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Models and Algorithm for Stochastic Network Designs

Tsinghua Science and Technology 2009年第3期14卷 341-351页

作者： Anthony Chen Juyoung Kim seungjae lee Jaisung Choi Department of Civil and Environmental Engineering Utah State UniversityLogan Utah 84322-4110 USA Center for National Transport Database The Korea Transport Institute2311 DaehwaDong Ilsan-Gu Goyang City Korea Department of Transportation Engineering University of SeoulDongdaemoon-Ku Seoul Korea

The network design problem （NDP） is one of the most difficult and challenging problems in transportation. Traditional NDP models are often posed as a deterministic bilevel program assuming that all relevant inputs are known with certainty. This paper presents three stochastic models for designing transportation networks with demand uncertainty. These three stochastic NDP models were formulated as the expected value model, chance-constrained model, and dependent-chance model in a bilevel programming framework using different criteria to hedge against demand uncertainty. Solution procedures based on the traffic assignment algorithm, genetic algorithm, and Monte-Carlo simulations were developed to solve these stochastic NDP models. The nonlinear and nonconvex nature of the bilevel program was handled by the genetic algorithm and traffic assignment algorithm, whereas the stochastic nature was addressed through simulations. Numerical experiments were conducted to evaluate the applicability of the stochastic NDP models and the solution procedure. Results from the three experiments show that the solution procedures are quite robust to different parameter settings.

关键词： user equilibrium traffic assignment network design bilevel program stochastic program

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Kinetic study on catalytic gasification of a modified sludge fuel

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Particuology 2008年第4期6卷 258-264页

作者： Byungho Song Dookie Kim seungjae lee Seokku Jeon Youngtai Choi Yoonseop Byoun Woonsig Moon Joonghee lee Honggun Kim Hongki lee Joongpyo Shim Department of Chemical Engineering Kunsan National University Department of Civil & Environmental Engineering Kunsan National University Korea Institute of Energy Research Process Plant Group Hyndai Engineering Co. Ltd. Korea Institute of Industrial Technology Micro Science Tech Co. Ltd. Core Technology Research Center for Fuel Cell Department of Mechanical & Auto. Engineering Jeonju University Department of Advanced Material Engineering Woosuk University

A new type of mixture fuel, sludge–oil–coal agglomerate (SOCA), was catalytically gasified with steam in a thermobalance reactor under atmospheric pressure. All the four catalysts studied (K2CO3, CaO, NiO and Fe2O3) were found capable of enhancing the steam gasification rate and significantly increasing the conversion of carbon. The ranking of catalytic activity was found to be K2CO3 CaO > NiO > Fe2O3. A modified volumetric-reaction model in the literature was used to describe the conversion behavior of the steam gasification studied by evaluating the kinetic parameters. Expressions of the apparent gasification rates for SOCA were presented for the design of catalytic gasification processes.

关键词： Sludge Coal Oil Steam gasification Catalyst Thermobalance Kinetics

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