The synthesis of spatially correlated random pressure fields

被引:28
|
作者
Elliott, SJ [1 ]
Maury, C
Gardonio, P
机构
[1] Univ Southampton, Inst Sound & Vibrat Res, Southampton SO17 1BJ, Hants, England
[2] Univ Technol Compiegne, Lab Roberval, CNRS, UMR 6066, F-60205 Compiegne, France
来源
关键词
D O I
10.1121/1.1850231
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
The feasibility is considered of synthesizing a spatially correlated random pressure field having specified statistical properties. Of particular interest is the use of a near-field array of acoustic sources to synthesize a pressure field whose statistical properties are similar to either a diffuse acoustic sound field or to that generated by a turbulent boundary layer (TBL). A formulation based on least-squares filter design is presented. Initially, the more fundamental question is addressed of how many uncorrelated signal components are required to approximate the pressure field. A one-dimensional analysis suggests that two uncorrelated components per acoustic wavelength are required to approximate a diffuse pressure field. Similarly, for a TBL pressure field, about one uncorrelated component per correlation length is required in the spanwise direction and about two uncorrelated components per correlation length are required in the streamwise direction. These estimates are in good agreement with theoretical predictions for an infinite array, based on the Fourier transform of the spatial correlation function. When a full simulation is performed, including the acoustic effect of an appropriately positioned array of monopole sources, it is found that the number of acoustic sources required to reasonably approximate the diffuse or TBL pressure field is only slightly greater than the lower bound on this number, set by the number of uncorrelated components required. (c) 2005 Acoustical Society of America.
引用
收藏
页码:1186 / 1201
页数:16
相关论文
共 50 条
  • [1] Estimation of Spatially-Correlated Random Fields With Compressed Observations
    Matamoros, Javier
    Anton-Haro, Carles
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2014, 13 (12) : 6542 - 6556
  • [2] A MULTILEVEL, HIERARCHICAL SAMPLING TECHNIQUE FOR SPATIALLY CORRELATED RANDOM FIELDS
    Osborn, Sarah
    Vassilevski, Panayot S.
    Villa, Umberto
    SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2017, 39 (05): : S543 - S562
  • [3] On Sampling Spatially-Correlated Random Fields for Complex Geometries
    Pezzuto, Simone
    Quaglino, Alessio
    Potse, Mark
    FUNCTIONAL IMAGING AND MODELING OF THE HEART, FIMH 2019, 2019, 11504 : 103 - 111
  • [4] Estimation of Spatially Correlated Random Fields in Heterogeneous Wireless Sensor Networks
    Nevat, Ido
    Peters, Gareth W.
    Septier, Francois
    Matsui, Tomoko
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (10) : 2597 - 2609
  • [5] An efficient and accurate algorithm for generating spatially-correlated random fields
    Fang, JN
    Tacher, L
    COMMUNICATIONS IN NUMERICAL METHODS IN ENGINEERING, 2003, 19 (10): : 801 - 808
  • [6] A Comparative Study of Stochastic Collocation Methods for Flow in Spatially Correlated Random Fields
    Chang, Haibin
    Zhang, Dongxiao
    COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 2009, 6 (03) : 509 - 535
  • [7] Gaussian Random Fields as a Model for Spatially Correlated Log-Normal Fading
    Catrein, Daniel
    Mathar, Rudolf
    ATNAC: 2008 AUSTRALASIAN TELECOMMUNICATION NETWOKS AND APPLICATIONS CONFERENCE, 2008, : 153 - 157
  • [8] MAPPING AND SYNTHESIS OF RANDOM PRESSURE FIELDS
    KAREEM, A
    JOURNAL OF ENGINEERING MECHANICS-ASCE, 1989, 115 (10): : 2325 - 2332
  • [9] A wave field synthesis approach to reproduction of spatially correlated sound fields
    Berry, Alain
    Dia, Rokhiya
    Robin, Olivier
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2012, 131 (02): : 1226 - 1239
  • [10] An algorithm for generating spatially correlated random fields using Cholesky decomposition and ordinary kriging
    Yang, Yang
    Wang, Pengfei
    Brandenberg, Scott J.
    COMPUTERS AND GEOTECHNICS, 2022, 147