Results 191 to 200 of about 87,373,027 (240)

Complex soliton wave patterns of Gross-Pitaevskii systems: application in quantum and optical engineering. [PDF]

Sci Rep
Bilal M, Alawaideh YM, Rehman SU, Popa IL, Al-Khamiseh BM, Ghannam H.   +5 more
europepmc   +1 more source

Stochastic Galerkin and Monte Carlo Methods for Parabolic Problems: Numerical Performance of Variational Matrix‐Free Approximations

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.
ABSTRACT Stochastic Galerkin methods offer unexplored potential for the numerical simulation of parabolic problems with random variables, in particular if they are combined with variational discretizations of the space and time variables. Due to the high dimensionality, the solution of the arising algebraic systems do not become feasible without ...
Moataz Dawor, Nils Margenberg, Markus Bause   +2 more
wiley   +1 more source

Investigation of the effectiveness of the thermal conductivity of the Bingham fluid subjected to the dispersion of nanoparticles and dissipation effects. [PDF]

Sci Rep
Imtiaz K, Nawaz M, Alharbi SO, Alzahrani SM.   +3 more
europepmc   +1 more source

Inverse problems for semilinear elliptic PDE with a general nonlinearity a(x,u)$a(x,u)$

Transactions of the London Mathematical Society, Volume 13, Issue 1, December 2026.
Abstract This article studies the inverse problem of recovering a nonlinearity in an elliptic equation Δu+a(x,u)=0$\Delta u + a(x,u) = 0$ from boundary measurements of solutions. Previous results based on first‐order linearization achieve this under a sign condition on ∂ua(x,u)$\partial _u a(x,u)$, and results based on higher order linearization ...
David Johansson, Janne Nurminen, Mikko Salo   +2 more
wiley   +1 more source

Thermal Performance of ternary hybrid nanofluid with activation energy and surface tension gradient using HCM and YOM models. [PDF]

Discov Nano
Ettoumi M, Safra I, Secer A, Rakhmonov F, Kanwal S.   +4 more
europepmc   +1 more source

UniNS: A Neuro‐Symbolic Framework for Structure‐Regularized Causal Modeling of Catalytic Nanorobot Swarms in Confined Tumor Microenvironments

Applied Research, Volume 5, Issue 5, October 2026.
UniNS is a hybrid neuro‐symbolic framework that simulates nanoscale swarms in tumor microenvironments by coupling mesoscopic hydrodynamics with structure‐regularized causal discovery. It reduces biochemical prediction errors by 27.3% and dynamically prevents spurious correlations, offering a scalable, thermodynamically consistent testbed for precision ...
Xinyuan Chen, Nurdatillah Hasim, Norliana Muslim, Mohd Nizam Husen   +3 more
wiley   +1 more source

Dynamical analysis and exact solitary wave solutions of [Formula: see text]-dimensional integro-differential Jaulent-Miodek equation using two analytical schemes. [PDF]

Sci Rep
Nasir B, Abbas M, Yousaf MZ, Nazir T, El-Rahman MA, Birhanu A.   +5 more
europepmc   +1 more source

Structurally Cascaded Physics‐Informed Graph Neural Networks for Mechanotransduction‐Aware Tumor Microenvironment Modeling

Applied Research, Volume 5, Issue 5, October 2026.
This study introduces a structurally cascaded physics‐informed graph neural network to model tumor microenvironments accurately. By enforcing a directional dependency from mechanical strain to biochemical secretion, the method eliminates unphysical artifacts and significantly improves predictive accuracy for precision healthcare applications.
Xinyuan Chen, Nurashikin Saaludin, Mohd Nizam Husen   +2 more
wiley   +1 more source

Physics-augmented Multi-task Gaussian Process for Modeling Spatiotemporal Dynamics. [PDF]

IEEE Trans Autom Sci Eng
Zhang XC, Yao B.
europepmc   +1 more source

Subspace Acceleration for Efficient Nonlinear Water Wave Simulation

International Journal for Numerical Methods in Fluids, Volume 98, Issue 10, Page 1165-1180, October 2026.
We introduce an exponentially weighted subspace acceleration technique to reduce GMRES iterations for solving the Poisson equation with time‐dependent coefficients in nonlinear, dispersive free‐surface flows governed by the incompressible Navier‐Stokes equations. The method significantly reduces memory requirements and computational complexity compared
Rasmus Kleist Hørlyck Sørensen, Margherita Guido, Allan Peter Engsig‐Karup, Daniel Kressner   +3 more
wiley   +1 more source