改进X荧光光谱仪快速检测土壤中重金属

针对传统能量色散X荧光仪(energy dispersive X-ray fluorescence,EDXRF)分析土壤中微量重金属测量精确度低的问题,提出了一种X荧光仪改进方法。为了减少反射X射线的影响,入射X射线垂直照射样品,探测器平行放置与样品一侧且垂直于X射线。样品与探测器之间由准直器连接。对国家标样测量结果表明,仪器对Mo,Zn,Cu,Pb,Zr,Nb的检出限为0.4,6.68,1.97,6.84,1.60,7.59 mg·kg-1。各元素对数偏差在0～0.05之间。元素含量在三倍检出限以上RSD%(GBW)小于7,元素含量在三倍检出限内RSD%(GBW)小于15。为了验证改进后X荧光仪测量效果,在大兴安岭地区采集土壤样品与传统荧光仪进行比较分析。改进X荧光仪提高了土壤中微量重金属测量精度,满足野外地质普查要求。     

Weighted Compact Scheme for Shock Capturing

In this paper a new class of finite difference schemes - the Weighted Compact Schemes are proposed. According to the idea of the WENO schemes, the Weighted Compact Scheme is constructed by a combination of the approximations of derivatives on candidate stencils with properly assigned weights so that the non-oscillatory property is achieve when discontinuities appear. The primitive function reconstruction method of ENO schemes is applied to obtain the conservative form of the Weighted Compact Scheme. This new scheme not only preserves the characteristic of standard compact schemes and achieves high order accuracy and high resolution using a compact stencil, but also can accurately capture shock waves and discontinuities without oscillation. Numerical examples show the new scheme is very promising and successful.     

Multiaxial yield surface of transversely isotropic foams: Part I—Modeling

A new yield criterion is proposed for transversely isotropic solid foams. Its derivation is based on the hypothesis that the yielding in foams is driven by the total strain energy density, rather than a completely phenomenological approach. This allows defining the yield surface with minimal number of parameters and does not require complex experiments. The general framework used leads to the introduction of new scalar measures of stress and strain (characteristic stress and strain) for transversely isotropic foams. Furthermore, the central hypothesis that the total strain energy density drives yielding in foams ascribes to the characteristic stress an analogous role of von Mises stress in metal plasticity. Unlike the overwhelming majority of yield models in literature the proposed model recognizes the tension–compression difference in yield behavior of foams through a linear mean stress term. Predictions of the proposed yield model are in excellent agreement with the results of uniaxial, biaxial and triaxial FE analyses implemented on both isotropic and transversely isotropic Kelvin foam models.     

EAST 六自由度内窥机械臂的逆运动学算法研究

为了实现 EAST 装置真空室内的内窥多关节机械臂的实时高精度控制,提出了一种逆运动学算法,即建立机械臂多变量的方程组,转化成为矩阵的特征值问题求解。为了验证和满足实际控制的需要,还基于 VC++6.0 开发了 MFC 运动学算法程序。结果表明,该算法能在 ms 级别内得到机械臂的所有运动学逆解。     

Effect of regularized delta function on accuracy of immersed boundary method

The immersed boundary method is an effective technique for modeling and simulating fluid-structure interactions especially in the area of biomechanics. The effect of the regularized delta function on the accuracy is an important subject in the property study. A method of manufactured solutions is used in the research. The computational code is first verified to be mistake-free by using smooth manufactured solutions. Then, a jump in the manufactured solution for pressure is introduced to study the accuracy of the immersed boundary method. Four kinds of regularized delta functions are used to test the effect on the accuracy analysis. By analyzing the discretization errors, the accuracy of the immersed boundary method is proved to be first-order. The results show that the regularized delta function cannot improve the accuracy, but it can change the discretization errors in the entire computational domain.     

Design of short pulse laser driven opacity experiments

Hot electrons created by short, intense laser pulses can heat solid density material to temperatures of order 500 eV. Inertial confinement can maintain such hot-dense plasmas for times of order 10 ps. This provides a platform for measurement of basic properties of hot dense matter, such as opacity and equation-of-state. In this paper we describe the role of computational modeling in the design and analysis of such opacity experiments. We describe a method to model the hot electron transport and deposition and the resulting target radiation-hydrodynamics. We present several design concepts to achieve uniform, long-lasting plasmas.     

基于全谱数据挖掘技术的土壤有机质高光谱预测建模研究

可见/近红外高光谱技术与建模方法是当前土壤近地传感器研究领域的重要方向,可应用于土壤养分信息的快速获取和农田作物的精确施肥管理。以浙江省水稻土为研究对象,利用以非线性模型为核心的数据挖掘技术,包括随机森林、支持向量机、人工神经网络等方法分别建立了不同建模集和验证集的原始光谱与有机质含量的估测模型。结果表明：研究比较的1∶1,3∶1和全部样本建模并全部验证的三种样本模式划分对建模的结果有一定的影响。相较于目前常用的偏最小二乘回归(PLSR)建模方法而言,非线性模型RF和SVM也取得了较好的建模精度,三种模式下其RDP值均大于1.4。特别是采用SVM建模方法所得模型具有很好的预测能力,模式二下其RDP值达到2.16。同时引入ANN方法改进建立的PLSR-ANN方法显著提高了PLSR的模型预测能力。     

显微镜工作台定位系统的设计与实现

设计了一套基于AT89C52单片机的显微镜工作台定位系统。机械传动部分采用小模数齿轮实现机械运动和动力的传递,单片机电路控制部分实现计数脉冲的获取和电机的控制,上位机控制环节完成用户命令的发布。该系统可以按照预先设定的方式控制电机,实现显微镜工作台的二维运动,两方向重复定位精度±50μm,满足了多波长光存储实验的要求,同时为医疗检验提供了自动化手段。     

Brownian dynamic simulation for the prediction of effective thermal conductivity of nanofluid

Nanofluid is a colloidal solution of nanosized solid particles in liquids. Nanofluids show anomalously high thermal conductivity in comparison to the base fluid, a fact that has drawn the interest of lots of research groups. Thermal conductivity of nanofluids depends on factors such as the nature of base fluid and nanoparticle, particle concentration, temperature of the fluid and size of the particles. Also, the nanofluids show significant change in properties such as viscosity and specific heat in comparison to the base fluid. Hence, a theoretical model becomes important in order to optimize the nanofluid dispersion (with respect to particle size, volume fraction, temperature, etc.) for its performance. As molecular dynamic simulation is computationally expensive, here the technique of Brownian dynamic simulation coupled with the Green Kubo model has been used in order to compute the thermal conductivity of nanofluids. The simulations were performed for different concentration ranging from 0.5 to 3 vol%, particle size ranging from 15 to 150 nm and temperature ranging from 290 to 320 K. The results were compared with the available experimental data, and they were found to be in close agreement. The model also brings to light important physical aspect like the role of Brownian motion in the thermal conductivity enhancement of nanofluids.     

Modeling of In2O3-10 wt% ZnO thin film properties for transparent conductive oxide using neural networks

Effects of deposition process parameters on the deposition rate and the electrical properties of In₂O₃–10 wt% ZnO (IZO) thin films were modeled and analyzed by using the error back-propagation neural networks (BPNN). Output models were represented by response surface plots and the fitness of models was estimated by calculating the root mean square error (RMSE). The deposition rate of IZO thin films is affected by the RF power and the substrate temperature. The electrical properties of the IZO thin films are mainly controlled by O₂ ratio and the substrate temperature. The predicted output characteristics by BPNN can sufficiently explain the mechanism of IZO deposition process. Thus, neural network models can provide the reliable explanation of IZO film deposition.