Hybrid LTA vehicle controllability as affected by buoyancy ratio

The zero and low speed controllability of heavy lift airships under various wind conditions as affected by the buoyancy ratio are investigated. A series of three hybrid LTA vehicls were examined, each having a dynamic thrust system comprised of four H-34 helicopters, but with buoyant envelopes of different volumes (and hence buoyancies), and with varying percentage of helium inflation and varying useful loads (hence gross weights). Buoyancy ratio, B, was thus examined varying from approximately 0.44 to 1.39. For values of B greater than 1.0, the dynamic thrusters must supply negative thrust (i.e. downward)

Correlation of laser velocimeter measurements over a wing with results of two prediction techniques

The flow field at the center line of an unswept wing with an aspect ratio of eight was determined using a two dimensional viscous flow prediction technique for the flow field calculation, and a three dimensional potential flow panel method to evaluate the degree of two dimensionality achieved at the wing center line. The analysis was made to provide an acceptable reference for comparison with velocity measurements obtained from a fringe type laser velocimeter optics systems operating in the backscatter mode in the Langley V/STOL tunnel. Good agreement between laser velocimeter measurements and theoretical results indicate that both methods provide a true representation of the velocity field about the wing at angles of attack of 0.6 and 4.75 deg

New Developments of Laser Desorption Ionization Mass Spectrometry in Plant Analysis

The structural identification of natural products is one of the major focus areas of analytical chemistry research. Mass spectrometry (MS) has long been used to obtain molecular weights and further molecular formulae. In the past, former ionization sources such as electronic impact unfortunately limited MS analysis to predominately volatile, polar, and thermostable compounds. However, recent developments in soft ionization techniques such as electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), or laser desorption/ionization (LDI) have gradually extended MS analysis to a much wide range of chemical structures. As far as small natural compounds are concerned, LDI sources are still seldom used because of specific technical limitations. Indeed, the photoionization process of LDI is generally assisted by a matrix, which is a small molecule carrying strong UV chromophore. The process is then called matrix‐assisted laser desorption/ionization (MALDI) process. MALDI ionization therefore induces the formation of numerous matrix ions that commonly appear in the range 0–600 Da, and consequently interfere with molecular ions originating from many natural products. For this reason, the correct signal assignment is highly impaired in the critical region of interest. As LDI and MALDI are not only soft ionization processes but also quite sensitive techniques yielding high resolution spectra when coupled to a time‐of‐flight (TOF) analyzer, different attempts have been made to adapt these techniques for the analysis of natural products. Three of them will be more specifically discussed in this chapter: (i) LDI on neat gold surfaces obtained by physical vapor diffusion (PVD), (ii) desorption/ionization on self‐assembled monolayer surfaces (DIAMS), and (iii) the use of specific matrices for the selective detection of alkaloids

Incommensurate phonon anomaly and the nature of charge density waves in cuprates

While charge density wave (CDW) instabilities are ubiquitous to superconducting cuprates, the different ordering wavevectors in various cuprate families have hampered a unified description of the CDW formation mechanism. Here we investigate the temperature dependence of the low energy phonons in the canonical CDW ordered cuprate La$_{1.875}$Ba$_{0.125}$CuO$_{4}$. We discover that the phonon softening wavevector associated with CDW correlations becomes temperature dependent in the high-temperature precursor phase and changes from a wavevector of 0.238 reciprocal space units (r.l.u.) below the ordering transition temperature up to 0.3~r.l.u. at 300~K. This high-temperature behavior shows that "214"-type cuprates can host CDW correlations at a similar wavevector to previously reported CDW correlations in non-"214"-type cuprates such as YBa$_{2}$Cu$_{3}$O$_{6+\delta}$. This indicates that cuprate CDWs may arise from the same underlying instability despite their apparently different low temperature ordering wavevectors.Comment: Accepted in Phys. Rev. X; 9 pages; 5 figures; 3 pages of supplementary materia

Optimal model parameters for multi-objective large-eddy simulations

A methodology is proposed for the assessment of error dynamics in large-eddy simulations. It is demonstrated that the optimization of model parameters with respect to one flow property can be obtained at the expense of the accuracy with which other flow properties are predicted. Therefore, an approach is introduced which allows to assess the total errors based on various flow properties simultaneously. We show that parameter settings exist, for which all monitored errors are "near optimal," and refer to such regions as "multi-objective optimal parameter regions." We focus on multi-objective errors that are obtained from weighted spectra, emphasizing both large- as well small-scale errors. These multi-objective optimal parameter regions depend strongly on the simulation Reynolds number and the resolution. At too coarse resolutions, no multi-objective optimal regions might exist as not all error-components might simultaneously be sufficiently small. The identification of multi-objective optimal parameter regions can be adopted to effectively compare different subgrid models. A comparison between large-eddy simulations using the Lilly-Smagorinsky model, the dynamic Smagorinsky model and a new Re-consistent eddy-viscosity model is made, which illustrates this. Based on the new methodology for error assessment the latter model is found to be the most accurate and robust among the selected subgrid models, in combination with the finite volume discretization used in the present study

Random Networks with Tunable Degree Distribution and Clustering

We present an algorithm for generating random networks with arbitrary degree distribution and Clustering (frequency of triadic closure). We use this algorithm to generate networks with exponential, power law, and poisson degree distributions with variable levels of clustering. Such networks may be used as models of social networks and as a testable null hypothesis about network structure. Finally, we explore the effects of clustering on the point of the phase transition where a giant component forms in a random network, and on the size of the giant component. Some analysis of these effects is presented.Comment: 9 pages, 13 figures corrected typos, added two references, reorganized reference