Corrosion Behaviour of the Anodised A356 Aluminium Alloy Produced by the Rheo-High Pressure Die Casting Process

2014 ◽  
Vol 1019 ◽  
pp. 67-73 ◽  
Author(s):  
Levy Chauke ◽  
Kalenda Mutombo ◽  
Gonasagren Govender

<span><p>Semi-solid metal forming of aluminium alloys has demonstrated the capability to produce near net shaped high integrity components. Anodising of these components for aesthetic and/or improved corrosion resistance is specified by some designers or users of this technology. The corrosion behaviour of fully anodised and partially anodised A356 aluminium alloy plates produced using the CSIR Rheo-High Pressure Die Casting (CSIR-RHPDC) process was investigated using immersion testing in a 3.5% NaCl solution with pH = 7. Optical microscope equipped with image analysis software and scanning electron microscope (SEM) equipped with Energy Dispersive X-ray Spectroscopy (EDS) were used to evaluate the behaviour of the corroded samples. The fully anodised sample showed that the anodised surface displayed some surface degradation. This degradation was more severe on the anodised surface with surface liquid segregation (SLS), but provided sufficient protection to prevent corrosion of the base metal. The partially anodised sample showed severe corrosion of the based metal with the corrosion concentrated in the silicon rich eutectic and SLS regions.</p> <span style="font-family: Times New Roman; font-size: medium;" face="Times New Roman" size="3"> </span>

2012 ◽  
Vol 192-193 ◽  
pp. 161-166 ◽  
Author(s):  
Madeleine du Toit ◽  
Patronica Letsoalo ◽  
Heinrich Möller

Near-net shape casting of wrought aluminium alloys has proven to be difficult due to a tendency towards hot tearing during cooling. Rheocasting, or semi-solid metal (SSM) processing followed by high pressure die casting (HPDC), has recently been shown to be an effective alternative to conventional die casting, yielding near-net shape wrought aluminium alloy castings with less risk of hot tearing. This casting process involves pouring the liquid metal into a processing cup, which is then transferred into a coil for induction stirring and simultaneous forced air cooling. When the metal reaches the semi-solid casting temperature, the resultant slurry is transferred to a high pressure die casting machine and cast to near-net shape. This modifies the as-cast microstructure, yielding a more globular primary phase and results in mechanical properties in the -T6 condition closely approaching those of wrought material in the same condition. Little information is currently available on the response of SSM-HPDC material to welding. This project investigated the influence of autogenous laser and gas tungsten arc welding on the microstructure and mechanical properties of aluminium 7017 after rheocasting. It is possible to successfully weld this material without solidification or liquation cracking. The effect of welding on the rheocast microstructure in the heat-affected zone and weld metal was shown, and the hardness and tensile properties of the resulting joints in the as-welded condition were tested and related to the microstructures achieved.


Author(s):  
M. Imad Khan ◽  
Saeid Nahavandi ◽  
Yakov Frayman

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.


2019 ◽  
Vol 104 ◽  
pp. 177-188 ◽  
Author(s):  
Dorra Abid ◽  
Ahmed Ktari ◽  
Dhouha Mellouli ◽  
Nedia Gafsi ◽  
Nader Haddar

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