基于相关性分析的PCBA热力学模型修正

目的精确且高效地对印制电路板组件热力学模型进行修正。方法采用基于拉丁超立方抽样试验设计和Speraman等级相关系数计算公式的相关性分析方法,找出电子产品热仿真试验中对元器件表面温度值影响较大的输入参数,然后进一步分析得出输入与输出之间的函数关系。在此基础上给出印制电路板组件(PCBA)热力学模型修正的一般方法流程。最后利用该方法对某航空电子产品中一块PCBA的热力学模型进行修正。结果修正结果较精确且只调用2次有限元软件。结论该热模型修正方法具有较高的精确性和高效性,可推广用于工程实践。     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取;提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列;发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性;构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测;在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

崇明东滩湿地沉积物重金属污染的磁诊断

对取自崇明东滩的高潮滩、中潮滩和低潮滩的沉积物柱样进行了磁学、粒度、重金属含量等指标的分析、比较与综合研究. 结果表明:在以粉砂为主的崇明东滩,通过污染负荷指数法进行评价,除低潮滩无污染外,中潮滩和高潮滩均有中度的重金属污染. 选取中度重金属污染的高潮滩沉积物柱样进行粒度、重金属含量以及磁性参数的相关性分析显示,χ_fd,χ_ARM/SIRM与重金属含量和粘土(粒径<4 μm)之间有较高的相关性,并以此建立了磁诊断线性回归模型;χ_fd和χ_ARM/SIRM可作为重金属含量的替代指标.      

微生物脱臭研究应用进展

随着恶臭气体污染成为环境污染的重大问题,对恶臭气体的控制和治理逐渐兴起。文章论述了用微生物法治理恶臭气体污染的基本原理,国内外研究现状以及主要工艺的类型和特点。讨论微生物法的主要影响因素,总结其存在的问题,并对发展趋势做了介绍。     

运用QSPR预测有机磷农药的色谱保留值

通过计算43种有机磷农药的各种结构参数,运用多元线性回归分析方法比较了适用于有机磷农药色谱保留值的定量关系表达式,建立了有机磷农药结构参数对色谱保留值的QSPR模型.模型分析表明:磷酸酯与硫逐磷酸酯两类有机磷农药的模型非交叉验证相关系数R2分别为0.991和0.998,标准误差SE分别为0.0539和0.2874,交叉验证相关系数Q2分别为0.976和0.990,标准偏差Scv分别为0.086和0.610.在已知磷酸酯与硫逐磷酸酯两类有机磷农药结构参数的情况下,此模型可有助于有机磷农药的色谱分析.     

防空导弹的综合环境可靠性试验剖面研究

为有效地进行防空导弹综合环境可靠性试验,根据试验剖面的模拟真实性、应力适当性和试验可操作性的要求,确定以防空导弹随战车值勤和空中飞行为主要试验阶段。主要研究了地面和空中2种试验环境中温度应力、湿度、振动应力和电应力等环境参数的确定,并给出了相应的原则或计算公式。最后讨论了如何确定试验时间的问题,并绘出了综合环境可靠性试验剖面图。     

拉萨河夏季氢氧同位素空间分布特征及分析

稳定同位素示踪技术是河流水文过程研究的重要方式,可以用来判定河流补给的来源、研究河流与其它水体相互作用、示踪水文循环过程等.本文采用TC/EA-IRMS分析法对拉萨河水体的氢氧同位素进行测定,分析了 δD和δ18O的含量及空间分布特征,并分析了拉萨河的同位素效应,包括与大气降水氢氧同位素的关系、氢氧同位素的沿程变化特征...     

基于人工神经网络的气体泄爆最大超压预测研究

为解决传统经验公式在预测气体泄爆中最大超压出现时的较大偏差或过于保守的问题,提出使用人工神经网络预测气体泄爆最大超压。基于124组实验数据,采用BP与RBF神经网络,通过优化算法计算与迭代循环对泄爆样本中的影响因素进行降维与选择,并确定2类神经网络本身在学习与计算气体泄爆样本时的相关参数。结果表明:PCA（主成分分析法）在当前样本条件下的降维效果较差,而通过迭代对比确认气体泄爆样本中的5类特征全部保留时神经网络的训练模拟效果最好;通过对124组实验数据进行随机挑选训练集与测试集的训练模拟结果发现,神经网络对气体泄爆中最大超压的预测效果较好;通过对比Molkov提出的和经Fakandu等改进的NFPA 68经验公式以及2类神经网络的预测结果表明,神经网络相比于传统气体泄爆经验公式具有明显优势。