Model order reduction for real-time hybrid simulation: Comparing polynomial chaos expansion and neural network methods

Adaptive model predictive control for actuation dynamics compensation in real-time hybrid simulation

(2022) N. Tsokanas et al.   MECHANISM AND MACHINE THEORY

A model‐order reduction framework for hybrid simulation based on component‐mode synthesis

(2020) Gaetano Miraglia et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

A Self‐tuning Robust Control System for nonlinear real‐time hybrid simulation

(2020) Amin Maghareh et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

The Influence of the Activation Function in a Convolution Neural Network Model of Facial Expression Recognition

(2020) Yingying Wang et al.   Applied Sciences-Basel

A global sensitivity analysis framework for hybrid simulation

(2020) G. Abbiati et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Data-driven polynomial chaos expansion for machine learning regression

(2019) Emiliano Torre et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Knowledge-enhanced deep learning for simulation of tropical cyclone boundary-layer winds

(2019) Reda Snaiki et al.   JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS

Application of Artificial Neural Networks in Hybrid Simulation

(2019) Mucha   Applied Sciences-Basel

Benchmark control problem for real-time hybrid simulation

(2019) Christian E. Silva et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Dual Craig-Bampton component mode synthesis method for model order reduction of nonclassically damped linear systems

(2018) Fabian M. Gruber et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

(2018) Rohit K. Tripathy et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Model-reduction techniques for reliability-based design problems of complex structural systems

(2016) H.A. Jensen et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Metamodeling of dynamic nonlinear structural systems through polynomial chaos NARX models

(2015) M.D. Spiridonakos et al.   COMPUTERS & STRUCTURES

Model-reduction techniques for Bayesian finite element model updating using dynamic response data

(2014) H.A. Jensen et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A Short Review on Model Order Reduction Based on Proper Generalized Decomposition

(2011) Francisco Chinesta et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

Modeling hysteretic nonlinear behavior of bridge aerodynamics via cellular automata nested neural network

(2011) Teng Wu et al.   JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS

Adaptive sparse polynomial chaos expansion based on least angle regression

(2010) Géraud Blatman et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Dynamic mode decomposition of numerical and experimental data

(2010) PETER J. SCHMID   JOURNAL OF FLUID MECHANICS

Global sensitivity analysis using polynomial chaos expansions

(2007) Bruno Sudret   RELIABILITY ENGINEERING & SYSTEM SAFETY