Finite element analysis of fluid-filled elastic piping systems

Two finite element procedures are described for predicting the dynamic response of general 3-D fluid-filled elastic piping systems. The first approach, a low frequency procedure, models each straight pipe or elbow as a sequence of beams. The contained fluid is modeled as a separate coincident sequence axial members (rods) which are tied to the pipe in the lateral direction. The model includes the pipe hoop strain correction to the fluid sound speed and the flexibility factor correction to the elbow flexibility. The second modeling approach, an intermediate frequency procedure, follows generally the original Zienkiewicz-Newton scheme for coupled fluid-structure problems except that the velocity potential is used as the fundamental fluid unknown to symmetrize the coefficient matrices. From comparisons of the beam model predictions to both experimental data and the 3-D model, the beam model is validated for frequencies up to about two-thirds of the lowest fluid-filled labor pipe mode. Accurate elbow flexibility factors are seen to be crucial for effective beam modeling of piping systems

An approach to market analysis for lighter than air transportation of freight

An approach is presented to marketing analysis for lighter than air vehicles in a commercial freight market. After a discussion of key characteristics of supply and demand factors, a three-phase approach to marketing analysis is described. The existing transportation systems are quantitatively defined and possible roles for lighter than air vehicles within this framework are postulated. The marketing analysis views the situation from the perspective of both the shipper and the carrier. A demand for freight service is assumed and the resulting supply characteristics are determined. Then, these supply characteristics are used to establish the demand for competing modes. The process is then iterated to arrive at the market solution

Core polarization in chromium-53

Core polarization in chromium 5

Flat Histogram Method of Wang-Landau and N-fold Way

We present a method for estimating the density of states of a classical statistical model. The algorithm successfully combines the Wang-Landau flat histogram method with the N-fold way in order to improve efficiency of the original single spin flip version. We test our implementation of the Wang-Landau method with the two-dimensional nearest neighbor Ising model for which we determine the tunneling time and the density of states. Furthermore, we show that our new algorithm performs correctly at right edges of an energy interval over which the density of states is computed. This removes a disadvantage of the original single spin flip Wang-Landau method where results showed systematically higher errors in the density of states at right boundaries. We compare our data with the detailed numerical tests presented in a study by Wang and Swendsen where the original Wang-Landau method was tested against various other methods. Finally, we apply our method to a thin Ising film of size $32\times 32\times 6$ with antisymmetric surface fields. With the density of states obtained from the simulations we calculate canonical averages related to the energy such as internal energy, Gibbs free energy and entropy, but we also sample microcanonical averages during simulations in order to determine canonical averages of the susceptibility, the order parameter and its fourth order cumulant. We compare our results with simulational data obtained from a conventional MC algorithm.Comment: Latex, 19 pages, 12 encapsulated Postscript figure

Lifetimes and Gj factors in excited states of chromium. Hyperfine structure of Cr53

Electronic and nuclear properties of excited chromium isotopes using level crossing and double resonance spectroscopy technique

Absence of Structural Impact of Noble Nanoparticles on P3HT: PCBM Blends for Plasmon Enhanced Bulk-Heterojunction Organic Solar Cells Probed by Synchrotron Grazing Incidence X-Ray Diffraction

The incorporation of noble metal nanoparticles, displaying localized surface plasmon resonance, in the active area of donor-acceptor bulk-heterojunction organic photovoltaic devices is an industrially compatible light trapping strategy, able to guarantee better absorption of the incident photons and give an efficiency improvement between 12% and 38%. In the present work, we investigate the effect of Au and Ag nanoparticles blended with P3HT: PCBM on the P3HT crystallization dynamics by synchrotron grazing incidence X-ray diffraction. We conclude that the presence of (1) 80nm Au, (2) mix of 5nm, 50nm, 80nm Au, (3) 40nm Ag, and (4) 10nm, 40nm, 60nm Ag colloidal nanoparticles, at different concentrations below 0.3 wt% in P3HT: PCBM blends, does not affect the behaviour of the blends themselves

Effective g-factor in Majorana Wires

We use the effective g-factor of subgap states, g*, in hybrid InAs nanowires with an epitaxial Al shell to investigate how the superconducting density of states is distributed between the semiconductor core and the metallic shell. We find a step-like reduction of g* and improved hard gap with reduced carrier density in the nanowire, controlled by gate voltage. These observations are relevant for Majorana devices, which require tunable carrier density and g* exceeding the g-factor of the proximitizing superconductor. Additionally, we observe the closing and reopening of a gap in the subgap spectrum coincident with the appearance of a zero-bias conductance peak

Testing for seasonal unit roots by frequency domain regression

This paper develops univariate seasonal unit root tests based on spectral regression estimators. An advantage of the frequency domain approach is that it enables serial correlation to be treated non-parametrically. We demonstrate that our proposed statistics have pivotal limiting distributions under both the null and near seasonally integrated alternatives when we allow for weak dependence in the driving shocks. This is in contrast to the popular seasonal unit root tests of, among others, Hylleberg et al. (1990) which treat serial correlation parametrically via lag augmentation of the test regression. Moreover, our analysis allows for (possibly infinite order) moving average behaviour in the shocks, while extant large sample results pertaining to the Hylleberg et al. (1990) type tests are based on the assumption of a finite autoregression. The size and power properties of our proposed frequency domain regression-based tests are explored and compared for the case of quarterly data with those of the tests of Hylleberg et al. (1990) in simulation experiments.Seasonal unit root tests; moving average; frequency domain regression; spectral density estimator; Brownian motion