首页|New Machine Learning Findings from Northeast Electric Power University Outlined (Micro Segment Analysis and Machine Learning Prediction for Thermal-hydraulic Pa rameters of Propane Condensation Flow In a Pche Straight Channel)
New Machine Learning Findings from Northeast Electric Power University Outlined (Micro Segment Analysis and Machine Learning Prediction for Thermal-hydraulic Pa rameters of Propane Condensation Flow In a Pche Straight Channel)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingoriginating in Jilin, People’s Rep ublic of China, by NewsRx journalists, research stated, “In the LNGregasificati on process, the printed circuit heat exchangers(PCHE) is an ideal choice for vap orizer, withpropane as the intermediate working medium in the hot side of PCHE. In this work, numerical simulationsof propane condensation flow and heat trans fer at different operating parameters was carried out in asemi-circular straigh t channel of PCHE.”
JilinPeople’s Republic of ChinaAsiaAlkanesCyborgsEmerging TechnologiesMachine LearningPropaneNortheast E lectric Power University
NETL
NSTL
