Zobrazeno 1 - 10
of 2 758
pro vyhledávání: '"polynomial chaos expansion"'
Publikováno v:
Yuanzineng kexue jishu, Vol 58, Iss 10, Pp 2153-2161 (2024)
Uncertainties on results of reactor physics calculations basically originate from uncertainties of solvers, modeling parameters and nuclear data. The uncertainty quantification (UQ) of import core parameters is critical for the safety and reliability
Externí odkaz:
https://doaj.org/article/26cbf4a8de204eec97bbab353bf19c53
Publikováno v:
Advances in Bridge Engineering, Vol 5, Iss 1, Pp 1-25 (2024)
Abstract The approximation of complex engineering problems and mathematical regressions serves as the authentic inspiration behind the artificial intelligence metamodeling methods. Among these methods, polynomial chaos expansion, along with artificia
Externí odkaz:
https://doaj.org/article/0524ac92236340fd963e88dc1992810e
Publikováno v:
气体物理, Vol 9, Iss 4, Pp 27-38 (2024)
Since random uncertainty may cause severe aerodynamic performance fluctuations for the wing-mounted aircraft, the Gaussian process regression (GPR) surrogate model method based on was proposed. The strategy of adding sample points by active-learning
Externí odkaz:
https://doaj.org/article/ebf9c64c656e44d9a8b9fef78ea3b1b7
Autor:
Richard Amankwa Adjei, Chengwei Fan
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 18, Iss 1 (2024)
In this paper, a multi-objective optimization strategy for efficient design of turbomachinery blades using sparse active subspaces is implemented for a turbofan stage design. The proposed strategy utilized sparse polynomial chaos expansion on a limit
Externí odkaz:
https://doaj.org/article/97745f659efa47d0ac7eeed02198eb8e
Autor:
Geremy Loachamín-Suntaxi, Paris Papavasileiou, Eleni D. Koronaki, Dimitrios G. Giovanis, Georgios Gakis, Ioannis G. Aviziotis, Martin Kathrein, Gabriele Pozzetti, Christoph Czettl, Stéphane P.A. Bordas, Andreas G. Boudouvis
Publikováno v:
Chemical Engineering Journal Advances, Vol 20, Iss , Pp 100667- (2024)
This work introduces a comprehensive approach utilizing data-driven methods to elucidate the deposition process regimes in Chemical Vapor Deposition (CVD) reactors and the interplay of physical mechanism that dominate in each one of them. Through thi
Externí odkaz:
https://doaj.org/article/4e9abd65e7e242f6ba248349f64fd7b0
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract This research introduces a novel global sensitivity analysis (GSA) framework for agent-based models (ABMs) that explicitly handles their distinctive features, such as multi-level structure and temporal dynamics. The framework uses Grassmanni
Externí odkaz:
https://doaj.org/article/fe75001948f84a6cac38e4fc4effdcec
Akademický článek
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Akademický článek
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Autor:
Zhanlin Liu, Youngjun Choe
Publikováno v:
Journal of Safety Science and Resilience, Vol 4, Iss 4, Pp 358-365 (2023)
Polynomial chaos expansions (PCEs) have been used in many real-world engineering applications to quantify how the uncertainty of an output is propagated from inputs by decomposing the output in terms of polynomials of the inputs. PCEs for models with
Externí odkaz:
https://doaj.org/article/7dc2ac8a9dc440f6984bb47c5668d3df