Matches in SemOpenAlex for { <https://semopenalex.org/work/W2314657653> ?p ?o ?g. }
- W2314657653 endingPage "672" @default.
- W2314657653 startingPage "658" @default.
- W2314657653 abstract "Gradient-based sensitivity analysis has proven to be an enabling technology for many applications, including design of aerospace vehicles. However, conventional sensitivity analysis methods break down when applied to long-time averages of chaotic systems. This breakdown is a serious limitation because many aerospace applications involve physical phenomena that exhibit chaotic dynamics, most notably high-resolution large-eddy and direct numerical simulations of turbulent aerodynamic flows. A recently proposed methodology, Least Squares Shadowing (LSS), avoids this breakdown and advances the state of the art in sensitivity analysis for chaotic flows. The first application of LSS to a chaotic flow simulated with a large-scale computational fluid dynamics solver is presented. The LSS sensitivity computed for this chaotic flow is verified and shown to be accurate, but the computational cost of the current LSS implementation is high." @default.
- W2314657653 created "2016-06-24" @default.
- W2314657653 creator A5001238065 @default.
- W2314657653 creator A5017800332 @default.
- W2314657653 creator A5030839520 @default.
- W2314657653 creator A5053423876 @default.
- W2314657653 date "2018-02-01" @default.
- W2314657653 modified "2023-09-27" @default.
- W2314657653 title "Least-Squares Shadowing Sensitivity Analysis of Chaotic Flow Around a Two-Dimensional Airfoil" @default.
- W2314657653 cites W1966804957 @default.
- W2314657653 cites W1972362214 @default.
- W2314657653 cites W1974961323 @default.
- W2314657653 cites W1977294541 @default.
- W2314657653 cites W1983425133 @default.
- W2314657653 cites W1987941491 @default.
- W2314657653 cites W1988939884 @default.
- W2314657653 cites W2000256143 @default.
- W2314657653 cites W2002027679 @default.
- W2314657653 cites W2004516350 @default.
- W2314657653 cites W2019766130 @default.
- W2314657653 cites W2020031325 @default.
- W2314657653 cites W2024907874 @default.
- W2314657653 cites W2027619967 @default.
- W2314657653 cites W2036965147 @default.
- W2314657653 cites W2041360742 @default.
- W2314657653 cites W2054148923 @default.
- W2314657653 cites W2073686912 @default.
- W2314657653 cites W2075808749 @default.
- W2314657653 cites W2118376564 @default.
- W2314657653 cites W2130112398 @default.
- W2314657653 cites W2132427836 @default.
- W2314657653 cites W2140153041 @default.
- W2314657653 cites W2141394518 @default.
- W2314657653 cites W2146156763 @default.
- W2314657653 cites W2146907324 @default.
- W2314657653 cites W2160194150 @default.
- W2314657653 cites W2286035548 @default.
- W2314657653 cites W2316128330 @default.
- W2314657653 cites W2332948682 @default.
- W2314657653 cites W2416437410 @default.
- W2314657653 cites W2505374426 @default.
- W2314657653 cites W2728788387 @default.
- W2314657653 cites W4241674377 @default.
- W2314657653 cites W2963829141 @default.
- W2314657653 doi "https://doi.org/10.2514/1.j055389" @default.
- W2314657653 hasPublicationYear "2018" @default.
- W2314657653 type Work @default.
- W2314657653 sameAs 2314657653 @default.
- W2314657653 citedByCount "14" @default.
- W2314657653 countsByYear W23146576532019 @default.
- W2314657653 countsByYear W23146576532020 @default.
- W2314657653 countsByYear W23146576532021 @default.
- W2314657653 countsByYear W23146576532022 @default.
- W2314657653 countsByYear W23146576532023 @default.
- W2314657653 crossrefType "journal-article" @default.
- W2314657653 hasAuthorship W2314657653A5001238065 @default.
- W2314657653 hasAuthorship W2314657653A5017800332 @default.
- W2314657653 hasAuthorship W2314657653A5030839520 @default.
- W2314657653 hasAuthorship W2314657653A5053423876 @default.
- W2314657653 hasBestOaLocation W23146576532 @default.
- W2314657653 hasConcept C105795698 @default.
- W2314657653 hasConcept C112124176 @default.
- W2314657653 hasConcept C121332964 @default.
- W2314657653 hasConcept C127413603 @default.
- W2314657653 hasConcept C13393347 @default.
- W2314657653 hasConcept C134306372 @default.
- W2314657653 hasConcept C154945302 @default.
- W2314657653 hasConcept C1633027 @default.
- W2314657653 hasConcept C185429906 @default.
- W2314657653 hasConcept C21200559 @default.
- W2314657653 hasConcept C24326235 @default.
- W2314657653 hasConcept C2524010 @default.
- W2314657653 hasConcept C2777052490 @default.
- W2314657653 hasConcept C33923547 @default.
- W2314657653 hasConcept C38349280 @default.
- W2314657653 hasConcept C41008148 @default.
- W2314657653 hasConcept C527307 @default.
- W2314657653 hasConcept C57879066 @default.
- W2314657653 hasConcept C9936470 @default.
- W2314657653 hasConceptScore W2314657653C105795698 @default.
- W2314657653 hasConceptScore W2314657653C112124176 @default.
- W2314657653 hasConceptScore W2314657653C121332964 @default.
- W2314657653 hasConceptScore W2314657653C127413603 @default.
- W2314657653 hasConceptScore W2314657653C13393347 @default.
- W2314657653 hasConceptScore W2314657653C134306372 @default.
- W2314657653 hasConceptScore W2314657653C154945302 @default.
- W2314657653 hasConceptScore W2314657653C1633027 @default.
- W2314657653 hasConceptScore W2314657653C185429906 @default.
- W2314657653 hasConceptScore W2314657653C21200559 @default.
- W2314657653 hasConceptScore W2314657653C24326235 @default.
- W2314657653 hasConceptScore W2314657653C2524010 @default.
- W2314657653 hasConceptScore W2314657653C2777052490 @default.
- W2314657653 hasConceptScore W2314657653C33923547 @default.
- W2314657653 hasConceptScore W2314657653C38349280 @default.
- W2314657653 hasConceptScore W2314657653C41008148 @default.
- W2314657653 hasConceptScore W2314657653C527307 @default.
- W2314657653 hasConceptScore W2314657653C57879066 @default.
- W2314657653 hasConceptScore W2314657653C9936470 @default.