Results 181 to 190 of about 411,141 (342)

A Novel Methodology for the Automatic Decomposition of HAWT Wakes With K‐Means Clustering

open access: yesWind Energy, Volume 28, Issue 7, July 2025.
ABSTRACT This work presents a novel and automatic approach to process data from computational fluid dynamics at runtime, to identify and separate different regions of wind turbine wakes. The methodology is based on partitional clustering, in particular k‐Means, and applied to large eddy simulation (LES) computations of the wake of a DTU‐10‐MW wind ...
Lorenzo Tieghi   +4 more
wiley   +1 more source

Uncertainty propagation and sensitivity analysis for constrained optimization of nuclear waste vitrification

open access: yesJournal of the American Ceramic Society, Volume 108, Issue 7, July 2025.
Abstract The vitrification of high‐level waste (HLW) by heating a mixture of glass‐forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses ...
LaGrande Gunnell   +5 more
wiley   +1 more source

A parameter transformation of the anisotropic Matérn covariance function

open access: yesCanadian Journal of Statistics, Volume 53, Issue 2, June 2025.
Abstract We describe a polar coordinate transformation of the anisotropy parameters of the Matérn covariance function, which provides two benefits over the standard parameterization. First, it identifies a single point (the origin) with the special case of isotropy.
Kamal Rai, Patrick E. Brown
wiley   +1 more source

Discrete Entropies of Chebyshev Polynomials

open access: yesMathematics
Because of its flexibility and multiple meanings, the concept of information entropy in its continuous or discrete form has proven to be very relevant in numerous scientific branches. For example, it is used as a measure of disorder in thermodynamics, as
Răzvan-Cornel Sfetcu   +2 more
doaj   +1 more source

Sparse graph signals – uncertainty principles and recovery

open access: yesGAMM-Mitteilungen, Volume 48, Issue 2, June 2025.
ABSTRACT We study signals that are sparse either on the vertices of a graph or in the graph spectral domain. Recent results on the algebraic properties of random integer matrices as well as on the boundedness of eigenvectors of random matrices imply two types of support size uncertainty principles for graph signals.
Tarek Emmrich   +2 more
wiley   +1 more source

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