Results 71 to 80 of about 136,878 (263)

Deim-based pgd for multi-parametric nonlinear model reduction [PDF]

, 2013
A new technique for efficiently solving parametric nonlinear reduced order models in the Proper Generalized Decomposition (PGD) framework is presented here.
Aguado, Jose V., Chinesta, Francisco, Cueto, Elías, Huerta, Antonio, Leygue, Adrien   +4 more
core  

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Robust spectral proper orthogonal decomposition

Computer Physics Communications
Experimental measurements often present corrupted data and outliers that can strongly affect the main coherent structures extracted with the classical modal analysis techniques. This effect is amplified at high frequencies, whose corresponding modes are more susceptible to contamination from measurement noise and uncertainties.
Colanera A., Schmidt O. T., Chiatto M.
openaire   +2 more sources

Orthogonal decomposition of Lorentz transformations

, 2012
The canonical decomposition of a Lorentz algebra element into a sum of orthogonal simple (decomposable) Lorentz bivectors is discussed, as well as the decomposition of a proper orthochronous Lorentz transformation into a product of commuting Lorentz ...
Hanson, Jason
core   +1 more source

Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization

AIChE Journal, EarlyView.
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed, Tao Chen, Antonio del Rio Chanona, Lorenz T. Biegler, Michael Short   +4 more
wiley   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Proper orthogonal decomposition closure models for fluid flows: Burgers equation [PDF]

, 2013
This paper puts forth several closure models for the proper orthogonal decomposition (POD) reduced order modeling of fluid flows. These new closure models, together with other standard closure models, are investigated in the numerical simulation of the ...
Iliescu, Traian, San, Omer
core  

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, C. W. Rowley, C. W. Rowley, G. Berkooz, G. H. Golub, J. D. Murray, J. M. Burgers, L. Sirovich, Thorsten Bogner, W. H. Press   +9 more
core   +1 more source

A computationally optimal randomized proper orthogonal decomposition technique [PDF]

2016 American Control Conference (ACC), 2016
In this paper, we consider the model reduction problem of large-scale systems, such as systems obtained through the discretization of partial differential equations. We propose a computationally optimal randomized proper orthogonal decomposition (RPOD*) technique to obtain the reduced order model by perturbing the primal and adjoint system using ...
Yu, Dan, Chakravorty, Suman
openaire   +2 more sources

Analysis of astrometric catalogues with vector spherical harmonics

, 2012
Comparison of stellar catalogues with position and proper motion components using a decomposition on a set of orthogonal vector spherical harmonics. We show the theoretical and practical advantages of this technique as a result of invariance properties ...
Klioner, Sergei, Mignard, Francois
core   +3 more sources