Steady state thermal model for the hot chamber injection system in the pressure die casting process

1998 ◽  
Vol 82 (1-3) ◽  
pp. 27-45 ◽  
Author(s):  
I. Rosindale ◽  
K. Davey
Keyword(s):  
Steady State ◽  
Thermal Model ◽  
Die Casting ◽  
Casting Process ◽  
Injection System ◽  
Die Casting Process ◽  
Pressure Die Casting

Predicting heat extraction due to boiling in the cooling channels during the pressure die casting process

2000 ◽  
Vol 214 (3) ◽  
pp. 465-482 ◽  
Author(s):  
L D Clark ◽  
I Rosindale ◽  
K Davey ◽  
S Hinduja ◽  
P J Dooling
Keyword(s):  
Heat Transfer ◽  
Forced Convection ◽  
Die Casting ◽  
Casting Process ◽  
Nucleate Boiling ◽  
Heat Extraction ◽  
Film Boiling ◽  
Cooling Channels ◽  
Die Casting Process ◽  
Pressure Die Casting

The effect of boiling on the rate of heat extraction by cooling channels employed in pressure die casting dies is investigated. The cooling effect of the channels is simulated using a model that accounts for subcooled nucleate boiling and transitional film boiling as well as forced convection. The boiling model provides a continuous relationship between the rate of heat transfer and temperature, and can be applied to surfaces where forced convection, subcooled nucleate boiling and transitional film boiling are taking place in close proximity. The effects of physical parameters such as flow velocity, degree of subcooling, system pressure and bulk temperature are taken into account. Experimental results are obtained using a rig that simulates the pressure die casting process. The results are compared with the model predictions and are found to show good agreement. Instrumented field tests, on an industrial die casting machine, are also reported. These tests show the beneficial effects of boiling heat transfer in the pressure die casting process, including a 75 per cent increase in the production rate for the test component.

High-Pressure Die-Casting Process Modelling Using Neural Networks

2006 ◽  
pp. 182-198 ◽  
Author(s):  
M. Imad Khan ◽  
Saeid Nahavandi ◽  
Yakov Frayman
Keyword(s):  
High Pressure ◽  
Process Parameters ◽  
Current Knowledge ◽  
Die Casting ◽  
Process Condition ◽  
Industrial Process ◽  
Casting Process ◽  
High Pressure Die Casting ◽  
Die Casting Process ◽  
Pressure Die Casting

This chapter presents the application of a neural network to the industrial process modeling of high-pressure die casting (HPDC). The large number of inter- and intradependent process parameters makes it difficult to obtain an accurate physical model of the HPDC process that is paramount to understanding the effects of process parameters on casting defects such as porosity. The first stage of the work was to obtain an accurate model of the die-casting process using a feed-forward multilayer perceptron (MLP) from the process condition monitoring data. The second stage of the work was to find out the effect of different process parameters on the level of porosity in castings by performing sensitivity analysis. The results obtained are in agreement with the current knowledge of the effects of different process parameters on porosity defects, demonstrating the ability of the MLP to model the die-casting process accurately.

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