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Keywords
Numerical avalanche dynamics models have become an essential part of snow engineering. Coupled with field observations and historical records, they are especially helpful in understanding avalanche flow in complex terrain. However, their application poses several new challenges to avalanche engineers. A detailed understanding of the avalanche phenomena is required to construct hazard scenarios which involve the careful specification of initial conditions (release zone location and dimensions) and definition of appropriate friction parameters. The interpretation of simulation results requires an understanding of the numerical solution schemes and easy to use visualization tools. We discuss these problems by presenting the computer model RAMMS, which was specially designed by the SLF as a practical tool for avalanche engineers. RAMMS solves the depth-averaged equations governing avalanche flow with accurate second-order numerical solution schemes. The model allows the specification of multiple release zones in three-dimensional terrain. Snow cover entrainment is considered. Furthermore, two different flow rheologies can be applied: the standard Voellmy–Salm (VS) approach or a random kinetic energy (RKE) model, which accounts for the random motion and inelastic interaction between snow granules. We present the governing differential equations, highlight some of the input and output features of RAMMS and then apply the models with entrainment to simulate two well-documented avalanche events recorded at the Vallée de la Sionne test site.
Oxorhenium(V) complexes [ReOX3(PPh3)2] (X = Cl, Br) react with phenylacetylene under formation of complexes with ylide-type ligands. Compounds of the compositions [ReOCl3(PPh3){C(Ph)C(H)(PPh3)}] (1), [ReOBr3(OPPh3){C(Ph)C(H)(PPh3)}] (2), and [ReOBr3(OPPh3){C(H)C(Ph)(PPh3)}] (3) were isolated and characterized by X-ray diffraction. They contain a ligand, which was formed by a nucleophilic attack of released PPh3 at coordinated phenylacetylene. The structures of the products show that there is no preferable position for this attack. Cleavage of the Re–C bond in 3 and dimerization of the organic ligand resulted in the formation of the [{(PPh3)(H)CC(Ph)}2]2+ cation, which crystallized as its [(ReOBr4)(OReO3)]2– salt.
Realization of a calorimetric gas sensor on polyimide foil for applications in aseptic food industry
(2010)
Quantifying and minimizing uncertainty is vital for simulating technically and economically successful geothermal reservoirs. To this end, we apply a stochastic modelling sequence, a Monte Carlo study, based on (i) creating an ensemble of possible realizations of a reservoir model, (ii) forward simulation of fluid flow and heat transport, and (iii) constraining post-processing using observed state variables. To generate the ensemble, we use the stochastic algorithm of Sequential Gaussian Simulation and test its potential fitting rock properties, such as thermal conductivity and permeability, of a synthetic reference model and—performing a corresponding forward simulation—state variables such as temperature. The ensemble yields probability distributions of rock properties and state variables at any location inside the reservoir. In addition, we perform a constraining post-processing in order to minimize the uncertainty of the obtained distributions by conditioning the ensemble to observed state variables, in this case temperature. This constraining post-processing works particularly well on systems dominated by fluid flow. The stochastic modelling sequence is applied to a large, steady-state 3-D heat flow model of a reservoir in The Hague, Netherlands. The spatial thermal conductivity distribution is simulated stochastically based on available logging data. Errors of bottom-hole temperatures provide thresholds for the constraining technique performed afterwards. This reduce the temperature uncertainty for the proposed target location significantly from 25 to 12 K (full distribution width) in a depth of 2300 m. Assuming a Gaussian shape of the temperature distribution, the standard deviation is 1.8 K. To allow a more comprehensive approach to quantify uncertainty, we also implement the stochastic simulation of boundary conditions and demonstrate this for the basal specific heat flow in the reservoir of The Hague. As expected, this results in a larger distribution width and hence, a larger, but more realistic uncertainty estimate. However, applying the constraining post-processing the uncertainty is again reduced to the level of the post-processing without stochastic boundary simulation. Thus, constraining post-processing is a suitable tool for reducing uncertainty estimates by observed state variables.
The purpose of the current study was to examine the reproducibility of fascicle length and pennation angle of gastrocnemius medialis while human walking. To the best of our knowledge, this is the first study of the reproducibility of fascicle length and pennation angle of gastrocnemius medialis in vivo during human gait. Twelve males performed 10 gait trials on a treadmill, in 2 separate days. B-mode ultrasonography, with the ultrasound probe firmly adjusted in the transverse and frontal planes using a special cast, was used to measure the fascicle length and the pennation angle of the gastrocnemius medialis (GM). A Vicon 624 system with three cameras operating at 120 Hz was also used to record the ankle and knee joint angles. The results showed that measurements of fascicle length and pennation angle showed high reproducibility during the gait cycle, both within the same day and between different days. Moreover, the root mean square differences between the repeated waveforms of both variables were very small, compared with their ranges (fascicle length: RMS = ∼3 mm, range: 38–63 mm; pennation angle: RMS = ∼1.5°, range: 22–32°). However, their reproducibility was lower compared to the joint angles. It was found that representative data have to be derived by a wide number of gait trials (fascicle length ∼six trials, pennation angle more than 10 trials), to assure the reliability of the fascicle length and pennation angle in human gait.
As the field strength and, therefore, the operational frequency in MRI is increased, the wavelength approaches the size of the human head/body, resulting in wave effects, which cause signal decreases and dropouts. Several multichannel approaches have been proposed to try to tackle these problems, including RF shimming, where each element in an array is driven by its own amplifier and modulated with a certain (constant) amplitude and phase relative to the other elements, and Transmit SENSE, where spatially tailored RF pulses are used. In this article, a relatively inexpensive and easy to use imaging scheme for 7 Tesla imaging is proposed to mitigate signal voids due to B1 field inhomogeneity. Two time-interleaved images are acquired using a different excitation mode for each. By forming virtual receive elements, both images are reconstructed together using GRAPPA to achieve a more homogeneous image, with only small SNR and SAR penalty in head and body imaging at 7 Tesla.