主催: 日本エネルギー学会, 石炭科学部会, コークス工学研究部会, 重質油部会
共催: 石炭・炭素資源有効利用研究会
会議名: 第59回石炭科学会議
開催地: 札幌・道民活動センターかでる2.7（ハイブリッド開催）
開催日: 2022/10/20 - 2022/10/21
p. 2-3
The reaction rates of water gas shift reaction based on detailed chemistry from 1373 K to 1573 K were analyzed. The obtained data sets were used to train a neural network. For validation, temporal changes of mole fraction were simulated using the trained neural network, and the results were compared with those using detailed chemistry. Since the results of neural network were in good agreement with these of detailed chemistry, the neural network with information of nitrogen and temperature in the input layer was able to predict reaction rates with high accuracy.
