Results 171 to 180 of about 2,746 (252)

An Augmented Lagrangian Preconditioner for Navier–Stokes Equations With Runge–Kutta in Time

Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.
ABSTRACT We consider an implicit Runge–Kutta method for the numerical time integration of the nonstationary incompressible Navier–Stokes equations. This yields a sequence of nonlinear problems to be solved for the stages of the Runge–Kutta method. The resulting nonlinear system of differential equations is discretized using a finite element method.
Santolo Leveque, Yunhui He, Maxim Olshanskii   +2 more
wiley   +1 more source

Analytical analysis of the nonlinear fractional order Pochhammer-Chree equation with power-law nonlinearity in elastic materials. [PDF]

Sci Rep
Khalid M, Khalid NA, Ceesay B, Ahmed N.
europepmc   +1 more source

Building a Digital Twin for Material Testing: Model Reduction and Data Assimilation

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT The rapid advancement of industrial technologies, data collection, and handling methods has paved the way for the widespread adoption of digital twins (DTs) in engineering, enabling seamless integration between physical systems and their virtual counterparts.
Rubén Aylwin, Nina Beranek, Gajendra Babu Budihala, Matthias Mettenleiter, Goksu Oruc, Karsten Urban   +5 more
wiley   +1 more source

Homogenised balance equations for nematic liquid crystal flow in elastic porous media. [PDF]

Z Angew Math Phys
Alwady M, Mottram NJ, Penta R.
europepmc   +1 more source

On the Performance and Convergence of PINNs for Problems in Linear Elasticity

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT Physics‐informed neural networks (PINNs) have emerged as a promising approach for solving partial differential equations by embedding physical laws directly into the loss function. However, their performance characteristics for problems in computational mechanics remain insufficiently understood.
Dipraj Kadlag, Carolin Birk, Sundararajan Natarajan, Hauke Gravenkamp   +3 more
wiley   +1 more source

Parameter identification for PDEs using sparse interior data and a recurrent neural network. [PDF]

Sci Rep
Long J, Khaliq A, Furati KM.
europepmc   +1 more source

On MAP Estimates and Source Conditions for Drift Identification in SDEs

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT We consider the inverse problem of identifying the drift in an stochastic differential equation (SDE) from n$n$ observations of its solution at M+1$M+1$ distinct time points. We derive a corresponding maximum a posteriori (MAP) estimate, we prove differentiability properties as well as a so‐called tangential cone condition for the forward ...
Daniel Tenbrinck, Nikolas Uesseler, Philipp Wacker, Benedikt Wirth   +3 more
wiley   +1 more source

Deterministic, stochastic, and mean-field PDE models in neuroscience. [PDF]

Front Comput Neurosci
Çetin C, Piqueira JRC, İzgi B, Peker-Dobie A, Ahmetolan S, Özkaya M.   +5 more
europepmc   +1 more source

Emerging Treatments for Erectile Dysfunction

Trends in Urology &Men's Health, Volume 17, Issue 3, June 2026.
ABSTRACT Erectile dysfunction (ED) is a prevalent condition that can significantly affect men's sexual health and quality of life, and for which there are many well‐studied effective treatments. In spite of this, many individuals still seek out alternative therapies.
Resa Magill, Jeff Morrison, Juan Andino, Jasper Bash   +3 more
wiley   +1 more source

New analytical wave solutions for the gardner equation via the Riccati-modified extended simple equation method. [PDF]

Sci Rep
Jawarneh Y, Almusawa MY, Haleemzai I, Hakami AH, Ahmadini AAH, Albaity A.   +5 more
europepmc   +1 more source