Modeling of thermotransport phenomenon in metal alloys using artificial neural networks

Thermodiffusion in molten metals, also known as thermotransport, a phenomenon in which constituent elements of an alloy separate under the influence of non-uniform temperature field, is of significance in several applications. However, due to the complex inter-particle interactions, there is no theoretical formulation that can model this phenomenon with adequate accuracy. Keeping in mind the severe deficiencies of the present day thermotransport models and an urgent need of a reliable method in several engineering applications ranging from crystal growth to integrated circuit design to nuclear reactor designs, an engineering approach has been taken in which neurocomputing principles have been employed to develop artificial neural network models to study and quantify the thermotransport phenomenon in binary metal alloys. Unlike any other thermotransport model for molten metals, the neural network approach has been validated for several types of binary alloys, viz., concentrated, dilute, isotopic and non-isotopic metals. Additionally, to establish the soundness of the model and to highlight its potential as a unified computational analysis tool, it ability to capture several thermotransport trends has been shown. Comparison with other models from the literature has also been made indicating a superior performance of this technique with respect to several other well established thermotransport models.     

具有H2引燃的CH4，煤油超声速混合的三维数值研究

用双流体模型和分区算法,气相多组分N－S方程和液相Euler方程分别用迎风TVD格式和NND格式进行数值求解,相间相互作用项方程用二阶Runge-Kutta法求解,并首次对H2引燃的CH4和煤油横向喷射,混合问题进行了数值研究,结果表明：与喷射加碘空气的PLIF结果相比,本文和实验结果符合得很好,对直通道,后面喷嘴的穿透深度大,煤油较气态 穿透深度大,但难以被卷吸到喷嘴前的回流区内,流场出现无煤油区,H2和CH4均可扩散到回流区内,CH4和煤油引燃机理不同,对后台阶直通道,存在两个回流区,H2可扩散到这两个回流区,但CH4只能被卷吸到其喷嘴前的回流区,后台阶直通道增强混合的效果和引燃点火的可靠性更好。     

Convergence for a class of delayed recurrent neural networks without M-matrix condition

In this paper, we investigate the asymptotic behavior of solutions to a class of recurrent neural network model with delays. Without assuming M-matrix condition, it is shown that every solution of the network tends to an equilibrium point as t→∞. Our results improve and extend some corresponding ones already known.