Wyniki wyszukiwania - BazTech

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Microstructure, mechanical performance and wear behavior of AZ91D-B4C-ZrO2 hybrid composites

Gali Singaiah, Prattipati Prasanna

Composites Theory and Practice

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2022

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R. 22, nr 4

219--224

EN

The stir casting process was used to produce AZ91D magnesium alloy hybrid composites reinforced with boron carbide (B4C) and zirconia (ZrO2). The microstructure of the composites revealed heterogeneity in the reinforcing phase distribution. A pin-on-disc test was conducted to investigate the tribological features of the fabricated composites such as the wear and coefficient of friction under dry sliding conditions. Increased hardness was observed for the composites due to the dispersion of the reinforcement. The composite with 2 wt.% ZrO2 + 3 wt.% B4C exhibited a higher yield strength and increased tensile strength compared with the other specimens. It was observed that the addition of B4C and ZrO2 improved the wear resistance of the AZ91D alloy as reflected by the lower wear rate. Among all the specimens, the composite reinforced with 2 wt.% ZrO2 + 3 wt.% B4C has the highest wear resistance. Hence, it can be concluded from the present work that incorporating B4C and ZrO2 is a promising way to achieve better mechanical properties and wear properties of AZ91 composites.

2

Artificial neural networks in mechanical surface enhancement technique for the prediction of surface roughness and microhardness of magnesium alloy

Cagan S. C., Maci M., Buldum M. M., Maci C.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2019

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Vol. 67, nr 4

729--739

EN

The artificial neural network method (ANN) is widely used in both modeling and optimization of manufacturing processes. Determination of optimum processing parameters plays a key role as far as both cost and time are concerned within the manufacturing sector. The burnishing process is simple, easy and cost-effective, and thus it is more common to replace other surface finishing processes in the manufacturing sector. This study investigates the effect of burnishing parameters such as the number of passes, burnishing force, burnishing speed and feed rate on the surface roughness and microhardness of an AZ91D magnesium alloy using different artificial neural network models (i.e. the function fitting neural network (FITNET), generalized regression neural network (GRNN), cascade-forward neural network (CFNN) and feed-forward neural network (FFNN). A total of 1440 different estimates were made by means of ANN methods using different parameters. The best average performance results for surface roughness and microhardness are obtained by the FITNET model (i.e. mean square error (MSE): 0.00060608, mean absolute error (MAE): 0.01556013, multiple correlation coefficient (R): 0.99944545), using the Bayesian regularization process (trainbr)). The FITNET model is followed by the FFNN (i.e. MAE: 0.01707086, MSE: 0.00072907, R: 0.99932069) and CFNN (i.e. MAE: 0.01759166, MSE: 0.00080154, R: 0.99924845) models with very small differences, respectively. The GRNN model has noted worse estimation results (i.e. MSE: 0.00198232, MAE: 0.02973829, R: 0.99900783) as compared with the other models. As a result, MSE, MAE and R values show that it is possible to predict the surface roughness and microhardness results of the burnishing process with high accuracy using ANN models.

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Porównawcze elektrochemiczne badania korozyjne stopu magnezu AZ91D poddanego wygrzewaniu w różnych temperaturach

Rogowska R., Rogowski A.

TTS Technika Transportu Szynowego

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2012

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R. 19, nr 9

1031--1042, CD

PL

W pracy przedstawiono wyniki badań wpływu wygrzewania w piecu próżniowym w temperaturach 360°C, 380°C, 400°C, 420°C, 450°C przez okres 330 minut na odporność korozyjną stopu AZ91D. Badania odporności korozyjnej w 0,5M NaCl próbek nie wygrzewanych oraz obrobionych cieplnie przeprowadzono metodami elektrochemicznymi (badania stało- i zmiennoprądowe). Wykonano także badania dyfrakcyjne oraz morfologię powierzchni próbek. Wykazano, że wygrzewanie w piecu próżniowym powoduje zmniejszenie odporności korozyjnej stopu AZ91D.

EN

This paper presents the influence of annealing in a vacuum furnace at temperatures of 360° C, 380° C, 400° C, 420° C, 450° C for 330 minutes on corrosion resistance of AZ91D alloy. The corrosion resistance of the heat treated samples had been investigated in 0.5 M NaCl by the electrochemical methods (research fixed-and variable-current). The surface morphology and diffraction studies of the samples were performed. It was shown that heat treatment in a vacuum decreases the corrosion resistance of the samples made of AZ91D alloy.

4

Wielowarstwowe powłoki ochronne na odlewniczych stopach magnezu

Nieużyła Ł., Nawrat G., Krząkała A., Maciej A., Michalska J.

Ochrona przed Korozją

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2012

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nr 5

200-203

PL

W pracy przedstawiono wyniki badań dotyczące wytwarzania powłok konwersyjnych na stopie magnezu AZ91D przy zastosowaniu metody elektrochemicznego utleniania plazmowego. Następnie na tak zmodyfikowaną powierzchnię stopu nakładano powłokę SiO2-Al2O3 metodą zol-żel. Przedstawiono morfologię otrzymanych powłok, określono ich chropowatość oraz odporność na korozję. Stwierdzono, że wytworzenie powłok metodą elektrochemicznego utleniania plazmowego, a następnie ich uszczelnienie ceramiczną powłoką tlenkową powoduje wzrost odporności stopu na korozję.

EN

In the present work, we report results of investigations of conversion coatings obtaining on magnesium alloy AZ91D by means plasma electrolytic oxidation (PEO) method. Next, on modified alloy surface SiO2-Al2O3 coating was put on. Morphology of obtained coatings, their roughness and corrosion resistant are presented. It was found that coatings obtained by means PEO method and then tighten with ceramic coating show considerable increase of corrosion resistance.