The distribution of the nuclear ground-state spin in a two-body random ensemble(TBRE)was studied using a general classification neural network(NN)model with two-body interaction matrix elements as input features and t...The distribution of the nuclear ground-state spin in a two-body random ensemble(TBRE)was studied using a general classification neural network(NN)model with two-body interaction matrix elements as input features and the corresponding ground-state spins as labels or output predictions.The quantum many-body system problem exceeds the capability of our optimized NNs in terms of accurately predicting the ground-state spin of each sample within the TBRE.However,our NN model effectively captured the statistical properties of the ground-state spin because it learned the empirical regularity of the ground-state spin distribution in TBRE,as discovered by physicists.展开更多
We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Se...We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.展开更多
将既有的车辆-有砟轨道-路基-层状地基耦合系统垂向振动解析模型进行修改,使模型适应于板式无砟轨道的状况。针对我国客运专线线路情况,利用模型比较分析了有砟与板式无砟两种轨道结构下高速列车运行引起的地基振动,得到地基表面垂向振...将既有的车辆-有砟轨道-路基-层状地基耦合系统垂向振动解析模型进行修改,使模型适应于板式无砟轨道的状况。针对我国客运专线线路情况,利用模型比较分析了有砟与板式无砟两种轨道结构下高速列车运行引起的地基振动,得到地基表面垂向振动加速度的振级、时程曲线和Z振级,动应力的功率谱与时程曲线;并讨论了轨道随机不平顺对地基振动的影响。分析结果表明：板式无砟轨道具有更好的隔振能力,板式无砟轨道情况下的地基振动加速度和动应力都明显小于有砟轨道的情况,其中Z振级减小约10~20 d B,且减小振动的主要频率分布在10~40 Hz的中频范围内;移动轴荷载对地基的低频振动贡献较大,而轨道随机不平顺主要对中高频振动产生作用,且板式无砟轨道情况下轨道随机不平顺对地基振动的影响远大于有砟轨道的情况,因此板式无砟轨道需更严格控制轨道的平顺状态。展开更多
基金supported by the National Natural Science Foundation of China Youth Fund(12105234)。
文摘The distribution of the nuclear ground-state spin in a two-body random ensemble(TBRE)was studied using a general classification neural network(NN)model with two-body interaction matrix elements as input features and the corresponding ground-state spins as labels or output predictions.The quantum many-body system problem exceeds the capability of our optimized NNs in terms of accurately predicting the ground-state spin of each sample within the TBRE.However,our NN model effectively captured the statistical properties of the ground-state spin because it learned the empirical regularity of the ground-state spin distribution in TBRE,as discovered by physicists.
文摘We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.
文摘将既有的车辆-有砟轨道-路基-层状地基耦合系统垂向振动解析模型进行修改,使模型适应于板式无砟轨道的状况。针对我国客运专线线路情况,利用模型比较分析了有砟与板式无砟两种轨道结构下高速列车运行引起的地基振动,得到地基表面垂向振动加速度的振级、时程曲线和Z振级,动应力的功率谱与时程曲线;并讨论了轨道随机不平顺对地基振动的影响。分析结果表明：板式无砟轨道具有更好的隔振能力,板式无砟轨道情况下的地基振动加速度和动应力都明显小于有砟轨道的情况,其中Z振级减小约10~20 d B,且减小振动的主要频率分布在10~40 Hz的中频范围内;移动轴荷载对地基的低频振动贡献较大,而轨道随机不平顺主要对中高频振动产生作用,且板式无砟轨道情况下轨道随机不平顺对地基振动的影响远大于有砟轨道的情况,因此板式无砟轨道需更严格控制轨道的平顺状态。
