The buoyancy of groundwater can reduce the foundation bearing capa-city and cause the metro tunnels to float as a whole,which threatens the safety of structures seriously.Therefore,uplift piles are set up to improve t...The buoyancy of groundwater can reduce the foundation bearing capa-city and cause the metro tunnels to float as a whole,which threatens the safety of structures seriously.Therefore,uplift piles are set up to improve the structural sta-bility.In this paper,FLAC3D software is used to establish the calculation models of pile foundation.The bearing failure process of uplift piles was simulated to study the influencing factors on single pile load bearing capacity as well as the cooperative work laws of pile groups.The load-displacement curves of pile top under different length-diameter ratios,pile soil interface characteristics and pile types are obtained,respectively.The results showed that,increasing the length-diameter ratio and the pile-soil interface roughness properdly can improve the bear-ing capacity of uplift piles.Besides,changing the shapes of constant pile section can also improve it,which has the most significant effect concerning of saving material cost.In the loading process of pile groups,the ultimate bearing capacity of corner pile is the biggest,the side pile is the next,and the center pile is the smallest.The de formation characteristics of pile top are as follows:the center pile is the biggest,the side pile is the next,and comer pile is the smallest.Combined with the results,the uplift resistance of group piles can be enhanced pertinently,and the conclusions provide guidance for the design and construction of up lift piles in the actual engineer.展开更多
This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface ...This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface device while observing work of the robot with a video camera. We also investigate the effect of the proposed control by experiment. As cooperative work, we deal with work in which two robots carry an object together. The robot position control using force information finely adjusts the position of the robot arm to reduce the force applied to the object. Thus, the purpose of the control is to avoid large force so that the object is not broken. In our experiment, we make a comparison among the following three cases in order to clarify how to carry out the control effectively. In the first case, the two robots are operated manually by a user with his/her both hands. In the second case, one robot is operated manually by a user, and the other robot is moved automatically under the proposed control. In the last case, the object is carried directly by a human instead of the robot which is operated by the user in the second case. As a result, experimental results demonstrate that the control can help each system operated manually by the user to carry the object smoothly.展开更多
交通流量因受周期性特征、突发状况等多重因素影响,现有模型的预测精度无法满足实际要求.对此,本文提出了基于误差补偿的多模态协同交通流预测模型(Multimodal Collaborative traffic flow prediction model based on Error Compensatio...交通流量因受周期性特征、突发状况等多重因素影响,现有模型的预测精度无法满足实际要求.对此,本文提出了基于误差补偿的多模态协同交通流预测模型(Multimodal Collaborative traffic flow prediction model based on Error Compensation,MCEC).针对传统预测模型不能兼顾时间序列和协变量的问题,提出基于小波分析的特征拓展方法,该方法引入聚类算法得到节假日标签特征,将拥堵指数、交通事故图、天气信息作为拓展特征,对特征进行多尺度分解.在训练阶段,为达到充分学习各部分数据、最优匹配模型的效果,采用差分整合移动平均自回归模型(Autoreg Ressive Integrated Moving Average Model,ARIMA)、长短期记忆神经网络(Long Short-Term Memory network,LSTM)、限制动态时间规整技术(Dynamic Time Warping,DTW)以及自注意力机制(Self-Attention),设计了多模态协同模型训练.在误差补偿阶段,将得到的相应过程值输入基于支持向量机回归(Support Vector Regression,SVR)的误差补偿模块,对各分量的误差进行学习、补偿,并重构得到预测结果.使用公开的高速公路数据集对MCEC进行验证,在多个时间间隔下对比实验结果表明,MCEC在交通流量预测中的平均绝对百分比误差(Mean Absolute Percentage Error,MAPE)达到17.02%,比LSTM-SVR、ConvLSTM(Convolutional Long Short-Term Memory network)、ST-GCN(Spatial Temporal Graph Convolutional Networks)、MFFB(Multi-stream Feature Fusion Block)、Transformer等预测模型具有更高的预测精度,MCEC模型具有较好的有效性与合理性.展开更多
基金This work was supported by National Key Research,Development Project of China(2016YFC0802206)Disaster Prevention and Mitigation Collaborative Innovation Center for Large Infrastructure of Hebei Province(2017),and Postgraduate Innovative Funding Projects of Hebei Province(CXZZSS2018060).
文摘The buoyancy of groundwater can reduce the foundation bearing capa-city and cause the metro tunnels to float as a whole,which threatens the safety of structures seriously.Therefore,uplift piles are set up to improve the structural sta-bility.In this paper,FLAC3D software is used to establish the calculation models of pile foundation.The bearing failure process of uplift piles was simulated to study the influencing factors on single pile load bearing capacity as well as the cooperative work laws of pile groups.The load-displacement curves of pile top under different length-diameter ratios,pile soil interface characteristics and pile types are obtained,respectively.The results showed that,increasing the length-diameter ratio and the pile-soil interface roughness properdly can improve the bear-ing capacity of uplift piles.Besides,changing the shapes of constant pile section can also improve it,which has the most significant effect concerning of saving material cost.In the loading process of pile groups,the ultimate bearing capacity of corner pile is the biggest,the side pile is the next,and the center pile is the smallest.The de formation characteristics of pile top are as follows:the center pile is the biggest,the side pile is the next,and comer pile is the smallest.Combined with the results,the uplift resistance of group piles can be enhanced pertinently,and the conclusions provide guidance for the design and construction of up lift piles in the actual engineer.
文摘This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface device while observing work of the robot with a video camera. We also investigate the effect of the proposed control by experiment. As cooperative work, we deal with work in which two robots carry an object together. The robot position control using force information finely adjusts the position of the robot arm to reduce the force applied to the object. Thus, the purpose of the control is to avoid large force so that the object is not broken. In our experiment, we make a comparison among the following three cases in order to clarify how to carry out the control effectively. In the first case, the two robots are operated manually by a user with his/her both hands. In the second case, one robot is operated manually by a user, and the other robot is moved automatically under the proposed control. In the last case, the object is carried directly by a human instead of the robot which is operated by the user in the second case. As a result, experimental results demonstrate that the control can help each system operated manually by the user to carry the object smoothly.
