The following pages link to FEniCS (Q16493):
Displaying 50 items.
- On monolithic and Chorin-Temam schemes for incompressible flows in moving domains (Q2213753) (← links)
- Goal-oriented error estimation for the automatic variationally stable FE method for convection-dominated diffusion problems (Q2214461) (← links)
- Data-driven discovery of PDEs in complex datasets (Q2214651) (← links)
- Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty (Q2214671) (← links)
- Finite element solvers for Biot's poroelasticity equations in porous media (Q2214949) (← links)
- Symplectic dynamical low rank approximation of wave equations with random parameters (Q2216487) (← links)
- MFEM: a modular finite element methods library (Q2217082) (← links)
- The \textsc{Dune} framework: basic concepts and recent developments (Q2217088) (← links)
- LE\textsc{o}P\textsc{art}: a particle library for FE\textsc{ni}CS (Q2217108) (← links)
- T-IFISS: a toolbox for adaptive FEM computation (Q2217126) (← links)
- DuMu\(^{\text x} 3\) -- an open-source simulator for solving flow and transport problems in porous media with a focus on model coupling (Q2217142) (← links)
- A moving-domain CFD solver in FEniCS with applications to tidal turbine simulations in turbulent flows (Q2217154) (← links)
- FEM based robust design optimization with Agros and Ārtap (Q2217161) (← links)
- Open-source immersogeometric analysis of fluid-structure interaction using FEniCS and tIGAr (Q2217162) (← links)
- Adaptive dimension reduction to accelerate infinite-dimensional geometric Markov chain Monte Carlo (Q2221416) (← links)
- Multifidelity probability estimation via fusion of estimators (Q2221438) (← links)
- Bi-fidelity stochastic gradient descent for structural optimization under uncertainty (Q2221705) (← links)
- Bayesian-based predictions of COVID-19 evolution in Texas using multispecies mixture-theoretic continuum models (Q2221727) (← links)
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data (Q2222275) (← links)
- Theory and computation of electromagnetic fields and thermomechanical structure interaction for systems undergoing large deformations (Q2222283) (← links)
- ConvPDE-UQ: convolutional neural networks with quantified uncertainty for heterogeneous elliptic partial differential equations on varied domains (Q2222287) (← links)
- A flux-jump preserved gradient recovery technique for accurately predicting the electrostatic field of an immersed biomolecule (Q2222411) (← links)
- Rational Krylov methods for functions of matrices with applications to fractional partial differential equations (Q2222430) (← links)
- A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the small data regime (Q2222510) (← links)
- Comparison of energy stable simulation of moving contact line problems using a thermodynamically consistent Cahn-Hilliard Navier-Stokes model (Q2222652) (← links)
- Modeling the dynamics of PDE systems with physics-constrained deep auto-regressive networks (Q2222972) (← links)
- Development and analysis of both finite element and fourth-order in space finite difference methods for an equivalent Berenger's PML model (Q2223209) (← links)
- Adaptive \(C^0\) interior penalty methods for Hamilton-Jacobi-Bellman equations with cordes coefficients (Q2223838) (← links)
- Modeling, simulation, and optimization of geothermal energy production from hot sedimentary aquifers (Q2225332) (← links)
- PorePy: an open-source software for simulation of multiphysics processes in fractured porous media (Q2225348) (← links)
- Machine learning for accelerating macroscopic parameters prediction for poroelasticity problem in stochastic media (Q2226818) (← links)
- Banach spaces-based analysis of a fully-mixed finite element method for the steady-state model of fluidized beds (Q2226821) (← links)
- Extended group finite element method (Q2227999) (← links)
- A priori error estimates for the space-time finite element discretization of an optimal control problem governed by a coupled linear PDE-ODE system (Q2230371) (← links)
- High-performance implementation of discontinuous Galerkin methods with application in fluid flow (Q2230451) (← links)
- Theory and implementation of coupled port-Hamiltonian continuum and lumped parameter models (Q2231122) (← links)
- Constraint-preserving hybrid finite element methods for Maxwell's equations (Q2231648) (← links)
- Optimal control of the principal coefficient in a scalar wave equation (Q2234311) (← links)
- A locking-free finite element formulation for a non-uniform linear viscoelastic Timoshenko beam (Q2234892) (← links)
- A hyper-reduction method using adaptivity to cut the assembly costs of reduced order models (Q2236908) (← links)
- Machine learning augmented reduced-order models for FFR-prediction (Q2237421) (← links)
- Automatically adaptive, stabilized finite element method via residual minimization for heterogeneous, anisotropic advection-diffusion-reaction problems (Q2237764) (← links)
- Planar multi-patch domain parameterization for isogeometric analysis based on evolution of fat skeleton (Q2237787) (← links)
- Dimensionally consistent preconditioning for saddle-point problems (Q2237836) (← links)
- A weighted POD-reduction approach for parametrized PDE-constrained optimal control problems with random inputs and applications to environmental sciences (Q2239119) (← links)
- Parameter identification of a second-gradient model for the description of pantographic structures in dynamic regime (Q2239288) (← links)
- Adaptive mesh refinement and coarsening for diffusion-reaction epidemiological models (Q2241891) (← links)
- Simple and robust element-free Galerkin method with almost interpolating shape functions for finite deformation elasticity (Q2243451) (← links)
- A review on deep reinforcement learning for fluid mechanics (Q2245392) (← links)
- Immersed boundary finite element method for blood flow simulation (Q2245571) (← links)
