An artificial neural network-based algorithm, which adequately captures the complexity of the temper embrittlement phenomenon in NiCrMoV steels has been developed in order to predict the FATT50% value of material as a function of the chemical composition and serviced time. The model, validated using published data, relies for its training on a very large experimental data set of serviced rotors, aged up to 88, 000 hours, and it captures the interactions between input parameters using complex non-linear functions. The results agree with considerations reported in literature and provide analytical relations between evolution of the FATT50% value at various ageing time for a specific alloy compositions, as well as the influence of the main elements in the alloy composition.

Modelling thermal ageing embrittlement in turbine rotors using neural networks / Zonfrillo, G.; Nappini, D.. - ELETTRONICO. - 3B:(2014), pp. 1-7. (Intervento presentato al convegno ASME Turbo Expo 2014 tenutosi a Düsseldorf (Germany) nel June 16–20 2014) [10.1115/GT2014-25443].

Modelling thermal ageing embrittlement in turbine rotors using neural networks

ZONFRILLO, GIOVANNI;NAPPINI, DUCCIO
2014

Abstract

An artificial neural network-based algorithm, which adequately captures the complexity of the temper embrittlement phenomenon in NiCrMoV steels has been developed in order to predict the FATT50% value of material as a function of the chemical composition and serviced time. The model, validated using published data, relies for its training on a very large experimental data set of serviced rotors, aged up to 88, 000 hours, and it captures the interactions between input parameters using complex non-linear functions. The results agree with considerations reported in literature and provide analytical relations between evolution of the FATT50% value at various ageing time for a specific alloy compositions, as well as the influence of the main elements in the alloy composition.
2014
ASME Turbo Expo 2014: Turbine Technical Conference and Exposition
ASME Turbo Expo 2014
Düsseldorf (Germany)
June 16–20 2014
Zonfrillo, G.; Nappini, D.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/944534
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