219 research outputs found

    Structure-property characterization of rheocast and VADER processed IN-100 superalloy

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    Two recent solidification processes have been applied in the production of IN-100 nickel-base superalloy: rheocasting and vacuum arc double electrode remelting (VADER). A detailed microstructural examination has been made of the products of these two processes; associated tensile strength and fatigue crack propagation (FCP) rate at an elevated temperature were evaluated. In rheocasting, processing variables that have been evaluated include stirring speed, isothermal stirring time and volume fraction solid during isothermal stirring. VADER processed IN-100 was purchased from Special Metals Corp., New Hartford, NY. As-cast ingots were subjected to hot isostatic pressing (HIP) and heat treatment. Both rheocasting and VADER processed materials yield fine and equiaxed spherical structures, with reduced macrosegregation in comparison to ingot materials. The rheocast structures are discussed on the basis of the Vogel-Doherty-Cantor model of dendrite arm fragmentation. The rheocast ingots evaluated were superior in yield strength to both VADER and commercially cast IN-100 alloy. Rheocast and VADER ingots may have higher crack propagation resistance than P/M processed material

    Localized microstructure enhancement via Friction Stir Processing for die cast components

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    Friction stir processing (FSP) is an outgrowth of Friction stir welding (FSW) that locally manipulatesthe microstructure by imparting a high level of energy in the solid state resulting in improved mechanicalproperties. This study has shown that FSP can be implemented as a post-casting method to locally eliminatecasting defects, such as porosity, which is generated by gas evolution during casting. Coarse second phases arebroken into fine nearly equiaxed particles and uniformly distributed in the matrix. Moreover, grain refinementis obtained by dynamic recrystallization during FSP. This results in improved microhardness, tensile propertiesand fatigue properties of the cast FSP processed A206 alloy. In addition, FSP is a viable means to producelocalized composite structures in cast Al components. Such improvements have important implicationsfor manufactured components for a variety of automotive and other industrial applications. The convenienceof FSP as a post-processing step that can easily be adapted during machining operation makes it veryattractive to adopt. These results will be reviewed and discussed

    Teaching sustainable development in materials science and engineering

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    Preparing the next generation of materials scientists and engineers requires more than teaching them knowledge of material properties and behaviors. Materials science and engineering must also take into account materials sustainability in the context of society and the environment, as discussed throughout this issue. Including topics such as sustainability in a materials curriculum is not new. Issues of ethics, costs, and so on have long been an integral part of our education. Although detailed treatment of all such topics cannot be included in a general materials education curriculum, the concepts of sustainable development and the role of materials in a sustainable future can be introduced. Indeed, many materials science programs are beginning to include these topics in their curricula. This article discusses three such programs that the authors have helped design and implement in the United States, each taking a different approach to engaging students in these topics. The intention is not to provide an exhaustive overview of education in sustainable development, but rather to describe a range of strategies that are currently being applied and to raise pertinent issues in materials science education

    The continuous rheoconversion process (CRP™): optimization & industrial applications

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    Semi-solid metal (SSM) processing has emerged as a preferred manufacturing scheme due to the superior quality associated with semi-solid castings. In recent years, the driving force to reduce process cost requires the development of robust, commercially viable rheocasting (also termed slurry-on-demand (SoD)) processes. The continuous rheoconversion process (CRP™) is a novel SoD process that was developed at MPI/ WPI. The process is based on a passive liquid mixing technique in which the nucleation and growth of the primary phase are controlled using a specially designed "reactor". The reactor provides heat extraction, copious nucleation, and forced convection during the initial stage of solidification, thus leading to the formation of globular structures. This paper presents our recent work on the optimization of the CRPTM for industrial applications. Specifically, we will discuss critical issues of optimizing and simplifying the process to retrofit most die casting facilities. Salient results from simulations and several industrial trials that have been carried out with ACRC Consortium Members are reviewed and discussed

    Controlled diffusion solidification: application to metal casting

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    Wrought aluminum-based alloys exhibit superior physical and mechanical properties compared to conventional cast alloys. However, wrought alloys cannot be cast because they develop hot tears and hot cracks during solidification. For this reason, these alloys are typically cast into ingots and are subsequently brought to final shape by mechanical processes such as rolling, extrusion, drawing and forging. Controlled Diffusion Solidification (CDS) is a novel process that allows casting of wrought alloys directly into final shapes that are free of hot tears. The process follows a different route from conventional casting methods; in CDS two liquid alloys of predetermined composition and temperature are mixed together so that upon solidification the resultant alloy has a globular rather than a dendritic microstructure. The hot tearing tendency of wrought alloys originates from the inadequate permeability of their dendritic network, which obstructs the flow of interdendritic liquid and hinders compensation for shrinkage. CDS process details are presented and reviewed, and applications to die casting are also presented and discussed

    CASTABILITY MEASURES FOR DIECASTING ALLOYS: FLUIDITY, HOT TEARING, AND DIE SOLDERING

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    Tautologically, castability is a critical requirement in any casting process. Traditionally, castability in sandand permanent mold applications is thought to depend heavily on fluidity and hot tearing. Givencapital investments in dies, die soldering is a critical parameter to consider for diecasting. We discussquantitative and robust methods to insure repeatable metal casting for diecasting applications by investigatingthese three areas. Weight reduction initiatives call for progressively thinner sections, which in turnare dependent on reliable fluidity. Quantitative investigation of hot tearing is revealing how stress developsand yields as alloys solidify, and this has implications on part distortion even when pressure-castingmethodologies preclude hot tearing failures.Understanding the underlying mechanism of die soldering presents opportunities to develop methodsto avoid costly downtime and extend die life. Through an understanding of castability parameters,greater control over the diecasting process can be achieved

    Predicting compositions and properties of aluminum die casting alloys using artificial neural network

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    Despite the large number of existing alloys and alloy databases, identifying proper alloys for specific applications still remains a challenge. In order to facilitate the selection and prediction of aluminum die casting alloys and their properties, an electronic database - ?i-Select-Al? - has been developed by the Advanced Casting Research Center (ACRC) and the North American Die Casting Association (NADCA). The key to the predictions is the determination of a relationship between alloy properties, chemical composition, and processing variables. Theoretically, these relationships can be ?accurately? determined using fundamental physical principles. However, in practice, the underlying mechanisms are not fully understood and difficult to be utilized. In this case, approximate empirical models are considered. In version 1.0 of the software trend equations have been generated. The nature of these trend equations limits the applicability and prediction ability of the software. In order to improve the prediction power; relationships based on an artificial neural network (ANN) were exploited in version 2.0. ANN has proven to be a highly flexible tool, suitable to treat multiple-input conditions and nonlinear phenomena with complex relationships between input and output variables. This article presents the working mechanisms, the programming, and the application of ANN in this project. The results show that ANN is a valuable modelling tool for predicting properties- fromcomposition and composition- from-properties for aluminum die casting alloys
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