Results 61 to 70 of about 53,281 (190)

Multiscale Uncertainty Quantification with Arbitrary Polynomial Chaos

Computer Methods in Applied Mechanics and Engineering, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nick Pepper, Francesco Montomoli, Sanjiv Sharma   +2 more
openaire   +3 more sources

Polynomials and General Degree-Based Topological Indices of Generalized Sierpinski Networks

Complexity, 2021
Sierpinski networks are networks of fractal nature having several applications in computer science, music, chemistry, and mathematics. These networks are commonly used in chaos, fractals, recursive sequences, and complex systems.
Chengmei Fan, M. Mobeen Munir, Zafar Hussain, Muhammad Athar, Jia-Bao Liu   +4 more
doaj   +1 more source

Sensitivity Analysis of Metamaterial-Inspired SIW Focusing on Resonator Misalignment

IEEE Access
The performance of the metamaterial-inspired substrate-integrated waveguide is discussed in this work, concerning a resonator misalignment potentially caused by the fabrication process.
Stamatios A. Amanatiadis, Vasileios Salonikios, Michalis Nitas, Theodoros Zygiridis, Nikolaos V. Kantartzis, Traianos V. Yioultsis   +5 more
doaj   +1 more source

Stochastic tsunami inundation flow simulation via polynomial chaos approach

Journal of Fluid Science and Technology, 2018
In this research, 2D shallow water equations are expanded by an intrusive polynomial chaos approach for efficient uncertainty quantification in tsunami inundation flows.
Wataru YAMAZAKI, Tatsuya KATO, Tsubasa HOMMA, Koji SHIMOYAMA, Shigeru OBAYASHI   +4 more
doaj   +1 more source

Uncertainty Quantification of GEKO Model Coefficients on Compressible Flows

International Journal of Aerospace Engineering, 2021
In the present work, supersonic flows over an axisymmetric base and a 24-deg compression ramp are investigated using the generalized k-ω (GEKO) model implemented in the commercial software, ANSYS FLUENT.
Yeong-Ki Jung, Kyoungsik Chang, Jae Hyun Bae   +2 more
doaj   +1 more source

Efficient Statistical Extraction of the Per-Unit-Length Capacitance and Inductance Matrices of Cables with Random Parameters

Advanced Electromagnetics, 2015
Cable bundles often exhibit random parameter variations due to uncertain or uncontrollable physical properties and wire positioning. Efficient tools, based on the so-called polynomial chaos, exist to rapidly assess the impact of such variations on the ...
P. Manfredi, F. Canavero
doaj   +1 more source

Propagation of epistemic uncertainty in queueing models with unreliable server using chaos expansions

, 2017
In this paper, we develop a numerical approach based on Chaos expansions to analyze the sensitivity and the propagation of epistemic uncertainty through a queueing systems with breakdowns.
Abbas, Karim, Bachi, Katia, Chauvière, Cédric, Djellout, Hacène   +3 more
core  

Parameter Estimation for Mechanical Systems Using an Extended Kalman Filter [PDF]

, 2008
This paper proposes a new computational approach based on the Extended Kalman Filter (EKF) in order to apply the polynomial chaos theory to the problem of parameter estimation, using direct stochastic collocation.
Blanchard, Emmanuel, Sandu, Adrian, Sandu, Corina   +2 more
core  

Deep Polynomial Chaos Expansion

Polynomial chaos expansion (PCE) is a classical and widely used surrogate modeling technique in physical simulation and uncertainty quantification. By taking a linear combination of a set of basis polynomials - orthonormal with respect to the distribution of uncertain input parameters - PCE enables tractable inference of key statistical quantities ...
Exenberger, Johannes, Ranftl, Sascha, Peharz, Robert   +2 more
openaire   +2 more sources

Quantum computing of quantum chaos and imperfection effects

, 2000
We study numerically the imperfection effects in the quantum computing of the kicked rotator model in the regime of quantum chaos. It is shown that there are two types of physical characteristics: for one of them the quantum computation errors grow ...
A. Ekert, A. R. Calderbank, A. Steane, A. Steane, A. Sørensen, B. E. Kane, B. Georgeot, B. Georgeot, B. V. Chirikov, C. D. Bowden, C. Miquel, C. Miquel, C. Monroe, D. G. Cory, D. Jaksch, D. L. Shepelyansky, D. Loss, Dima L. Shepelyansky, E. Ott, F. L. Moore, F. M. Izrailev, G. Casati, G. K. Brennen, H. Ammann, J. I. Cirac, J. Preskill, L. K. Grover, L. M. K. Vandersypen, N. A. Gershenfeld, P. M. Platzman, P. W. Shor, Pil Hun Song, S. Fishman, V. Privman, Y. Nakamura   +34 more
core   +1 more source