Development and Validation of a Tokamak Skin Effect Transformer model

A control oriented, lumped parameter model for the tokamak transformer including the slow flux penetration in the plasma (skin effect transformer model) is presented. The model does not require detailed or explicit information about plasma profiles or geometry. Instead, this information is lumped in system variables, parameters and inputs. The model has an exact mathematical structure built from energy and flux conservation theorems, predicting the evolution and non linear interaction of the plasma current and internal inductance as functions of the primary coil currents, plasma resistance, non-inductive current drive and the loop voltage at a specific location inside the plasma (equilibrium loop voltage). Loop voltage profile in the plasma is substituted by a three-point discretization, and ordinary differential equations are used to predict the equilibrium loop voltage as function of the boundary and resistive loop voltages. This provides a model for equilibrium loop voltage evolution, which is reminiscent of the skin effect. The order and parameters of this differential equation are determined empirically using system identification techniques. Fast plasma current modulation experiments with Random Binary Signals (RBS) have been conducted in the TCV tokamak to generate the required data for the analysis. Plasma current was modulated in Ohmic conditions between 200kA and 300kA with 30ms rise time, several times faster than its time constant L/R\approx200ms. The model explains the most salient features of the plasma current transients without requiring detailed or explicit information about resistivity profiles. This proves that lumped parameter modeling approach can be used to predict the time evolution of bulk plasma properties such as plasma inductance or current with reasonable accuracy; at least in Ohmic conditions without external heating and current drive sources

Experimental and computational studies of structure and bonding in parent and reduced forms of the azo dye Orange II

The structure and bonding of the azo dye Orange II (Acid Orange 7) in parent and reduced forms have been studied using NMR, infrared, Raman, UV−visible, and electron paramagnetic resonance (EPR) spectroscopy, allied with density functional theory (DFT) calculations on three hydrazone models (no sulfonate, anionic sulfonate, and protonated sulfonate) and one azo model (protonated sulfonate). The calculated structures of the three hydrazone models are similar to each other and that of the model without a sulfonate group (Solvent Yellow 14) closely matches its reported crystal structure. The 1H and 13C NMR resonances of Orange II, assigned directly from 1D and 2D experimental data, indicate that it is present as ≥95% hydrazone in aqueous solution, and as a ca. 70:30 hydrazone:azo mixture in dimethyl sulfoxide at 300 K. Overall, the experimental data from Orange II are matched well by calculations on the hydrazone model with a protonated sulfonate group; the IR, Raman, and UV−visible spectra of Orange II are assigned to specific vibrational modes and electronic transitions calculated for this model. The EPR spectrum obtained on one-electron reduction of Orange II by the 2-hydroxy-2-propyl radical (•CMe2OH) at pH 4 is attributed to the hydrazyl radical produced on protonation of the radical anion. Calculations on reduced forms of the model dyes support this assignment, with electron spin density on the two nitrogen atoms and the naphthyl ring; in addition, they provide estimates of the structures, vibrational spectra, and electronic transitions of the radicals

The Relevance of a Back-Scatter Model for Depth-Averaged Flow Simulation

This study demonstrates the importance of a sophisticated sub-grid model when performing a depth-averaged unsteady RANS simulation of a shallow flow. The reduction of resolution and the spatial dimensions exclude important physical processes as present in three-dimensional turbulence. Especially the effect of the bottom turbulence on the formation of horizontal eddies appears of key importance. A method is proposed to incorporate these effects by means of a kinematic simulation that mimics the residual turbulent fluctuations in a straight channel flow after depth-averaging. This method is developed in the context of the evolution of large eddies in a shallow mixing layer. A comparison with experiments shows that the proposed method works satisfactory. Naturally, it does not fully account for the omission of all 3D-effects.Hydraulic EngineeringCivil Engineering and Geoscience

Vocal Diversity of Kloss’s Gibbons (Hylobates Klossii) in the Mentawai Islands, Indonesia

Gibbons (family Hylobatidae) are generally described as monogamous, frugivorous, arboreal, and territorial apes and inhabit tropical and subtropical forests of South and Southeast Asia (Marshall and Sugardjito 1986; Leighton 1987; Chivers 2001; Geissmann 2003). All gibbon species are known to produce elaborate, loud, long, and stereotyped patterns of vocalization often referred to as ‘‘songs’’ (Marshall and Marshall 1976; Haimoff 1984; Geissmann 1993, 1995, 2002b, 2003). Generally, song bouts are produced in the early morning and last approximately 10–30 min. Species-specific song characteristics in gibbons are thought to have a strong genetic component (Brockelman and Schilling 1984; Geissmann 1984; Tenaza 1985; Marshall and Sugardjito 1986; Mather 1992; Geissmann 1993). It has previously been demonstrated that gibbon song characteristics are useful for assessing systematic relationships on the level of the gibbon genus, species and local population, and for reconstructing gibbon phylogeny (Haimoff et al. 1982; Haimoff 1983; Creel and Preuschoft 1984; Haimoff et al. 1984; Marshall et al. 1984; Geissmann 1993, 2002a, b; Konrad and Geissmann 2006; Dallmann and Geissmann this volume)

Thermophysical properties of nanofluids

This paper discusses the current state of knowledge of the thermophysical properties of nanofluids. The viscosity, thermal conductivity and heat transfer of nanofluids are considered. Experimental and molecular dynamics data are presented. It is shown that viscosity and thermal conductivity of nanofluids generally cannot be described by classical theories. The transport coefficients of nanofluids depend not only on the volume concentration of the particles but also on their size and material. The viscosity increases with decreasing the particle size while the thermal conductivity increases with increasing the particle size. The reasons for this behavior are discussed. The heat transfer coefficient is determined by the nanofluid flow mode (laminar or turbulent). The use of the nanofluids as a coolant significantly affects the magnitude of the heat transfer coefficient. In laminar flow the heat transfer coefficient of nanofluids in all cases is much more than that of base fluids. It is shown that a 2%-nanofluid intensifies the heat exchange more than twice compared to water. The effect of using nanofluids in turbulent mode depends not only on the thermal conductivity of the nanofluid, but also on its viscosity