Effective temperature level of stream, namely stream pseudo temperature, is determined by its actual temperature and heat transfer temperature difference contribution value. Heat transfer temperature difference con-tr...Effective temperature level of stream, namely stream pseudo temperature, is determined by its actual temperature and heat transfer temperature difference contribution value. Heat transfer temperature difference con-tribution value of a stream depends on its heat transfer film coefficient, cost per unit heat transfer area, actual tem-perature, and so on. In the determination of the suitable heat transfer temperature difference contribution values of the stream, the total annual cost of multistream heat exchanger network (MSHEN) is regarded as an objective func-tion, and genetic/simulated annealing algorithm (GA/SA) is adopted for optimizing the heat transfer temperature difference contribution values of the stream. The stream pseudo temperatures are subsequently obtained. On the ba-sis of stream pseudo temperature, optimized MSHEN can be attained by the temperature-enthalpy (T-H) diagram method. This approach is characterized with fewer decision variables and higher feasibility of solutions. The calcu-lation efficiency of GA/SA can be remarkably enhanced by this approach and more probability is shown in search-ing the global optimum solution. Hence this approach is presented for solving industrial-sized MSHEN which is difficult to deal by traditional algorithm. Moreover, in the optimization of stream heat transfer temperature differ-ence contribution values, the effects of the stream temperature, the heat transfer film coefficient, and the construc-tion material of heat exchangers are considered, therefore this approach can be used to optimize and design heat exchanger network (HEN) with unequal heat transfer film coefficients and different of construction materials. The performance of the proposed approach has been demonstrated with three examples and the obtained solutions are compared with those available in literatures. The results show that the large-scale MSHEN synthesis problems can be solved to obtain good solutions with the modest computational effort.展开更多
For a multistream tundish,the uniformity among the streams plays a significant role in the quality of molten steel.How to analyze the uniformity quantitatively and optimize structures of a multistream tundish is an im...For a multistream tundish,the uniformity among the streams plays a significant role in the quality of molten steel.How to analyze the uniformity quantitatively and optimize structures of a multistream tundish is an important research content for a multistream tundish.A new approach was proposed to quantify the uniformity among the streams.And a physical study and a numerical study were carried out to optimize the structure of the diversion hole based on the prototype of a six-stream tundish in a steel plant.On the basis of average residence time,the uniformity of each flow was considered fully and then the optimal structure of the diversion hole was obtained by means of the comprehensive analysis of temperature field and velocity field.The results show that the optimum structural parameters adopted for diversion holes are height of 20 mm,angle of 15°and diameter of 80 mm.展开更多
The success of intelligent transportation systems relies heavily on accurate traffic prediction,in which how to model the underlying spatial-temporal information from traffic data has come under the spotlight.Most exi...The success of intelligent transportation systems relies heavily on accurate traffic prediction,in which how to model the underlying spatial-temporal information from traffic data has come under the spotlight.Most existing frameworks typically utilize separate modules for spatial and temporal correlations modeling.However,this stepwise pattern may limit the effectiveness and efficiency in spatial-temporal feature extraction and cause the overlook of important information in some steps.Furthermore,it is lacking sufficient guidance from prior information while modeling based on a given spatial adjacency graph(e.g.,deriving from the geodesic distance or approximate connectivity),and may not reflect the actual interaction between nodes.To overcome those limitations,our paper proposes a spatial-temporal graph synchronous aggregation(STGSA)model to extract the localized and long-term spatial-temporal dependencies simultaneously.Specifically,a tailored graph aggregation method in the vertex domain is designed to extract spatial and temporal features in one graph convolution process.In each STGSA block,we devise a directed temporal correlation graph to represent the localized and long-term dependencies between nodes,and the potential temporal dependence is further fine-tuned by an adaptive weighting operation.Meanwhile,we construct an elaborated spatial adjacency matrix to represent the road sensor graph by considering both physical distance and node similarity in a datadriven manner.Then,inspired by the multi-head attention mechanism which can jointly emphasize information from different r epresentation subspaces,we construct a multi-stream module based on the STGSA blocks to capture global information.It projects the embedding input repeatedly with multiple different channels.Finally,the predicted values are generated by stacking several multi-stream modules.Extensive experiments are constructed on six real-world datasets,and numerical results show that the proposed STGSA model significantly outperforms the benchmarks.展开更多
为提高供电恢复效果,更好地应对当前有源配电网信息-物理耦合程度不断加深的形势,提出了一种考虑信息流、能量流、业务流多流融合以及智能软开关(soft open point,SOP)作用的孤岛划分算法,基于该算法实现供电恢复策略。首先,为保证负荷...为提高供电恢复效果,更好地应对当前有源配电网信息-物理耦合程度不断加深的形势,提出了一种考虑信息流、能量流、业务流多流融合以及智能软开关(soft open point,SOP)作用的孤岛划分算法,基于该算法实现供电恢复策略。首先,为保证负荷的可靠恢复,该策略深入研究信息-物理耦合并建模,对节点信息重要度排序,讨论其对负荷恢复的影响;其次,构建了SOP的稳态模型,分析了SOP的工作原理及控制模式;接着,为了更大程度、更加灵活地恢复负荷,考虑SOP的作用,建立考虑光伏时变性及负荷运行特性的有源配电网孤岛划分模型;最后,算例仿真验证所提策略的有效性。展开更多
基金Supported by the Deutsche Forschungsgemeinschaft (DFG No.RO 294/9).
文摘Effective temperature level of stream, namely stream pseudo temperature, is determined by its actual temperature and heat transfer temperature difference contribution value. Heat transfer temperature difference con-tribution value of a stream depends on its heat transfer film coefficient, cost per unit heat transfer area, actual tem-perature, and so on. In the determination of the suitable heat transfer temperature difference contribution values of the stream, the total annual cost of multistream heat exchanger network (MSHEN) is regarded as an objective func-tion, and genetic/simulated annealing algorithm (GA/SA) is adopted for optimizing the heat transfer temperature difference contribution values of the stream. The stream pseudo temperatures are subsequently obtained. On the ba-sis of stream pseudo temperature, optimized MSHEN can be attained by the temperature-enthalpy (T-H) diagram method. This approach is characterized with fewer decision variables and higher feasibility of solutions. The calcu-lation efficiency of GA/SA can be remarkably enhanced by this approach and more probability is shown in search-ing the global optimum solution. Hence this approach is presented for solving industrial-sized MSHEN which is difficult to deal by traditional algorithm. Moreover, in the optimization of stream heat transfer temperature differ-ence contribution values, the effects of the stream temperature, the heat transfer film coefficient, and the construc-tion material of heat exchangers are considered, therefore this approach can be used to optimize and design heat exchanger network (HEN) with unequal heat transfer film coefficients and different of construction materials. The performance of the proposed approach has been demonstrated with three examples and the obtained solutions are compared with those available in literatures. The results show that the large-scale MSHEN synthesis problems can be solved to obtain good solutions with the modest computational effort.
基金Funding was provided by National Natural Science Foundation of China(Grant No.51774179)the project of Science Department of Liaoning Province(2019-ZD-0269).
文摘For a multistream tundish,the uniformity among the streams plays a significant role in the quality of molten steel.How to analyze the uniformity quantitatively and optimize structures of a multistream tundish is an important research content for a multistream tundish.A new approach was proposed to quantify the uniformity among the streams.And a physical study and a numerical study were carried out to optimize the structure of the diversion hole based on the prototype of a six-stream tundish in a steel plant.On the basis of average residence time,the uniformity of each flow was considered fully and then the optimal structure of the diversion hole was obtained by means of the comprehensive analysis of temperature field and velocity field.The results show that the optimum structural parameters adopted for diversion holes are height of 20 mm,angle of 15°and diameter of 80 mm.
基金partially supported by the National Key Research and Development Program of China(2020YFB2104001)。
文摘The success of intelligent transportation systems relies heavily on accurate traffic prediction,in which how to model the underlying spatial-temporal information from traffic data has come under the spotlight.Most existing frameworks typically utilize separate modules for spatial and temporal correlations modeling.However,this stepwise pattern may limit the effectiveness and efficiency in spatial-temporal feature extraction and cause the overlook of important information in some steps.Furthermore,it is lacking sufficient guidance from prior information while modeling based on a given spatial adjacency graph(e.g.,deriving from the geodesic distance or approximate connectivity),and may not reflect the actual interaction between nodes.To overcome those limitations,our paper proposes a spatial-temporal graph synchronous aggregation(STGSA)model to extract the localized and long-term spatial-temporal dependencies simultaneously.Specifically,a tailored graph aggregation method in the vertex domain is designed to extract spatial and temporal features in one graph convolution process.In each STGSA block,we devise a directed temporal correlation graph to represent the localized and long-term dependencies between nodes,and the potential temporal dependence is further fine-tuned by an adaptive weighting operation.Meanwhile,we construct an elaborated spatial adjacency matrix to represent the road sensor graph by considering both physical distance and node similarity in a datadriven manner.Then,inspired by the multi-head attention mechanism which can jointly emphasize information from different r epresentation subspaces,we construct a multi-stream module based on the STGSA blocks to capture global information.It projects the embedding input repeatedly with multiple different channels.Finally,the predicted values are generated by stacking several multi-stream modules.Extensive experiments are constructed on six real-world datasets,and numerical results show that the proposed STGSA model significantly outperforms the benchmarks.
文摘为提高供电恢复效果,更好地应对当前有源配电网信息-物理耦合程度不断加深的形势,提出了一种考虑信息流、能量流、业务流多流融合以及智能软开关(soft open point,SOP)作用的孤岛划分算法,基于该算法实现供电恢复策略。首先,为保证负荷的可靠恢复,该策略深入研究信息-物理耦合并建模,对节点信息重要度排序,讨论其对负荷恢复的影响;其次,构建了SOP的稳态模型,分析了SOP的工作原理及控制模式;接着,为了更大程度、更加灵活地恢复负荷,考虑SOP的作用,建立考虑光伏时变性及负荷运行特性的有源配电网孤岛划分模型;最后,算例仿真验证所提策略的有效性。
