Application of Muskingum routing method with variable parameters in ungauged basin

This paper describes a flood routing method applied in an ungauged basin, utilizing the Muskingum model with variable parameters of wave travel time K and weight coefficient of discharge x based on the physical characteristics of the river reach and flood, including the reach slope, length, width, and flood discharge. Three formulas for estimating parameters of wide rectangular, triangular, and parabolic cross sections are proposed. The influence of the flood on channel flow routing parameters is taken into account. The HEC-HMS hydrological model and the geospatial hydrologic analysis module HEC-GeoHMS were used to extract channel or watershed characteristics and to divide sub-basins. In addition, the initial and constant-rate method, user synthetic unit hydrograph method, and exponential recession method were used to estimate runoff volumes, the direct runoff hydrograph, and the baseflow hydrograph, respectively. The Muskingum model with variable parameters was then applied in the Louzigou Basin in Henan Province of China, and of the results, the percentages of flood events with a relative error of peak discharge less than 20% and runoff volume less than 10% are both 100%. They also show that the percentages of flood events with coefficients of determination greater than 0.8 are 83.33%, 91.67%, and 87.5%, respectively, for rectangular, triangular, and parabolic cross sections in 24 flood events. Therefore, this method is applicable to ungauged basins.

Accelerating dark energy models with anisotropic fluid in Bianchi type Ⅵ_0 space-time

Motivated by the increasing evidence for the need of a geometry that re- sembles Bianchi morphology to explain the observed anisotropy in the WMAP data, we have discussed some features of Bianchi type VI0 universes in the presence of a fluid that has an anisotropic equation of state （EoS） parameter in general relativity. We present two accelerating dark energy （DE） models with an anisotropic fluid in Bianchi type VI0 space-time. To ensure a deterministic solution, we choose the scale factor a（t） = √tnet, which yields a time-dependent deceleration parameter, representing a class of models which generate a transition of the universe from the early decelerating phase to the recent accelerating phase. Under suitable conditions, the anisotropic mod- els approach an isotropic scenario. The EoS for DE co is found to be time-dependent and its existing range for derived models is in good agreement with data from recent observations of type Ia supernovae （SNe Ia） （Knop et al. 2003）, SNe Ia data com- bined with cosmic microwave background （CMB） anisotropy and galaxy clustering statistics （Tegmark et al. 2004a）, as well as the latest combination of cosmological datasets coming from CMB anisotropies, luminosity distances of high redshift SNe Ia and galaxy clustering. For different values of n, we can generate a class of physically viable DE models. The cosmological constant A is found to be a positive decreasing function of time and it approaches a small positive value at late time （i.e. the present epoch）, which is corroborated by results from recent SN Ia observations. We also ob- serve that our solutions are stable. The physical and geometric aspects of both models are also discussed in detail.

Temperature-variable high-frequency dynamic modeling of PIN diode

The PIN diode model for high frequency dynamic transient characteristic simulation is important in conducted EMI analysis. The model should take junction temperature into consideration since equipment usually works at a wide range of temperature. In this paper, a temperature-variable high frequency dynamic model for the PIN diode is built, which is based on the Laplace-transform analytical model at constant temperature. The relationship between model parameters and temperature is expressed as temperature functions by analyzing the physical principle of these parameters. A fast recovery power diode MUR1560 is chosen as the test sample and its dynamic performance is tested under inductive load by a temperature chamber experiment, which is used for model parameter extraction and model verification. Results show that the model proposed in this paper is accurate for reverse recovery simulation with relatively small errors at the temperature range from 25 to 120 ℃.