𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Modelling the tap density of inorganic powders using neural networks

✍ Scribed by Vincent Moreschi; Sylvain Lalot; Christian Courtois; Anne Leriche

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
714 KB
Volume
29
Category
Article
ISSN
0955-2219

No coin nor oath required. For personal study only.

✦ Synopsis

In the present study, the tap relative density of five inorganic powders is modelled using neural networks. These powders are similar in shape but have different true density. A large number of mixings are prepared from three classes (coarse, medium, and fine particles) and modelled. The inputs of the neural networks are the 23 weight percentage intervals of the grain size distribution (38-2000 m). The estimated values are compared to those obtained by factorial plans. It is shown that very accurate results are obtained with a unique relatively small neural network. Finally, the neural network is used to determine the mixing leading to the highest tap relative density.

📜 SIMILAR VOLUMES

MODELLING UNKNOWN STRUCTURAL SYSTEMS THR
MODELLING UNKNOWN STRUCTURAL SYSTEMS THROUGH THE USE OF NEURAL NETWORKS
✍ CHASSIAKOS, A. G.; MASRI, S. F. 📂 Article 📅 1996 🏛 John Wiley and Sons 🌐 English ⚖ 822 KB

This paper explores the potential of using neural networks to identify the internal forces of typical systems encountered in the field of earthquake engineering and structural dynamics. After formulating the identification task as a neural network learning procedure, the method is applied to a repre

Analysis of the effect of reinforcement
Analysis of the effect of reinforcement particles on the compressibility of Al–SiC composite powders using a neural network model
✍ H.R. Hafizpour; M. Sanjari; A. Simchi 📂 Article 📅 2009 🏛 Elsevier Science ⚖ 727 KB

A neural network (ANN) model was developed to predict the densification of composite powders in a rigid die under uniaxial compaction. Al-SiC powder mixtures with various reinforcement volume fractions (0-30%) and particle sizes (50 nm to 40 lm) were prepared and their compressibility was studied in