Surface Projection Method for Visualizing Volumetric Data

The goal of this project was to explore, develop, and implement additional visualization methods for volumetric data within MindSeer. This paper discusses the implementation of one such visualization method, the surface projection method, and compares it to other existing methods

Parameter Identification of a Surface-to-Surface Missile from Flight Test Data

This document is a detailed project proposal for estimation of aerodynamic derivatives,fuel slosh parameters and flexible: body characteristics of a surface-to-surface missile from flight test data

Grain Surface Models and Data for Astrochemistry

AbstractThe cross-disciplinary field of astrochemistry exists to understand the formation, destruction, and survival of molecules in astrophysical environments. Molecules in space are synthesized via a large variety of gas-phase reactions, and reactions on dust-grain surfaces, where the surface acts as a catalyst. A broad consensus has been reached in the astrochemistry community on how to suitably treat gas-phase processes in models, and also on how to present the necessary reaction data in databases; however, no such consensus has yet been reached for grain-surface processes. A team of ∼25 experts covering observational, laboratory and theoretical (astro)chemistry met in summer of 2014 at the Lorentz Center in Leiden with the aim to provide solutions for this problem and to review the current state-of-the-art of grain surface models, both in terms of technical implementation into models as well as the most up-to-date information available from experiments and chemical computations. This review builds on the results of this workshop and gives an outlook for future directions

Cluster detection from surface-brightness fluctuations in SDSS data

Galaxy clusters can be detected as surface brightness enhancements in smoothed optical surveys. This method does not require individual galaxies to be identifiable, and enables clusters to be detected out to surprisingly high redshifts, as recently demonstrated by the Las Campanas Distant Cluster Survey (LCDCS). Here, we investigate redshift limits for cluster detection in the Sloan Digital Sky Survey (SDSS). Calibrating assumptions about the surface brightness profile, the mass-to-light ratio, and the spectral energy distribution of galaxy clusters using available observational data, we show that it should be possible to detect galaxy groups out to redshifts of ~0.5, and massive galaxy clusters out to redshifts of ~1.2 in summed r'+i'+z' SDSS data. Redshift estimates can be derived from the SDSS magnitudes of brightest cluster members out to redshifts near unity. Over the area of sky it covers, SDSS should find >~98% of the clusters detectable by the Planck satellite through the thermal Sunyaev-Zel'dovich effect. The few Planck clusters not detected in SDSS will almost all be at z>~1.2.Comment: 7 pages, submitted to Astronomy & Astrophysic

Satellite data for surface-mine inventory

To determine the feasibility of satellite data for surface-mine inventory, particularly as it applies to coal, a case study was conducted in Maryland. A band-ratio method was developed to measure disturbed surface areas, and it proved to be extendible both temporally and geographically. This method was used to measure area changes in the region over three time periods from September 1972 through July 1974 and to map the entire two-county area for 1973. For mines ranging between 31 and 244 acres (12 to 98 hectares) the measurement accuracy of total affected acreage was determined to be 92%. Mines of 120 acres (50 hectares) and larger were measured with greater accuracy, some within one percent of the actual area. The ability to identify, classify, and measure strip-mine surfaces in a two-county area (1,541 square kilometers - 595 square miles) of western Maryland was demonstrated through the use of computer processing. On the basis of these results the use of LANDSAT satellite data and multilevel sampling of aircraft and field verification inspections, multispectral analysis of digital data is shown to be an effective, rapid, and accurate means of monitoring the surface mining cycle

Impulse-driven surface breakdown data : a Weibull statistical analysis

Surface breakdown of oil-immersed solids chosen to insulate high-voltage, pulsed-power systems is a problem that can lead to catastrophic failure. Statistical analysis of the breakdown voltages, or times, associated with such liquid-solid interfaces can reveal useful information to aid system designers in the selection of solid materials. Described in this paper are the results of a Weibull statistical analysis, applied to both breakdown-voltage data and time-to-breakdown data generated in gaps consisting of five different solid polymers immersed in mineral oil. Values of the location parameter γ provide an estimate of the applied voltage below which breakdown will not occur, and under uniform-field conditions, γ varied from 192 kV (480 kV/cm) for polypropylene to zero for ultra-high molecular weight polyethylene. Longer times to breakdown were measured for UHMWPE when compared with the other materials. However, high values of the shape parameter β reported in the present paper suggest greater sensitivity to an increase in applied voltage – that is, the probability of breakdown increases more sharply with increasing applied voltage for UHMWPE compared to the other materials. Analysing peak-applied-voltage data, only PP consistently reflected a low value of β across the different sets of test conditions. In general, longer mean times to breakdown were found for solid materials of εr more closely matched to that of the surrounding mineral oi

Integration of multimodal data based on surface registration

The paper proposes and evaluates a strategy for the alignment of anatomical and functional data of the brain. The method takes as an input two different sets of images of a same patient: MR data and SPECT. It proceeds in four steps: first, it constructs two voxel models from the two image sets; next, it extracts from the two voxel models the surfaces of regions of interest; in the third step, the surfaces are interactively aligned by corresponding pairs; finally a unique volume model is constructed by selectively applying the geometrical transformations associated to the regions and weighting their contributions. The main advantages of this strategy are (i) that it can be applied retrospectively, (ii) that it is tri-dimensional, and (iii) that it is local. Its main disadvantage with regard to previously published methods it that it requires the extraction of surfaces. However, this step is often required for other stages of the multimodal analysis such as the visualization and therefore its cost can be accounted in the global cost of the process.Postprint (published version

Derivation of surface properties from Magellan altimetry data

The fit of the Hagfors model to the Magellan altimetry data provides a means to characterize the surface properties of Venus. However, the derived surface properties are only meaningful if the model provides a good representation of the data. The Hagfors model provides a good representation of the data. The Hagfors model is generally a realistic fit to surface scattering properties of a nadir-directed antenna such as the Magellan altimeter; however, some regions of the surface of Venus are poorly described by the existing model, according to the goodness of fit parameter provided on the ARCDR CD-ROMs. Poorly characterized regions need to be identified and fit to new models in order to derive more accurate surface properties for use in inferring the geological processes that affect the surface in those regions. We have compared the goodness of fit of the Hagfors model to the distribution of features across the planet, and preliminary results show a correlation between steep topographic slopes and poor fits to the standard model, as has been noticed by others. In this paper, we investigate possible relations between many classes of features and the ability of the Hagfors model to fit the observed echo profiles. In the regions that are not well characterized by existing models, we calculate new models that compensate for topographic relief in order to derive improved estimates of surface properties. Areas investigated to date span from longitude 315 through 45, at all latitudes covered by Magellan. A survey of those areas yields preliminary results that suggest that topographically high regions are well suited to the current implementation of the Hagfors model. Striking examples of such large-scale good fits are Alpha Regio, the northern edges of Lada Terra, and the southern edge of Ishtar Terra. Other features that are typically well fit are the rims of coronae such as Heng-O and the peaks of volcanos such as Gula Mons. Surprisingly, topographically low regions, such as the ubiquitous plains areas, are modeled poorly in comparison. However, this generalization has has exceptions: Lakshmi Planum is an elevated region that is not well fit compared to the rest of neighboring Ishtar, while the southern parts of topographically low Guinevere Planitia are characterized quite well by the Hagfors model. Features that are candidates for improved models are impact craters, coronae, ridges of significant scale, complex ridged terrains, moderate-sized mountains, and sharp terrain boundaries. These features are chosen because the goodness of fit is likely to be most affected either by departures from normal incidence angles or by sharp changes in terrain type within a single footprint. Most large features that are elevated with respect to their surroundings will suffer from steep slope effects, and smaller coronae and impact craters will probably suffer due to rapid changes in their appearance within a single footprint (10-20 km)