| Project/Area Number |
11650793
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
反応・分離工学
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| Research Institution | University of Tokyo |
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Principal Investigator |
TSUTSUMI Atsushi Univ.of Tokyo, Dept.of Chem.System.Eng., Associate Professor, 大学院・工学系研究科, 助教授 (00188591)
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| Project Period (FY) |
1999 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2000: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1999: ¥2,900,000 (Direct Cost: ¥2,900,000)
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| Keywords | Neural Networks / Virtual Reactor / Virtual Reaction Experiment / Dynamic Reaction Engineering / Nonlinear Systems / Virtual Reaction Systems / 仮想反応 / 仮想反応実験 / ニュートラルネットワーク |
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| Research Abstract |
In the present study, artificial neural networks have been applied to modeling the reaction kinetics of carbon-NOx reaction as a "virtual reaction system". The unsteady-state kinetic experiments were carried out using a fixed-bed flow reactor at various different experimental conditions altered continuously. The changes in the concentrations of O2, CO2, N2, NO and NO2 were measured as time series data of reaction kinetics by gas chromatography and a NOx meter. The time series data of reaction kinetics (the amount of catalyst and carbon, temperature and concentrations of reaction species versus time) was used for learning the neural networks. The mechanisms of carbon-NOx reaction are discussed based on the virtual experiments by means of trained neural network model.
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