Preliminary study on the production of functionally graded materials by friction stir processing

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia MecânicaAn investigation was carried out to evaluate the potential application of Friction Stir Processing (FSP) to produce Functionally Graded Materials (FGM‟s). Friction stir processed materials can be considered as FGM‟s since the localized microstructural modification results in a gradual property modification. Therefore, to enhance hardness and ductility at specific superficial levels, surface layers of processed material were produced by multiple-pass FSP with an overlap ratio of 0.5. Overlapping was done on the advancing (AS) and retreating sides (RS) to study potential differences on the resulting mechanical properties. It was observed that processing in these two conditions led to different surface topography, since overlapping by the advancing side resulted in a wave-like surface profile. The mechanisms involved in FSP also led to its exploitation for the production of particle-reinforced Metal Matrix Composite (MMC) materials, as the severe plastic deformation produced during the process promotes the dispersion of the particles within the matrix. An investigation was conducted in order to produce aluminium based functionally graded MMCs reinforced by SiC ceramic particles with median size of 118.8, 37.4 and 12.3 micron. AA5083 aluminium alloy plates in the H111 and partially annealed conditions were processed. Several strategies for reinforcement were investigated and its influence on the particle distribution and homogeneity. The most promising results were achieved when the pin fully overlapped the groove. SiC fraction area analysis revealed two orthogonal gradients. Since FSP was used as a surface processing technique, the magnitude of the microstructural effects generated by the tool gradually decreases along the depth of the processed material. A second gradient was generated parallel to the bead surface due to the asymmetric nature of material flow around the tool. The use of smaller sized particles led to more homogeneous composite layers and smother gradients. Tool wear was very significant, proving that SiC reinforcement is not the most suitable method to produce FGM‟s

Characterisation of semi-solid deformation behaviour of aluminium-copper alloys via combined x-ray microtomography and nite element modelling

The production of aluminium sheet is expensive and energy intensive despite the reduced environmental impact during use. Twin roll casting is a method of directly producing aluminium alloys in near net shape directly to sheet at a fraction of the energy costs of conventional DC casting / hot rolling. It also requires a fraction of the capital cost. Although sheet can be produced, defects (segregates, surface bleeds, buckling, etc.) can arise which limit the range of alloys which can be cast. This project aims to elucidate the complex mechanisms causing these defects through a combined experimental and computational study of semi-solid deformation in aluminium alloys. Columnar dendritic structures were generated for Al-Cu alloys through directional solidi cation experiments and quanti ed in three dimensions (3D) using x-ray microtomography (XMT). The -Al and the Cu-rich interdendritic liquid were segmented using image analysis. These 3D datasets were exported as meshes to be used in control volume and nite element codes. Firstly, the ow between the dendrites was simulated by solving the Stokes equation and permeability tensor was calculated as a function of the fraction solid. The size of representative volume element was estimated to be 4-6 times the characteristic length scale in the microstructure. Secondly, nite element simulations were performed on 3D columnar dendritic structures to estimate their mechanical properties and derive constitutive behaviour as a function of temperature, strain-rate and fraction solid. Temperature and strain-rate dependent compression tests were performed in the Gleeble on alloys with dendritic composition to determine the mechanical properties of the monolithic Al-dendrites. The fraction solid dependency term in the constitutive equation was determined as a purely geometric factor which could be easily replicated in other alloys systems. Lastly, hot tearing was directly observed in an Al- 12 wt.%Cu alloy by combining x-ray/synchrotron radiography with a new tensile/compression apparatus capable of measuring strain, load and quantifying the microstructure during controlled solidi cation of Al alloy specimen. Using this new apparatus, the deformation of primary dendrites and the concomitant ow of Cu-rich interdendritic uid was observed during isothermal and constant cooling rate conditions. Initially, strain was observed to be accommodated by liquid ow, but as the load is increased, void formation combined with liquid necking between grains was prevalent

Coupling in situ synchrotron X-ray tomographic microscopy and numerical simulation to quantify the influence of intermetallic formation on permeability in aluminium–silicon–copper alloys

AbstractThe influence of the β-Al5FeSi intermetallic phase on permeability evolution during solidification in an Al–Si–Cu alloy with a columnar dendritic microstructure has been numerically studied at solid fractions between 0.10 and 0.85. The fluid flow simulations were performed on a semisolid microstructure extracted directly from a single solidifying specimen, enabling the first study of permeability variation on an individual microstructure morphology that is evolving in solid fraction. The 3-D geometries were imaged at the TOMCAT beamline using 4-D (3-D+time) in situ synchrotron-based X-ray tomographic microscopy. The results illustrate the major effect of intermetallic particles on flow blockage and permeability. Intermetallics that grow normal to the flow direction were found to have a greater impact on the flow field in comparison to intermetallics in the parallel flow direction. An analytical expression, based on the anisotropic Blake–Kozeny model, was developed with a particle blockage term that takes into account the effects of intermetallic particles on permeability. In the regime of primary-phase solidification, a good fit between the analytical expression and the simulation results is found

Modification of aluminium-silicon alloys by rare-earth additions

Cast aluminium-silicon (Al-Si) alloys are used extensively in various industries due to their advantageous properties such as high strength-to-weight ratio, good corrosion resistance and high fluidity which allows for defect-free complex castings. Under normal casting conditions the microstructure is composed of silicon needles in an aluminium matrix. These provide propagation planes for defects and therefore deteriorate the mechanical properties. By adding certain elements, usually strontium (Sr), the Si needles change to fibres, however this is also known to increase porosity in castings. The mechanism that causes the change from needles to fibres has been extensively debated and a number of theories can be found in the literature, revolving around both the nucleation and growth stages of eutectic Si. In this thesis high purity materials were used to prepare hypoeutectic unmodified and Sr-modified Al-Si alloys to which cerium (Ce) or yttrium (Y) were added and differences between these alloys in the solidification progression and microstructure were investigated. The addition of 1% Ce or Y to unmodified Al-Si produced a partially modified eutectic Si, whilst full modification was retained when these were added to Sr-modified Al-Si. These additions also resulted in a significant decrease in the eutectic growth temperatures and in the formation of Al2Si2Ce or Al2Si2Y intermetallic phases. It is suggested that similar to the Al2Si2Sr in Sr-modified Al-Si these intermetallic phases nucleate on aluminium phosphide (AlP) and thus do not allow for the nucleation of eutectic silicon on this phase. Three dimensional atom probe tomography (3D APT) of Y-partially-modified Al-Si showed a preferential segregation of yttrium within the eutectic Si. By means of optical microscopy and high resolution x-ray computed tomography (XCT), it was also demonstrated that the Sr modification significantly increases the porosity in cast Al-Si alloys which is reduced following the rare-earth additions

Characterization of Porosity Defects in Selectively Laser Melted IN718 and Ti- 6A1-4V via Synchrotron X-Ray Computed Tomography

Additive manufacturing (AM) is a method of fabrication involving the joining of feedstock material together to form a structure. Additive manufacturing has been developed for use with polymers, ceramics, composites, biomaterials, and metals. Of the metal additive manufacturing techniques, one of the most commonly employed for commercial and government applications is selective laser melting (SLM). SLM operates by using a high-powered laser to melt feedstock metal powder, layer by layer, until the desired near-net shape is completed. Due to the inherent function of AM and particularly SLM, it holds much promise in the ability to design parts without geometrical constraint, cost-effectively manufacture them, and reduce material waste. Because of this, SLM has gained traction in the aerospace, automotive, and medical device industries, which often use uniquely shaped parts for specific functions. These industries also have a tendency to use high performance metallic alloys that can withstand the sometimes-extreme operating conditions that the parts experience. Two alloys that are often used in these parts are Inconel 718 (IN718) and Ti-6Al-4V (Ti64). Both of these materials have been routinely used in SLM processing but have been often marked by porosity defects in the as-built state. Since large amounts of porosity is known to limit material mechanical performance, especially in fatigue life, there is a general need to inspect and quantify this material characteristic before part use in these industries. One of the most advanced porosity inspection methods is via X-ray computed tomography (CT). CT uses a detector to capture scattered X-rays after passing through the part. The detector images are then reconstructed to create a tomograph that can be analyzed using image processing techniques to visualize and quantify porosity. In this research, CT was performed on both materials at a 30 μm “low resolution” (LR) for different build orientations and processing conditions. Furthermore, a synchrotron beamline was used to conduct CT on small samples of the SLM IN718 and Ti64 specimens at a 0.65 μm “high resolution” (HR), which to the author’s knowledge is the highest resolution (for SLM IN718) and matches the highest resolution (for SLM Ti64) reported for porosity CT investigations of these materials. Tomographs were reconstructed using TomoPy 1.0.0, processed using ImageJ and Avizo 9.0.2, and quantified in Avizo and Matlab. Results showed a relatively low amount of porosity in the materials overall, but a several order of magnitude increase in quantifiable porosity volume fraction from LR to HR observations. Furthermore, quantifications and visualizations showed a propensity for more and larger pores to be present near the free surfaces of the specimens. Additionally, a plurality of pores in the HR samples were found to be in close proximity (10 μm or less) to each other

Application of deep learning methods in materials microscopy for the quality assessment of lithium-ion batteries and sintered NdFeB magnets

Die Qualitätskontrolle konzentriert sich auf die Erkennung von Produktfehlern und die Überwachung von Aktivitäten, um zu überprüfen, ob die Produkte den gewünschten Qualitätsstandard erfüllen. Viele Ansätze für die Qualitätskontrolle verwenden spezialisierte Bildverarbeitungssoftware, die auf manuell entwickelten Merkmalen basiert, die von Fachleuten entwickelt wurden, um Objekte zu erkennen und Bilder zu analysieren. Diese Modelle sind jedoch mühsam, kostspielig in der Entwicklung und schwer zu pflegen, während die erstellte Lösung oft spröde ist und für leicht unterschiedliche Anwendungsfälle erhebliche Anpassungen erfordert. Aus diesen Gründen wird die Qualitätskontrolle in der Industrie immer noch häufig manuell durchgeführt, was zeitaufwändig und fehleranfällig ist. Daher schlagen wir einen allgemeineren datengesteuerten Ansatz vor, der auf den jüngsten Fortschritten in der Computer-Vision-Technologie basiert und Faltungsneuronale Netze verwendet, um repräsentative Merkmale direkt aus den Daten zu lernen. Während herkömmliche Methoden handgefertigte Merkmale verwenden, um einzelne Objekte zu erkennen, lernen Deep-Learning-Ansätze verallgemeinerbare Merkmale direkt aus den Trainingsproben, um verschiedene Objekte zu erkennen. In dieser Dissertation werden Modelle und Techniken für die automatisierte Erkennung von Defekten in lichtmikroskopischen Bildern von materialografisch präparierten Schnitten entwickelt. Wir entwickeln Modelle zur Defekterkennung, die sich grob in überwachte und unüberwachte Deep-Learning-Techniken einteilen lassen. Insbesondere werden verschiedene überwachte Deep-Learning-Modelle zur Erkennung von Defekten in der Mikrostruktur von Lithium-Ionen-Batterien entwickelt, von binären Klassifizierungsmodellen, die auf einem Sliding-Window-Ansatz mit begrenzten Trainingsdaten basieren, bis hin zu komplexen Defekterkennungs- und Lokalisierungsmodellen, die auf ein- und zweistufigen Detektoren basieren. Unser endgültiges Modell kann mehrere Klassen von Defekten in großen Mikroskopiebildern mit hoher Genauigkeit und nahezu in Echtzeit erkennen und lokalisieren. Das erfolgreiche Trainieren von überwachten Deep-Learning-Modellen erfordert jedoch in der Regel eine ausreichend große Menge an markierten Trainingsbeispielen, die oft nicht ohne weiteres verfügbar sind und deren Beschaffung sehr kostspielig sein kann. Daher schlagen wir zwei Ansätze vor, die auf unbeaufsichtigtem Deep Learning zur Erkennung von Anomalien in der Mikrostruktur von gesinterten NdFeB-Magneten basieren, ohne dass markierte Trainingsdaten benötigt werden. Die Modelle sind in der Lage, Defekte zu erkennen, indem sie aus den Trainingsdaten indikative Merkmale von nur "normalen" Mikrostrukturmustern lernen. Wir zeigen experimentelle Ergebnisse der vorgeschlagenen Fehlererkennungssysteme, indem wir eine Qualitätsbewertung an kommerziellen Proben von Lithium-Ionen-Batterien und gesinterten NdFeB-Magneten durchführen

Revealing hot tear formation dynamics in Al–Cu alloys with X-ray radiography

Hot tears can arise during the late part of alloy solidification because of the shrinkage of isolated liquid as it turns to solid and may have a catastrophic effect on cast tensile properties. Although there are correlations to suggest alloy hot tear sensitivity to casting conditions, they do not capture the influence of microstructure on tearing, such as second-phase particles or intermetallic compounds (IMCs) commonly present in engineering alloys. We use in situ X-ray radiography to quantify the formation and growth behaviour of hot tears in Al-5Cu and Al-5Cu-1Fe alloys during solidification. An automated hot tear detection, tracking and merging algorithm is developed and applied to reveal the role of Fe-rich IMC particles, typical of recycled alloys, on hot tear behaviour. These defects are termed hot tears here on the basis of their complex, extended inter-connected morphology, distinct from more rounded shrinkage porosity. We also visualise and quantify the velocity of interdendritic flow driven by solidification shrinkage, and estimate the pressure changes due to shrinkage. Hot tearing starts at lower solid fraction when IMCs are present due to reduced interdendritic flow, and hot tear formation is more spatially homogeneous, less clustered and more numerous. We show that the largest, most damaging hot tears form from many merging events, that is enhanced by the presence of IMCs

Investigation of Solidification Defect Formation by Three-Dimensional Reconstruction of Dendritic Structures.

Convective flow within the mushy zone of directionally solidified superalloys can result in the formation of freckles and misoriented grains. These defects signal not only a disruption in the columnar or single crystal nature of the component but also a tendency toward reduction in life and performance. Approximations of the onset of convective flow in the mush have primarily used the Rayleigh criteria as a predictor for the occurrence of freckles. However, a detailed understanding of fluid flow at the scale of the dendritic structure is still lacking. This research utilizes three-dimensional dendritic structures obtained from the solid-liquid interface of directionally solidified nickel-base superalloys as direct inputs to fluid flow models. These models have been utilized to assess the permeability of the dendritic array. Implications of simulations will be discussed with reference to the Rayleigh criteria and freckle prediction.Ph.D.Materials Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/76001/1/jonnymad_1.pd