(1.浙江大學(xué)熱能工程研究所,杭州 310027;
2.東北大學(xué)， 沈陽(yáng) 110006)
摘 要: 在前人試驗(yàn)研究工作的基礎(chǔ)上，利用人工神經(jīng)網(wǎng)絡(luò)法對(duì)大直徑漿體輸送管道的淤積臨界流速進(jìn)行了擬合和預(yù)測(cè)。結(jié)果表明，預(yù)測(cè)淤積臨界流速與實(shí)測(cè)淤積臨界流速基本一致，利用人工神經(jīng)網(wǎng)絡(luò)法研究漿體管道輸送問(wèn)題是可行的；同其他淤積臨界速度的公式相比，所建立的網(wǎng)絡(luò)模型精度高。
關(guān)鍵字: 神經(jīng)網(wǎng)絡(luò) 漿體輸送 淤積臨界流速
（1.Institute for Thermal Power Engineering, Zhejiang University, Hangzhou 310027
2.Northeastern University, Shenyang 110006）
Abstract:Based on the previous experimental works, critical deposition velocity in large pipe has been fitted and predicated by artificial neural network. The results show that the predicated velocities are in agreement with measured ones; Study on slurry transportation in pipe by artificial neural network is practical and the established model is higher in precision compared with the other formulas of critical deposition velocity.
Key words: neural network slurry transportation critical deposition velocity
