Tackling Flow Stress of Zirconium Alloys

摘要: Flow stress during hot deformation is essentially controlled by the chemistry of material, initial microstructure/texture, strain, strain rate, path, triaxility and temperature deformation. A comprehensive literature survey has been performed to realize this fact completely. In present research, a neural network model under Bayesian framework created correlate complex relationship between flow with its influencing parameters in various grades zirconium alloys at different conditions. The trained published experimental database obtained from experiments alloys. Performance evaluated; excellent agreements experimentally measured calculated data are obtained. analysis permits estimation error bars whose magnitude strongly depends on their position input space. employed confirm that predictions reasonably accurate context basic metallurgical/solid mechanics theories principles. work clearly identified regions space where further should be encouraged necessary. This will useful design manufacture new generation future for nuclear power plant components according needs engineers/scientists controlling alloying elements other possible result shows computation very effective tool $$\textit{non-linear}$$ behaviour any