Many applications of computational fluid dynamics require multiple simulations of a flow
under different input conditions. In this paper, a numerical algorithm is developed to …

The Helmholtz equation is the simplest possible model of wave propagation, describing
timeharmonic solutions of the wave equation. We study the Helmholtz equation with …

We study an iterative low-rank approximation method for the solution of the steady-state
stochastic Navier--Stokes equations with uncertain viscosity. The method is based on …

We develop a low‐rank tensor decomposition algorithm for the numerical solution of a
distributed optimal control problem constrained by two‐dimensional time‐dependent Navier …

We study efficient solution methods for stochastic eigenvalue problems arising from
discretization of self-adjoint PDEs with random data, where the underlying operators depend …

In this paper, a linear combination of quadratic modified hat functions is proposed to solve
stochastic Itô–Volterra integral equation with multi-stochastic terms. All known and unknown …

We study the time-dependent Navier–Stokes equations in the context of stochastic finite
element discretizations. Specifically, we assume that the viscosity is a random field given in …

Incorporating probabilistic terms in mathematical models is crucial for capturing and
quantifying uncertainties in real-world systems. Indeed, randomness can have a significant …

Solving convection diffusion equation is widely required in many fields of science,
technology and engineering. The calculation is usually difficult and time-consuming. In this …

We present a method for linear stability analysis of systems with parametric uncertainty
formulated in the stochastic Galerkin framework. Specifically, we assume that for a model …