Simultaneous estimation of aerosol optical constants and size distribution from angular light-scattering measurement signals

The angular light-scattering measurement（ALSM） method combined with an improved artificial bee colony algorithm is introduced to determine aerosol optical constants and aerosol size distribution（ASD） simultaneously. Meanwhile, an optimized selection principle of the ALSM signals based on the sensitivity analysis and principle component analysis（PCA）is proposed to improve the accuracy of the retrieval results. The sensitivity analysis of the ALSM signals to the optical constants or characteristic parameters in the ASD is studied first to find the optimized selection region of measurement angles. Then, the PCA is adopted to select the optimized measurement angles within the optimized selection region obtained by sensitivity analysis. The investigation reveals that, compared with random selection measurement angles, the optimized selection measurement angles can provide more useful measurement information to ensure the retrieval accuracy. Finally,the aerosol optical constants and the ASDs are reconstructed simultaneously. The results show that the retrieval accuracy of refractive indices is better than that of absorption indices, while the characteristic parameters in ASDs have similar retrieval accuracy. Moreover, the retrieval accuracy in studying L-N distribution is a little better than that in studying Gamma distribution for the difference of corresponding correlation coefficient matrixes of the ALSM signals. All the results confirm that the proposed technique is an effective and reliable technique in estimating the aerosol optical constants and ASD simultaneously.

Analysis of Low-level Temperature Inversions and Their Effects on Aerosols in the Lower Atmosphere

High-quality and continuous radiosonde, aerosol and surface meteorology datasets are used to investigate the statistical characteristics of meteorological parameters and their effects on aerosols. The data were collected at the Atmospheric Radiation Measurement Southern Great Plains climate research facility during 2000–15. The parameters and vertical distribution of temperature inversion layers were found to have strong diurnal and seasonal changes. For surface-based temperature inversion (SBI), the mean frequency and depth of temperature inversion layers were 39.4% and 198 m, respectively. The temperature difference between the top and bottom of SBI was 4.8℃, and so the temperature gradient was 2.4℃(100 m)^-1. The detailed vertical distributions of temperature inversion had been determined, and only the temperature inversion layers below 1000 m showed diurnal and seasonal variations. Mean surface aerosol number concentrations increased by 43.0%, 21.9% and 49.2% when SBIs were present at 0530, 1730 and 2330 LST, respectively. The effect of SBI on surface aerosol concentration was weakest in summer (18.1%) and strongest in winter (58.4%). During elevated temperature inversion events, there was no noticeable difference in surface aerosol number concentrations. Temperature differences and temperature gradients across SBIs correlated fairly well with aerosol number concentrations, especially for temperature gradients. The vertical distribution of aerosol optical properties with and without temperature inversions was different. Surface aerosol measurements were representative of the air within (below), but not above, SBIs and EIs. These results provide a basis for developing a boundary layer aerosol accumulation model and for improving radiative transfer models in the lower atmosphere.

In-Situ Measurement of Droplet Size Distribution by Light Scattering Method

Inversion of droplet size distribution in two-phase flow from light scattering has been considered involved because it is in general reduced to the solution of Fredholm integral equation of the first kind that was always ill-posed. By using the Rosin-Rammler distributiona priori as the particulate size distribution model in the liquid-gas two-phase flow, a method via the solution of a two-parameter nonlinear programming problem to determine the droplet size distribution has been developed. A measurement system based on the technique is designed and applied in the shock test of blades of steam turbine. 100-hours continuous monitoring of the droplets in the liquid-gas two-phase flow of 8.0 Pa and 120 °C was performed and the details of the experiments are given out. It is shown that the technique is simple and efficient for in-situ real time measuring droplets in the liquid-gas two-phase flow.

Single-peak distribution model of particulate size for welding aerosols

A large number of particulate size distributions of welding aerosols are measured by means of DMPS method, several distribution types are presented. Among them the single peak distribution is the basic composing unit of particulate size. The research on the mathematic models and distributions functions shows that the single peak distribution features the log normal distribution. The diagram estimating method (DEM) is a concise approach to dealing with distribution types, obtaining distribution functions for the particulate sizes of welding aerosols. It proves that the distribution function of particulate size possesses the extending property, being from quantity distribution to volume, as well as high order moment distributions, with K S method verifying the application of single peak distribution and of DEM.

Dynamic assessment method of air target threat based on improved GIFSS

As the air combat environment becomes more complicated and changeable, accurate threat assessment of air target has a significant impact on air defense operations. This paper proposes an improved generalized intuitionistic fuzzy soft set (GIFSS) method for dynamic assessment of air target threat. Firstly, the threat assessment index is reasonably determined by analyzing the typical characteristics of air targets. Secondly, after the GIFSS at different time is obtained, the index weight is determined by the intuitionistic fuzzy set entropy and the relative entropy theory. Then, the inverse Poisson distribution method is used to determine the weight of time series, and then the time-weighted GIFSS is obtained. Finally, threat assessment of five air targets is carried out by using the improved GIFSS (I-GIFSS) and comparison methods. The validity and superiority of the proposed method are verified by calculation and comparison.

Statistical Inference of Sine Inverse Rayleigh Distribution

We study in this manuscript a new one-parameter model called sine inverse Rayleigh(SIR)model that is a new extension of the classical inverse Rayleigh model.The sine inverse Rayleigh model is aiming to provide morefit-ting for real data sets of purposes.The proposed extension is moreflexible than the original inverse Rayleigh(IR)model and it hasmany applications in physics and medicine.The sine inverse Rayleigh distribution can havea uni-model and right skewed probability density function(PDF).The hazard rate function(HRF)of sine inverse Rayleigh distribution can be increasing and J-shaped.Sev-eral of thenew model’s fundamental characteristics,namely quantile function,moments,incompletemoments,Lorenz and Bonferroni Curves are studied.Four classical estimation methods forthe population parameters,namely least squares(LS),weighted least squares(WLS),maximum likelihood(ML),and percentile(PC)methods are discussed,and the performanceof the four estimators(namely LS,WLS,ML and PC estimators)are also compared bynumerical implementa-tions.Finally,three sets of real data are utilized to compare the behavior of the four employed methods forfinding an optimal estimation of the new distribution.

A New Three-Parameter Inverse Weibull Distribution with Medical and Engineering Applications

The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility.This addition is beneficial in a variety of fields,including reliability,economics,engineering,biomedical science,biological research,environmental studies,and finance.For modeling real data,several expanded classes of distributions have been established.The modified alpha power transformed approach is used to implement the new model.The datamatches the new inverseWeibull distribution better than the inverse Weibull distribution and several other competing models.It appears to be a distribution designed to support decreasing or unimodal shaped distributions based on its parameters.Precise expressions for quantiles,moments,incomplete moments,moment generating function,characteristic generating function,and entropy expression are among the determined attributes of the new distribution.The point and interval estimates are studied using the maximum likelihood method.Simulation research is conducted to illustrate the correctness of the theoretical results.Three applications to medical and engineering data are utilized to illustrate the model’s flexibility.

2022年门源M_(S)6.9地震的同震滑动分布:联合InSAR、GPS和地表位错的贝叶斯建模

2022年1月8日青海省门源M_(S)6.9地震发生于托莱山断裂东段和冷龙岭断裂西段的交汇部位,其运动学特征关系到青藏高原北缘的动力学行为,同时也是区域地震危险性评估中的基础数据.本研究针对该地震,综合InSAR和GPS观测的同震位移场,以及野外地质调查的同震位错数据,采用贝叶斯反演方法,构建同震滑动分布,断层模型采用三角网格更好地刻画断层的不规则几何形态.结果显示,本次左旋走滑型地震的主要滑动发生在冷龙岭断裂西段,深度范围约2~6 km,计算的地震矩为0.95×10^(19)N·m,对应矩震级M_(W)6.65.利用多数据的联合反演解析出,沿走向存在两个滑动集中区,东侧的最大滑动达约4.8 m.震间亏损能量和库仑应力分析表明,托莱山断裂和冷龙岭断裂仍存在未来发震潜能;该地震造成的应力变化,对长期地震空区金强河—毛毛山段落有加载作用,因此,该段未来地震危险性值得关注.

热载荷下星载天线逆有限元变形重构方法

为实现星载天线结构在服役过程中的实时变形监测,针对真实分布式热载荷下的星载天线板结构,研究了基于应变监测的逆有限元变形重构方法.首先,针对星载天线板结构提出了一种基于四节点四边形逆向壳单元的变形监测方法,通过建立基于位移梯度的单元划分方法,对逆有限元单元划分进行优化,采用最小二乘误差函数构造结构应变与位移的矩阵关系.其次,建立天线板热试验系统,获取典型热载荷下的结构温度分布.然后,建立典型实验温差状态下的复合材料星载天线板结构有限元模型,获取结构表面应变和位移.最后,在典型热载荷下,验证所提变形重构方法的有效性.结果表明,变形重构的位移误差不超过0.5 mm,说明逆有限元法能够在典型热载荷下准确重构天线板变形.

Toward Improved Accuracy in Quasi-Static Elastography Using Deep Learning

Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues.The quality of reconstruction results in elastography is highly sensitive to the noise induced by imaging measurements and processing.To address this issue,we propose a deep learning(DL)model based on conditional Generative Adversarial Networks(cGANs)to improve the quality of nonhomogeneous shear modulus reconstruction.To train this model,we generated a synthetic displacement field with finite element simulation under known nonhomogeneous shear modulus distribution.Both the simulated and experimental displacement fields are used to validate the proposed method.The reconstructed results demonstrate that the DL model with synthetic training data is able to improve the quality of the reconstruction compared with the well-established optimization method.Moreover,we emphasize that our DL model is only trained on synthetic data.This might provide a way to alleviate the challenge of obtaining clinical or experimental data in elastography.Overall,this work addresses several fatal issues in applying the DL technique into elastography,and the proposed method has shown great potential in improving the accuracy of the disease diagnosis in clinical medicine.

基于三节点逆元法与光纤传感器的机翼形态重构方法

基于应变信息的飞机机翼结构形态重构技术,可为“仿生式机翼”的气动外形、气弹特性以及隐身性能控制提供数据支撑。为实现对飞机机翼的变形监测,本文提出一种基于三节点逆有限元法和应变信息采集的形态重构方法,并给出相应的光频域反射型分布式光纤传感器布局形式。首先,建立飞机机翼简化模型,开展基于有限元分析结果的形态重构方法仿真验证。其次,构建基于分布式光纤传感器的机翼简化模型应变监测与形态重构试验系统。研究表明,自然下垂工况下,机翼简化模型形态重构相对误差平均值约为4.01%;弯扭组合工况下,机翼简化模型形态重构相对误差平均值约为6.34%。本文所提方法适用于不同载荷工况下飞机机翼变形监测,能够为可变体机翼形态调控与机载共型天线相位补偿提供帮助。

基于克里格法刻画砂岩型铀矿U、Ra和U-Ra平衡系数垂向分布规律--以二连盆地芒来铀矿床为例

砂岩型铀矿是绿色经济可采的重要能源矿种,目前是世界上重要的铀矿勘探类型之一。二连盆地芒来铀矿床、鄂尔多斯盆地纳岭沟铀矿床铀矿体多呈板状产出,板状铀矿体成因备受关注。为研究砂岩型铀矿内部U、Ra和铀镭平衡系数(Kp)分布的垂向分布规律,本文以二连盆地芒来铀矿床为例,采用具有网格精度高优点的克里格插值法研究U、Ra和Kp垂向分布规律,分别利用放射性样品分析数据和定量伽马测井五点式反褶积法反演U含量数据,通过克里格法精细刻画砂岩型矿体中U、Ra和Kp分布的垂向分布规律。研究发现,该矿床板状矿体内部具有卷状的特征,Kp分布形态可以用来判断含氧含铀水的运移方向以及氧化强弱。该方法对研究铀矿体形态、铀矿成矿规律和后续地浸开采具有重要意义。

A New Modified Inverse Lomax Distribution: Properties, Estimation and Applications to Engineering and Medical Data

In this paper,a modified form of the traditional inverse Lomax distribution is proposed and its characteristics are studied.The new distribution which called modified logarithmic transformed inverse Lomax distribution is generated by adding a new shape parameter based on logarithmic transformed method.It contains two shape and one scale parameters and has different shapes of probability density and hazard rate functions.The new shape parameter increases the flexibility of the statistical properties of the traditional inverse Lomax distribution including mean,variance,skewness and kurtosis.The moments,entropies,order statistics and other properties are discussed.Six methods of estimation are considered to estimate the distribution parameters.To compare the performance of the different estimators,a simulation study is performed.To show the flexibility and applicability of the proposed distribution two real data sets to engineering and medical fields are analyzed.The simulation results and real data analysis showed that the Anderson-Darling estimates have the smallest mean square errors among all other estimates.Also,the analysis of the real data sets showed that the traditional inverse Lomax distribution and some of its generalizations have shortcomings in modeling engineering and medical data.Our proposed distribution overcomes this shortage and provides a good fit which makes it a suitable choice to model such data sets.

Inverse Length Biased Maxwell Distribution:Statistical Inference with an Application

In this paper,we suggested and studied the inverse length biased Maxell distribution(ILBMD)as a new continuous distribution of one parameter.The ILBMD is obtained by considering the inverse transformation technique of the Maxwell length biased distribution.Statistical characteristics of the ILBMD such as the moments,moment generating function,mode,quantile function,the coefficient of variation,coefficient of skewness,Moors and Bowley measures of kurtosis and skewness,stochastic ordering,stress-strength reliability,and mean deviations are obtained.In addition,the Bonferroni and Lorenz curves,Gini index,the reliability function,the hazard rate function,the reverse hazard rate function,the odds function,and the distributions of order statistics for the ILBMD,are presented.The ILBMD parameter is estimated using the maximum likelihood method,the method of moments,the maximum product of spacing technique,the ordinary and weight least square procedures,and the Cramer-Von-Mises methods.The Fishers information,as well as the Rényi and q-entropies,are derived.To investigate the usefulness of the proposed lifetime distribution and to illustrate the purpose of the study,a real dataset of the relief times of 20 patients receiving an analgesic is used.

液力变矩器叶轮能容定向优化反设计方法

为提升液力变矩器性能的同时优化内部流场载荷分布,在对变矩器叶片设计过程中通过对泵轮动力载荷的合理设计,采用反设计方法并基于流场特性对变矩器能容性能进行定向设计,通过优化叶片形状增大液力元件的能容,同时改善流场平顺性。设计结果表明,反设计方法使泵轮能容提升了5.2%,同时内流场施加到叶表的载荷幅值下降了4.9%,反设计方法实现了泵轮能容的定向优化设计。

基于散射矩阵的气溶胶识别与粒径分布反演研究

散射矩阵是描述介质散射特性的重要参数,该参数对介质的理化特性敏感。为研究利用该参数对气溶胶进行识别及理化特性获取的可行性,设计并实验测量了聚α烯烃和氯化钠两种气溶胶样品的散射矩阵,讨论了二者矩阵元素的角度分布规律,并基于Mie散射理论,采用模板匹配的方法利用测量结果对聚α烯烃气溶胶的粒径分布进行了反演。结果表明通过矩阵元素的角度分布规律可以对两种气溶胶进行有效识别与区分,结合相关散射模型与反演方法还可以获得气溶胶的理化特性。该研究为气溶胶识别及其理化特性的获取提供了方法参考。

基于GF-5(02)卫星DPC数据的2022年春季陆表细粒子气溶胶光学厚度空间分布

大气细粒子气溶胶主要来源于人类生产生活排放,可以反映人为活动对大气的影响,因此细粒子气溶胶光学厚度(AOD_(f))是大气环境领域重要的基础大气参数之一。本研究基于查找表反演方法,利用高光谱观测卫星[GF-5(02)]多角度偏振成像仪(DPC)数据,得到2022年春季(3&5月)的全球陆表AOD_(f),并通过AERONET对反演结果进行了初步验证。对AOD_(f)的分析结果表明:1)全球陆表AOD_(f)分布呈现明显的南北差异,南半球基本为低值,北半球的高值区域主要集中在亚洲地区;2)中国地区陆表AOD_(f)在“胡焕庸线”两侧差别显著,东南侧的高值主要集中在川渝腹地、华北平原和两广地区,而西北侧基本表现为低值覆盖,人为和自然因素均对AOD_(f)的分布有一定的影响;3)南亚地区和非洲中-北部的AOD_(f)分布与当地燃烧活动产生的烟尘以及季风环流等因素有一定的相关性。此外,DPC的AOD_(f)数据与MODIS细粒子产品的对比结果表明二者的AOD_(f)高值区域分布基本一致,而DPC在高亮地表有着更为完整的反演结果,可以为全球和重点区域的大气环境监测提供支持。

基于混合Lanczos-Tikhonov算法的绝缘子表面电荷反演计算

表面电荷反演计算是表面电荷密度分布测量的重要环节。该文针对盆式或锥形绝缘子这类平移变化系统,引入迭代正则化方法,提出了基于Lanczos双对角化与Tikhonov正则化算法混合方法的表面电荷反演算法。通过Lanczos双对角化将电位-电荷之间的矩阵运算投影至维数更小的子空间后,应用Tikhonov正则化求解子空间投影最小二乘问题,大大减小了矩阵的计算量;同时引入自适应加权广义交叉验证(A-WGCV)方法选择正则化参数;结合仿真算例讨论了该算法的实现过程以及计算精度,并与视在电荷法及维纳滤波法进行了对比;最后,通过粉尘图法验证了该算法的准确性和可靠性,并结合粉尘图像和算法反演两种方法获取了针电极下不同电压等级下的电荷分布。

辽宁东鞍山铁矿三维地质建模与深部找矿应用

为查明东鞍山铁矿多种类型矿体的空间形态和矿物组分的空间分布情况,指导矿山开展深部找矿工作,基于矿区水平断面与钻孔数据等地质资料,依托3DMine平台,采用三维地质建模和距离幂次反比法分别建立研究区矿体模型和品位分布模型。在三维模型基础上,结合矿床成因和矿体分布规律,基于“相似类比”和“地质异常”两种矿床勘查理论,提取找矿预测要素,开展深部找矿应用,在矿区深部圈定找矿靶区2处,拓宽了东鞍山铁矿深部找矿空间。

采用PSO算法的页岩气水平井DTS数据反演方法

为了实现页岩气水平井产出剖面、人工裂缝参数、压裂改造区缝网渗透率等多维未知参数的定量解释,提出了采用粒子群优化算法(Particle Swarm Optimization,PSO)的页岩气水平井分布式光纤温度传感(Distributed Temperature Sensing,DTS)数据反演方法。该方法由温度剖面正演预测模型和PSO算法组成,其中温度剖面正演预测模型用于每一步反演迭代中模拟页岩气水平井温度剖面,PSO算法则是在每一步迭代计算中优化更新产出剖面、裂缝参数等未知参量,进而逐渐减小模拟的温度剖面与实测DTS数据之间的误差,直至收敛。一口现场井的应用结果表明,预测的温度剖面与实测DTS数据吻合较好,各有效人工裂缝位置处的绝对温度偏差小于0.03℃;产出剖面反演结果与现场PLT(Production Logging Tool,生产测井工具)测试产量相吻合,单压裂段流量最大偏差仅0.291×10^(4)m^(3)/d,验证了该方法的可靠性。该方法可为进一步实现均衡产出剖面、提高单井产量提供依据。