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7 - Optimization tools

Published online by Cambridge University Press:  03 February 2011

Hans Lukas
Affiliation:
Max-Planck Institute, Stuttgart
Suzana G. Fries
Affiliation:
SGF Scientific Consultancy
Bo Sundman
Affiliation:
Royal Institute of Technology, Stockholm
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Summary

In this chapter, two of the most commonly used types of software for optimization, BINGSS and PARROT, are described.

Common features

Handling bad starting coefficients

The definition of the “error” (vi in Eq. (2.52)) is based on the “calculated value” (Fi(Cj, xki)), which is often defined by an equilibrium calculation with two or more phases. The initial set of adjustable coefficients may result in improper Gibbs-energy functions, with which this equilibrium cannot be calculated. As an example, in Fig. 7.1 such a situation is shown for a two-phase equilibrium, liquid + bcc. There Gbcc at all compositions is larger than Gliquid and the construction of a common tangent is impossible, so also no equilibrium can be calculated numerically.

The experimental information is either “at temperature T1 there is a two-phase equilibrium, liquid + bcc, for which the composition of the bcc phase was measured as (xbcc = x′)” or “in a single-phase bcc sample of composition x′ on heating the first liquid appears at temperature T1” (see Fig. 4.4).

In the least-squares calculation for Eq. (2.52) no “calculated value” (Fi(Cj, xki)) can be provided as long as the starting values for the Gibbs-energy descriptions of liquid and bcc phases behave as in Fig. 7.1. To find better starting values by trial and error is not easy and is time-consuming. Therefore it is desirable to have a method whereby this problem is avoided and that can start even with a very bad initial set of adjustable coefficients.

Type
Chapter
Information
Computational Thermodynamics
The Calphad Method
, pp. 203 - 242
Publisher: Cambridge University Press
Print publication year: 2007

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  • Optimization tools
  • Hans Lukas, Max-Planck Institute, Stuttgart, Suzana G. Fries, SGF Scientific Consultancy, Bo Sundman, Royal Institute of Technology, Stockholm
  • Book: Computational Thermodynamics
  • Online publication: 03 February 2011
  • Chapter DOI: https://doi.org/10.1017/CBO9780511804137.008
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  • Optimization tools
  • Hans Lukas, Max-Planck Institute, Stuttgart, Suzana G. Fries, SGF Scientific Consultancy, Bo Sundman, Royal Institute of Technology, Stockholm
  • Book: Computational Thermodynamics
  • Online publication: 03 February 2011
  • Chapter DOI: https://doi.org/10.1017/CBO9780511804137.008
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Optimization tools
  • Hans Lukas, Max-Planck Institute, Stuttgart, Suzana G. Fries, SGF Scientific Consultancy, Bo Sundman, Royal Institute of Technology, Stockholm
  • Book: Computational Thermodynamics
  • Online publication: 03 February 2011
  • Chapter DOI: https://doi.org/10.1017/CBO9780511804137.008
Available formats
×