A new formulation for martensite start temperature of Fe–Mn–Si shape memory alloys using genetic programming

Autor:	Murat Eskil, Erdoğan Kanca
Rok vydání:	2008
Předmět:	Soft computing General Computer Science Chemistry Metallurgy Iron alloys General Physics and Astronomy Genetic programming General Chemistry Shape-memory alloy Computational Mathematics Mechanics of Materials Robustness (computer science) Martensite General Materials Science Algorithm
Zdroj:	Computational Materials Science. 43:774-784
ISSN:	0927-0256
Popis:	This study presents genetic programming (GP) soft computing technique as a new tool for the formulation of martensite start temperature ( M s ) of Fe–Mn–Si shape memory alloys for various compositions and heat treatments. The objective of this study is to provide a different formulation to design composition at certain ranges and to verify the robustness of GP for the formulation of such characterization problems. The training and testing patterns of the proposed GP formulation is based on well established experimental results from the literature. The GP based formulation results are compared with experimental results and found to be quite reliable.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5c3f65e2491f223c08bb336c5f729e0b https://doi.org/10.1016/j.commatsci.2008.01.042 Zobrazit plný text záznamu Full Text from ScienceDirect