1993
DOI: 10.1006/jcph.1993.1142
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Dispersion-Relation-Preserving Finite Difference Schemes for Computational Acoustics

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Cited by 1,974 publications
(1,257 citation statements)
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“…The LEE in generalized coordinates are solved using a finite-difference solver, in which spatial derivatives are approximated with a seven-point, fourth-order dispersion relation preserving (DRP) scheme [23]. A four-stage optimized explicit Runge-Kutta scheme [24] is used to advance the time solution.…”
Section: Methodsmentioning
confidence: 99%
“…The LEE in generalized coordinates are solved using a finite-difference solver, in which spatial derivatives are approximated with a seven-point, fourth-order dispersion relation preserving (DRP) scheme [23]. A four-stage optimized explicit Runge-Kutta scheme [24] is used to advance the time solution.…”
Section: Methodsmentioning
confidence: 99%
“…For aeroacoustics computations fourth order finite volume schemes have been designed and have successfully been exploited (e.g., see [23,46]), but their application is restricted by the requirement of carefully generated structured grids. Thus a higher order DG scheme appears to be a reliable alternative to existing approaches, as the obtained results demonstrate that the DG method is a strong candidate for computational aero-acoustics problems.…”
Section: Propagation Of a Spherical Acoustic Wavementioning
confidence: 99%
“…low dissipation and dispersion) to accurately resolve convective ow-features over a wide range of space/time scales and amplitudes. To meet this need, most prior approaches have utilized high-order accurate 每nite di erence methods such as the compact schemes in Reference [30] and the dispersion relation preserving methods in Reference [31]. Typically these methods utilize symmetric 每nite-di erence stencils that result in zero inherent numerical dissipation.…”
Section: Spatial Discretizationmentioning
confidence: 99%
“…We conclude this section with a comparison of the original formulation (15)- (17) and reformulation (31), (32). In reformulation (31), (32) the optimization variable is h = g t .…”
Section: Problem Reformulationmentioning
confidence: 99%