2020
DOI: 10.1137/19m1276492
|View full text |Cite
|
Sign up to set email alerts
|

Multiscale Analysis of Spectral Broadening of Acoustic Waves by a Turbulent Shear Layer

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 23 publications
0
2
0
Order By: Relevance
“…Now (37) shows that if the ambient medium is frozen (i.e., independent of t), then the wave frequency is unchanged, as expected. Alternatively, a time-dependent ambient medium is responsible for the spectral broadening, or "haystacking," effect of the acoustic spectrum around a tone frequency [12,13,15,24,27]. Spatial variations of the ambient flow velocity and sound speed are responsible for the phase shift effect [31], which is manifested in the evolution of the wave vector k along the paths.…”
Section: Evolution Propertiesmentioning
confidence: 99%
See 1 more Smart Citation
“…Now (37) shows that if the ambient medium is frozen (i.e., independent of t), then the wave frequency is unchanged, as expected. Alternatively, a time-dependent ambient medium is responsible for the spectral broadening, or "haystacking," effect of the acoustic spectrum around a tone frequency [12,13,15,24,27]. Spatial variations of the ambient flow velocity and sound speed are responsible for the phase shift effect [31], which is manifested in the evolution of the wave vector k along the paths.…”
Section: Evolution Propertiesmentioning
confidence: 99%
“…ε n dp (2π) n f (εp) φ(k − p) , and thereforeP (x, εD x )f x ε φ(x) = R n dk (2π) n e ix•k P (x, εk) f n e ix•k P (x, εk) R n ε n dp (2π) n f (εp) φ(k − p) = R n dk (2πε) n e i x ε •k P (x, k) y ε •(k−p) φ(y)dy = R n e −i( x ε −y)•(k−p) φ(x − εy)ε n dy ,so that one finally hasP (x, εD x )f n e i x ε •k P (x, k) R n dp (2π) n f (p) R n x ×R n y e −i( x ε −y)•(k−p) φ(x−εy)ψ(x)ε n dydx = n e i x ε •p f (p)W ε [φ, ψ](x, k − p) ,which when identified with (78) gives the claimed result. Regarding(24), it now suffices to observe thatW ε f x ε P (x, εD x )φ, ψ = R n dp (2π) n e i x ε •p f (p)W ε [P (x, εD x )φ, ψ](x, k − p) = R n dp (2π) n e i x ε •p f (p)P (x, k − p)W ε [φ, ψ](x, k − p) + O(ε) ,…”
mentioning
confidence: 99%