Results 41 to 50 of about 114,105 (252)
A Randomized Proper Orthogonal Decomposition Method for Reducing Large Linear Systems [PDF]
, 2015 The proper orthogonal decomposition (POD) method is a powerful tool for reducing large data systems which can quickly overwhelm modern computing tools. In this thesis we provide a link between randomized projections and statistical methods by introducing
Marvin, Brad
core
Guide to Spectral Proper Orthogonal Decomposition [PDF]
, 2020 This paper discusses the spectral proper orthogonal decomposition and its use in identifying modes, or structures, in flow data. A specific algorithm based on estimating the cross-spectral density tensor with Welch’s method is presented, and guidance is ...
Colonius, Tim, Schmidt, Oliver T.
core
Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems
Advanced Functional Materials, EarlyView.MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley +1 more source
Density Matrix Renormalization for Model Reduction in Nonlinear Dynamics
, 2007 We present a novel approach for model reduction of nonlinear dynamical systems based on proper orthogonal decomposition (POD). Our method, derived from Density Matrix Renormalization Group (DMRG), provides a significant reduction in computational effort ...
A. C. Antoulas +9 more
core +1 more source
Four Decades of Studying Global Linear Instability: Progress and Challenges [PDF]
, 2012 Global linear instability theory is concerned with the temporal or spatial development of small-amplitude perturbations superposed upon laminar steady or time-periodic three-dimensional flows, which are inhomogeneous in two(and periodic in one)or all ...
Gómez, F. +4 more
core +3 more sources
Proper Orthogonal Decomposition as Surrogate Model for Aerodynamic Optimization
International Journal of Aerospace Engineering, 2016 A surrogate model based on the proper orthogonal decomposition is developed in order to enable fast and reliable evaluations of aerodynamic fields. The proposed method is applied to subsonic turbulent flows and the proper orthogonal decomposition is ...
Valentina Dolci, Renzo Arina
doaj +1 more source
Applied Sciences, 2022 An enhanced interpolation approach is developed for simulating nonseparable nonstationary ground motions on the basis of the spectral representation method, which mainly contains two steps of interpolations and an optimization. Firstly, the interpolation
Ning Zhao +5 more
doaj +1 more source
Unlocking Photodetection Mode Switching from a Simple Lateral Design
Advanced Functional Materials, EarlyView.A simple lateral 2D perovskite photodetector capable of switching among transient, continuous, and dual transient/continuous photoresponse modes is achieved by integrating photoconductive effects with capacitive coupling from the SiO2/Si substrate. Such light‐programmable photodetection mode switching enables triple‐channel information transmission and
Zijun (June) Yong +10 more
wiley +1 more source
Application of machine learning to viscoplastic flow modeling
, 2018 We present a method to construct reduced-order models for duct flows of Bingham media. Our method is based on proper orthogonal decomposition (POD) to find a low-dimensional approximation to the velocity and artificial neural network to approximate the ...
Koroteev, D. +2 more
core +1 more source
Simulation of hyperelastic materials in real-time using Deep Learning [PDF]
, 2019 The finite element method (FEM) is among the most commonly used numerical methods for solving engineering problems. Due to its computational cost, various ideas have been introduced to reduce computation times, such as domain decomposition, parallel ...
Cotin, Stéphane +2 more
core +5 more sources