An ideal grain refiner has been designed for Al-7Si alloy by performing sensitivity analysis of trained artificial neural network (ANN) model. An ANNs model has been developed for solving these complex grain refinement phenomena in Al-7Si alloy. The model predictions and the analysis are well in agreement with the experimental results and existing metallurgical facts. Uncertainty in predictions helped in finding a new phenomenon at lower addition levels of grain refiner. © 2012 ASM International.

Budaraju Srinivasa Murty

Department of Metallurgical and Materials Engineering

ANNS MODELS

Artificial neural network models

GRAIN REFINER

Model prediction

Aluminum

Forecasting

Grain refinement

Grain size and shape

Neural Networks

Refining

Sensitivity analysis

Silicon

Silicon alloys

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Journal of Materials Engineering and Performance

Neural networks, which are known for mapping non-linear and complex systems, have been used in the present study to model the grain-refinement behavior of Al-7Si alloy. The development of a feed forward neural network (FFNN) model with back-propagation (BP) learning algorithm has been presented for the prediction of the grain size, as a function of Ti and B addition level and holding time during grain refinement of Al-7Si alloy. Comparison of the predicted and experimental results shows that the FFNN model can predict the grain size of Al-7Si alloy with good learning precision and generalization. © 2004 Elsevier B.V. All rights reserved.

Materials Science and Engineering A

Prediction of grain size of Al-7Si Alloy by neural networks

Materials Science and Engineering: A

Modeling medium carbon steels by using artificial neural networks

Encyclopedia of Materials: Science and Technology

Neural Networks in Materials Science

International Materials Reviews

Grain refinement of aluminium and its alloys by heterogeneous nucleation and alloying

Development of an efficient grain refiner for Al–7Si alloy

Design of an ideal grain-refiner alloy for Al-7Si alloy using artificial neural networks

Journal	Journal of Materials Engineering and Performance
ISSN	10599495
Open Access	No