Modeling fluid interactions with the rigid mush in alloy solidification

Macrosegregation is a casting defect characterized by long range composition differences on the length scale of the ingot. These variations in local composition can lead to the development of unwanted phases that are detrimental to mechanical properties. Unlike microsegregation, in which compositions vary over the length scale of the dendrite arms, macrosegregation cannot be removed by subsequent heat treatment, and so it is critical to understand its development during solidification processing. Due to the complex nature of the governing physical phenomena, many researchers have turned to numerical simulations for these predictions, but properly modeling alloy solidification presents a variety of challenges. Among these is the appropriate treatment of the interface between the bulk fluid and the rigid mushy zone. In this region, the non-linear and coupled behavior of heat transfer, fluid mechanics, solute transport, and alloy thermodynamics has a dramatic effect on macrosegregation predictions. This work investigates the impact of numerical approximations at this interface in the context of a mixture model for alloy solidification. First, the numerical prediction of freckles in columnar solidification is investigated, and the predictive ability of the model is evaluated. The model is then extended to equiaxed solidification, in which the analogous interface is the transition of free-floating solid particles to a rigid dendritic network. Various models for grain attachment are investigated, and found to produce significant artifacts caused by the discrete nature of their implementation on the numerical grid. To reduce the impact of these artifacts, a new continuum grain attachment model is proposed and evaluated. The differences between these models are compared using uncertainty quantification, and recommendations for future research are presented

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

Reconstruction of solidification history from cast microstructure in remelted nickel alloy 718

Digital image analysis techniques were developed to autonomously characterize dendritic solidification microstructures and estimate melt pool profiles and solidification rates in remelted nickel alloy 718 ingots. Automated macrophotography was used to image dendritic microstructures in etched ingot cross-sections and create large image montages. Two analysis techniques, particle identification and two-point correlation function analysis, were developed to measure primary dendrite arm orientation and secondary dendrite arm spacing from these digital image montages. Particle identification techniques identified individual primary dendrite arms from the montage images. Primary dendrite arm orientations were measured from the geometry and location of the identified particles. A peak-counting technique was then implemented to measure secondary dendrite arm spacing after primary dendrite arms were identified. Two-point correlation functions were used to measure average primary dendrite arm orientations and secondary dendrite arm spacings from controlled image areas. Fourier analysis was then used to measure the primary dendrite arm orientation from the two-point correlation function. A peak-counting technique was used to measure secondary dendrite arm spacing after primary dendrite arm orientation was measured. The results produced using both analysis techniques were used to estimate melt pool profiles and solidification rates in a remelted alloy 718 ingot. Melt pool profile and solidification rate histories were calculated from primary dendrite arm orientations and secondary dendrite arm spacings, respectively. The techniques developed in this dissertation provide new technology and data needed by industry to validate computational process models of remelting processes such as electro-slag remelting (ESR) and vacuum-arc remelting (VAR).Mechanical Engineerin

{3D} Morphable Face Models -- Past, Present and Future

In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed. The challenges in building and applying these models, namely capture, modeling, image formation, and image analysis, are still active research topics, and we review the state-of-the-art in each of these areas. We also look ahead, identifying unsolved challenges, proposing directions for future research and highlighting the broad range of current and future applications

3D Human Face Reconstruction and 2D Appearance Synthesis

3D human face reconstruction has been an extensive research for decades due to its wide applications, such as animation, recognition and 3D-driven appearance synthesis. Although commodity depth sensors are widely available in recent years, image based face reconstruction are significantly valuable as images are much easier to access and store. In this dissertation, we first propose three image-based face reconstruction approaches according to different assumption of inputs. In the first approach, face geometry is extracted from multiple key frames of a video sequence with different head poses. The camera should be calibrated under this assumption. As the first approach is limited to videos, we propose the second approach then focus on single image. This approach also improves the geometry by adding fine grains using shading cue. We proposed a novel albedo estimation and linear optimization algorithm in this approach. In the third approach, we further loose the constraint of the input image to arbitrary in the wild images. Our proposed approach can robustly reconstruct high quality model even with extreme expressions and large poses. We then explore the applicability of our face reconstructions on four interesting applications: video face beautification, generating personalized facial blendshape from image sequences, face video stylizing and video face replacement. We demonstrate great potentials of our reconstruction approaches on these real-world applications. In particular, with the recent surge of interests in VR/AR, it is increasingly common to see people wearing head-mounted displays. However, the large occlusion on face is a big obstacle for people to communicate in a face-to-face manner. Our another application is that we explore hardware/software solutions for synthesizing the face image with presence of HMDs. We design two setups (experimental and mobile) which integrate two near IR cameras and one color camera to solve this problem. With our algorithm and prototype, we can achieve photo-realistic results. We further propose a deep neutral network to solve the HMD removal problem considering it as a face inpainting problem. This approach doesn\u27t need special hardware and run in real-time with satisfying results

Hybrid Ageing Patterns for Face Age Estimation

Wrinkles can be embedded in several image-based applications as a descriptor for human skin. However, wrinkle-based age estimation research has not been widely addressed. In this paper, we introduce a Multi-scale Wrinkle Patterns (MWP) representation, investigate the effect of wrinkles on face age estimation and propose Hybrid Ageing Patterns (HAP) for face age estimation. To define the wrinkle regions more precisely, a template consisting of 10 regions constructed relatively to a set of automatically located facial landmarks is used. We extract the multi-scale wrinkles in each region and encode them into MWP. We use Support Vector Regression to estimate age from the combination of such patterns. The performance of the algorithms is assessed by using Mean Absolute Error (MAE) on three state-of-the-art datasets - FG-NET, FERET and MORPH. We observe that MWP produces a comparable MAE of 4.16 on FERET to the state of the art. Finally we propose HAP, which combines the features from MWP and the Facial Appearance Model (FAM), and demonstrate improved performance on FERET and MORPH with MAE of 3.02 (±2.92) and 3.68 (±2.98), respectively. Therefore, we conclude that MWP is an important complementary feature for face age estimation

Serum 25-hydroxyvitamin D concentration in relation to melanoma progress

Dr Wyatt’s study investigated the complex relationship between vitamin D and melanoma, specifically if vitamin D status is associated with more aggressive melanomas. Exposure to solar ultraviolet radiation is the principal risk factor for melanoma and also the main source of vitamin D. This research found that insufficient vitamin D at time of melanoma diagnosis is significantly associated with poorer prognosis (as defined by tumour thickness). These results will contribute to a more refined public health message concerning melanoma and vitamin D, particularly in Queensland, which has the highest global incidence of melanoma, but vitamin D deficiency is not uncommon