Cu/Al multilayers were produced by high-temperature accumulative roll bonding(ARB)methods up to three passes.To achieve a high bonding strength,prior to ARB processing,the Cu and Al sheets were heated to 350,400,450 a...Cu/Al multilayers were produced by high-temperature accumulative roll bonding(ARB)methods up to three passes.To achieve a high bonding strength,prior to ARB processing,the Cu and Al sheets were heated to 350,400,450 and 500 ℃,respectively.The mechanical properties were evaluated by tensile tests.The microstructure was examined by optical microscopy and scanning electron microscopy equipped with energy dispersive spectrometry.The ultimate tensile stress,the grain size and the thickness of diffusion layer of lamellar composites increase with rolling temperature.When the rolling temperature is 400 ℃,the laminates show the highest ductility,but the yield stress is the lowest.As the rolling temperature further increases,both the yield stress and the ultimate tensile stress increase and the ductility decreases slightly.The mechanical properties of lamellar composites processed by low and high temperature ARB are determined by grain size and the thickness of diffusion layer,respectively.展开更多
Using monitored active layer thickness(ALT) and environmental variables of 10 observation fields along the Qinghai-Tibet Highway in permafrost region of the Qinghai-Tibetan Plateau(QTP),a model for ALT estimation was ...Using monitored active layer thickness(ALT) and environmental variables of 10 observation fields along the Qinghai-Tibet Highway in permafrost region of the Qinghai-Tibetan Plateau(QTP),a model for ALT estimation was developed.The temporal and spatial characteristics of the ALT were also analyzed.The results showed that in the past 30 years ALT in the study region increased at a rate of 1.33 cm a-1.Temperatures at the upper limit of permafrost and at 50 cm depth,along with soil cumulative temperature at 5 cm depth also exhibited a rising trend.Soil heat flux increased at a rate of 0.1 Wm-2 a-1.All the above changes demonstrated that the degradation of permafrost happened in the study region on the QTP.The initial thawing date of active layer was advanced,while the initial freezing date was delayed.The number of thawing days increased to a rate of 1.18 da-1.The variations of active layer were closely related to the permafrost type,altitude,underlying surface type and soil composition.The variations were more evident in cold permafrost region than in warm permafrost region,in high-altitude region than in low-altitude region,in alpine meadow region than in alpine steppe region;and in fine-grained soil region than in coarse-grained soil region.展开更多
【目的】利用土壤近表面空气温湿度与土壤内部参数的关联关系对耕作层土壤水分、温度进行精准预测,为实现精细化农业种植管理提供服务。【方法】针对土壤耕作层水分、温度预测在训练集获取与模型验证等方面的实际需求,设计了基于嵌入式...【目的】利用土壤近表面空气温湿度与土壤内部参数的关联关系对耕作层土壤水分、温度进行精准预测,为实现精细化农业种植管理提供服务。【方法】针对土壤耕作层水分、温度预测在训练集获取与模型验证等方面的实际需求,设计了基于嵌入式系统及窄带物联网(Narrow band internet of things,NB-IoT)无线通信技术的物联网数据采集系统。在此基础上基于深度Q学习(Deep Q network,DQN)算法探索了一种模型组合策略,以长短期记忆(Long short-term memory,LSTM)、门限循环单元(Gated recurrent unit,GRU)与双向长短期记忆网络(Bidirectional long short-term memory,Bi-LSTM)为基础模型进行加权组合,获得了DQN-L-G-B组合预测模型。【结果】数据采集系统实现了对等间隔时间序列环境数据的长时间稳定可靠采集,可以为基于深度学习的土壤水分、温度时间序列预测工作提供准确的训练集与验证集数据。相对于LSTM、Bi-LSTM、GRU、L-G-B等模型,DQN-L-G-B组合模型在2种土壤类型(壤土、砂土)耕作层上水分与温度预测中的均方根误差(Root mean square error,RMSE)、平均绝对误差(Mean absolute error,MAE)、平均百分比误差(Mean absolute percentage error,MAPE)都有一定程度的降低,R2提高了约0.1%。【结论】通过该物联网数据采集系统与DNQ-L-G-B组合模型,可以有效地完成基于土壤近表面空气温、湿度对耕作层土壤中水分、温度的精准预测。展开更多
基金Project(51674303) supported by the National Natural Science Foundation of ChinaProject supported by National Youth Thousand Plan of China+2 种基金Project(2018RS3015) supported by Huxiang High-Level Talent Gathering Program of Hunan Province,ChinaProject(2019CX006) supported by Innovation Driven Program of Central South University,ChinaProject supported by the Research Fund of the Key Laboratory of High Performance Complex Manufacturing at Central South University,China
文摘Cu/Al multilayers were produced by high-temperature accumulative roll bonding(ARB)methods up to three passes.To achieve a high bonding strength,prior to ARB processing,the Cu and Al sheets were heated to 350,400,450 and 500 ℃,respectively.The mechanical properties were evaluated by tensile tests.The microstructure was examined by optical microscopy and scanning electron microscopy equipped with energy dispersive spectrometry.The ultimate tensile stress,the grain size and the thickness of diffusion layer of lamellar composites increase with rolling temperature.When the rolling temperature is 400 ℃,the laminates show the highest ductility,but the yield stress is the lowest.As the rolling temperature further increases,both the yield stress and the ultimate tensile stress increase and the ductility decreases slightly.The mechanical properties of lamellar composites processed by low and high temperature ARB are determined by grain size and the thickness of diffusion layer,respectively.
基金supported by the National Natural Science Foundation of China(40871037,40830533 and 40901042)the Hundred Talents Program of the Chinese Academy of Sciences(51Y251571)+4 种基金the National Basic Research Program of China(2007CB411504 and 2007CB411505)Infrastructure Projects from Chinese Ministry Science and Technology(2008FY110200)the State Key Laboratory of Cryospheric Science(SKLCS-ZZ-2010-03)Background of ecological monitoring for the ecological environment protection and construction in Three-Rivers Source Nature Resource Protection Areas-Permafrost monitoring and assessment projectthe Cryosphere Research Station on the Qinghai-Xizang Plateau,Chinese Academic Sciences
文摘Using monitored active layer thickness(ALT) and environmental variables of 10 observation fields along the Qinghai-Tibet Highway in permafrost region of the Qinghai-Tibetan Plateau(QTP),a model for ALT estimation was developed.The temporal and spatial characteristics of the ALT were also analyzed.The results showed that in the past 30 years ALT in the study region increased at a rate of 1.33 cm a-1.Temperatures at the upper limit of permafrost and at 50 cm depth,along with soil cumulative temperature at 5 cm depth also exhibited a rising trend.Soil heat flux increased at a rate of 0.1 Wm-2 a-1.All the above changes demonstrated that the degradation of permafrost happened in the study region on the QTP.The initial thawing date of active layer was advanced,while the initial freezing date was delayed.The number of thawing days increased to a rate of 1.18 da-1.The variations of active layer were closely related to the permafrost type,altitude,underlying surface type and soil composition.The variations were more evident in cold permafrost region than in warm permafrost region,in high-altitude region than in low-altitude region,in alpine meadow region than in alpine steppe region;and in fine-grained soil region than in coarse-grained soil region.
文摘【目的】利用土壤近表面空气温湿度与土壤内部参数的关联关系对耕作层土壤水分、温度进行精准预测,为实现精细化农业种植管理提供服务。【方法】针对土壤耕作层水分、温度预测在训练集获取与模型验证等方面的实际需求,设计了基于嵌入式系统及窄带物联网(Narrow band internet of things,NB-IoT)无线通信技术的物联网数据采集系统。在此基础上基于深度Q学习(Deep Q network,DQN)算法探索了一种模型组合策略,以长短期记忆(Long short-term memory,LSTM)、门限循环单元(Gated recurrent unit,GRU)与双向长短期记忆网络(Bidirectional long short-term memory,Bi-LSTM)为基础模型进行加权组合,获得了DQN-L-G-B组合预测模型。【结果】数据采集系统实现了对等间隔时间序列环境数据的长时间稳定可靠采集,可以为基于深度学习的土壤水分、温度时间序列预测工作提供准确的训练集与验证集数据。相对于LSTM、Bi-LSTM、GRU、L-G-B等模型,DQN-L-G-B组合模型在2种土壤类型(壤土、砂土)耕作层上水分与温度预测中的均方根误差(Root mean square error,RMSE)、平均绝对误差(Mean absolute error,MAE)、平均百分比误差(Mean absolute percentage error,MAPE)都有一定程度的降低,R2提高了约0.1%。【结论】通过该物联网数据采集系统与DNQ-L-G-B组合模型,可以有效地完成基于土壤近表面空气温、湿度对耕作层土壤中水分、温度的精准预测。
