Browsing by Author "Liou, TS"

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Analysis of high-field hole transport characteristics in Si1-xGex alloys with a bond orbital band structure
(1996-01-01)
Liou, TS
;
Wang, TH
;
Chang, CY
;
交大名義發表
;
電子工程學系及電子研究所
We present an analysis of high-field hole transport in strained Si1-xGex alloys using a Monte Carlo technique. A bond orbital model is employed to calculate the valence-band structure in the simulation so that the transport behavior of high-energy holes can be described accurately. The model combines the k . p and the tight binding methods and contains no fitting parameters. The spin-orbit interaction and lattice-mismatch-induced biaxial compressive strain are included in the model. The steady state hole drift velocity and the impact ionization rate are calculated as a function of an electric field up to 500 kV/cm. Good agreement between experiment and simulation is obtained. (C) 1996 American Institute of Physics.
Conditional expectation for evaluation of risk groundwater flow and solute transport: one-dimensional analysis
(1997-12-10)
Liou, TS
;
Yeh, HD
;
環境工程研究所
;
Institute of Environmental Engineering
A one-dimensional groundwater transport equation with two uncertain parameters, groundwater velocity and longitudinal dispersivity, is investigated in this paper. The analytical uncertainty of the predicted contaminant concentration is derived by the first-order mean-centered uncertainty analysis. The risk of the contaminant transport is defined as the probability that the concentration exceeds a maximum acceptable upper limit. Five probability density functions including the normal, lognormal, gamma, Gumbel, and Weibull distributions are chosen as the models for predicting the concentration distribution. The risk for each distribution is derived analytically based on the conditional probability. The mean risk and confidence interval are then computed by Monte Carlo simulation where the groundwater velocity and longitudinal dispersivity are assumed to be lognormally and normally distributed, respectively. Results from the conditional expectation of an assumed damage function show that the unconditional expectation generally underestimates the damage for low risk events. It is found from the sensitivity analysis that the mean longitudinal dispersivity is the most sensitive parameter and the variance of longitudinal dispersivity is the least sensitive one among those distribution models except the gamma and Weibull distributions. (C) 1997 Elsevier Science B.V.