Results 91 to 100 of about 13,481 (226)
Bi-fidelity reduced polynomial chaos expansion for uncertainty quantification [PDF]
, 2021 Felix Newberry +3 more
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, 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 +3 more
core
Simulation of Stochastic Quantum Systems Using Polynomial Chaos Expansions
Physical Review Letters, 2013 We present an approach to the simulation of quantum systems driven by classical stochastic processes that is based on the polynomial chaos expansion, a well-known technique in the field of uncertainty quantification. The polynomial chaos expansion represents the system density matrix as a series of orthogonal polynomials in the principle components of ...
Young, Kevin C., Grace, Matthew D.
openaire +4 more sources
Systematic Parameter Selection for Short Fiber Polymer Composite Direct Fiber Simulation
Polymer Composites, Volume 47, Issue 7, Page 6319-6340, 10 April 2026.Interactions of individually simulated fibers are systematically calibrated such that their orientation history agrees with the results from analytical orientation models. ABSTRACT The orientation of fibers in short discontinuous fiber reinforced polymer composites is a critical factor in determining final mechanical and thermal properties.
Jason B. Pierce, Douglas E. Smith
wiley +1 more source
Sensors, 2017 A microstructure beam is one of the fundamental elements in MEMS devices like cantilever sensors, RF/optical switches, varactors, resonators, etc.
Lili Gao, Zai-Fa Zhou, Qing-An Huang
doaj +1 more source
Engineering Reports, Volume 8, Issue 4, April 2026.Rat swarm position update mechanism in HRSA‐RSO, illustrating the collective exploration behavior around the prey target (A*, B*). ABSTRACT The permutation flow shop scheduling problem (PFSSP) is a classical NP‐hard problem that aims to determine an optimal job sequence across machines to minimize makespan.
Mourad Mzili +5 more
wiley +1 more source
Polynomial Chaos Expansion for Operator Learning
Operator learning (OL) has emerged as a powerful tool in scientific machine learning (SciML) for approximating mappings between infinite-dimensional functional spaces. One of its main applications is learning the solution operator of partial differential equations (PDEs).
Sharma, Himanshu +2 more
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Polynomial chaos expansion for sensitivity analysis of model output with dependent inputs
, 2021 Thierry A. Mara, William E. Becker
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A polynomial chaos expansion in dependent random variables
Journal of Mathematical Analysis and Applications, 2018 26 pages, three figures, four tables; accepted by Journal of Mathematical Analysis and Applications.
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