A three-dimensional mathematical model was developed to investigate the effect of gas blowing nozzle angles on multiphase flow,circulation flow rate,and mixing time during Ruhrstahl-Heraeus(RH) refining process.Also,a...A three-dimensional mathematical model was developed to investigate the effect of gas blowing nozzle angles on multiphase flow,circulation flow rate,and mixing time during Ruhrstahl-Heraeus(RH) refining process.Also,a water model with a geometric scale of 1:4 from an industrial RH furnace of 260 t was built up,and measurements were carried out to validate the mathematical model.The results show that,with a conventional gas blowing nozzle and the total gas flow rate of 40 L·min^(-1),the mixing time predicted by the mathematical model agrees well with the measured values.The deviations between the model predictions and the measured values are in the range of about 1.3%–7.3% at the selected three monitoring locations,where the mixing time was defined as the required time when the dimensionless concentration is within 3% deviation from the bath averaged value.In addition,the circulation flow rate was 9 kg·s^(-1).When the gas blowing nozzle was horizontally rotated by either 30° or 45°,the circulation flow rate was found to be increased by about 15% compared to a conventional nozzle,due to the rotational flow formed in the up-snorkel.Furthermore,the mixing time at the monitoring point 1,2,and 3 was shortened by around 21.3%,28.2%,and 12.3%,respectively.With the nozzle angle of 30° and 45°,the averaged residence time of 128 bubbles in liquid was increased by around 33.3%.展开更多
Most of the intelligent surveillances in the industry only care about the safety of the workers.It is meaningful if the camera can know what,where and how the worker has performed the action in real time.In this paper...Most of the intelligent surveillances in the industry only care about the safety of the workers.It is meaningful if the camera can know what,where and how the worker has performed the action in real time.In this paper,we propose a light-weight and robust algorithm to meet these requirements.By only two hands'trajectories,our algorithm requires no Graphic Processing Unit(GPU)acceleration,which can be used in low-cost devices.In the training stage,in order to find potential topological structures of the training trajectories,spectral clustering with eigengap heuristic is applied to cluster trajectory points.A gradient descent based algorithm is proposed to find the topological structures,which reflects main representations for each cluster.In the fine-tuning stage,a topological optimization algorithm is proposed to fine-tune the parameters of topological structures in all training data.Finally,our method not only performs more robustly compared to some popular offline action detection methods,but also obtains better detection accuracy in an extended action sequence.展开更多
基金financially supported by the National Natural Science Foundation of China(No.51704062)the Fundamental Research Funds for the Central Universities,China(No.N2025019)。
文摘A three-dimensional mathematical model was developed to investigate the effect of gas blowing nozzle angles on multiphase flow,circulation flow rate,and mixing time during Ruhrstahl-Heraeus(RH) refining process.Also,a water model with a geometric scale of 1:4 from an industrial RH furnace of 260 t was built up,and measurements were carried out to validate the mathematical model.The results show that,with a conventional gas blowing nozzle and the total gas flow rate of 40 L·min^(-1),the mixing time predicted by the mathematical model agrees well with the measured values.The deviations between the model predictions and the measured values are in the range of about 1.3%–7.3% at the selected three monitoring locations,where the mixing time was defined as the required time when the dimensionless concentration is within 3% deviation from the bath averaged value.In addition,the circulation flow rate was 9 kg·s^(-1).When the gas blowing nozzle was horizontally rotated by either 30° or 45°,the circulation flow rate was found to be increased by about 15% compared to a conventional nozzle,due to the rotational flow formed in the up-snorkel.Furthermore,the mixing time at the monitoring point 1,2,and 3 was shortened by around 21.3%,28.2%,and 12.3%,respectively.With the nozzle angle of 30° and 45°,the averaged residence time of 128 bubbles in liquid was increased by around 33.3%.
基金Our research has been supported in part by National Natural Science Foundation of China under Grants 61673261 and 61703273.We gratefully acknowledge the support from some companies.
文摘Most of the intelligent surveillances in the industry only care about the safety of the workers.It is meaningful if the camera can know what,where and how the worker has performed the action in real time.In this paper,we propose a light-weight and robust algorithm to meet these requirements.By only two hands'trajectories,our algorithm requires no Graphic Processing Unit(GPU)acceleration,which can be used in low-cost devices.In the training stage,in order to find potential topological structures of the training trajectories,spectral clustering with eigengap heuristic is applied to cluster trajectory points.A gradient descent based algorithm is proposed to find the topological structures,which reflects main representations for each cluster.In the fine-tuning stage,a topological optimization algorithm is proposed to fine-tune the parameters of topological structures in all training data.Finally,our method not only performs more robustly compared to some popular offline action detection methods,but also obtains better detection accuracy in an extended action sequence.
