A nonlinear reduced order modeling method for dynamic two|phase ...

A nonlinear reduced-order modeling method for dynamic two-phase ...

This article presents a nonlinear reduced-order modeling method for evaporators in vapor compression systems. This method utilizes linearized reduction ...

A nonlinear reduced-order modeling method for dynamic two-phase ...

A nonlinear reduced-order modeling method for dynamic two-phase flow heat exchanger simulations - Texas A&M University (TAMU) Scholar profile, educations, ...

A nonlinear reduced order modeling method for dynamic two-phase ...

Abstract. This article presents a nonlinear reduced-order modeling method for evaporators in vapor compression systems. This method utilizes linearized ...

Nonlinear reduced-order modeling of the forced and autonomous ...

The second model is based on the full nonlinear membrane equation, solved by means of a HDHB approach. The two models are adopted to investigate the forced ...

Nonlinear System Identification, Reduced Order Modeling, and ...

This method was recently applied to a beam with a bolted lap joint to identify the damping nonlinearities and the effects on the structural dynamics [8]. This ...

A Nonlinear Model Order Reduction Framework for Dynamic Vapor ...

This paper proposes a reduced order modeling approach for vapor compression cycles (VCC) that involves application of nonlinear model order reduction (MOR) ...

A reduced order method for nonlinear parameterized partial ...

Dynamic mode decomposition (DMD) is a popular and efficient data-driven method for ROM, however, it is proposed for the model order reduction of time-dependent ...

Reduced Order Modeling - MATLAB & Simulink - MathWorks

Reduced order modeling (ROM) and model order reduction (MOR) are techniques for reducing the computational complexity of a full-order, high-fidelity model.

Nonlinear Reduced-Order Modeling from Data by Prof. George Haller.

... reduced dynamics on these SSMs gives a rigorous way to construct accurate and predictive reduced-order models for solids, fluids, and ...

Reduced Order Models for Nonlinear Dynamic Analysis With ...

The reduced nonlinear forces are represented by a polynomial expansion obtained by the stiffness evaluation procedure (STEP) and then corrected by means of a ...

Data-driven nonlinear reduced-order modeling of unsteady fluid ...

In modeling the time-evolution of the reduced space, there are two main approaches, namely, black box modeling methods30 and dynamic system ...

Enhancing high-fidelity nonlinear solver with reduced order model

In this study, a novel ROM-assisted approach is developed to improve the computational efficiency of FOM nonlinear solvers by using ROM's ...

Reduced Order Modeling Based on Complex Nonlinear Modal ...

... two-step nonlinear reduced order modeling approach is proposed. First, the autonomous nonlinear system is analyzed using the generalized Fourier-Galerkin method ...

Data-based reduced-order modeling of nonlinear two-time-scale ...

Subsequently, a nonlinear sparse identification approach is employed to calculate a dynamic model of nonlinear first-order ordinary differential equations ...

What is nonlinear model reduction - oden.utexas.edu

The most popular method to reduce nonlinear systems is proper orthogonal decomposition (POD). To make the resulting reduced models computationally efficient, ...

A hybrid reduced-order modeling technique for nonlinear structural ...

Request PDF | A hybrid reduced-order modeling technique for nonlinear structural dynamic simulation | Thin-walled structures are always subjected to a large ...

Non-intrusive reduced order modelling for the dynamics of ...

Non-intrusive methods have been used since two decades to derive reduced-order models for geometrically nonlinear structures.

Nonlinear Model Order Reduction via Dynamic Mode Decomposition

We propose a new technique for obtaining reduced order models for nonlinear dynamical systems. Specifically, we advocate the use of the recently developed ...

‎Data-driven Reduced Order Modeling and Model Updating of ...

Many non-intrusive reduced order modeling methods ... nonlinear structures, providing accurate dynamic simulations with dramatically reduced computational cost.

Indirect reduced-order modelling: using nonlinear manifolds to ...

Early works have focused on modal reduction methods, originally developed for linear dynamics, in which the number of DOFs is reduced through a ...