3种评价牙膏磨损性能的方法比较

研究比较了表面粗糙度法、ISO11609中附录A的放射性示踪法及附录B的表面轮廓法3种评价牙膏磨损性能的体外实验方法。实验结果表明,对于含有同种类型摩擦剂(二氧化硅或天然碳酸钙)的牙膏试样,表面粗糙度法Ra值的测试结果与放射性示踪法RDA值及表面轮廓法磨损深度的测试结果均具有良好的相关性。同时,与ISO11609中的2种方法相比,表面粗糙度法具有操作简单、刷磨过程压力可控、检测仪器性价比高、数据重复性好、测试结果不易被牙膏配方中磷酸盐等组分干扰等特点。

一种评价牙膏磨损性能的方法研究

研究并提出了一种评价牙膏磨损性能的新方法——表面粗糙度法。本方法利用自主创新研发的,具有刷磨压力全程可控及实时显示功能的L8-Ⅱ型刷磨仪作为刷磨仪器,聚甲基丙烯酸甲酯(PMMA)磨块作为代替牙本质的实验材料进行体外实验。在刷磨测试前后用表面粗糙度仪测定PMMA磨块表面的Ra值,通过PMMA磨块表面Ra值的差值评价牙膏试样对PMMA磨块的磨损性。方法研究的过程中着重对L8-Ⅱ型刷磨仪全程刷磨压力的变化规律、PMMA磨块上Ra值的测量位置等条件进行了考量,最终确立了最优化的实验条件。实验结果表明,对于同种类型磨擦剂(二氧化硅或天然碳酸钙)的牙膏试样,本研究方法 Ra值的测试结果与ISO11609中附录A放射性示踪法RDA值及附录B表面轮廓法磨损深度的测试结果均具有良好的相关性。同时,相比较ISO11609中的两种方法,本方法还具有操作简单、刷磨过程压力可控、检测仪器性价比高、数据重复性好、实验误差小、测试结果不易被牙膏配方中磷酸盐等组分干扰等优点。

A Method for Surface Roughness Parameter Estimation in Passive Microwave Remote Sensing

Surface roughness parameter is an important factor and obstacle for retrieving soil moisture in passive microwave remote sensing.Two statistical parameters,root mean square (RMS) height (s) and correlation length (l),are designed for describing the roughness of a randomly rough surface.The roughness parameter measured by traditional way is independence of frequency,soil moisture and soil heterogeneity and just the ″geometric″ roughness of random surface.This ″geometric″ roughness can not fully explain the scattered thermal radiation by the earth's surface.The relationship between ″geometric″ roughness and integrated roughness (contain both ″geometric″ roughness and ″dielectric″ roughness) is linked by empirical coefficient.In view of this problem,this paper presents a method for estimating integrated surface roughness from radiometer sampling data at different frequencies,which mainly based on the flourier relationship between power spectral density distribution and spatial autocorrelation function.We can obtain integrated surface roughness at different frequencies by this method.Besides "geometric" roughness,this integrated surface roughness not only contains "dielectric" roughness but also includes frequency dependence.Combined with Q/H model the polarization coupling coefficient can also be obtained for both H and V polarization.Meanwhile,the simulated numerical results show that radiometer with a sensitivity of 0.1 K can distinguish the different surface roughness and the change of roughness with frequency for the same rough surface.This confirms the feasibility of radiometer sampling method for estimating the surface roughness theoretically.This method overcomes the problem of ″dielectric″ roughness measurement to some extent and can achieve the integrated surface roughness within a microwave pixel which can serve soil moisture inversion better than the ″geometric″ roughness.

Evaluation of surface roughness and optimization of cutting parameters in turning of AA2024 alloy under different cooling-lubrication conditions using RSM method

In the present study,the effect of reduction of cutting fluid consumption on the surface quality and tool wear was studied.Mathematical models were developed to predict the surface roughness using response surface methodology(RSM).Analysis of variance(ANOVA)was used to investigate the significance of the developed regression models.The results showed that the coefficient of determination values(R^2)for the developed models was 97.46%for dry,89.32%for flood mode(FM),and 99.44%for MQL,showing the high accuracy of fitted models.Also,under the minimum quantity lubrication(MQL)condition,the surface roughness improved by 23%−44%and 19%−41%compared with dry and FM,respectively,and the SEM images of machined surface proved the statement.The prepared SEM images of tool rake face also showed a considerable decrease in adhesion wear.Built-up edge and built-up layer were the two main products of the adhesion wear,and energy-dispersive X-ray spectroscopy(EDX)analysis of specific points on the tool faces helped to discover the chemical compositions of adhered materials.By changing dry and FM to MQL mode,dominant mechanism of tool wear in machining aluminum alloy was significantly decreased.Breakage wear that led to early failure of cutting edge was also controlled by MQL technique.

Modeling of rough surfaces with given roughness parameters

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.

Modeling and analysis of surface roughness on machining of Nimonic C-263 alloy by PVD coated carbide insert

The effects of the cutting parameters （cutting speed, feed rate and depth of cut） on the surface roughness in machining the Nimonic C-263 alloy were investigated. The experiments were conducted using Taguchi＇s experimental design. The effect of cutting parameters on surface roughness was evaluated and the optimum cutting conditions for minimizing the surface roughness were determined. A second order model was established between the cutting parameters and surface roughness, using the response surface methodology. The experimental results revealed that among the parameters considered, the feed rate is the most significant which influences the surface roughness, followed by the cutting speed. The predicted values and measured values are fairly close, which indicates that the developed model can be effectively used to predict the surface roughness in machining the Nimonic C-263 alloy. The predicted values are validated using the additive law.

Parametric optimization of electrochemical machining of Al/15% SiC_p composites using NSGA-Ⅱ

Electrochemical machining（ECM） is one of the important non-traditional machining processes,which is used for machining of difficult-to-machine materials and intricate profiles.Being a complex process,it is very difficult to determine optimal parameters for improving cutting performance.Metal removal rate and surface roughness are the most important output parameters,which decide the cutting performance.There is no single optimal combination of cutting parameters,as their influences on the metal removal rate and the surface roughness are quite opposite.A multiple regression model was used to represent relationship between input and output variables and a multi-objective optimization method based on a non-dominated sorting genetic algorithm-Ⅱ（NSGA-Ⅱ） was used to optimize ECM process.A non-dominated solution set was obtained.

Optimum design of carbon/carbon ablative property based on genetic algorithm

An optimum design model has been proposed for carbon/carbon ablative property based on genetic algorithm,in which the optimum parameters are the number of woven satins,K of fiber bundles,layers per unit height,the average distance of puncture fibers in Z direction and Ply Stacking angle,and the constraint conditions are the density and diameter of carbon fibers and the density of carbon matrix.The results demonstrate that after optimization,the overall height of the ablative carbon/carbon surface is reduced by 56.5%,the standard deviation is reduced by 34.9% and the surface roughness is reduced by 12.6%,which suggests the remarkable improvement of ablative homogeneity.The present investigation can provide practical methodology for the optimum design of carbon/carbon ablative property and the development of new carbon/carbon composites.

Modeling bidirectional reflection distribution function of microscale random rough surfaces

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.