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• W2816629103 abstract "Softening at elevated temperatures is known to be a serious problem in aluminium alloys which restricts its wide span of application. Existing database on age-hardenable aluminium alloys (2XXX, 6XXX and 7XXX) is utilized in consolidation to design Al alloy with superior performance measured in terms of the mechanical properties, viz. yield strength, ultimate tensile strength and %Elongation, at different temperature regimes. Data on all three alloy groups are merged to a single database for developing the data-driven rough-fuzzy model, to utilize the effect of all possible precipitations and achieve stability of microstructure at elevated temperatures, without significantly compromising the ductility. The database consists of fifteen compositional and processing variables as the input variables, and three mechanical properties as the outputs. Rough-fuzzy approach is employed for modelling the complex alloy system due to its capability to bring out the most significant variables (removing redundant ones), and to formulate if-then rules to explain the system by adding a fuzzy element to it. This makes the model transparent also. The problem with conflicting objectives of increasing strength as well as ductility, is solved through multi-objective optimization using genetic algorithm to design alloys. The alloy is designed from the Pareto solutions and when developed experimentally shows promising results for further exploration." @default.
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• W2816629103 date "2018-10-01" @default.
• W2816629103 modified "2023-10-05" @default.
• W2816629103 title "Intelligent design optimization of age-hardenable Al alloys" @default.
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• W2816629103 doi "https://doi.org/10.1016/j.commatsci.2018.07.006" @default.
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