Last edited by Taumi
Friday, April 24, 2020 | History

3 edition of Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics found in the catalog.

Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics

Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics

  • 367 Want to read
  • 16 Currently reading

Published by Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, National Technical Information Service, distributor in Hampton, VA, [Springfield, Va .
Written in English

    Subjects:
  • Boundary conditions.,
  • Dissipation.,
  • Finite difference theory.,
  • Fourier analysis.,
  • Runge-Kutta method.,
  • Sound waves.,
  • Time marching.,
  • Wave dispersion.,
  • Wave equations.,
  • Wave propagation.

  • Edition Notes

    Other titlesLow dissipation and -disperson Runge-Kutta schemes for computational acoustics.
    StatementF.Q. Hu, M.Y. Hussaini, J. Manthey.
    SeriesICASE report -- no. 94-102., NASA contractor report -- 195022., NASA contractor report -- NASA CR-195022.
    ContributionsHussaini, M. Yousuff., Manthey, J., Institute for Computer Applications in Science and Engineering.
    The Physical Object
    FormatMicroform
    Pagination1 v.
    ID Numbers
    Open LibraryOL18083169M

    All the primitive variables, auxiliary variables and reconstructed variables are stored in a consistent way with the Taylor-basis DG counterpart. The fully implicit method is implemented for steady problems, while a third-order implicit Runge-Kutta (IRK), i.e., ESDIRK3 time marching method is implemented for unsteady flows. O Scribd é o maior site social de leitura e publicação do mundo.


Share this book
You might also like
Grade-level program document

Grade-level program document

Asas story

Asas story

Builders guide to passive solar home design and land development

Builders guide to passive solar home design and land development

Falmouth reservoir.

Falmouth reservoir.

Writing role playing games in AMOS.

Writing role playing games in AMOS.

lamp of the wicked

lamp of the wicked

Legislative history of the Fishery conservation and management act of 1976

Legislative history of the Fishery conservation and management act of 1976

Big as life

Big as life

Charitable gambling impact study

Charitable gambling impact study

Surface temperature reconstructions for the last 2,000 years

Surface temperature reconstructions for the last 2,000 years

Banking Operations

Banking Operations

Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics Download PDF EPUB FB2

Low-Dissipation and -Dispersion Runge-Kutta (LDDRK) schemes are proposed, based on an optimization that minimizes the dissipation and dispersion errors for wave propagation. order Optimizations of both single-step and two-step alternating schemes are considered.

A Low-Dispersion and Low-Dissipation Implicit Runge-Kutta Scheme Article in Journal of Computational Physics (1) January with Reads How we measure 'reads'. A new fourth-order six-stage Runge–Kutta numerical integrator that requires 2N-storage (N is the number of degrees of freedom of the system) Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics book low.

Low-dissipation and low-dispersion Runge-Kutta schemes Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics book computational acoustics Journal Article Hu, F Q ; Manthey, J L ; Hussaini, M Y - Journal of Computational Physics In this paper, we investigate accurate and efficient time advancing methods for computational acoustics, where nondissipative and nondispersive properties are of critical.

Hu, F.Q. Hussaini, M.Y. Manthey, J.L. Low-Dissipation and Low-Dispersion Runge-Kutta Schemes for Computational Acoustics Journal of Computational Physics Hu, F.Q. On Absorbing Boundary Conditions of Linearized Euler Equations by a Perfectly Matched Layer Journal of Computational Physics Author: Christopher K.

Tam. Hyperbolic Runge–Kutta Method Using Evolutionary Algorithm A. Arun Govind Neelan, Low-Dissipation Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics book Low-Dispersion Runge–Kutta Schemes for Computational Acoustics,” Optimized Low Dispersion and Low Dissipation Runge-Kutta Algorithms in Author: A.

Arun Govind Neelan, Manoj T. Nair. Stanescu, W.G. Habashi2N-storage low dissipation and dispersion Runge–Kutta schemes for computational acoustics J. Comput. Phys., (2) (), pp. Cited by: Low-dissipation and low-dispersion Runge–Kutta schemes for computational acoustics.

Journal of Computational Physics, (1), pp. – Hu, F. On absorbing boundary conditions for linearized Euler equations by a perfectly matched layer.

Journal of Computational Physics, (1), pp. –   Towards Clean Propulsion with Synthetic Fuels: Computational Aspects and Analysis.

J.L. Manthey, Low-dissipation and low-dispersion Runge-Kutta schemes for computational acoustics. Comput. Pitsch H. () Towards Clean Propulsion with Synthetic Fuels: Computational Aspects and Analysis. In: Nagel W., Kröner D., Resch M. (eds) High Author: Mathis Bode, Marco Davidovic, Heinz Pitsch.

Abstract. Low-dissipation and -disperson Runge-Kutta schemes for computational acoustics book this contribution, we present an application of a computational aeroacoustics code as a hybrid Zonal DNS tool. The extension of the Non-Linear Perturbation Equations (NLPE) with viscous terms is presented as well as Cited by: 7.

SIAM Journal on Numerical Analysis() A low-dispersion and low-dissipation implicit Runge–Kutta scheme. Journal of Computational Physics() Development of semi-implicit Runge-Kutta schemes and application to Cited by: A new time domain methodology for Computational Aeroacoustics (CAA) is proposed.

The time domain wave packet (TDWP) method employs a temporally compact broadband pulse for acoustic sources.

As the radiation and transmission of acoustic waves of all frequencies within the numerical resolution are embedded in the propagation of the wave packet Cited by: 2. Hu, F. Q., Hussaini, M. Y., and Manthey, J., Low-dissipation and low-dispersion Runge-Kutta schemes for computational acoustics, NASA CR, Google Scholar [11] Book Review: The Finite Difference Method in Partial Differential Equations Cited by: Low-dissipation and low­ dispersion Runge-Kutta schemes for computational acous­ tics.

J Comp Phys ; [8] Tam C, Dong Z. Wall boundary condition for high-order finite-difference schemes in computational : W. Schröder, R. Ewert. () A strongly S-stable low-dissipation and low-dispersion Runge-Kutta scheme for convection diffusion systems.

Aerospace Science and Technol () Optimized diagonally implicit Runge-Kutta schemes for time-dependent wave propagation by:   In this paper, an explicit acoustical wave propagator (AWP) is introduced to described the time-domain evolution of acoustical waves.

Hu, M. Hussaini, and J. Manthey, “ Low-dissipation and low-dispersion Runge–Kutta schemes for computational acoustics,” J. Comput. by:   There are several areas, however, where the numerical anisotropy can significantly affect the numerical solution based on finite difference or finite volume schemes (examples include computational acoustics, computational electromagnetics, elasticity or seismology).Cited by: 4.

Low-dissipation and low-dispersion Runge–Kutta schemes for computational acoustics. J Comput Phys ; – Google Scholar | Crossref | ISI. Aeroacoustics of a stagnation flow near a rigid wall Physics of Flu ( “ Low-dissipation and low-dispersion Runge–Kutta schemes for computational aeroacoustics,” J.

Comput. Phys.Cited by: Hu FQ, Hussaini MY, Manthey JL () Low-dissipation and low-dispersion runge-kutta schemes for computational acoustics. J Comput Physics (1)– zbMATH CrossRef MathSciNet Google Scholar [34]Cited by: 1.

In time, Runge-Kutta (Low Dispersion and Dissipation Runge-Kutta) method with low-dispersion and low-dissipation was applied to push ahead. Nonreflecting boundary condition was adopted at the far-field boundary. In the meanwhile, numerical filtering was conducted for numerically computational : Guo-bing Fan, Jian-ming Yan.

of the numerical anisotropy was performed in the book of Vichnevetsky [45] where, among others, 2N-storage low-dissipation dispersion Runge-Kutta schemes for computational acoustics, Journal of Computational Physics Vol.

pp. ().Cited by: 4. This paper presents the development of a fourth-order finite difference computational aeroacoustics solver. The solver works with a structured multi-block grid domain strategy, and it has been parallelized efficiently by using an interface treatment based on the method of characteristics.

More importantly, it extends the characteristic boundary condition Author: Bidur Khanal, Alistair Saddington, Kevin Knowles. Full text of "Second Computational Aeroacoustics (CAA) Workshop on Benchmark Problems" See other formats. acoustics based on a hybrid approach using linearized equations, like linearized Euler Equations, Linearized Perturbed Compressible Equations etc.

For numerical methods, the well-known techniques like DRP-scheme for spatial discretization, low-dissipation and low-dispersion Runge-Kutta schemes of fourth order. Low-dissipation and -dispersion Runge-Kutta schemes for computational acoustics.

Journal Computers of Physics,DUCK, P. W., LASSEIGNE, D. G., & Hussaini, M. On the interaction between the shock wave attached to a wedge and freestream disturbances.

THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS, 7, The DGM formulation for the LNS equations is described in Section 3, as well as the time integration algorithm, based on a low dissipation formulation of a fourth-order accurate Runge–Kutta scheme.

Explicit time integration, more appropriate for acoustic wave propagation, avoids the inversion of a large algebraic system, and it is well Cited by: 2. This series of volumes on the “Frontiers of Computational Fluid Dynamics” was introduced to honor contributors who have made a major impact on the field.

The first volume was published in and was dedicated to Prof Antony Jameson; the second was published in and was dedicated to Prof Earl Murman. Appadu R Optimized low dispersion and low dissipation Runge-Kutta algorithms in computational aeroacoustics.

Applied Mathematics & Information Sciences, 8(1)(), Appadu AR Applications and spectral analysis of some optimized high order low dispersion and low dissipation schemes.

schemes: the DRP scheme and the OPC scheme. A low dispersion and low dissipation Runge-Kutta proposed by Hu and coworkers () is employed for the time stepping procedure, and combined with the DRP and OPC schemes.

A study of the dispersive characteristics and stability is presented for these schemes. The boundary treatment is presented in. High-order finite difference schemes can be classified into two main categories: explicit schemes and Pade-type or compact schemes. Explicit schemes compute the numerical derivatives directly at each grid by using large stencils, while compact schemes obtain all the numerical derivatives along a grid line using smaller stencils and solving a.

However, numerical dissipation can still be introduced by time integration, e.g., explicit Runge-Kutta schemes. We recently analysed and compared several 6th-order spatial schemes for LES: the standard central FD, the upwind-biased FD, the filtered compact difference (FCD), and the discontinuous Galerkin (DG) schemes, with the same time.

AA Aero- and Thermo-Acoustical Coupling in Energy Applications I • Tuesday, 08 June • hrs. A generalized sound extrapolation method for turbulent flows. Siyang Zhong. The two-stage fourth-order low-dissipation low-dispersion Runge–Kutta (LDDRK) scheme Low-dissipation and low-dispersion Runge–Kutta schemes for computational acoustics.

by: 8. Brehler, M. Schirwon, D. Göddeke, and P. Krummrich, “A GPU-Accelerated Fourth-Order Runge-Kutta in the Interaction Picture Method for the Simulation of Nonlinear Signal Propagation in Multimode Fibers,” Journal of Lightwave Technology, vol.

35, no. 17, pp. –, Jeffery White, Robert Baurle, Travis Fisher, Jesse Quinlan and William Black Low-Dissipation Advection Schemes Designed for Large Eddy Simulations of Hypersonic Propulsion Systems / Alexander Kurganov and Yu Liu, New adaptive artificial viscosity method for hyperbolic systems of conservation laws, Journal of Computational.

Full text of "Advanced Computational Methods In Science And Engineering" See other formats. Bogey, C. & Bailly, C.,Direct computation of infrasound propagation in inhomogeneous atmosphere using a low-dispersion and low-dissipation algorithm, in Computational Fluid Dynamicsedited by H.

Choi, H.G. Choi & J.Y. Yoo, Springer, ISBN. Computational Fluid Dynamics. CHAPMAN & HALL/CRC Numerical Analysis and Scientific Computing Aims and scope: Scientific computing and numerical analysis provide invaluable tools for the sciences and engineering.

This series aims to capture new developments and summarize state-of-the-art methods over the whole spectrum of these fields. Time discretization is carried out based on a fourth-order Runge–Kutta scheme and spatial discretization is based on a fourth-order staggered scheme.

We have performed comparisons, not shown here, that demonstrate that in our case there is no significant benefit of using a more sophisticated scheme such as a low-dissipation and low-dispersion Cited by: 6.

Table pdf contents for issues of Journal of Scientific Computing Last update: Fri Sep 13 MDT Volume 1, Number 1, Volume 1, Number 2, Volume 2, Number 1, March, Volume 2, Number 2, June, Volume 2, Number 3, September, Volume 2, Number 4, December, Series = {Lecture Notes in computational science and engineering}, Volume = {40}} @Article {AnBa01, Title = {Microlocal diagonalization of strictly hyperbolic pseudodifferential systems and application to the design of radiation conditions in electromagnetism}, Author = {X.

Antoine and H. Barucq}, Journal = {SIAM J. Appl. Math.}, Year = {}.Abarbanel, Saul; Ebook, David; Carpenter, Mark H., ON THE REMOVAL OF BOUNDARY ERRORS CAUSED BY RUNGE-KUTTA INTEGRATION OF NON-LINEAR PARTIAL DIFFERENTIAL EQUATIONS, ICASE ReportBorggaard, Jeff; Burns, John, A SENSITIVITY EQUATION APPROACH TO SHAPE OPTIMIZATION IN FLUID FLOWS.