Investigation of microstructure and mechanical properties by direct metal deposition

Microstructure and properties of Direct Metal Deposition (DMD) parts are very crucial to meeting industrial requirements of parts quality. Prediction, and control of microstructure and mechanical properties have attracted much attention during conventional metal manufacturing process under different conditions. However, there is few investigations focused on microstructure simulation and mechanical properties control under different process parameters during DMD process. This dissertation is intended to develop a multiscale model to investigate Ti6Al4V grain structure development and explore Ti6Al4V based functionally graded material (FGM) deposit properties during DMD process. The first research topic is to investigate and develop a cellular automaton-finite element (CA-FE) coupled model to combine with thermal history and simulate nucleation sites, grain growth orientation and rate, epitaxial growth of new grains, remelting of preexisting grains, metal addition, and grain competitive growth. The second research topic is to develop grain growth algorithm, which is appropriate for highly non-uniform temperature field and high cooling rate, to control grain structure under real-time changing process parameters. The third research topic is to investigate the influence of process parameters on microstructure and properties of Ti6Al4V-based FGMs, which are fabricated with different TiC volume fraction from 0 to 30vol%. The microstructure, Vickers hardness, phase identification, tensile properties of FGM are measured to investigate the fabricated FGM qualities. The Digital Image Correlation (DIC) is developed to analyze Young\u27s modulus versus composition of FGM parts --Abstract, page iv

Phase Field Simulation of Dendritic Solidification of Ti-6Al-4V During Additive Manufacturing Process

In this study, the phase field method is applied to simulate the phase transformation of Ti-6Al-4V from liquid phase to solid phase during solidification. The simulated results show the dendritic arms grow along the direction of the heat flow. Droplets are found formed inside the dendrites. Solute enriches in the liquid near the dendritic tips and between the dendritic arms. The effects of various processing parameters, including local temperature gradient, scan speed, and cooling rate, on dendrites morphology and growth velocity are studied. The results show that the higher temperature gradient, scan speed, and cooling rate will result in smaller dendritic arm spacing and higher growth velocity. The simulated dendritic morphology and arm spacings are in good agreement with experimental data and theoretical predictions

Modeling Dendritic Solidification using Lattice Boltzmann and Cellular Automaton Methods

This dissertation presents the development of numerical models based on lattice Boltzmann (LB) and cellular automaton (CA) methods for solving phase change and microstructural evolution problems. First, a new variation of the LB method is discussed for solving the heat conduction problem with phase change. In contrast to previous explicit algorithms, the latent heat source term is treated implicitly in the energy equation, avoiding iteration steps and improving the formulation stability and efficiency. The results showed that the model can deal with phase change problems more accurately and efficiently than explicit LB models. Furthermore, a new numerical technique is introduced for simulating dendrite growth in three dimensions. The LB method is used to calculate the transport phenomena and the CA is employed to capture the solid/liquid interface. It is assumed that the dendritic growth is driven by the difference between the local actual and local equilibrium composition of the liquid in the interface. The evolution of a threedimensional (3D) dendrite is discussed. In addition, the effect of undercooling and degree of anisotropy on the kinetics of dendrite growth is studied. Moreover, effect of melt convection on dendritic solidification is investigated using 3D simulations. It is shown that convection can change the kinetics of growth by affecting the solute distribution around the dendrite. The growth features of twodimensional (2D) and 3D dendrites are compared. Furthermore, the change in growth kinetics and morphology of Al-Cu dendrites is studied by altering melt undercooling, alloy composition and inlet flow velocity. The local-type nature of LB and CA methods enables efficient scaling of the model in petaflops supercomputers, allowing the simulation of large domains in 3D. The model capabilities with large scale simulations of dendritic solidification are discussed and the parallel performance of the algorithm is assessed. Excellent strong scaling up to thousands of computing cores is obtained across the nodes of a computer cluster, along with near-perfect weak scaling. Considering the advantages offered by the presented model, it can be used as a new tool for simulating 3D dendritic solidification under convection

Multi-scale modeling of transport phenomena and microstructure development in laser keyhole welding

This study is focused on a multi-scale investigation of laser keyhole welding processes based on numerical modeling techniques

Multiscale modelling of the influence of convection on dendrite formation and freckle initiation during vacuum arc remelting

Vacuum Arc Remelting (VAR) is employed to produce homogeneous ingots with a controlled, fine, microstructure. It is applied to reactive and segregation prone alloys where convection can influence microstructure and defect formation. In this study, a microscopic solidification model was extended to incorporate both forced and natural convection. The Navier-Stokes equations were solved for liquid and mushy zones using a modified projection method. The energy conservation and solute diffusion equations were solved via a combined stochastic nucleation approach along with a finite difference solution to simulate dendritic growth. This microscopic model was coupled to a 3D transient VAR model which was developed by using a multi-physics modelling software package, PHYSICA. The multiscale model enables simulations covering the range from dendrites (in microns) to the complete process (in meters). These numerical models were used to investigate: (i) the formation of dendritic microstructures under natural and forced convections; (ii) initiation of solute channels (freckles) in directional solidification in terms of interdendritic thermosolutal convection; and (iii) the macroscopic physical dynamics in VAR and their influence on freckle formation. 2D and 3D dendritic microstructure were simulated by taking into account both solutal and thermal diffusion for both constrained and unconstrained growth using the solidification model. For unconstrained equiaxed dendritic growth, forced convection was found to enhance dendritic growth in the upstream region while retarding downstream growth. In terms of dimensionality, dendritic growth in 3D is faster than 2D and convection promotes the coarsening of perpendicular arms and side branching in 3D. For constrained columnar dendritic growth, downward interdendritic convection is stopped by primary dendritic arms in 2D; this was not the case in 3D. Consequently, 3D simulations must be used when studying thermosolutal convection during solidification, since 2D simulations lead to inappropriate results. The microscopic model was also used to study the initiation of freckles for Pb-Sn alloys, predicting solute channel formation during directional solidification at a microstructural level for the first time. These simulations show that the local remelting due to high solute concentrations and continuous upward convection of segregated liquid result in the formation of sustained open solute channels. High initial Sn compositions, low casting speeds and low temperature gradients, all promote the initiation of these solute channels and hence freckles. to study the initiation of freckles for Pb-Sn alloys, predicting solute channel formation during directional solidification at a microstructural level for the first time. These simulations show that the local remelting due to high solute concentrations and continuous upward convection of segregated liquid result in the formation of sustained open solute channels. High initial Sn compositions, low casting speeds and low temperature gradients, all promote the initiation of these solute channels and hence freckles

Simulation of Channel Segregation During Directional Solidification of In—75 wt pct Ga. Qualitative Comparison with In Situ Observations

International audienceFreckles are common defects in industrial casting. They result from thermosolutal convection due to buoyancy forces generated from density variations in the liquid. The present paper proposes a numerical analysis for the formation of channel segregation using the three-dimensional (3D) cellular automaton (CA)—finite element (FE) model. The model integrates kinetics laws for the nucleation and growth of a microstructure with the solution of the conservation equations for the casting, while introducing an intermediate modeling scale for a direct representation of the envelope of the dendritic grains. Directional solidification of a cuboid cell is studied. Its geometry, the alloy chosen as well as the process parameters are inspired from experimental observations recently reported in the literature. Snapshots of the convective pattern, the solute distribution, and the morphology of the growth front are qualitatively compared. Similitudes are found when considering the coupled 3D CAFE simulations. Limitations of the model to reach direct simulation of the experiments are discussed

A mathematical model of dendritic microstructures in nickel-based superalloys

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Numerical Modeling of the Additive Manufacturing (AM) Processes of Titanium Alloy

It is easy to understand why industry and, especially, aerospace engineers love titanium. Titanium parts weigh roughly half as much as steel parts, but its strength is far greater than the strength of many alloy steels giving it an extremely high strength-to-weight ratio. Most titanium alloys are poor thermal conductors, thus heat generated during cutting does not dissipate through the part and machine structure, but concentrates in the cutting area. The high temperature generated during the cutting process also causes a work hardening phenomenon that affects the surface integrity of titanium, and could lead to geometric inaccuracies in the part and severe reduction in its fatigue strength [Benes, 2007]. On the contrary, additive manufacturing (AM) is an effective way to process titanium alloys as AM is principally thermal based, the effectiveness of AM processes depends on the material\u27s thermal properties and its absorption of laser energy rather than on its mechanical properties. Therefore, brittle and hard materials can be processed easily if their thermal properties (e.g., conductivity, heat of fusion, etc.) are favorable, such as titanium. Cost effectiveness is also an important consideration for using additive manufacturing for titanium processing. Parts or products cast and/or machined from titanium and its alloys are very expensive, due to the processing difficulties and complexities during machining and casting. AM processes however, have been found to be very cost effective because they can produce near-net shape parts from these high performance metals with little or no machining [Liou & Kinsella, 2009]. In the aerospace industry, titanium and its alloys are used for many large structural components. When traditional machining/cast routines are adopted, conversion costs for these heavy section components can be prohibitive due to long lead time and low-yield material utilization [Eylon & Froes, 1984]. AM processes have the potential to shorten lead time and increase material utilization in these applications. The following sections 1.1, 1.2 and 1.3 summarize the fundamental knowledge for the modeling of additive manufacturing processes

Microstructural evolution during the homogenization heat treatment of 6XXX and 7XXX aluminum alloys

Homogenization heat treatment of as-cast billets is an important step in the processing of aluminum extrusions. Microstructural evolution during homogenization involves elimination of the eutectic morphology by spheroidisation of the interdendritic phases, minimization of the microsegregation across the grains through diffusion, dissolution of the low-melting phases, which enhances the surface finish of the extrusions, and precipitation of nano-sized dispersoids (for Cr-, Zr-, Mn-, Sc-containing alloys), which inhibit grain boundary motion to prevent recrystallization. Post-homogenization cooling reprecipitates some of the phases, changing the flow stress required for subsequent extrusion. These precipitates, however, are deleterious for the mechanical properties of the alloy and also hamper the age-hardenability and are hence dissolved during solution heat treatment. Microstructural development during homogenization and subsequent cooling occurs both at the length scale of the Secondary Dendrite Arm Spacing (SDAS) in micrometers and dispersoids in nanometers. Numerical tools to simulate microstructural development at both the length scales have been developed and validated against experiments. These tools provide easy and convenient means to study the process. A Cellular Automaton-Finite Volume-based model for evolution of interdendritic phases is coupled with a Particle Size Distribution-based model for precipitation of dispersoids across the grain. This comprehensive model has been used to study the effect of temperature, composition, as-cast microstructure, and cooling rates during post-homogenization quenching on microstructural evolution. The numerical study has been complimented with experiments involving Scanning Electron Microscopy, Energy Dispersive Spectroscopy, X-Ray Diffraction and Differential Scanning Calorimetry and a good agreement has with numerical results has been found. The current work aims to study the microstructural evolution during homogenization heat treatment at both length scales which include the (i) dissolution and transformation of the as-cast secondary phases; (ii) precipitation of dispersoids; and (iii) reprecipitation of some of the secondary phases during post-homogenization cooling. The kinetics of the phase transformations are mostly diffusion controlled except for the η to S phase transformation in 7XXX alloys which is interface reaction rate controlled which has been implemented using a novel approach. Recommendations for homogenization temperature, time, cooling rates and compositions are made for Al-Si-Mg-Fe-Mn and Al-Zn-Cu-Mg-Zr alloys. The numerical model developed has been applied for a through process solidification-homogenization modeling of a Direct-Chill cast AA7050 cylindrical billet to study the radial variation of microstructure after solidification, homogenization and post-homogenization cooling