Elsevier Science Home
Computer Physics Communications Program Library
Full text online from Science Direct
Programs in Physics & Physical Chemistry
CPC Home

[Licence| Download | New Version Template] absa_v1_0.gz(4 Kbytes)
Manuscript Title: A program for the extraction of bulk viscosities from sound absorption data.
Authors: H. Moraal
Catalogue identifier: ABSA_v1_0
Distribution format: gz
Journal reference: Comput. Phys. Commun. 3(1972)1
Programming language: Fortran.
Computer: IBM 360/75.
Operating system: HASP/0S 360.
RAM: 2K words
Word size: 32
Keywords: Liquid state physics, Plasma physics, Transport, Kinetic theory, Sound absorption, Rotational relaxation, Bulk viscosity, Least squares fitting.
Classification: 12, 19.11.

Nature of problem:
Sound absorption measurements in polyatomic gases contain information about the energetically inelastic collisions which take place in the gas, i.e., those collisions in which the rotational state of one or both of the molecules changes. This fact manifests itself through the so-called bulk or volume viscosity. It is the purpose of this communication to describe a method whereby a reduced bulk viscosity may be obtained from the sound absorption data directly.

Solution method:
The unknown bulk viscosity enters the problem as a parameter in a determinantal equation. The program is designed so as to reconstruct the polynomial in two variables represented by this equation. This part of the program is useful wherever a polynomial is given in a determinantal form. In this case considered here, the two variables are the complex propagation constant, the imaginary part of which is proportional to the measured sound absorption coefficient, and the reduced collision frequency. The coefficients of the reconstructed polynomial are now functions of the unknown. These values are chosen in a systematic way so as to minimise the sum of the squares of the calculated differences of the theoretical and measured sound absorption coefficients.

Unusual features:
The experimental data can directly be used as input for the program.

Running time:
The time depends on the number of experimental data available; for less than 50 data points the average is about 2-3 min.