Back to Search
Start Over
Alloy Design Based on Computational Thermodynamics and Multi-objective Optimization: The Case of Medium-Mn Steels
- Source :
- Metallurgical and Materials Transactions A. 48:2584-2602
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- A new alloy design methodology is presented for the identification of alloy compositions, which exhibit process windows (PWs) satisfying specific design objectives and optimized for overall performance. The methodology is applied to the design of medium-Mn steels containing Al and/or Ni. By implementing computational alloy thermodynamics, a large composition space was investigated systematically to map the fraction and stability of retained austenite as a function of intercritical annealing temperature. Alloys exhibiting PWs, i.e., an intercritical annealing range, which when applied satisfies the given design objectives, were identified. A multi-objective optimization method, involving Pareto optimality, was then applied to identify a list of optimum alloy compositions, which maximized retained austenite amount and stability, as well as intercritical annealing temperature, while minimized overall alloy content. A heuristic approach was finally employed in order to rank the optimum alloys. The methodology provided a final short list of alloy compositions and associated PWs ranked according to their overall performance. The proposed methodology could be the first step in the process of computational alloy design of medium-Mn steels or other alloy systems.
- Subjects :
- Austenite
Materials science
Rank (linear algebra)
Heuristic (computer science)
Alloy
Metallurgy
Metals and Alloys
Stability (learning theory)
02 engineering and technology
Function (mathematics)
engineering.material
021001 nanoscience & nanotechnology
Condensed Matter Physics
Multi-objective optimization
020501 mining & metallurgy
Design objective
0205 materials engineering
Mechanics of Materials
engineering
0210 nano-technology
Subjects
Details
- ISSN :
- 15431940 and 10735623
- Volume :
- 48
- Database :
- OpenAIRE
- Journal :
- Metallurgical and Materials Transactions A
- Accession number :
- edsair.doi...........0fa911596abdad9820feea717edf52f2