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This work presents an efficient numerical method based on spectral expansions for simulation of heat and moisture diffusive transfers through multilayered porous materials. Traditionally, by using the finite-difference approach, the problem…

Computational Engineering, Finance, and Science · Computer Science 2020-02-20 Suelen Gasparin , Denys Dutykh , Nathan Mendes

In this paper, we propose a new adaptation of the D-iteration algorithm to numerically solve the differential equations. This problem can be reinterpreted in 2D or 3D (or higher dimensions) as a limit of a diffusion process where the…

Numerical Analysis · Computer Science 2012-04-30 Dohy Hong

In this work, two Crank-Nicolson schemes without corrections are developed for sub-diffusion equations. First, we propose a Crank-Nicolson scheme without correction for problems with regularity assumptions only on the source term. Second,…

Numerical Analysis · Mathematics 2024-01-23 Han Zhou , Wenyi Tian

This work considers the subdiffusion problem with non-positive memory, which not only arises from physical laws with memory, but could be transformed from sophisticated models such as subdiffusion or subdiffusive Fokker-Planck equation with…

Numerical Analysis · Mathematics 2025-05-09 Wenlin Qiu , Xiangcheng Zheng

A singularly perturbed parabolic problem of convection-diffusion type with a discontinuous initial condition is examined. An analytic function is identified which matches the discontinuity in the initial condition and also satisfies the…

Numerical Analysis · Mathematics 2022-02-15 Jose Luis Gracia , Eugene O'Riordan

We present a finite-difference integration algorithm for solution of a system of differential equations containing a diffusion equation with nonlinear terms. The approach is based on Crank-Nicolson method with predictor-corrector algorithm…

Computational Physics · Physics 2019-07-05 V. P. Lipp , B. Rethfeld , M. E. Garcia , D. S. Ivanov

The transport equation of active motion is generalised to consider time-fractional dynamics for describing the anomalous diffusion of self-propelled particles observed in many different systems. In the present study, we consider an…

Statistical Mechanics · Physics 2023-10-27 Francisco J. Sevilla , Guillermo Chacón-Acosta , Trifce Sandev

In this paper, we present a sparse grid-based Monte Carlo method for solving high-dimensional semi-linear nonlocal diffusion equations with volume constraints. The nonlocal model is governed by a class of semi-linear partial…

Numerical Analysis · Mathematics 2025-07-08 Changtao Sheng , Bihao Su , Chenglong Xu

Diffusion in nonhomogeneous media is described by a dynamical process driven by a general Levy noise and subordinated to a random time; the subordinator depends on the position. This problem is approximated by a multiplicative process…

Statistical Mechanics · Physics 2015-06-18 Tomasz Srokowski

Problems with localized nonhomogeneous material properties present well-known challenges for numerical simulations. In particular, such problems may feature large differences in length scales, causing difficulties with meshing and…

Numerical Analysis · Mathematics 2021-11-23 Alex Viguerie , Silvia Bertoluzza , Alessandro Veneziani , Ferdinando Auricchio

The effective, fast transport of matter through porous media is often characterized by complex dispersion effects. To describe in mathematical terms such situations, instead of a simple macroscopic equation (as in the classical Darcy's…

Numerical Analysis · Mathematics 2025-05-06 Surendra Nepal , Vishnu Raveendran , Michael Eden , Rainey Lyons , Adrian Muntean

The gradient discretisation method (GDM) is a generic framework for designing and analysing numerical schemes for diffusion models. In this paper, we study the GDM for the porous medium equation, including fast diffusion and slow diffusion…

Numerical Analysis · Mathematics 2020-04-02 Jerome Droniou , Kim-Ngan Le

Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When equipped with a guidance mechanism, these models can also…

Machine Learning · Computer Science 2026-05-04 Saeed Mohseni-Sehdeh , Walid Saad , Kei Sakaguchi , Tao Yu

We introduce a novel explicit and stable numerical algorithm to solve the spatially discretized heat or diffusion equation. We compare the performance of the new method with analytical and numerical solutions. We show that the method is…

Computational Physics · Physics 2020-08-04 Endre Kovács

Unconstrained optimization problems become more common in scientific computing and engineering applications with the rapid development of artificial intelligence, and numerical methods for solving them more quickly and efficiently have been…

Optimization and Control · Mathematics 2025-04-17 Lin Li , Pengcheng Xie , Li Zhang

In this article, we consider numerical schemes for polynomial diffusions on the unit ball, which are solutions of stochastic differential equations with a diffusion coefficient of the form $\sqrt{1-|x|^{2}}$. We introduce a semi-implicit…

Probability · Mathematics 2022-06-14 Takuya Nakagawa , Dai Taguchi , Tomooki Yuasa

Addressing real-world optimization problems becomes particularly challenging when analytic objective functions or constraints are unavailable. While numerous studies have addressed the issue of unknown objectives, limited research has…

This paper investigates the simultaneous identification of a spatially dependent potential and the initial condition in a subdiffusion model based on two terminal observations. The existence, uniqueness, and conditional stability of the…

Numerical Analysis · Mathematics 2025-10-28 Xu Wu , Jiang Yang , Zhi Zhou

This paper concerns the use of asymptotic expansions for the efficient solving of forward and inverse problems involving a nonlinear singularly perturbed time-dependent reaction--diffusion--advection equation. By using an asymptotic…

Numerical Analysis · Mathematics 2023-02-15 Dmitrii Chaikovskii , Ye Zhang

The characterization of diffusion processes is a keystone in our understanding of a variety of physical phenomena. Many of these deviate from Brownian motion, giving rise to anomalous diffusion. Various theoretical models exists nowadays to…

Statistical Mechanics · Physics 2024-04-15 Gorka Muñoz-Gil , Guillem Guigó i Corominas , Maciej Lewenstein