the exterior Stokes problem in two |  dimensions. A nonlocal boundary condition is defined using |  a nonsingular-kernel Dirichlet-to-Dirichlet (DtD | ) mapping, which maps the Dirichlet data on an interior
关键词: Exterior Stokes problem |  Dirichlet-to-Dirichlet mapping |  Mixed finite elements |  Bubble function |  Error estimates

6. An all-frequency stable integral system for Maxwell's equations in 3-D penetrable media: continuous and discrete model analysis NSTL国家科技图书文献中心

Ganesh, Mahadevan |  Hawkins, Stuart C.... -  《Advances in computational mathematics》 - 2025,51(1) - 共37页

摘要:We introduce a new system of surface integral |  equations for Maxwell's transmission problem in three |  dimensions (3-D). This system has two remarkable features | , both of which we prove. First, it is well-posed at |  all frequencies. Second, the underlying linear
关键词: Electromagnetic scattering |  Dielectric |  Weakly singular integral equations |  Surface integral equations |  Stabilization |  Spectral numerical convergence

7. Parametric model order reduction for a wildland fire model via the shifted POD-based deep learning method NSTL国家科技图书文献中心

Shubhaditya,Burela |  Philipp,Krah... -  《Advances in computational mathematics》 - 2025,51(1) - 共43页

摘要:Abstract Parametric model order reduction |  techniques often struggle to accurately represent transport | -dominated phenomena due to a slowly decaying Kolmogorov n | -width. To address this challenge, we propose a non | -intrusive, data-driven methodology that combines the
关键词: Model order reduction |  Shifted proper orthogonal decomposition |  Data-driven models |  Deep learning |  Artificial neural networks |  Wildland fires |  68T07 |  65F55 |  35Q35 |  76-10

8. Strong convergence of a fully discrete scheme for stochastic Burgers equation with fractional-type noise NSTL国家科技图书文献中心

Wang, Yibo |  Cao, Wanrong -  《Advances in computational mathematics》 - 2025,51(2) - 共32页

摘要:We investigate numerical approximations for |  the stochastic Burgers equation driven by an |  additive cylindrical fractional Brownian motion with |  Hurst parameter H is an element of(12,1)documentclass | [12pt]{minimal} usepackage{amsmath} usepackage{wasysym
关键词: Stochastic Burgers equation |  Fractional Brownian motion |  Tamed exponential Euler method |  Strong convergence |  Non-globally monotone nonlinearity

9. A scaling fractional asymptotical regularization method for linear inverse problems NSTL国家科技图书文献中心

Yuan, Lele |  Zhang, Ye -  《Advances in computational mathematics》 - 2025,51(1) - 共37页

摘要:In this paper, we propose a Scaling Fractional |  Asymptotical Regularization (S-FAR) method for solving linear |  ill-posed operator equations in Hilbert spaces | , inspired by the work of (2019 Fract. Calc. Appl. Anal. 22 | (3) 699-721). Our method is incorporated into the
关键词: Linear operator equation |  Ill-posed problems |  Fractional asymptotical regularization |  Convergence rates |  De-biasing |  Sparse thresholding

10. A difference finite element method based on nonconforming finite element methods for 3D elliptic problems NSTL国家科技图书文献中心

Song, Jianjian |  Sheen, Dongwoo... -  《Advances in computational mathematics》 - 2025,51(1) - 共31页

摘要:In this paper, a class of 3D elliptic |  equations is solved by using the combination of the finite |  difference method in one direction and nonconforming finite |  element methods in the other two directions. A finite | -difference (FD) discretization based on P1documentclass
关键词: Difference finite element method |  Crouzeix-Raviart element |  Park-Sheen element |  3D elliptic equation |  Error estimation
检索条件出处:Advances in computational mathematics
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