Effects of Processing Parameters on Microstructure Evolution of Al-7Si-Mg Alloy by Cooling Slope Casting

Thường, Nguyễn Văn; Hussain, Zuhailawati; Seman, Anasyida Abu; Huy, Tran Duc; Dhindaw, B. K.

doi:10.1007/s11665-015-1458-5

Cited by 11 publications

(6 citation statements)

References 12 publications

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“…3 shows the least grain size of 33 lm while having the maximum shape factor which is in accordance with the microstructure. The present finding is in contradiction with most of the previous studies (Table 1) which shows a minimum grain size and maximum shape factor at higher cooling slope angles [4,[11][12][13][14][15]. The experimental investigations by Taghavi et al [11] and Das et al [4,12,15] concluded 40°(slope length of 400 mm) and 60°angle (slope length of 500 mm) to be the optimum cooling slope angle respectively.…”

Section: Microstructural Characterizationcontrasting

confidence: 99%

Effect of Cooling Slope Angle on Microstructure of Al-7Si Alloy

Acharya

Kumar

Mandal

2015

Trans Indian Inst Met

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Attempts were made to obtain non-dendritic microstructure in Al-7Si alloy by pouring the melt on mild steel cooling slope. The melt was poured into the slope at different angles-15°, 30°, 45°and 60°. The pouring temperatures chosen were 630°C, 640°C and 650°C corresponding to melt superheat of 15°C, 25°C and 35°C.The results indicate that a lowest slope angle of 15 o along with superheat of 15°C leads to microstructure with minimum grain size of 33 lm and shape factor of 0.81. The findings showed that lower slope angles would yield minimum grain size, are in contradiction to earlier studies, which could be related only to the lowest possible superheats used in the present study.

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Section: Microstructural Characterizationcontrasting

confidence: 99%

Effect of Cooling Slope Angle on Microstructure of Al-7Si Alloy

Acharya

Kumar

Mandal

2015

Trans Indian Inst Met

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“…The complexity in optimizing the process parameters in cooling slope technique has led many researchers to delve into this domain of optimization of cooling slope technique. Few such investigations have been highlighted [8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Optimization of processing parameters of cooling slope process for semi-solid casting of ADC 12 Al alloy

Gautam

Mandal

Roy

et al. 2018

J Braz. Soc. Mech. Sci. Eng.

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In the present work, the effect of processing parameters of cooling slope techniques (pouring temperature, slope angle and slope length) of ADC 12 Al alloy on its microstructural evolution has been studied in detail. A series of cooling slope casting experiments were conducted by varying the pouring temperature (580, 585 and 590°C), slope length (400, 500 and 600 mm) and slope angle (30°, 45°and 60°). The effect of processing parameters on the response factors, viz. degree of sphericity and particle size, has been investigated by applying analysis of variance (ANOVA), interaction graphs obtained using response surface methodology. The obtained results infer that optimum values of the degree of sphericity (0.865) and particle size (49.30) are observed for the following set of processing parameters, namely 585°C pouring temperature, 500 mm slope length and 45°slope angle. ANOVA results show that the pouring temperature is the most significant input variables that influence degree of sphericity and particle size followed by slope length and slope angle. The values of output variables obtained from confirmation experiment, performed at 95% confidence level, ensure that they are well within the permissible limits.

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“…The DS and PS are commonly influenced by different cooling slope parameters process viz: pouring temperature, pouring distance, and slanting angle. These parameters are the major cooling slope process parameters used to affect billet performance and quality [3][4].…”

Section: Introductionmentioning

confidence: 99%

Jaya Algorithm for Optimization of Cooling Slope Casting Process Parameters

Said

Sallehuddin

Radzi

et al. 2021

J. Phys.: Conf. Ser.

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This study proposed the Jaya algorithm to estimate an improved value of billet performance through the cooling casting process. Jaya algorithm is a recent evolution-based algorithm that simulates using stochastic behaviour. The algorithm concept is the solution obtained for a given problem should move towards the best solution and should avoid the worst solution. This algorithm requires only the common control parameters and does not require any algorithm specific control parameters. To the best our knowledge, Jaya algorithm is not yet been used computational approach for optimization practice, particularly in the Cooling casting process. Three Cooling slope parameters process that influences the billet performance measurements, a maximum degree of sphericity and minimum grain size are pouring temperature, slanting angle, and travelling distance. The results show that the Jaya algorithm gave a better optimal solution for the maximum degree of sphericity and minimum particle size than experimental data.

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Effects of Processing Parameters on Microstructure Evolution of Al-7Si-Mg Alloy by Cooling Slope Casting

Cited by 11 publications

References 12 publications

Effect of Cooling Slope Angle on Microstructure of Al-7Si Alloy

Effect of Cooling Slope Angle on Microstructure of Al-7Si Alloy

Optimization of processing parameters of cooling slope process for semi-solid casting of ADC 12 Al alloy

Jaya Algorithm for Optimization of Cooling Slope Casting Process Parameters

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