文中将坐标伸缩完全匹配层CPML引入到弱无条件稳定算法HIE-FDTD中研究其吸波性能。详细推导了2维TE波模型中CPML在HIE-FDTD算法中应用的差分公式。为检验本文所提方法的吸波效能,建立了计算模型,将其与其它吸收边界条件的吸波性能进行...文中将坐标伸缩完全匹配层CPML引入到弱无条件稳定算法HIE-FDTD中研究其吸波性能。详细推导了2维TE波模型中CPML在HIE-FDTD算法中应用的差分公式。为检验本文所提方法的吸波效能,建立了计算模型,将其与其它吸收边界条件的吸波性能进行了综合比较,计算了HIE-FDTD算法选取不同条件数时的反射误差,并详细说明如何合理选取α,κmax和σmax来实现最佳相对误差。结果显示:当将本文所提方法的CPML层数设置为8时,其反射误差为-62 d B,低于传统FDTD方法的-58 d B;当选取α=0.05,κmax=10,σmax/σopt=1.3可以实现低至-83 d B的最大相对误差;在仿真中,其比传统FDTD方法也约减少48%的计算时间。展开更多
文中将CPML引入3维弱无条件稳定算法HIE-FDTD中,详细推到了CPML在3维弱无条件稳定HIE-FDTD中的差分公式。为了验证CPML在3维HIE-FDTD中的吸波性能,建立了数值计算模型,并将CPML的吸波性能同其它几种常用的吸收边界条件进行了比较。结果...文中将CPML引入3维弱无条件稳定算法HIE-FDTD中,详细推到了CPML在3维弱无条件稳定HIE-FDTD中的差分公式。为了验证CPML在3维HIE-FDTD中的吸波性能,建立了数值计算模型,并将CPML的吸波性能同其它几种常用的吸收边界条件进行了比较。结果显示,当将CPML层数设置为8时,其最大反射误差为-72 d B,远低于传统FDTD方法的反射误差。另外,当匹配层参数设置为α=0.05,可以在一个较大范围内选取κmax和σmax来实现最佳误差,从而使得在选值时易于预测反射情况。展开更多
In this paper,a detailed introduction is given to the check method of the BRDF experiment bench which is built on our own. Measurement is made on the BRDF of the standard white plate made of polytetrafluoroethylene(PT...In this paper,a detailed introduction is given to the check method of the BRDF experiment bench which is built on our own. Measurement is made on the BRDF of the standard white plate made of polytetrafluoroethylene(PTFE)with reference to the existing standard white plate whose surface reflectance is known and by the method of theory approximate and relative comparison. On the basis of that,the BRDF value of the standard white plate in the wave band of 0.6328μm is given and the experiment bench is checked,the relative error of the experiment bench being within 20%.展开更多
In machining processes, errors of rough in dimension, shape and location lead to changes in processing quantity, and the material of a workpiece may not be uniform. For these reasons, cutting force changes in machinin...In machining processes, errors of rough in dimension, shape and location lead to changes in processing quantity, and the material of a workpiece may not be uniform. For these reasons, cutting force changes in machining, making the machining system deformable. Consequently errors in workpieces may occur. This is called the error reflection phenomenon. Generally, such errors can be reduced through repeated processing while using appropriate processing quantity in each processing based on operator's experience.According to the theory of error reflection, the error reflection coefficient indicates the extent to which errors of rough influence errors of workpieces. It is related to several factors such as machining condition, hardness of the workpiece, etc. This non-linear relation cannot be worked out using any formula. RBF neural network can approximate a non-linear function within any precision and be trained fast. In this paper, non-linear mapping ability of a fuzzy-neural network is utilized to approximate the non-linear relation. After training of the network with swatch collection obtained in experiments, an appropriate output can be obtained when an input is given. In this way, one can get the required number of processing and the processing quantity each time from the machining condition. Angular rigidity of a machining system,hardness of workpiece, etc., can be input in a form of fuzzy values. Feasibility in solving error reflection and optimizing machining parameters with a RBF neural network is verified by a simulation test with MATLAB.展开更多
We examined regional empirical equations for estimating the surface concentration of particulate organic carbon （POC） in the South China Sea. These algorithms are based on the direct relationships between POC and th...We examined regional empirical equations for estimating the surface concentration of particulate organic carbon （POC） in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance, Rrs（λB）/Rrs（555）. The best error statistics among the considered formulas were produced using the power function POC （rag/ m3）=262.173 [Rrs（443）/Rrs（555）]^-0.940. This formula resulted in a small mean bias of approximately -2.52%, a normalized root mean square error of 31.1%, and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm, in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-to- blue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally, we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.展开更多
文摘文中将坐标伸缩完全匹配层CPML引入到弱无条件稳定算法HIE-FDTD中研究其吸波性能。详细推导了2维TE波模型中CPML在HIE-FDTD算法中应用的差分公式。为检验本文所提方法的吸波效能,建立了计算模型,将其与其它吸收边界条件的吸波性能进行了综合比较,计算了HIE-FDTD算法选取不同条件数时的反射误差,并详细说明如何合理选取α,κmax和σmax来实现最佳相对误差。结果显示:当将本文所提方法的CPML层数设置为8时,其反射误差为-62 d B,低于传统FDTD方法的-58 d B;当选取α=0.05,κmax=10,σmax/σopt=1.3可以实现低至-83 d B的最大相对误差;在仿真中,其比传统FDTD方法也约减少48%的计算时间。
文摘文中将CPML引入3维弱无条件稳定算法HIE-FDTD中,详细推到了CPML在3维弱无条件稳定HIE-FDTD中的差分公式。为了验证CPML在3维HIE-FDTD中的吸波性能,建立了数值计算模型,并将CPML的吸波性能同其它几种常用的吸收边界条件进行了比较。结果显示,当将CPML层数设置为8时,其最大反射误差为-72 d B,远低于传统FDTD方法的反射误差。另外,当匹配层参数设置为α=0.05,可以在一个较大范围内选取κmax和σmax来实现最佳误差,从而使得在选值时易于预测反射情况。
文摘In this paper,a detailed introduction is given to the check method of the BRDF experiment bench which is built on our own. Measurement is made on the BRDF of the standard white plate made of polytetrafluoroethylene(PTFE)with reference to the existing standard white plate whose surface reflectance is known and by the method of theory approximate and relative comparison. On the basis of that,the BRDF value of the standard white plate in the wave band of 0.6328μm is given and the experiment bench is checked,the relative error of the experiment bench being within 20%.
文摘In machining processes, errors of rough in dimension, shape and location lead to changes in processing quantity, and the material of a workpiece may not be uniform. For these reasons, cutting force changes in machining, making the machining system deformable. Consequently errors in workpieces may occur. This is called the error reflection phenomenon. Generally, such errors can be reduced through repeated processing while using appropriate processing quantity in each processing based on operator's experience.According to the theory of error reflection, the error reflection coefficient indicates the extent to which errors of rough influence errors of workpieces. It is related to several factors such as machining condition, hardness of the workpiece, etc. This non-linear relation cannot be worked out using any formula. RBF neural network can approximate a non-linear function within any precision and be trained fast. In this paper, non-linear mapping ability of a fuzzy-neural network is utilized to approximate the non-linear relation. After training of the network with swatch collection obtained in experiments, an appropriate output can be obtained when an input is given. In this way, one can get the required number of processing and the processing quantity each time from the machining condition. Angular rigidity of a machining system,hardness of workpiece, etc., can be input in a form of fuzzy values. Feasibility in solving error reflection and optimizing machining parameters with a RBF neural network is verified by a simulation test with MATLAB.
基金Supported by the National Natural Science Foundation of China(Nos.41376042,41176035)the Natural Science for Youth Foundation(No.41206029)+2 种基金the Youth Foundation by South China Sea Institute of Oceanology,Chinese Academy of Sciences(No.SQ201102)the Open Research Fund of State Key Laboratory of Estuarine and Coastal Research(No.SKLEC-KF201302)the Open Project Program of State Key Laboratory of Tropical Oceanography,South China Sea Institute of Oceanology,Chinese Academy of Sciences(No.LTOZZ1201)
文摘We examined regional empirical equations for estimating the surface concentration of particulate organic carbon （POC） in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance, Rrs（λB）/Rrs（555）. The best error statistics among the considered formulas were produced using the power function POC （rag/ m3）=262.173 [Rrs（443）/Rrs（555）]^-0.940. This formula resulted in a small mean bias of approximately -2.52%, a normalized root mean square error of 31.1%, and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm, in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-to- blue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally, we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.
