Results 51 to 60 of about 183 (122)
Machine-precision solution of Fredholm integral equations via barycentric physics-informed method
This paper presents a barycentric physics-informed (BPI) computational method for solving second-kind Fredholm integral equations. Unlike conventional Multi-Layer Perceptrons (MLPs) used in Physics-Informed Neural Networks (PINNs) that introduce inherent
Qinghua Wu
doaj +1 more source
Fast Nodal Hessian Computation for Peridynamic Fracture Simulation
A fast, exact nodal Hessian computation for Non‐Ordinary State‐Based Peridynamics is introduced through analytical simplification and a warp‐centric GPU strategy. The method accelerates preconditioned solvers and Vertex Block Descent, enabling interactive fracture simulation with physical accuracy.
Yuxiong Qin +2 more
wiley +1 more source
Solving Stochastic Climate‐Economy Models: A Deep Least‐Squares Monte Carlo Approach
ABSTRACT Stochastic versions of recursive integrated climate‐economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of state variables and stochastic shocks increases, solving these models via deterministic grid‐based dynamic programming (e.g., value‐function iteration/projection ...
Aleksandar Arandjelović +4 more
wiley +1 more source
Chebyshev Finite Difference Method for Solving Constrained Quadratic Optimal Control Problems
. In this paper the Chebyshev finite difference method is employed for finding the approximate solution of time varying constrained optimal control problems.
M. Maleki*, M. Dadkhah Tirani
doaj
ABSTRACT Fluid‐filled phase‐field fracture simulations require robust, scalable solvers that can handle strongly nonlinear, non‐smooth mechanics and tightly coupled flow on locally refined meshes. In this work, we develop an adaptive finite element framework for quasi‐static, fluid‐filled phase‐field fractures that combines semi‐smooth Newton methods ...
Leon M. Kolditz +3 more
wiley +1 more source
In this investigation, we present a new method for addressing fractional neutral pantograph problems, utilizing the Bernstein polynomials method.
M.H.T. Alshbool
doaj +1 more source
Broadband Electromagnetic Field Prediction at Unseen Wavelengths via Physics‐Guided Neural Operators
A physics‐guided neural operator is trained on electromagnetic field distributions at discrete wavelengths across diverse nanophotonic structures. At inference, given any permittivity map and query wavelength, the model predicts continuous broadband electric‐field distributions with full‐wave accuracy, including wavelengths unseen during training ...
Joonhyuk Seo +3 more
wiley +1 more source
Efficient Tensor Completion Algorithms for Highly Oscillatory Operators
ABSTRACT We address the problem of recovering highly oscillatory operators, represented as n×n$$ n\times n $$ matrices with a fixed set of observed entries. Given that these matrices can be well compressed by butterfly matrix decomposition of L=𝒪(logn) levels requiring only O(nlogn)$$ O\left(n\log n\right) $$ degrees of freedom, we propose a novel ...
Navjot Singh +3 more
wiley +1 more source
The Internet of Drones (IoD) overcomes the physical limitations of traditional ground networks with its dynamic topology and 3D spatial flexibility, playing a crucial role in various fields.
Zhaobin Li +4 more
doaj +1 more source
ABSTRACT We study a random recursive tree model featuring complete redirection called the random friend tree and introduced by Saramäki and Kaski (2004). Vertices are attached sequentially, one by one, by selecting an existing target vertex and connecting to one of its neighbours (or friends), chosen uniformly at random.
Louigi Addario‐Berry +5 more
wiley +1 more source

