Pages that link to "Item:Q401582"

The following pages link to The GNAT method for nonlinear model reduction: effective implementation and application to computational fluid dynamics and turbulent flows (Q401582):

Displaying 50 items.

• Reduced order borehole induction modelling (Q5071729) (← links)
• Reduced Operator Inference for Nonlinear Partial Differential Equations (Q5088794) (← links)
• Piecewise-Global Nonlinear Model Order Reduction for PDE-Constrained Optimization in High-Dimensional Parameter Spaces (Q5095491) (← links)
• SNS: A Solution-Based Nonlinear Subspace Method for Time-Dependent Model Order Reduction (Q5112544) (← links)
• Interpolatory Rational Model Order Reduction of Parametric Problems Lacking Uniform Inf-Sup Stability (Q5115712) (← links)
• Stability of Discrete Empirical Interpolation and Gappy Proper Orthogonal Decomposition with Randomized and Deterministic Sampling Points (Q5131990) (← links)
• Interpolation-Based Model Order Reduction for Polynomial Systems (Q5147986) (← links)
• A Novel Iterative Penalty Method to Enforce Boundary Conditions in Finite Volume POD-Galerkin Reduced Order Models for Fluid Dynamics Problems (Q5163915) (← links)
• Model Order Reduction for Problems with Large Convection Effects (Q5223287) (← links)
• Data-Driven Time Parallelism via Forecasting (Q5230597) (← links)
• Failure Probability Estimation of Linear Time Varying Systems by Progressive Refinement of Reduced Order Models (Q5237184) (← links)
• Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics (Q5254410) (← links)
• Reduced basis techniques for nonlinear conservation laws (Q5254430) (← links)
• Nonlinear Model Order Reduction via Dynamic Mode Decomposition (Q5357971) (← links)
• Nonintrusive Reduced Order Modelling of Convective Boussinesq Flows (Q5880413) (← links)
• Learning physics-based models from data: perspectives from inverse problems and model reduction (Q5887831) (← links)
• Reduced basis methods for time-dependent problems (Q5887836) (← links)
• An efficient data-driven multiscale stochastic reduced order modeling framework for complex systems (Q6048418) (← links)
• Neural-network-augmented projection-based model order reduction for mitigating the Kolmogorov barrier to reducibility (Q6054198) (← links)
• A non‐linear non‐intrusive reduced order model of fluid flow by auto‐encoder and self‐attention deep learning methods (Q6060947) (← links)
• An adaptive projection‐based model reduction method for nonlinear mechanics with internal variables: Application to thermo‐hydro‐mechanical systems (Q6069991) (← links)
• Space‐local reduced‐order bases for accelerating reduced‐order models through sparsity (Q6071407) (← links)
• Preconditioned least‐squares Petrov–Galerkin reduced order models (Q6071434) (← links)
• A new method to interpolate POD reduced bases–Application to the parametric model order reduction of a gas bearings supported rotor (Q6082584) (← links)
• Reduced order modeling of parametrized pulsatile blood flows: hematocrit percentage and heart rate (Q6085392) (← links)
• Efficient and accurate nonlinear model reduction via first-order empirical interpolation (Q6087928) (← links)
• Predictive reduced order modeling of chaotic multi-scale problems using adaptively sampled projections (Q6095092) (← links)
• On the impact of dimensionally-consistent and physics-based inner products for POD-Galerkin and least-squares model reduction of compressible flows (Q6095138) (← links)
• A reduced order with data assimilation model: theory and practice (Q6100085) (← links)
• Updating an uncertain and expensive computational model in structural dynamics based on one single target FRF using a probabilistic learning tool (Q6101638) (← links)
• Front transport reduction for complex moving fronts (Q6111405) (← links)
• A multifidelity deep operator network approach to closure for multiscale systems (Q6116145) (← links)
• Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems (Q6118558) (← links)
• Non-intrusive data-driven reduced-order modeling for time-dependent parametrized problems (Q6119246) (← links)
• Extended tensor decomposition model reduction methods: training, prediction, and design under uncertainty (Q6120135) (← links)
• Non-linear manifold reduced-order models with convolutional autoencoders and reduced over-collocation method (Q6158995) (← links)
• A nonlinear-manifold reduced-order model and operator learning for partial differential equations with sharp solution gradients (Q6185246) (← links)
• Energy-conserving hyper-reduction and temporal localization for reduced order models of the incompressible Navier-Stokes equations (Q6196594) (← links)
• Registration-based model reduction of parameterized PDEs with spatio-parameter adaptivity (Q6196631) (← links)
• Fluid structure interaction by means of variational multiscale reduced order models (Q6496290) (← links)
• A fast and accurate domain decomposition nonlinear manifold reduced order model (Q6497183) (← links)
• Finding characteristically rich nonlinear solution space: a statistical mechanics approach (Q6497775) (← links)
• Gappy AE: a nonlinear approach for gappy data reconstruction using auto-encoder (Q6550133) (← links)
• Reduced order multirate schemes in industrial circuit simulation (Q6551445) (← links)
• Field-to-field coupled fluid structure interaction: a reduced order model study (Q6553237) (← links)
• Efficient grid deformation using deterministic sampling-based data reduction (Q6553393) (← links)
• Parametrized reduced order modeling for cracked solids (Q6553425) (← links)
• A minimally invasive, efficient method for propagation of full-field uncertainty in solid dynamics (Q6554045) (← links)
• Fixed-precision randomized low-rank approximation methods for nonlinear model order reduction of large systems (Q6554164) (← links)
• Transported snapshot model order reduction approach for parametric, steady-state fluid flows containing parameter-dependent shocks (Q6555323) (← links)