We investigated the solid–liquid suspension characteristics in the tank with a liquid height/tank diameter ratio of 1.5 stirred by a novel long-short blades(LSB) impeller by the Euler granular flow model coupled with...We investigated the solid–liquid suspension characteristics in the tank with a liquid height/tank diameter ratio of 1.5 stirred by a novel long-short blades(LSB) impeller by the Euler granular flow model coupled with the standard k–ε turbulence model. After validation of the local solid holdup by experiments,numerical predictions have been successfully used to explain the influences of impeller rotating speed,particle density, particle size, liquid viscosity and initial solid loading on the solid suspension behavior,i.e. smaller particles with lower density are more likely to be suspended evenly in the liquid with higher liquid viscosity. At a low impeller rotating speed(N), increase in N leads to an obvious improvement in the solid distribution homogeneity. Moreover, the proposed LSB impeller has obvious advantages in the uniform distribution of the solid particles compared with single Rushton turbine(RT), dual RT impellers or CBY hydrofoil impeller under the same power consumption.展开更多
Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In ...Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.展开更多
The mechanism of long-short composite piled raft foundation was discussed. Assuming the relationship between shear stress and shear strain of the surrounding soil was elasto-plastic, shear displacement method was empl...The mechanism of long-short composite piled raft foundation was discussed. Assuming the relationship between shear stress and shear strain of the surrounding soil was elasto-plastic, shear displacement method was employed to establish the different explicit relational equations between the load and the displacement at the top of pile in either elastic or elasto-plastic period. Then Mylonakis ＆ Gazetas model was introduced to simulate the interaction between two piles or between piles and soil. Considering the effect of cushion, the flexible coefficients of interaction were provided, With the addition of a relevant program, the settlement calculation for long-short composite piled raft foundation was developed which could be used to account for the interaction of piles, soil and cushion. Finally, the calculation method was used to analyze an engineering example. The calculated value of settlement is 10.2 ram, which is close to the observed value 8.8 mm.展开更多
This work focuses on the design improvement of the long-short blades(LSB)impeller by using pitched short blades(SBs)to regulate the flow field in the stirred vessel.After mesh size evaluation and velocity field valida...This work focuses on the design improvement of the long-short blades(LSB)impeller by using pitched short blades(SBs)to regulate the flow field in the stirred vessel.After mesh size evaluation and velocity field validation by the particle image velocimetry,large eddy simulation method coupled with sliding mesh approach was used to study the effect of the pitched SBs on the flow characteristics.We changed the inclined angles of the SBs from 30°to 60°and compared the flow characteristics when the impeller was operated in the down-pumping and up-pumping modes.In the case of down-pumping mode,the power number is relatively smaller and vortexes below the SBs are suppressed,leading to turbulence intensification in the bottom of the vessel.Whereas in the case of up-pumping mode,the axial flow rate in the center increased significantly with bigger power number,resulting in more efficient mass exchange between the axial and radial flows in the whole vessel.The LSB with 45°inclined angle of the SBs in the up-pumping mode has the most uniform distributions of flow field and turbulent kinetic energy compared with other impeller configurations.展开更多
In the present paper, we investigate the well-posedness of the global solutionfor the Cauchy problem of generalized long-short wave equations. Applying Kato＇s methodfor abstract quasi-linear evolution equations and a...In the present paper, we investigate the well-posedness of the global solutionfor the Cauchy problem of generalized long-short wave equations. Applying Kato＇s methodfor abstract quasi-linear evolution equations and a priori estimates of solution,we get theexistence of globally smooth solution.展开更多
New exact solutions expressed by the Jacobi elliptic functions are obtained to the long-short wave interaction equations by using the modified F-expansion method. In the limit case, solitary wave solutions and triangu...New exact solutions expressed by the Jacobi elliptic functions are obtained to the long-short wave interaction equations by using the modified F-expansion method. In the limit case, solitary wave solutions and triangular periodic wave solutions are obtained as well.展开更多
The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-shor...The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-short term memory(LSTM)network was used to estimate the depth of unloading relaxation zones on the left bank foundation of the Baihetan Arch Dam.Principal component analysis indicates that rock charac-teristics,the structural plane,the protection layer,lithology,and time are the main factors.The LSTM network results demonstrate the unloading relaxation characteristics of the left bank,and the relationships with the factors were also analyzed.The structural plane has the most significant influence on the distribution of unloading relaxation zones.Compared with massive basalt,the columnar jointed basalt experiences a more significant unloading relaxation phenomenon with a clear time effect,with the average unloading relaxation period being 50 d.The protection layer can effectively reduce the unloading relaxation depth by approximately 20%.展开更多
功率预测是实现电能供需平衡、维持电网稳定运行的一项重要任务.随着分布式海上光伏系统的发展,光伏利用率不断提升,同时对光伏功率预测提出了更高的要求.针对机器学习方法在光伏功率时间序列预测中存在的样本数量不足、预测精度低以及...功率预测是实现电能供需平衡、维持电网稳定运行的一项重要任务.随着分布式海上光伏系统的发展,光伏利用率不断提升,同时对光伏功率预测提出了更高的要求.针对机器学习方法在光伏功率时间序列预测中存在的样本数量不足、预测精度低以及隐私泄露等问题,提出一种基于联邦学习和变分模态分解的长短期记忆神经网络功率预测模型(long short-term memory neural network power forecasting model based on federated learning and variational mode decomposition,FL-VMD-LSTM).利用主成分分析法和三次样条插值对气象数据进行预处理,同时利用VMD将光伏功率时间序列分解为多个分量进行分步预测,降低光伏功率时间序列的非平稳性和复杂度.通过横向联邦学习的本地训练和参数聚合方法,实现在保证数据隐私安全情况下的光伏功率预测.通过4个算例进行仿真实验,验证结果表明FL-VMD-LSTM模型在光伏功率预测方面具有较高精度,与传统算法相比,RMSE和MAE分别降低了55.7%和55.5%.展开更多
基金the financial support from the National Natural Science Foundation of China (22078058)Open Research Fund Program of CAS Key Laboratory of Energy Regulation Materials (ORFP2020–02)
文摘We investigated the solid–liquid suspension characteristics in the tank with a liquid height/tank diameter ratio of 1.5 stirred by a novel long-short blades(LSB) impeller by the Euler granular flow model coupled with the standard k–ε turbulence model. After validation of the local solid holdup by experiments,numerical predictions have been successfully used to explain the influences of impeller rotating speed,particle density, particle size, liquid viscosity and initial solid loading on the solid suspension behavior,i.e. smaller particles with lower density are more likely to be suspended evenly in the liquid with higher liquid viscosity. At a low impeller rotating speed(N), increase in N leads to an obvious improvement in the solid distribution homogeneity. Moreover, the proposed LSB impeller has obvious advantages in the uniform distribution of the solid particles compared with single Rushton turbine(RT), dual RT impellers or CBY hydrofoil impeller under the same power consumption.
基金supported by the National Natural Science Foundation of China(No.62276204)Open Foundation of Science and Technology on Electronic Information Control Laboratory,Natural Science Basic Research Program of Shanxi,China(Nos.2022JM-340 and 2023-JC-QN-0710)China Postdoctoral Science Foundation(Nos.2020T130494 and 2018M633470).
文摘Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.
基金Project (50378036) supported by the National Natural Science Foundation of China
文摘The mechanism of long-short composite piled raft foundation was discussed. Assuming the relationship between shear stress and shear strain of the surrounding soil was elasto-plastic, shear displacement method was employed to establish the different explicit relational equations between the load and the displacement at the top of pile in either elastic or elasto-plastic period. Then Mylonakis ＆ Gazetas model was introduced to simulate the interaction between two piles or between piles and soil. Considering the effect of cushion, the flexible coefficients of interaction were provided, With the addition of a relevant program, the settlement calculation for long-short composite piled raft foundation was developed which could be used to account for the interaction of piles, soil and cushion. Finally, the calculation method was used to analyze an engineering example. The calculated value of settlement is 10.2 ram, which is close to the observed value 8.8 mm.
基金financial support from the National Natural Science Foundation of China (22078058)。
文摘This work focuses on the design improvement of the long-short blades(LSB)impeller by using pitched short blades(SBs)to regulate the flow field in the stirred vessel.After mesh size evaluation and velocity field validation by the particle image velocimetry,large eddy simulation method coupled with sliding mesh approach was used to study the effect of the pitched SBs on the flow characteristics.We changed the inclined angles of the SBs from 30°to 60°and compared the flow characteristics when the impeller was operated in the down-pumping and up-pumping modes.In the case of down-pumping mode,the power number is relatively smaller and vortexes below the SBs are suppressed,leading to turbulence intensification in the bottom of the vessel.Whereas in the case of up-pumping mode,the axial flow rate in the center increased significantly with bigger power number,resulting in more efficient mass exchange between the axial and radial flows in the whole vessel.The LSB with 45°inclined angle of the SBs in the up-pumping mode has the most uniform distributions of flow field and turbulent kinetic energy compared with other impeller configurations.
文摘In the present paper, we investigate the well-posedness of the global solutionfor the Cauchy problem of generalized long-short wave equations. Applying Kato＇s methodfor abstract quasi-linear evolution equations and a priori estimates of solution,we get theexistence of globally smooth solution.
文摘New exact solutions expressed by the Jacobi elliptic functions are obtained to the long-short wave interaction equations by using the modified F-expansion method. In the limit case, solitary wave solutions and triangular periodic wave solutions are obtained as well.
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFC0407004)the Natural Science Foundation of China(Grants No.51939004 and 11772116).
文摘The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-short term memory(LSTM)network was used to estimate the depth of unloading relaxation zones on the left bank foundation of the Baihetan Arch Dam.Principal component analysis indicates that rock charac-teristics,the structural plane,the protection layer,lithology,and time are the main factors.The LSTM network results demonstrate the unloading relaxation characteristics of the left bank,and the relationships with the factors were also analyzed.The structural plane has the most significant influence on the distribution of unloading relaxation zones.Compared with massive basalt,the columnar jointed basalt experiences a more significant unloading relaxation phenomenon with a clear time effect,with the average unloading relaxation period being 50 d.The protection layer can effectively reduce the unloading relaxation depth by approximately 20%.
文摘功率预测是实现电能供需平衡、维持电网稳定运行的一项重要任务.随着分布式海上光伏系统的发展,光伏利用率不断提升,同时对光伏功率预测提出了更高的要求.针对机器学习方法在光伏功率时间序列预测中存在的样本数量不足、预测精度低以及隐私泄露等问题,提出一种基于联邦学习和变分模态分解的长短期记忆神经网络功率预测模型(long short-term memory neural network power forecasting model based on federated learning and variational mode decomposition,FL-VMD-LSTM).利用主成分分析法和三次样条插值对气象数据进行预处理,同时利用VMD将光伏功率时间序列分解为多个分量进行分步预测,降低光伏功率时间序列的非平稳性和复杂度.通过横向联邦学习的本地训练和参数聚合方法,实现在保证数据隐私安全情况下的光伏功率预测.通过4个算例进行仿真实验,验证结果表明FL-VMD-LSTM模型在光伏功率预测方面具有较高精度,与传统算法相比,RMSE和MAE分别降低了55.7%和55.5%.
