Michels, Dominik L.; Mueller, J. Paul T.(SIGGRAPH ASIA 2016 Courses on - SA '16, Association for Computing Machinery (ACM), 2016-11-28)[Conference Paper]
Many natural phenomena which occur in the realm of visual computing and computational physics, like the dynamics of cloth, fibers, fluids, and solids as well as collision scenarios are described by stiff Hamiltonian equations of motion, i.e. differential equations whose solution spectra simultaneously contain extremely high and low frequencies. This usually impedes the development of physically accurate and at the same time efficient integration algorithms. We present a straightforward computationally oriented introduction to advanced concepts from classical mechanics. We provide an easy to understand step-by-step introduction from variational principles over the Euler-Lagrange formalism and the Legendre transformation to Hamiltonian mechanics. Based on such solid theoretical foundations, we study the underlying geometric structure of Hamiltonian systems as well as their discrete counterparts in order to develop sophisticated structure preserving integration algorithms to efficiently perform high fidelity simulations.
Liu, Zhaolun; AlTheyab, Abdullah; Hanafy, Sherif M.; Schuster, Gerard T.(SEG Technical Program Expanded Abstracts 2016, Society of Exploration Geophysicists, 2016-09-06)[Conference Paper]
We demonstrate that near-surface heterogeneities can be imaged by natural migration of backscattered surface waves in common shot gathers. No velocity model is required because the data are migrated onto surface points with the virtual Green's functions computed from the shot gathers. Migrating shot gathers recorded by 2D and 3D land surveys validates the effectiveness of detecting nearsurface heterogeneities by natural migration. The implication is that more accurate hazard maps can be created by migrating surface waves in land surveys.
Dodla, Venkata B.; Srinivas, Desamsetti; Dasari, Hari Prasad; Gubbala, Chinna Satyanarayana(Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI, SPIE-Intl Soc Optical Eng, 2016-05-03)[Conference Paper]
Tropical cyclone prediction, in terms of intensification and movement, is important for disaster management and mitigation. Hitherto, research studies were focused on this issue that lead to improvement in numerical models, initial data with data assimilation, physical parameterizations and application of ensemble prediction. Weather Research and Forecasting (WRF) model is the state-of-art model for cyclone prediction. In the present study, prediction of tropical cyclone (Phailin, 2013) that formed in the North Indian Ocean (NIO) with and without data assimilation using WRF model has been made to assess impacts of data assimilation. WRF model was designed to have nested two domains of 15 and 5 km resolutions. In the present study, numerical experiments are made without and with the assimilation of scatterometer winds, and radiances from ATOVS and ATMS. The model performance was assessed in respect to the movement and intensification of cyclone. ATOVS data assimilation experiment had produced the best prediction with least errors less than 100 km up to 60 hours and producing pre-deepening and deepening periods accurately. The Control and SCAT wind assimilation experiments have shown good track but the errors were 150-200 km and gradual deepening from the beginning itself instead of sudden deepening.
Yan, Feilong; Nan, Liangliang; Wonka, Peter(ACM Transactions on Graphics, Association for Computing Machinery (ACM), 2016-11-11)[Conference Paper]
We propose a framework for global registration of building scans. The first contribution of our work is to detect and use portals (e.g., doors and windows) to improve the local registration between two scans. Our second contribution is an optimization based on a linear integer programming formulation. We abstract each scan as a block and model the blocks registration as an optimization problem that aims at maximizing the overall matching score of the entire scene. We propose an efficient solution to this optimization problem by iteratively detecting and adding local constraints. We demonstrate the effectiveness of the proposed method on buildings of various styles and that our approach is superior to the current state of the art.
The large specific surface, and the associated high density of surface states was found to limit the light output power and quantum efficiency of nanowire-array devices, despite their potential for addressing the “green-gap” and efficiency-droop issues. The phonon and carrier confinement in nanowires also led to junction heating, and reduced heat dissipation. In this paper, we will present our studies on effective surface states passivation in InGaN/GaN quantum-disks (Qdisks)-in-nanowire light-emitting diodes (LEDs) and lasers grown on silicon (Si), as well as our recent work on nanowires LEDs grown on bulk-metal, a non-conventional substrate.
Pattnaik, Sonali; Tsvankin, Ilya; Wang, Hui; Alkhalifah, Tariq Ali(SEG Technical Program Expanded Abstracts 2016, Society of Exploration Geophysicists, 2016-09-06)[Conference Paper]
Full-waveform inversion in anisotropic media using reflected waves suffers from the strong non-linearity of the objective function and trade-offs between model parameters. Estimating long-wavelength model components by fixing parameter perturbations, referred to as reflection-waveform inversion (RWI), can mitigate nonlinearity-related inversion issues. Here, we extend RWI to acoustic VTI (transversely isotropic with a vertical symmetry axis) media. To minimize trade-offs between the model parameters, we employ a new hierarchical two-stage approach that operates with the P-wave normal-moveout velocity and anisotropy coefficents ζ and η. First, is estimated using a fixed perturbation in ζ, and then we invert for η by fixing the updated perturbation in . The proposed 2D algorithm is tested on a horizontally layered VTI model.
Many fascinating properties of materials depend strongly on the local chemical environment. This is the case for many complex oxides, such as materials with colossal magnetoresistance, where small variations of composition at the atomic scale can affect drastically the macroscopic properties. The main objective of the present work is to analyze the local chemical composition with atomic resolution and to find out if any underlying chemical order is in any way connected to the magnetic properties of double perovskite La2-2xSr1+2xMn2O7 (LSMO) manganite oxides. For these compounds, charge and orbital ordering are observed for some doping values near x = 0.50 [1, 2].
For this purpose, we have use aberration corrected scanning transmission electron microscopy (STEM) combined with electron energy-loss spectroscopy (EELS) measurements and also theoretical simulations. We have compared different compositions within three distinct magnetic regions of the phase diagram: a ferromagnetic metallic sample with x=0.36, an insulating, antiferromagnetic (AF) x=0.56 and an additional AF x=0.50 sample which also exhibits charge ordering.
High angle annular dark-field (HAADF) images, also known as Z-contrast, confirm that our single crystals exhibit high crystal quality. No secondary phases or defects are observed. Figure 1 displays an atomic resolution image obtained with the c-axis perpendicular to the electron beam of a x=0.50 sample. The perovskite (P)-like planes and the rock salt (R)-like planes are clearly observed, highlighted in green and red, respectively, on the image. The P-like planes exhibit a slightly high contrast, suggesting a possible La enrichment. EELS atomic resolution maps (inset) support a high degree of La segregation on those planes, while R-like planes are Sr rich. However, due to dechanneling of the beam, detailed image simulations are essential to accurately quantify the local chemical composition in an atomic column-by-atomic column fashion. For all our samples, we find a significant degree of long-range chemical ordering, which increases in the AF range. However, ordering is not complete and it cannot explain by itself the macroscopic electronic ordering phenomena .
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