3D Visualization of Morphological Evolution of Large Defects during Spark Plasma Sintering of Alumina Granules

The mechanical reliability of products must be assured for scaling up and production of complex-shaped components by spark plasma sintering (SPS) of spray-dried granules. The evolution of morphologies of pores and defects, which control the mechanical strength, is investigated by using synchrotron X-ray multiscale tomography during SPS of alumina granules at 1300 °C. While large defects arising from the hierarchical granule packing structure cannot be removed by pressureless sintering, crack-like defects and branched rodlike defects are almost eliminated by SPS at stresses higher than 30 and 50 MPa, respectively. But, small ellipsoidal porous regions, which may arise from aggregates or dimples of granules, cannot be removed even at a pressure of 50 MPa. A very large defect is also found by using micro-CT. It is supposed that this defect is formed from a large void in loosely packed granules. The shrinkage of large voids and the elimination of crack-like defects are explained by the theoretical prediction based on the continuum theory of sintering.     

Garment Model Extraction from Clothed Mannequin Scan

Modelling garments with rich details require enormous time and expertise of artists. Recent works re-construct garments through segmentation of clothed human scan. However, existing methods rely on certain human body templates and do not perform as well on loose garments such as skirts. This paper presents a two-stage pipeline for extracting high-fidelity garments from static scan data of clothed mannequins. Our key contribution is a novel method for tracking both tight and loose boundaries between garments and mannequin skin. Our algorithm enables the modelling of off-the-shelf clothing with fine details. It is independent of human template models and requires only minimal mannequin priors. The effectiveness of our method is validated through quantitative and qualitative comparison with the baseline method. The results demonstrate that our method can accurately extract both tight and loose garments within reasonable time.     

CMAS degradation of ytterbium aluminum garnets

The degradation of ytterbium aluminum garnet (YbAG) exposed to molten Ca–Mg–Fe–Al–Si–O (CMAS) at 1673 K was investigated for two kinds of dense polycrystalline YbAG with compositions deviating slightly from stoichiometry, referred to as Al- and Yb-rich. The mitigation of the CMAS attack for Yb-rich YbAG was markedly superior to that for the Al-rich one. For both types of YbAG, corrosion progressed due to the preferential penetration of the CMAS melt along grain boundaries in the thickness direction and the simultaneous dissolution of crystal grains into the melt. The lower of the corroded region consisted of YbAG crystals with a core/shell-I/shell-II structure. Shell-I contained alkaline earth, silicon, and iron cations, whereas these cations were hardly detected in shell-II. Growth of the shell-I region was considered to progress by dissolution and reprecipitation through the melt existing around it, and finally, the melt disappeared, resulting in the formation of a thin shell-II region containing little of these ions. The formation and growth of the shell-I region were found to be promoted by making the YbAG Yb-rich, resulting in enhancement of the resistance to CMAS.     

Hot water resistance of glass‐fiber and glass‐bead reinforced thermoplastics

The hot water resistance of three kinds of short glass fiber or glass bead‐reinforced plastics [polyphenyleneether (PPE), polyphenylenesulfide (PPS), and polyoxymethylene (POM)] was studied by hot water immersion testing, tensile testing and water‐hammer fatigue testing. It was found that the degradation of the strength was observed only for the reinforced plastics under hot water immersion and that the change of the tensile strength was most drastic in glass fiber‐reinforced PPS (GFPPS). Scanning electron microscope (SEM) observations of the tensile fracture surface revealed that the change in tensile strength was attributable to the deterioration of the interface between the glass fiber and the matrix resin. The results of acoustic emission analysis also supported the conclusion that the change in strength was due to the deterioration of the interface. Although the change in the tensile strength of glass fiber‐reinforced PPE (GFPPE) was small compared with that of GFPPS, debonding between the glass fiber and the matrix resin and surface cracks was observed on the surface of the GFPPE specimens.     

Data-driven modelling of turbine wake interactions and flow resistance in large wind farms

Turbine wake and local blockage effects are known to alter wind farm power production in two different ways: (1) by changing the wind speed locally in front of each turbine and (2) by changing the overall flow resistance in the farm and thus the so-called farm blockage effect. To better predict these effects with low computational costs, we develop data-driven emulators of the ‘local’ or ‘internal’ turbine thrust coefficient $C_T^{\ast }$ as a function of turbine layout. We train the model using a multi-fidelity Gaussian process (GP) regression with a combination of low (engineering wake model) and high-fidelity (large eddy simulations) simulations of farms with different layouts and wind directions. A large set of low-fidelity data speeds up the learning process and the high-fidelity data ensures a high accuracy. The trained multi-fidelity GP model is shown to give more accurate predictions of $C_T^{\ast }$ compared to a standard (single-fidelity) GP regression applied only to a limited set of high-fidelity data. We also use the multi-fidelity GP model of $C_T^{\ast }$ with the two-scale momentum theory (Nishino & Dunstan 2020, J. Fluid Mech. 894, A2) to demonstrate that the model can be used to give fast and accurate predictions of large wind farm performance under various mesoscale atmospheric conditions. This new approach could be beneficial for improving annual energy production (AEP) calculations and farm optimization in the future.     

Fundamental evaluation of direct-cooling technology for in-wheel drive system

We are developing a small and lightweight direct-drive system toward the realization of in-wheel electric vehicles (EVs). To increase the power density of the motor, we developed a direct-cooling motor that immersed the core, coils, and magnets in cooling oil and improved cooling efficiency. Moreover, we performed measurements of frictional loss, measurement of pressure drop, and a continuous heat-run test on the test bench. The results demonstrated that direct cooling is effective and continuous operation can be achieved. Additionally, it was found that the coil temperature can be controlled by the flow rate of the cooling oil. In this paper, we report on the concept of direct cooling and the measurement results.     

Makeup Extraction of 3D Representation via Illumination-Aware Image Decomposition

Facial makeup enriches the beauty of not only real humans but also virtual characters; therefore, makeup for 3D facial models is highly in demand in productions. However, painting directly on 3D faces and capturing real-world makeup are costly, and extracting makeup from 2D images often struggles with shading effects and occlusions. This paper presents the first method for extracting makeup for 3D facial models from a single makeup portrait. Our method consists of the following three steps. First, we exploit the strong prior of 3D morphable models via regression-based inverse rendering to extract coarse materials such as geometry and diffuse/specular albedos that are represented in the UV space. Second, we refine the coarse materials, which may have missing pixels due to occlusions. We apply inpainting and optimization. Finally, we extract the bare skin, makeup, and an alpha matte from the diffuse albedo. Our method offers various applications for not only 3D facial models but also 2D portrait images. The extracted makeup is well-aligned in the UV space, from which we build a large-scale makeup dataset and a parametric makeup model for 3D faces. Our disentangled materials also yield robust makeup transfer and illumination-aware makeup interpolation/removal without a reference image.