2000
DOI: 10.2514/2.963
|View full text |Cite
|
Sign up to set email alerts
|

Inverse Aeroacoustic Problem for a Rectangular Wing

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
3
0

Year Published

2002
2002
2024
2024

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 10 publications
(3 citation statements)
references
References 20 publications
0
3
0
Order By: Relevance
“…In the past decades, acoustic imaging methods based on microphone array measurements [16], such as beamforming methods [17,18], inverse methods [19,20] and nearfield acoustic holography methods [21,22], have been widely used to identify the aeroacoustic sources in moving medium. These methods were originally proposed for static aeroacoustic sources.…”
Section: Introductionmentioning
confidence: 99%
“…In the past decades, acoustic imaging methods based on microphone array measurements [16], such as beamforming methods [17,18], inverse methods [19,20] and nearfield acoustic holography methods [21,22], have been widely used to identify the aeroacoustic sources in moving medium. These methods were originally proposed for static aeroacoustic sources.…”
Section: Introductionmentioning
confidence: 99%
“…Lu et al [14], suggested a model of air acoustic of interactions in addition, a rotor and a stator according to integral equations of sound. Also, there are some other researches who worked on the interactions of a plate in a jet stream [15][16][17]. One of the most recent studies has been done by Trabelsi et al [18] where unsteady rotating forces in a fan have been derived using inverse method.…”
Section: Introductionmentioning
confidence: 99%
“…Inferring the noise source information from noise measurements is common in the acoustic community. For instance, the acoustic noise data have been used for localization of the noise source [37,38], detection of the underwater environment [39,40], and inversion of wall pressure [41,42]. Besides, inferring optimal parameters in a noise model [43,44] from noise data was also investigated.…”
mentioning
confidence: 99%