Effects of squeeze casting parameters on density, macrostructure and hardness of LM13 alloy

Maleki, Ali; Niroumand, Behzad; Shafyei, A.

doi:10.1016/j.msea.2006.04.099

Cited by 155 publications

(75 citation statements)

References 3 publications

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“…The experiments performed by various researchers using classical engineering approach to study the effects of squeeze pressure, casting temperature, die temperatures, time delay, inoculants and pressure duration on solidification time, density, secondary dendrite arm spacing, grain size, hardness, tensile and impact strengths of different aluminium based alloys [48][49][50][51][52][53][54][55][56][57][58][59][60]. The following advantages and limitations have been identified from the above discussed literatures,…”

Section: Classical Engineering Experimental Approachmentioning

confidence: 99%

Modelling in Squeeze Casting Process-Present State and Future Perspectives

Patel¹,

MB²

2015

Adv Automob Eng

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The growing demand in today's competitive manufacturing environment has encouraged the researchers to develop and apply modelling tools. The development and application of modelling tools help the casting industries to considerably increase productivity and casting quality. Till date there is no universal standard available to model and optimize any of the manufacturing processes. However the present work discusses the advantages and limitations of some conventional and non-conventional modelling tools applied for various casting processes. In addition the research effort made by various authors till date in modelling and optimization of the squeeze casting process has been reported. Furthermore the necessary steps for prediction and optimization are high lightened by identifying the trends in the literature. Ultimately this research paper explores the scope for future research in online control of the process by automatically adjusting the squeeze cast process parameters through reverse prediction by utilizing the soft computing tools namely, Neural Network, Genetic Algorithms, Fuzzy-logic Controllers and their different combinations. The present work also proposed a detailed methodology, starting from the selection of process variables till the best process variable combinations for extreme values of the outputs responsible for better product quality using experimental, prediction and optimization methodology. Citation: Manjunath Patel GC, Krishna P, Parappagoudar MB (2015) Modelling in Squeeze Casting Process-Present State and Future Perspectives. Modelling in Squeeze Casting

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Section: Classical Engineering Experimental Approachmentioning

confidence: 99%

Modelling in Squeeze Casting Process-Present State and Future Perspectives

Patel¹,

MB²

2015

Adv Automob Eng

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“…The method of calculating heat transfer coefficients as reported by Santos et al (2001) and Maleki et al, (2006) is based on the knowledge of known temperature histories at the interior points of the casting or mould together with the numerical models of heat flow during solidification. These temperatures are difficult to measure due to the difficulty in locating accurate position of thermocouple at the interface.…”

Section: Heat Transfer Coefficient Evaluationsmentioning

confidence: 99%

Experimental determination of heat transfer coefficients during squeeze casting of aluminium

Aweda

Adeyemi

2009

Journal of Materials Processing Technology

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“…% Mn can form strengthening phases, and play adispersion strengthening effect, which can improve the mechanical properties of Al-5.0Cu-based alloys [23][24][25][26]. Squeeze casting is a common method for preparing high performance materials and components because of the reduction of the shrinkage and thermal crack defects in the alloy [27][28][29], where high densification samples can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Microstructures and Properties Evolution of Al-Cu-Mn Alloy with Addition of Vanadium

Meng

Wang

Zhao

et al. 2016

Metals

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Abstract:The effect of the vanadium addition on the microstructure, the precipitation behavior, and the mechanical properties of the Al-5.0Cu-0.4Mn alloy has been studied. The as-cast Al-5.0Cu-0.4Mn alloy was produced by squeeze casting and the heat treatment was carried out following the standard T6 treatment. It is shown that, with the addition of V, grain refinement of aluminum occurred. During heat treatment, the addition of V accelerates the precipitation kinetics of θ (Al 2 Cu) phase along the grain boundaries, and promotes the growth rate of the θ in the α(Al) matrix. Meanwhile, the addition of V retards the precipitation of T (Al 20 Cu 2 Mn 3 ) phase. The tensile strength of the Al-5.0Cu-0.4Mn alloy increases with the increase of V content, which can be explained by combined effects of the solid solution strengthening and precipitate strengthening. However, excessively high V addition deteriorates the mechanical properties by forming brittle coarse intermetallic phases.

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Effects of squeeze casting parameters on density, macrostructure and hardness of LM13 alloy

Cited by 155 publications

References 3 publications

Modelling in Squeeze Casting Process-Present State and Future Perspectives

Modelling in Squeeze Casting Process-Present State and Future Perspectives

Experimental determination of heat transfer coefficients during squeeze casting of aluminium

Microstructures and Properties Evolution of Al-Cu-Mn Alloy with Addition of Vanadium

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