Fabry-Perot Measurements of the Dynamics of Globular Cluster Cores: M15 (NGC~7078)

We report the first use of the Rutgers Imaging Fabry-Perot Spectrophotometer to study the dynamics of the cores of globular clusters. We have obtained velocities for cluster stars by tuning the Fabry-Perot to take a series of narrow-band images at different wavelengths across one of the Na D (5890 AA) absorption lines. Measuring the flux in every frame yields a short portion of the spectrum for each star simultaneously. This proves to be a very efficient method for obtaining accurate stellar velocities; in crowded regions we are able to measure hundreds of velocities in 3-4 hours of observing time. We have measured velocities with uncertainties of less than 5 km/s for 216 stars within 1.5' of the center of the globular cluster M15 (NGC 7078). The paper is a uuencoded compressed postscript file

The Stellar Populations of the Carina Dwarf Spheroidal Galaxy: I. a New Color-Magnitude Diagram for the Giant and Horizontal Branches

We report on the first in a series of studies of the Carina dwarf spheroidal galaxy, a nearby satellite of our Galaxy. Our two major results are: 1) precise BI photometry (\sigma_{B-I} \simlt 0.05 for V \simlt 22) for 11,489 stars in the Carina field, and 2) the detection of two, morphologically distinct, horizontal branches, which confirms that star formation in Carina occurred in two well-separated episodes. The old horizontal branch and RR Lyrae instability strip belong to a > 10 Gyr stellar population, while the populous red-clump horizontal branch belongs to an approximately 6 Gyr stellar population. We derive a distance modulus $(m-M)_0=20.09 \pm 0.06$ for Carina from the apparent magnitudes of the old horizontal branch and the tip of the red giant branch, and discuss modifications to the previously estimated distance, total magnitude, and stellar ages. Using the color of the red giant branch, we estimate the metallicities of the younger and older populations to be [Fe/H] = -2.0 and -2.2, respectively.Comment: 18 pages, 9 figures, uses AAS LaTex macros, PostScript figures available through anonymous ftp, accepted for publication in the Astronomical Journal, DAO-tsh94-

Quantitative comparison of planar coded aperture imaging reconstruction methods

Imaging distributions of radioactive sources plays a substantial role in nuclear medicine as well as in monitoring nuclear waste and its deposit. Coded Aperture Imaging (CAI) has been proposed as an alternative to parallel or pinhole collimators, but requires image reconstruction as an extra step. Multiple reconstruction methods with varying run time and computational complexity have been proposed. Yet, no quantitative comparison between the different reconstruction methods has been carried out so far. This paper focuses on a comparison based on three sets of hot-rod phantom images captured with an experimental γ-camera consisting of a Tungsten-based MURA mask with a 2 mm thick 256 × 256 pixelated CdTe semiconductor detector coupled to a Timepix© readout circuit. Analytical reconstruction methods, MURA Decoding, Wiener Filter and a convolutional Maximum Likelihood Expectation Maximization (MLEM) algorithm were compared to data-driven Convolutional Encoder-Decoder (CED) approaches. The comparison is based on the contrast-to-noise ratio as it has been previously used to assess reconstruction quality. For the given set-up, MURA Decoding, the most commonly used CAI reconstruction method, provides robust reconstructions despite the assumption of a linear model. For single image reconstruction, however, MLEM performed best of all analytical reconstruction methods, but took on average 45 times longer than MURA Decoding. The fastest reconstruction method is the Wiener Filter with a run time 4.3 times faster compared to MURA Decoding and a mediocre quality. The CED with a specifically tailored training set was able to succeed the most commonly used MURA decoding on average by a factor between 1.37 and 2.60 and an equal run time

Analysis of linearized inverse problems in ultrasound transmission imaging

The purpose of this paper is to analyze the linearized inverse problem during the iterativesolution process of the ill-posed nonlinear inverse problem of image reconstruction for ultra-sound transmission imaging. We show that the conjugate gradient applied to normal equation(CGNE) method gives more reliable solutions for linearized systems than Tikhonov regular-ization methods. The linearized systems are more sensitive when treated by CGNE than byTikhonov regularization methods. The Tikhonov regularization is less effective at the be-ginning of the outer-loop iteration, where the nonlinearity is dominating while the conjugategradient for the linearized system stops earlier. Only when the linear approximation is goodenough to describe the whole system, Tikhonov regularization can fully play its role and giveslightly better reconstruction results as compared to CGNE in a very noisy case

Sixteen years of bathymetry and waves at San Diego beaches.

Sustained, quantitative observations of nearshore waves and sand levels are essential for testing beach evolution models, but comprehensive datasets are relatively rare. We document beach profiles and concurrent waves monitored at three southern California beaches during 2001-2016. The beaches include offshore reefs, lagoon mouths, hard substrates, and cobble and sandy (medium-grained) sediments. The data span two energetic El Niño winters and four beach nourishments. Quarterly surveys of 165 total cross-shore transects (all sites) at 100 m alongshore spacing were made from the backbeach to 8 m depth. Monthly surveys of the subaerial beach were obtained at alongshore-oriented transects. The resulting dataset consists of (1) raw sand elevation data, (2) gridded elevations, (3) interpolated elevation maps with error estimates, (4) beach widths, subaerial and total sand volumes, (5) locations of hard substrate and beach nourishments, (6) water levels from a NOAA tide gauge (7) wave conditions from a buoy-driven regional wave model, and (8) time periods and reaches with alongshore uniform bathymetry, suitable for testing 1-dimensional beach profile change models

Coupled Hydromechanical Modelling of a Vertical Hydraulic Sealing System Based on the Sandwich Principle

For the shaft sealing of a repository for radioactive waste, a Sandwich sealing system was developed by KIT-CMM consisting of bentonite-based sealing segments (DS) and sand mixture-based equipotential segments (ES). To demonstrate the functionality of the Sandwich sealing system, various laboratory tests (MiniSandwich tests and semi-technical scale experiments) have been carried out before a large-scale experiment has been implemented in situ at the Mont Terri Rock Laboratory (CH). An important coupled process in the Sandwich system is the swelling deformation of the DS while aqueous fluid penetrates into the system. Consequently, the interparticle porosity (effective porosity) of the DS decreases by swelling strain, resulting in a reduction in the permeability of the DS. Pore space of the ES also decreases slightly due to swelling stress in the adjacent DS, which also leads to a reduction in the permeability of the ES. To understand the coupled hydromechanical processes of the Sandwich sealing system, a numerical model was developed to interpret the experimental observations from the MiniSandwich tests and to parameterize different components. A linear swelling model for DS and empirical functions for the swelling deformation-induced permeability change for both DS and ES segments were introduced into the coupled model with Richards’ flow and elastic model. Sensitivity analysis with parameter variations of the most important parameters reduces the uncertainty in the system behavior

Including Ice Effects in a Storm Surge Modeling System

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

USCT Image Reconstruction: Acceleration using Gauss-Newton Preconditioned Conjugate Gradient

Ultrasound transmission tomography offers quantitative characterization of the tissue or materials by their speed of sound and attenuation. Reconstruction of such images is an inverse problem which is solved iteratively based on a forward model of the Helmholtz equation by paraxial approximation and thus is time-consuming. Hence, developing optimizers that decrease this time, in particular reducing the number of forward propagations is of high relevance in order to bring this technology into clinical practice. In this paper, we solve the inverse problem of reconstruction in a two-level strategy, by an outer and an inner loop. At each iteration of the outer loop, the system is linearized and this linear subproblem is solved in the inner loop with a preconditioned conjugate gradient (CG). A standard Cholesky preconditioning method based on the system matrix is compared with a matrix-free Quasi-Newton update approach, where a preconditioned matrix-vector product is computed at the beginning of every CG iteration. We also use a multigrid scheme with multi-frequency reconstruction to get a convergent rough reconstruction at a lower frequency and then refine it on a higher-resolution grid. The Cholesky preconditioning reduces the number of CG iterations by approx. 70%~85%; but the computation time for determining the system matrix for the Cholesky preconditioner is dominating, offsetting the gains of the reduction of iterations. The matrix-free preconditioning method saves approx. 30% of the computation time on average for single-frequency and multi-frequency reconstruction. For the robust multifrequency reconstruction, we test three breast-like numerical phantoms resulting in a deviation of 0.13 m/s on average in speed of sound reconstruction and a deviation of 5.4% on average in attenuation reconstruction, from the ground truth simulation