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This work presents a probabilistic scheme for solving semilinear nonlocal diffusion equations with volume constraints and integrable kernels. The nonlocal model of interest is defined by a time-dependent semilinear partial…

Numerical Analysis · Mathematics 2022-05-03 Minglei Yang , Guannan Zhang , Diego Del-Castillo-Negrete , Yanzhao Cao

This article provides a general iterative approximation to partial differential equations, and thus establish existence of smooth solution. The heart of the method is to contract (or expand) the boundary conditions uniformly in the domain,…

Analysis of PDEs · Mathematics 2024-07-16 Chang Gao

We propose a general method for optimization with semi-infinite constraints that involve a linear combination of functions, focusing on the case of the exponential function. Each function is lower and upper bounded on sub-intervals by…

Optimization and Control · Mathematics 2014-01-13 Bogdan Dumitrescu , Bogdan C. Sicleru , Florin Avram

Using the simple case of Blasius similarity solution, we illustrate a recently developed general method that reduces a strongly nonlinear problem into a weakly nonlinear analysis. The basic idea is to find a quasi-solution $F_0$ that…

Classical Analysis and ODEs · Mathematics 2015-06-17 O. Costin , T. Kim , S. Tanveer

This study presents a collection of purely data-driven workflows for constructing reduced-order models (ROMs) for distributed dynamical systems. The ROMs we focus on, are data-assisted models inspired by, and templated upon, the theory of…

We provide of a method to integrate first order non-linear systems of differential equations with variable coefficients. It determines approximate solutions given initial or boundary conditions or even for Sturm-Liouville problems. This…

Classical Analysis and ODEs · Mathematics 2025-03-05 Manuel Gadella , Luis P. Lara

Equation-free approaches have been proposed in recent years for the computational study of multiscale phenomena in engineering problems where evolution equations for the coarse-grained, system-level behavior are not explicitly available. In…

Dynamical Systems · Mathematics 2007-05-23 Yu Zou , Ioannis G. Kevrekidis , Roger G. Ghanem

This dissertation explores block decomposable methods for large-scale optimization problems. It focuses on alternating direction method of multipliers (ADMM) schemes and block coordinate descent (BCD) methods. Specifically, it introduces a…

Optimization and Control · Mathematics 2026-01-15 Leandro Farias Maia

Interface problems have long been a major focus of scientific computing, leading to the development of various numerical methods. Traditional mesh-based methods often employ time-consuming body-fitted meshes with standard discretization…

Numerical Analysis · Mathematics 2023-08-09 Xurong Chi , Jingrun Chen , Zhouwang Yang

A new analytical approximation function is proposed to accurately fit the solution of a fractional differential equation of order one-half, whose nonhomogeneous term is defined by a modified Bessel function of the first kind. The exact…

General Mathematics · Mathematics 2025-12-03 Byron Droguett , Pablo Martin , Eduardo Rojas , Jorge Olivares

We investigate solutions to the functional equation $f(f(x)) = e^x$, which can be interpreted as the problem of finding a half iterate of the exponential map. While no elementary solution exists, we construct and analyze non-elementary…

Numerical Analysis · Mathematics 2025-09-30 Sanay Nesargi , Gregory Roudenko

Scientific and engineering problems often involve parametric partial differential equations (PDEs), such as uncertainty quantification, optimizations, and inverse problems. However, solving these PDEs repeatedly can be prohibitively…

Numerical Analysis · Mathematics 2023-07-04 Jun Sur Richard Park , Xueyu Zhu

In this work, a coarse-graining method previously proposed by the authors in a companion paper based on solving diffusion equations is applied to CFD-DEM simulations, where coarse graining is used to obtain solid volume fraction, particle…

Computational Physics · Physics 2015-01-07 Rui Sun , Heng Xiao

In this paper we develop the Greedy Recombination Interpolation Method (GRIM) for finding sparse approximations of functions initially given as linear combinations of some (large) number of simpler functions. In a similar spirit to the…

Numerical Analysis · Mathematics 2024-03-11 Terry Lyons , Andrew D. McLeod

We present a numerical scheme for the solution of nonlinear mixed-dimensional PDEs describing coupled processes in embedded tubular network system in exchange with a bulk domain. Such problems arise in various biological and technical…

Computational Engineering, Finance, and Science · Computer Science 2021-11-23 Timo Koch , Hanchuan Wu , Martin Schneider

We resolve a longstanding open problem in the computational modeling of nonlinear plates by introducing a numerical method that exactly enforces the isometry constraint, namely, that the first fundamental form of the mid-surface coincides…

Numerical Analysis · Mathematics 2026-05-11 Brendan Keith , Frédéric Marazzato

Recent works have established the utility of sparsity-promoting norms for extracting spatially-localized instability mechanisms in fluid flows, with possible implications for flow control. However, these prior works have focused on linear…

Fluid Dynamics · Physics 2023-11-17 A. Leonid Heide , Maziar S. Hemati

We introduce an iterative method to solve problems in small-strain non-linear elasticity, termed ``Phase-Space Iterations'' (PSIs). The method is inspired by recent work in data-driven computational mechanics, which reformulated the classic…

Numerical Analysis · Mathematics 2024-11-26 Gaëtan Cortes , Nur Cristian Sangiorgio , Joaquin Garcia-Suarez

Our interest lies in exploring the ability of a coupled nonlocal system of two quasilinear parabolic partial differential equations to produce phase separation patterns. The obtained patterns are referred here as morphologies. Our target…

Statistical Mechanics · Physics 2023-08-09 Rainey Lyons , Stela Andrea Muntean , Emilio N. M. Cirillo , Adrian Muntean

Increasingly larger data sets of processes in space and time ask for statistical models and methods that can cope with such data. We show that the solution of a stochastic advection-diffusion partial differential equation provides a…

Methodology · Statistics 2016-02-18 Fabio Sigrist , Hans R. Künsch , Werner A. Stahel