The study of flow diversions in open channels plays an important practical role in the design and management of open-channel networks for irrigation or drainage. To accurately predict the mean flow and turbulence char...The study of flow diversions in open channels plays an important practical role in the design and management of open-channel networks for irrigation or drainage. To accurately predict the mean flow and turbulence characteristics of open-channel dividing flows, a hybrid LES-RANS model, which combines the large eddy simulation （LES） model with the Reynolds-averaged Navier-Stokes （RANS） model, is proposed in the present study. The unsteady RANS model was used to simulate the upstream and downstream regions of a main channel, as well as the downstream region of a branch channel. The LES model was used to simulate the channel diversion region, where turbulent flow characteristics are complicated. Isotropic velocity fluctuations were added at the inflow interface of the LES region to trigger the generation of resolved turbulence. A method based on the virtual body force is proposed to impose Reynolds-averaged velocity fields near the outlet of the LES region in order to take downstream flow effects computed by the RANS model into account and dissipate the excessive turbulent fluctuations. This hybrid approach saves computational effort and makes it easier to properly specify inlet and outlet boundary conditions. Comparison between computational results and experimental data indicates that this relatively new modeling approach can accurately predict open-channel T-diversion flows.展开更多
Two Delayed-Detached Eddy Simulation(DDES) models, and a Large-Eddy Simulation(LES) model are used to investigate the turbulent flows and mixed convection between a hot plate and a cold plate via the software FLUENT. ...Two Delayed-Detached Eddy Simulation(DDES) models, and a Large-Eddy Simulation(LES) model are used to investigate the turbulent flows and mixed convection between a hot plate and a cold plate via the software FLUENT. The two DDES models include Production-limited DDES(PL-DDES) and Improved DDES(IDDES) models.The Wall-Adapting Local Eddy-Viscosity(WALE) model is the used LES model. The numerical computations are performed at Reynolds number Reb= 4494 and different Richardson numbers Ri = 0.025, 0.048, 0.1. The comparing data is from the Direct Numerical Simulation(DNS) at Reb= 4494 and Ri = 0.048. The comparison reveals that the two DDES models have better performance in predicting time-averaged parameters than the WALE model in the aiding flow. The best predicted time-averaged results are obtained by the PL-DDES model in the opposing flow. Furthermore, the results of different Ri obtained by the PL-DDES model agree well with the DNS data.展开更多
Stock market is volatile and predicting stock prices is a challenging task.Stock prices are influenced by multiple factors,and prediction using only numerical or image features is ineffective.To solve this problem,we ...Stock market is volatile and predicting stock prices is a challenging task.Stock prices are influenced by multiple factors,and prediction using only numerical or image features is ineffective.To solve this problem,we propose a Hybrid Channel Stock model that incorporates multiple features of basic stock data,K-line charts and technical indicator factors for predicting the closing price of a stock on day n+1.The model combines multiple aspects of data and uses a multi-channel structure including improved CNN-TW,bidirectional LSTM and Transformer network.First,we construct the multi-channel branches of the multi-faceted feature fusion input network model;second,in this paper,we will use the concatenate method to stitch the output of each branch as the input of the rest of the network;the last layer in the network is the fully connected layer,which combines the linear activation function regression to output the predicted prices.Finally,we conducted extensive experiments on the Dow 30,SSH 50 and CSI100 indices.The experimental results show that the Hybrid Channel Stock method has the best performance with the smallest MSE,RMSE,MAE and MAPE compared with existing models.in addition,the experiments on different trading days validate the stability and effectiveness of the model,providing an important reference for investors to make stock investment decisions.展开更多
The RNG κ-ε model considering the buoyancy effect, which is solved by the hybrid finite analytic method, is used to simulate the mixture of the horizontal round thermal buoyant jet in compound open channel flow. The...The RNG κ-ε model considering the buoyancy effect, which is solved by the hybrid finite analytic method, is used to simulate the mixture of the horizontal round thermal buoyant jet in compound open channel flow. The mixing features near the spout and flowing characteristic of the secondary currents are studied by numerical simulation. Meanwhile, （1） the distribution of the measured isovels for stream-wise velocity, （2） secondary currents, （3） the distribution of the measured isovels for temperature of typical cross-section near the spout, were obtained by the three-dimensional Micro ADV and the temperature measuring device. Compared with experimental data, the RNG κ-ε model based on buoyancy effect can preferably simulate the jet which performs the bifurcation phenomenon, jet reattachment （Conada effect） and beach secondary currents phenomenon with the effect of ambient flow, buoyancy, and secondary currents of compound section and so on.展开更多
针对车联网中高通信需求和高移动性造成的车对车链路(Vehicle to Vehicle,V2V)间的信道冲突及网络效用低下的问题,提出了一种基于并联门控循环单元(Gated Recurrent Unit,GRU)和长短期记忆网络(Long Short-Term Memory,LSTM)的组合模型...针对车联网中高通信需求和高移动性造成的车对车链路(Vehicle to Vehicle,V2V)间的信道冲突及网络效用低下的问题,提出了一种基于并联门控循环单元(Gated Recurrent Unit,GRU)和长短期记忆网络(Long Short-Term Memory,LSTM)的组合模型的车联网信道分配算法。算法以降低V2V链路信道碰撞率和空闲率为目标,将信道分配问题建模为分布式深度强化学习问题,使每条V2V链路作为单个智能体,并通过最大化每回合平均奖励的方式进行集中训练、分布式执行。在训练过程中借助GRU训练周期短和LSTM拟合精度高的组合优势去拟合深度双重Q学习中Q函数,使V2V链路能快速地学习优化信道分配策略,合理地复用车对基础设施(Vehicle to Infrastructure,V2I)链路的信道资源,实现网络效用最大化。仿真结果表明,与单纯使用GRU或者LSTM网络模型的分配算法相比,该算法在收敛速度方面加快了5个训练回合,V2V链路间的信道碰撞率和空闲率降低了约27%,平均成功率提升了约10%。展开更多
混合渠道是指在由单个制造商和零售商组成的供应链中,制造商和零售商在传统零售渠道的基础上,增开网络直销渠道。针对这种渠道结构,文章将第三方物流(third party logistics,简称3PL)服务提供商引入到供应链中来,利用博弈理论模型研究...混合渠道是指在由单个制造商和零售商组成的供应链中,制造商和零售商在传统零售渠道的基础上,增开网络直销渠道。针对这种渠道结构,文章将第三方物流(third party logistics,简称3PL)服务提供商引入到供应链中来,利用博弈理论模型研究该三级混合分销渠道供应链的渠道定价与协调问题。基于集中决策和分散决策两种情形,分别建立了Nash和Stackelberg博弈模型,并给出了两种情况下的均衡价格,研究表明,在一定条件下,系统总利润随着经销主体差异和渠道价格差异的增大而增加。最后通过算例比较分析了不同条件下各节点企业的均衡价格与利润。展开更多
文摘The study of flow diversions in open channels plays an important practical role in the design and management of open-channel networks for irrigation or drainage. To accurately predict the mean flow and turbulence characteristics of open-channel dividing flows, a hybrid LES-RANS model, which combines the large eddy simulation （LES） model with the Reynolds-averaged Navier-Stokes （RANS） model, is proposed in the present study. The unsteady RANS model was used to simulate the upstream and downstream regions of a main channel, as well as the downstream region of a branch channel. The LES model was used to simulate the channel diversion region, where turbulent flow characteristics are complicated. Isotropic velocity fluctuations were added at the inflow interface of the LES region to trigger the generation of resolved turbulence. A method based on the virtual body force is proposed to impose Reynolds-averaged velocity fields near the outlet of the LES region in order to take downstream flow effects computed by the RANS model into account and dissipate the excessive turbulent fluctuations. This hybrid approach saves computational effort and makes it easier to properly specify inlet and outlet boundary conditions. Comparison between computational results and experimental data indicates that this relatively new modeling approach can accurately predict open-channel T-diversion flows.
基金Supported by the Program of International Science and Technology Cooperation of China(2016YFE0118100)Dongguan Innovative Research team Program(2014607119).
文摘Two Delayed-Detached Eddy Simulation(DDES) models, and a Large-Eddy Simulation(LES) model are used to investigate the turbulent flows and mixed convection between a hot plate and a cold plate via the software FLUENT. The two DDES models include Production-limited DDES(PL-DDES) and Improved DDES(IDDES) models.The Wall-Adapting Local Eddy-Viscosity(WALE) model is the used LES model. The numerical computations are performed at Reynolds number Reb= 4494 and different Richardson numbers Ri = 0.025, 0.048, 0.1. The comparing data is from the Direct Numerical Simulation(DNS) at Reb= 4494 and Ri = 0.048. The comparison reveals that the two DDES models have better performance in predicting time-averaged parameters than the WALE model in the aiding flow. The best predicted time-averaged results are obtained by the PL-DDES model in the opposing flow. Furthermore, the results of different Ri obtained by the PL-DDES model agree well with the DNS data.
基金supported by these three foundation programs:the Science and Technology Research Project(Youth)of Chongqing Municipal Education Commission(KJQN202201142)the Chongqing Research Program of Basic Research Frontier Technology(CSTB2022BSXM-JCX0069CCCC)the Training Program of the National Natural Science Foundation of China and National Social Science Fund of China of Chongqing University of Technology(2022PYZ030)。
文摘Stock market is volatile and predicting stock prices is a challenging task.Stock prices are influenced by multiple factors,and prediction using only numerical or image features is ineffective.To solve this problem,we propose a Hybrid Channel Stock model that incorporates multiple features of basic stock data,K-line charts and technical indicator factors for predicting the closing price of a stock on day n+1.The model combines multiple aspects of data and uses a multi-channel structure including improved CNN-TW,bidirectional LSTM and Transformer network.First,we construct the multi-channel branches of the multi-faceted feature fusion input network model;second,in this paper,we will use the concatenate method to stitch the output of each branch as the input of the rest of the network;the last layer in the network is the fully connected layer,which combines the linear activation function regression to output the predicted prices.Finally,we conducted extensive experiments on the Dow 30,SSH 50 and CSI100 indices.The experimental results show that the Hybrid Channel Stock method has the best performance with the smallest MSE,RMSE,MAE and MAPE compared with existing models.in addition,the experiments on different trading days validate the stability and effectiveness of the model,providing an important reference for investors to make stock investment decisions.
基金Project supported by the National Natural Science Foundation of China (Nos.50479038 and 50679061)the Open Foundation of State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology (No.LP0601)
文摘The RNG κ-ε model considering the buoyancy effect, which is solved by the hybrid finite analytic method, is used to simulate the mixture of the horizontal round thermal buoyant jet in compound open channel flow. The mixing features near the spout and flowing characteristic of the secondary currents are studied by numerical simulation. Meanwhile, （1） the distribution of the measured isovels for stream-wise velocity, （2） secondary currents, （3） the distribution of the measured isovels for temperature of typical cross-section near the spout, were obtained by the three-dimensional Micro ADV and the temperature measuring device. Compared with experimental data, the RNG κ-ε model based on buoyancy effect can preferably simulate the jet which performs the bifurcation phenomenon, jet reattachment （Conada effect） and beach secondary currents phenomenon with the effect of ambient flow, buoyancy, and secondary currents of compound section and so on.
文摘针对车联网中高通信需求和高移动性造成的车对车链路(Vehicle to Vehicle,V2V)间的信道冲突及网络效用低下的问题,提出了一种基于并联门控循环单元(Gated Recurrent Unit,GRU)和长短期记忆网络(Long Short-Term Memory,LSTM)的组合模型的车联网信道分配算法。算法以降低V2V链路信道碰撞率和空闲率为目标,将信道分配问题建模为分布式深度强化学习问题,使每条V2V链路作为单个智能体,并通过最大化每回合平均奖励的方式进行集中训练、分布式执行。在训练过程中借助GRU训练周期短和LSTM拟合精度高的组合优势去拟合深度双重Q学习中Q函数,使V2V链路能快速地学习优化信道分配策略,合理地复用车对基础设施(Vehicle to Infrastructure,V2I)链路的信道资源,实现网络效用最大化。仿真结果表明,与单纯使用GRU或者LSTM网络模型的分配算法相比,该算法在收敛速度方面加快了5个训练回合,V2V链路间的信道碰撞率和空闲率降低了约27%,平均成功率提升了约10%。
文摘混合渠道是指在由单个制造商和零售商组成的供应链中,制造商和零售商在传统零售渠道的基础上,增开网络直销渠道。针对这种渠道结构,文章将第三方物流(third party logistics,简称3PL)服务提供商引入到供应链中来,利用博弈理论模型研究该三级混合分销渠道供应链的渠道定价与协调问题。基于集中决策和分散决策两种情形,分别建立了Nash和Stackelberg博弈模型,并给出了两种情况下的均衡价格,研究表明,在一定条件下,系统总利润随着经销主体差异和渠道价格差异的增大而增加。最后通过算例比较分析了不同条件下各节点企业的均衡价格与利润。
