Evolutionary Design of Nickel-Based Superalloys Using Data-Driven Genetic Algorithms and Related Strategies
Published 2014 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Evolutionary Design of Nickel-Based Superalloys Using Data-Driven Genetic Algorithms and Related Strategies
Authors
Keywords
-
Journal
MATERIALS AND MANUFACTURING PROCESSES
Volume 30, Issue 4, Pages 488-510
Publisher
Informa UK Limited
Online
2014-11-18
DOI
10.1080/10426914.2014.984203
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Soft computing techniques in advancement of structural metals
- (2013) S Datta et al. INTERNATIONAL MATERIALS REVIEWS
- Genetic Programming Evolved through Bi-Objective Genetic Algorithms Applied to a Blast Furnace
- (2013) Brijesh Kumar Giri et al. MATERIALS AND MANUFACTURING PROCESSES
- Optimal Design of Titanium Alloys for Prosthetic Applications Using a Multiobjective Evolutionary Algorithm
- (2013) Shubhabrata Datta et al. MATERIALS AND MANUFACTURING PROCESSES
- Designing Cu-Zr Glass Using Multiobjective Genetic Algorithm and Evolutionary Neural Network Metamodels–Based Classical Molecular Dynamics Simulation
- (2013) Ansul Bansal et al. MATERIALS AND MANUFACTURING PROCESSES
- Genetic Algorithms, a Nature-Inspired Tool: A Survey of Applications in Materials Science and Related Fields: Part II
- (2013) Wojciech Paszkowicz MATERIALS AND MANUFACTURING PROCESSES
- Computational thermodynamics, Gaussian processes and genetic algorithms: combined tools to design new alloys
- (2013) F Tancret MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING
- Multi-Objective Genetic Algorithms and Genetic Programming Models for Minimizing Input Carbon Rates in a Blast Furnace Compared with a Conventional Analytic Approach
- (2013) Rajesh Jha et al. STEEL RESEARCH INTERNATIONAL
- Promise of multiobjective genetic algorithms in coating performance formulation
- (2013) N. Chakraborti SURFACE ENGINEERING
- Using support vector machine for materials design
- (2013) Wen-Cong Lu et al. Advances in Manufacturing
- Genetic programming through bi-objective genetic algorithms with a study of a simulated moving bed process involving multiple objectives
- (2012) Brijesh Kumar Giri et al. APPLIED SOFT COMPUTING
- Pareto-optimal analysis of Zn-coated Fe in the presence of dislocations using genetic algorithms
- (2012) Pankaj Rajak et al. COMPUTATIONAL MATERIALS SCIENCE
- Calculation of alloying effect of Ruthenium in Ni-based single-crystal superalloys
- (2012) F. Sun et al. COMPUTATIONAL MATERIALS SCIENCE
- Computational thermodynamics and genetic algorithms to design affordable γ′-strengthened nickel–iron based superalloys
- (2012) F Tancret MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING
- Data-Driven Pareto Optimization for Microalloyed Steels Using Genetic Algorithms
- (2012) Aman Kumar et al. STEEL RESEARCH INTERNATIONAL
- Phases in Zn-coated Fe analyzed through an evolutionary meta-model and multi-objective Genetic Algorithms
- (2011) Pankaj Rajak et al. COMPUTATIONAL MATERIALS SCIENCE
- Application of genetic programming for modelling of material characteristics
- (2011) Leo Gusel et al. EXPERT SYSTEMS WITH APPLICATIONS
- Cu―Zn separation by supported liquid membrane analyzed through Multi-objective Genetic Algorithms
- (2011) Debanga Nandan Mondal et al. HYDROMETALLURGY
- Stress Corrosion Cracking Resistant Aluminum Alloys: Optimizing Concentrations of Alloying Elements and Tempering
- (2011) Suvrat Bhargava et al. MATERIALS AND MANUFACTURING PROCESSES
- A nature-inspired multi-objective optimisation strategy based on a new reduced space searching algorithm for the design of alloy steels
- (2010) Qian Zhang et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Analyzing Fe–Zn system using molecular dynamics, evolutionary neural nets and multi-objective genetic algorithms
- (2009) Baidurya Bhattacharya et al. COMPUTATIONAL MATERIALS SCIENCE
- Designing nanoprecipitation strengthened UHS stainless steels combining genetic algorithms and thermodynamics
- (2008) W. Xu et al. COMPUTATIONAL MATERIALS SCIENCE
- A response surface method-based hybrid optimizer
- (2008) Marcelo J. Colaço et al. INVERSE PROBLEMS IN SCIENCE AND ENGINEERING
- Optimizing chemistry of bulk metallic glasses for improved thermal stability
- (2008) G S Dulikravich et al. MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreDiscover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversation