Published July 2019 | Version v1
Journal article

Adjoint characteristic decomposition of one-dimensional waves

Creators

  • 1. Cambridge University, Engineering Department, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)

Description

Adjoint methods enable the accurate calculation of the sensitivities of a quantity of interest. The sensitivity is obtained by solving the adjoint system, which can be derived by continuous or discrete adjoint strategies. In acoustic wave propagation, continuous and discrete adjoint methods have been developed to compute the eigenvalue sensitivity to design parameters and passive devices (Aguilar et al., 2017, [1]). In this short communication, it is shown that the continuous and discrete adjoint characteristic decompositions, and Riemann invariants, are connected by a similarity transformation. The results are shown in the Laplace domain. The adjoint characteristic decomposition is applied to a one-dimensional acoustic resonator, which contains a monopole source of sound. The proposed framework provides the foundation to tackle larger acoustic networks with a discrete adjoint approach, opening up new possibilities for adjoint-based design of problems that can be solved by the method of characteristics.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.jcp.2019.03.032

Additional details

Identifiers

DOI
10.1016/j.jcp.2019.03.032;
PII
S0021999119302153;

Publishing Information

Journal Title
Journal of Computational Physics (Print)
Journal Volume
388
Journal Page Range
p. 454-461
ISSN
0021-9991
CODEN
JCTPAH

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54126784
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
ACOUSTICS; DESIGN; EIGENVALUES; MONOPOLES; ONE-DIMENSIONAL CALCULATIONS; RESONATORS; SENSITIVITY; SOUND WAVES; WAVE PROPAGATION
Descriptors DEC
ELECTRONIC EQUIPMENT; EQUIPMENT

Optional Information

Copyright
Copyright (c) 2019 Elsevier Inc. All rights reserved.