Method of Data Reduction and Uncertainty Estimation for Platinum-Group Element Data Using Inductively Coupled Plasma-Mass Spectrometry

A data reduction method is described for determining platinum-group element (PGE) abundances by inductively coupled plasma-mass spectrometry (ICP-MS) using external calibration or the method of standard addition. Gravimetric measurement of volumes, the analysis of reference materials and the use of procedural blanks were all used to minimise systematic errors. Internal standards were used to correct for instrument drift. A linear least squares regression model was used to calculate concentrations from drift-corrected counts per second (cps). Furthermore, mathematical manipulations also contribute to the uncertainty estimates of a procedure. Typical uncertainty estimate calculations for ICP-MS data manipulations involve: (1) Carrying standard deviations from the raw cps through the data reduction or (2) calculating a standard deviation from multiple final concentration calculations. It is demonstrated that method 2 may underestimate the uncertainty estimate of the calculated data. Methods 1 and 2 do not typically include an uncertainty estimate component from a regression model. As such models contribute to the uncertainty estimates affecting the calculated data, an uncertainty estimate component from the regression must be included in any final error calculations. Confidence intervals are used to account for uncertainty estimates from the regression model. These confidence intervals are simpler to calculate than uncertainty estimates from method 1, for example. The data reduction and uncertainty estimation method described here addresses problems of reporting PGE data from an article in the literature and addresses both precision and accuracy. The method can be applied to any analytical technique where drift corrections or regression models are used.     

Application of genetic BP network to discriminating earthquakes and explosions

Introduction Artificial Neural Network (ANN) is an important branch of artificial intelligence. It is proposed on the foundation of the study on modern neural science, is a man-made network that can implement some functions based on the mans comprehensive understanding for cerebral neural network (HAN, WANG, 1997). ANN is a mathematical model of simplified human brain neural network and is used to simulate the structures and functions of human brain neural network. ANN is a complex netw…     

三维地震数据离散光滑插值的共轭梯度法

针对三维地震数据插值,提出采用Laplacian算子进行光滑约束的插值方法,并借鉴Mallet研究的离散光滑插值思路,采用预条件共轭梯度法,直接生成网格节点上的值,从而回避寻求满足插值方程的函数. 为了实现其中Laplacian算子的快速求逆,文中引入Claerbout螺旋坐标系谱因式分解理论. 在螺旋坐标系下,Laplacian算子的表示矩阵具有Toeplitz结构,其快速求逆可由谱法LU分解实现. 基于二维离散光滑插值,文中还给出共轭梯度法与NMO相结合的沿时间切片逐层处理的离散光滑插值流程. 最后,应用该方法对模型数据和实际三维地震数据进行了处理.     

Seismic structural control using semi-active tuned mass dampers

This paper focuses on how to determine the instantaneous damping of the semi-active tuned mass damper (SATMD) with continuously variable damping. An off-and-towards-equilibrium (OTE) algorithm is employed to examine the control performance of the structure/SATMD system by considering the damping as an assumptive control action. The damping modification of the SATMD is carried out according to the proposed OTE algorithm, which is formulated based on analysis of the structural movement under external excitations, and the measured responses of the structure at every time instant. As examples two numerical simulations of a five-storey and a ten-storey shear structures with a SATMD on the roof are conducted. The effectiveness on vibration reduction of MDOF systems subjected to seismic excitations is discussed. Analysis results show that the behavior of the structure with a SATMD is significantly improved and the feasibility of applying the OTE algorithm to the structural control design of SATMD is also verified.     

投影寻踪门限回归模型在年径流预测中的应用

为预测年径流这类同维复杂动力系统，提出了投影寻踪门限回归（PPTR）模型。构造了新的投影指标函数，用门限回归（TR）模型描述投影值与预测对象间的非线性关系，并用实码加速遗传算法优化投影指标指数函数和TR模型参数。实例的计算结果表明，用PPTR模型预测年径流是可行而有效的。PPRT模型简便、适用性强，克服了目前投影寻踪方法计算量大、编程实现困难的缺点，有利投影寻踪方法的推广应用，为解决高维非线性复杂预测问题提供了新途径。     

一种求气井二项式方程系数的新方法

针对开发早期气田缺乏产能试井资料的实际情况，由于无法用传统的压力降法计算产能方程，故而基于最优化算法，提出了一种利用稳定生产数据和井控储量求取气井产能方程系数的新方法。在只知道稳定生产数据情况下便可进行计算分析。该方法在气田进行了实际应用，并和实际资料以及传统试凑法计算的结果进行了比较，表明方法的计算结果较为可靠。     

基坑支护结构水平变形预测的遗传神经网络方法

采用遗传算法和误差反向传播算法相结合的混合算法来训练前馈人工神经网络,先用遗传学习算法进行全局训练,再用BP算法进行精确训练。就遗传算法过程中的选择、变异进行了探索,提出了用BP网络训练产生变异的遗传算法。作为实例,将该方法应用于预测基坑支护结构水平变形中。结果表明,该方法有收敛速度较快、预测精度高等优点。     

等离子体发射光谱法直接测定海洋沉积物中的微量稀土元素

应用全谱直读电感耦合等离子体发射光谱法对海洋沉积物中微量稀土元素的测定进行了研究，选择了最佳的仪器工作条件，采用多谱线拟合技术进行校正，样品的加标回收率为94．0％-110．0％。方法采用海底沉积物国家一级标准物质进行验证，测定结果与标准值较吻合，各元素10次测定的RSD≤11．3％。     

碱熔沉淀-等离子体质谱法测定地质样品中的多元素

采用过氧化钠焙融或偏硼酸锂熔融分解样品，将提取液碱性沉淀，通过过滤分离掉大量熔剂，再将沉淀用酸复溶后用等离子体质谱测定26个元素。通过对比，偏硼酸锂熔融—酸提取—碱性沉淀的方案，空白低，易操作，成本低，大多数元素测定结果的相对误差＜10％，相对标准偏差＜5％(n＝10)，与标准值相吻合。     

乙醇增强—电感耦合等离子体质谱法直接测定地质样品中碲

建立了HF—HN03密封酸溶以及Na2O2熔融处理样品，乙醇增强灵敏度，电感耦合等离子体质谱直接测定地质样品中微量和超痕量碲的方法。样品溶液中加入乙醇(φ＝4％)，在0．85L/min的载气流速下，碲信号可增强2．5倍以上。碲的方法检出限(100，DF＝1000)为0．02μg/g。用土壤和水系沉积物国家一级标准物质验证了方法的准确度，标准物质的绝大多数分析结果与标准值的误差在允许范围内。分析了大洋多金属结核样品及深海沉积物样品中的微量碲，结果与其他方法相符，精密度试验RSD(n＝3)＜10％。