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A Constraint Satisfaction Algorithm for the Generalized Inverse Phase Stability Problem
Author(s) -
Edgar Galvan,
Richard Malak,
Sean Gibbons,
Raymundo Arróyave
Publication year - 2016
Publication title -
journal of mechanical design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.911
H-Index - 120
eISSN - 1528-9001
pISSN - 1050-0472
DOI - 10.1115/1.4034581
Subject(s) - pointwise , stability (learning theory) , inverse problem , mathematical optimization , constraint (computer aided design) , phase (matter) , mathematics , algorithm , phase diagram , inverse , computer science , mathematical analysis , physics , geometry , quantum mechanics , machine learning
Researchers have used the (calculation of phase diagram) CALPHAD method to solve the forward phase stability problem of mapping from specific thermodynamic conditions (material composition, temperature, pressure, etc.) to the associated phase constitution. Recently, optimization has been used to solve the inverse problem: mapping specific phase constitutions to the thermodynamic conditions that give rise to them. These pointwise results, however, are of limited value since they do not provide information about the forces driving the point to equilibrium. In this paper, we investigate the problem of mapping a desirable region in the phase constitution space to corresponding regions in the space of thermodynamic conditions. We term this problem the generalized inverse phase stability problem (GIPSP) and model the problem as a continuous constraint satisfaction problem (CCSP). In this paper, we propose a new CCSP algorithm tailored for the GIPSP. We investigate the performance of the algorithm on Fe–Ti binary alloy system using ThermoCalc with the TCFE7 database against a related algorithm. The algorithm is able to generate solutions for this problem with high performance.

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