This paper examines several multi-model combination techniques: the Simple Multi-model Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.

We review the transition melting studies carried out at Mainz, and describe a recently developed model used to explain that the relatively low melting slopes are due to the partially filled d-bands, and the persistence of the pressure induced s-d transition. The basic tenets of the model have now been reconfirmed by new measurements for Cu and Ni. The measurements show that Cu which has a filled 3d-band, has a melt slope that is about 2.5 greater than its neighbor Ni. In the case of Mo, the apparent discrepancy of DAC melting measurements with shock melting can be explained by accounting for the change in melt slope due to the bcc-cp transition observed in the shock studies. The Fe melt curve is revisited. The possible relevance of the Jahn-Teller effect and recently observed transition metal melts with Icosahedral Short-Range Order (ISRO) is discussed.

Melting curves of Cu and Ni were measured to 97 GPa (3800 K) and 60 GPa (2970 K), respectively, in the laser-heated diamond cell. The measured melting temperatures of Cu are in good agreement with recent theoretical calculations. The melting slope (dT/dP) of Cu, which has a filled d-electron band, is about 2.5 times steeper than for Ni, which with one less electron, has a partially unfilled d-electron band. The relatively low melting slope obtained for Ni, measured using identical experimental methods as for Cu, is consistent with our previous measurements for other transition metals with partially filled d-bands, which are in serious disagreement with theoretical estimates. The present results confirm the key role d-shell electrons play in determining the high pressure melting curves.

The intent of this chapter is to provide the basics of using x-ray diffraction techniques in order to obtain information on the structure and morphology of the nanosystems, and also to point out some of its strengths and weaknesses when compare to other characterization techniques. X-ray scattering examines over a wide range of density domains from a tenth to a thousandth angstrom. Essentially, this covers a whole range of condensed matter, including the structure and morphology of nanosystems, particularly useful for examining nanostructures in lifescience. This range of domain size requires both the wide-angle x-ray scattering (WAXS) and small-angle (SAXS) x-ray scattering techniques. Roughly WAXS covers from 2 nm down, and SAXS covers from .5 nm to 100 nm and possibly 1,000 nm for a finely tuned instrument. Brief theoretical description of both WAXS and SAXS will be given in this chapter. WAXS, by itself is a powerful technique in providing information on the crystallographic structure or lack of structure, atomic positions and sizes in a unit cell, to some extend, chemical compositions and as well as chemical stoichiometry. Examples of such experiments will also be given. In order to be able to describe the technique of x-ray scattering, some …

Trabecular bone structure and bone density contribute to the strength of bone and are important in the study of osteoporosis. Wavelets are a powerful tool to characterize and quantify texture in an image. In this study the thickness of trabecular bone was analyzed in 8 cylindrical cores of the vertebral spine. Images were obtained from 3 Tesla (T) magnetic resonance imaging (MRI) and micro-computed tomography ({micro}CT). Results from the wavelet based analysis of trabecular bone were compared with standard two-dimensional structural parameters (analogous to bone histomorphometry) obtained using mean intercept length (MR images) and direct 3D distance transformation methods ({micro}CT images). Additionally, the bone volume fraction was determined from MR images. We conclude that the wavelet based analyses delivers comparable results to the established MR histomorphometric measurements. The average deviation in trabecular thickness was less than one pixel size between the wavelet and the standard approach for both MR and {micro}CT analysis. Since the wavelet based method is less sensitive to image noise, we see an advantage of wavelet analysis of trabecular bone for MR imaging when going to higher resolution.

Molecular dynamics simulations of nanocrystalline (nc) copper under shock loading show an unexpected ultra-high strength behind the shock front. The strength at high pressure can be up to twice the value at low pressure, for all grain sizes studied here (5-50 nm grains, with up to {approx}4 10{sup 8} atoms). Partial and perfect dislocations, twinning, and debris from dislocation interactions are found behind the shock front. Results are interpreted in terms of the pressure dependence of both deformation mechanisms active at these grain sizes, namely dislocation plasticity and grain boundary sliding. These simulations, together with new shock experiments on nc nickel, raise the possibility of achieving ultra-hard materials during and after shock loading.

A model of random polycrystals of porous laminates is introduced to provide a means for studying geomechanical properties of double-porosity reservoirs. Calculations on the resulting earth reservoir model can proceed semi-analytically for studies of either the poroelastic or transport coefficients. Rigorous bounds of the Hashin-Shtrikman type provide estimates of overall bulk and shear moduli, and thereby also provide rigorous error estimates for geomechanical constants obtained from up-scaling based on a self-consistent effective medium method. The influence of hidden (or presumed unknown) microstructure on the final results can then be evaluated quantitatively. Detailed descriptions of the use of the model and some numerical examples showing typical results for the double-porosity poroelastic coefficients of a heterogeneous reservoir are presented.

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