Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines 2018
DOI: 10.1007/978-3-319-92943-9_2
|View full text |Cite
|
Sign up to set email alerts
|

Uncertainty Quantification in CFD: The Matrix of Knowledge

Abstract: of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specif… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
1
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 95 publications
0
1
0
Order By: Relevance
“…While such tensions exist for many of the derived LLR parameter values, we also find areas of congruence, particularly in the fundamental forms of mass-conditioned property kernels. Congruent results offer a necessary step of verification (e.g., Salvadori 2019), meaning that halo populations with consistent stellar MPRs emerge from independent solutions of the equations governing the complex, non-linear system of large-scale structure. A validation step using observational data must be done using observable proxies for the intrinsic true properties we use here.…”
Section: Introductionmentioning
confidence: 99%
“…While such tensions exist for many of the derived LLR parameter values, we also find areas of congruence, particularly in the fundamental forms of mass-conditioned property kernels. Congruent results offer a necessary step of verification (e.g., Salvadori 2019), meaning that halo populations with consistent stellar MPRs emerge from independent solutions of the equations governing the complex, non-linear system of large-scale structure. A validation step using observational data must be done using observable proxies for the intrinsic true properties we use here.…”
Section: Introductionmentioning
confidence: 99%
“…The NACA 0021 airfoil was evaluated with three mesh types: refined, medium, and coarse. Using the Grid Convergence Index (GCI) approach by Celik, the discretization error was assessed [21]. Simulations were conducted, and the average power coefficient values were found for each mesh.…”
Section: Grid Convergence Analysismentioning
confidence: 99%