Baosteel＇ s Slag Short Flow（BSSF） is an innovative process for steelmaking slag treatment that was developed by Baosteel. The process principles, flow-chart, parameters and component systems of the BSSF for steelma...Baosteel＇ s Slag Short Flow（BSSF） is an innovative process for steelmaking slag treatment that was developed by Baosteel. The process principles, flow-chart, parameters and component systems of the BSSF for steelmaking slag treatment are presented. Characteristics of the finished BSSF slag are summarized by analyzing the slag＇ s physical and chemical performances. Several Utilization methods for the BSSF slag are given.展开更多
Traffic flow prediction in urban areas is essential in the IntelligentTransportation System (ITS). Short Term Traffic Flow (STTF) predictionimpacts traffic flow series, where an estimation of the number of vehicleswil...Traffic flow prediction in urban areas is essential in the IntelligentTransportation System (ITS). Short Term Traffic Flow (STTF) predictionimpacts traffic flow series, where an estimation of the number of vehicleswill appear during the next instance of time per hour. Precise STTF iscritical in Intelligent Transportation System. Various extinct systems aim forshort-term traffic forecasts, ensuring a good precision outcome which was asignificant task over the past few years. The main objective of this paper is topropose a new model to predict STTF for every hour of a day. In this paper,we have proposed a novel hybrid algorithm utilizing Principal ComponentAnalysis (PCA), Stacked Auto-Encoder (SAE), Long Short Term Memory(LSTM), and K-Nearest Neighbors (KNN) named PALKNN. Firstly, PCAremoves unwanted information from the dataset and selects essential features.Secondly, SAE is used to reduce the dimension of input data using onehotencoding so the model can be trained with better speed. Thirdly, LSTMtakes the input from SAE, where the data is sorted in ascending orderbased on the important features and generates the derived value. Finally,KNN Regressor takes information from LSTM to predict traffic flow. Theforecasting performance of the PALKNN model is investigated with OpenRoad Traffic Statistics dataset, Great Britain, UK. This paper enhanced thetraffic flow prediction for every hour of a day with a minimal error value.An extensive experimental analysis was performed on the benchmark dataset.The evaluated results indicate the significant improvement of the proposedPALKNN model over the recent approaches such as KNN, SARIMA, LogisticRegression, RNN, and LSTM in terms of root mean square error (RMSE)of 2.07%, mean square error (MSE) of 4.1%, and mean absolute error (MAE)of 2.04%.展开更多
In order to evaluate the effects of the short blade locations on the anti-cavitation performance of the splittel bladed inducer and the pump, 5 inducers with different short blade locations are designed, Cavitation si...In order to evaluate the effects of the short blade locations on the anti-cavitation performance of the splittel bladed inducer and the pump, 5 inducers with different short blade locations are designed, Cavitation simulatior and experimental tests of the pumps with these inducers are carried out. The algebraic slip mixture model in th CFX software is adopted for cavitation simulation. The results show that there is a vortex at the inlet of the indu（ er. Asymmetric cavitation on the inducer and on the impeller is observed. The analysis shows that the short blad locations have a minor effect on the internal flow field in the inducer and on the external performance of th pump, but have a significant effect on the anti-cavitation performance. It is suggested that the inducer shoul be designed appropriately. The present simulations found an optimal inducer with better anti-cavitatio performance.展开更多
文摘Baosteel＇ s Slag Short Flow（BSSF） is an innovative process for steelmaking slag treatment that was developed by Baosteel. The process principles, flow-chart, parameters and component systems of the BSSF for steelmaking slag treatment are presented. Characteristics of the finished BSSF slag are summarized by analyzing the slag＇ s physical and chemical performances. Several Utilization methods for the BSSF slag are given.
文摘Traffic flow prediction in urban areas is essential in the IntelligentTransportation System (ITS). Short Term Traffic Flow (STTF) predictionimpacts traffic flow series, where an estimation of the number of vehicleswill appear during the next instance of time per hour. Precise STTF iscritical in Intelligent Transportation System. Various extinct systems aim forshort-term traffic forecasts, ensuring a good precision outcome which was asignificant task over the past few years. The main objective of this paper is topropose a new model to predict STTF for every hour of a day. In this paper,we have proposed a novel hybrid algorithm utilizing Principal ComponentAnalysis (PCA), Stacked Auto-Encoder (SAE), Long Short Term Memory(LSTM), and K-Nearest Neighbors (KNN) named PALKNN. Firstly, PCAremoves unwanted information from the dataset and selects essential features.Secondly, SAE is used to reduce the dimension of input data using onehotencoding so the model can be trained with better speed. Thirdly, LSTMtakes the input from SAE, where the data is sorted in ascending orderbased on the important features and generates the derived value. Finally,KNN Regressor takes information from LSTM to predict traffic flow. Theforecasting performance of the PALKNN model is investigated with OpenRoad Traffic Statistics dataset, Great Britain, UK. This paper enhanced thetraffic flow prediction for every hour of a day with a minimal error value.An extensive experimental analysis was performed on the benchmark dataset.The evaluated results indicate the significant improvement of the proposedPALKNN model over the recent approaches such as KNN, SARIMA, LogisticRegression, RNN, and LSTM in terms of root mean square error (RMSE)of 2.07%, mean square error (MSE) of 4.1%, and mean absolute error (MAE)of 2.04%.
基金Supported by the National Natural Science Foundation of China(51406185,51276172)the China Scholarship Council Project in 2012(201208330325)+1 种基金the Third Level 151 Talent Project in Zhejiang Provincethe Professional Leader Leading Project in 2013(lj2013005)
文摘In order to evaluate the effects of the short blade locations on the anti-cavitation performance of the splittel bladed inducer and the pump, 5 inducers with different short blade locations are designed, Cavitation simulatior and experimental tests of the pumps with these inducers are carried out. The algebraic slip mixture model in th CFX software is adopted for cavitation simulation. The results show that there is a vortex at the inlet of the indu（ er. Asymmetric cavitation on the inducer and on the impeller is observed. The analysis shows that the short blad locations have a minor effect on the internal flow field in the inducer and on the external performance of th pump, but have a significant effect on the anti-cavitation performance. It is suggested that the inducer shoul be designed appropriately. The present simulations found an optimal inducer with better anti-cavitatio performance.
