Modeling of rough surfaces with given roughness parameters is studied,where surfaces with Gaussian height distribution and exponential auto-correlation function(ACF) are concerned.A large number of micro topography sa...Modeling of rough surfaces with given roughness parameters is studied,where surfaces with Gaussian height distribution and exponential auto-correlation function(ACF) are concerned.A large number of micro topography samples are randomly generated first using the rough surface simulation method with FFT.Then roughness parameters of the simulated roughness profiles are calculated according to parameter definition,and the relationship between roughness parameters and statistical distribution parameters is investigated.The effects of high-pass filtering with different cut-off lengths on the relationship are analyzed.Subsequently,computing formulae of roughness parameters based on standard deviation and correlation length are constructed with mathematical regression method.The constructed formulae are tested with measured data of actual topographies,and the influences of auto-correlation variations at different lag lengths on the change of roughness parameter are discussed.The constructed computing formulae provide an approach to active modeling of rough surfaces with given roughness parameters.展开更多
The radiative properties of three different materials surfaces with one-dimensional microscale random roughness were obtained with the finite difference time domain method(FDTD) and near-to-far-field transformation.Th...The radiative properties of three different materials surfaces with one-dimensional microscale random roughness were obtained with the finite difference time domain method(FDTD) and near-to-far-field transformation.The surface height conforms to the Gaussian probability density function distribution.Various computational modeling issues that affect the accuracy of the predicted properties were discussed.The results show that,for perfect electric conductor(PEC) surfaces,as the surface roughness increases,the magnitude of the spike reduces and eventually the spike disappears,and also as the ratio of root mean square roughness to the surface correlation distance increases,the retroreflection becomes evident.The predicted values of FDTD solutions are in good agreement with the ray tracing and integral equation solutions.The overall trend of bidirectional reflection distribution function(BRDF) of PEC surfaces and silicon surfaces is the same,but the silicon's is much less than the former's.The BRDF difference from two polarization modes for the gold surfaces is little for smaller wavelength,but it is much larger for the longer wavelength and the FDTD simulation results agree well with the measured data.In terms of PEC surfaces,as the incident angle increases,the reflectivity becomes more specular.展开更多
基金Projects(51535012,U1604255)supported by the National Natural Science Foundation of ChinaProject(2016JC2001)supported by the Key Research and Development Project of Hunan Province,China
文摘Modeling of rough surfaces with given roughness parameters is studied,where surfaces with Gaussian height distribution and exponential auto-correlation function(ACF) are concerned.A large number of micro topography samples are randomly generated first using the rough surface simulation method with FFT.Then roughness parameters of the simulated roughness profiles are calculated according to parameter definition,and the relationship between roughness parameters and statistical distribution parameters is investigated.The effects of high-pass filtering with different cut-off lengths on the relationship are analyzed.Subsequently,computing formulae of roughness parameters based on standard deviation and correlation length are constructed with mathematical regression method.The constructed formulae are tested with measured data of actual topographies,and the influences of auto-correlation variations at different lag lengths on the change of roughness parameter are discussed.The constructed computing formulae provide an approach to active modeling of rough surfaces with given roughness parameters.
基金Project(2009AA05Z215) supported by the National High-Tech Research and Development Program of China
文摘The radiative properties of three different materials surfaces with one-dimensional microscale random roughness were obtained with the finite difference time domain method(FDTD) and near-to-far-field transformation.The surface height conforms to the Gaussian probability density function distribution.Various computational modeling issues that affect the accuracy of the predicted properties were discussed.The results show that,for perfect electric conductor(PEC) surfaces,as the surface roughness increases,the magnitude of the spike reduces and eventually the spike disappears,and also as the ratio of root mean square roughness to the surface correlation distance increases,the retroreflection becomes evident.The predicted values of FDTD solutions are in good agreement with the ray tracing and integral equation solutions.The overall trend of bidirectional reflection distribution function(BRDF) of PEC surfaces and silicon surfaces is the same,but the silicon's is much less than the former's.The BRDF difference from two polarization modes for the gold surfaces is little for smaller wavelength,but it is much larger for the longer wavelength and the FDTD simulation results agree well with the measured data.In terms of PEC surfaces,as the incident angle increases,the reflectivity becomes more specular.
