韦伯分布布谷鸟搜索算法颗粒粒径分布反演

韦伯分布在非线性寻优问题中具有较好的寻优精度和全局搜索能力,为此提出一种基于韦伯分布的布谷鸟搜索（WCS）算法来解决颗粒粒径分布反演的问题。使用WCS算法对服从Johnson’s S_B分布、Rosin-Rammler分布和正态分布的单峰颗粒系和双峰颗粒系进行颗粒粒径分布的反演,并分别与其他传统算法的处理结果进行比较。结果表明,WCS算法的整体效果优于人工鱼群算法和人工蜂群算法,且改进后的4种重尾分布CS算法的标准差比原CS算法提升2～3个数量级。目标函数散射光能加入噪声后,WCS算法比其他三种重尾分布的相对均方根误差值至少可降低1/2。使用小角前向散射测量系统对单峰颗粒系和双峰混合颗粒系进行实验研究,发现WCS算法的相对均方根误差比原CS算法降低约为40%。     

非球形颗粒系粒径分布的机器学习反演算法

动态光散射技术在微米与亚微米级颗粒系粒径分析领域中具有广泛应用,但缺乏非球形颗粒系粒径分布（PSD）的反演模型和算法,限制了其在生物医疗等领域中的应用。基于机器学习方法,设计了基于广义回归神经网络（GRNN）的PSD反演模型和算法,可应用于多角度动态光散射法的粒径分析场景中。以生物医疗领域中的双凹圆饼形和椭球形血红细胞作为典型的非球形颗粒物模型,通过仿真实验测试了所设计的算法。实验结果表明,与传统的正则化Tikhonov算法相比,所设计的反演算法粒径分析准确性更好且耗时更短。对多角度动态光散射法中的散射角度数量进行了仿真实验。结果表明,仅使用2个散射角度处获得的数据依然能实现非球形颗粒系粒径分布的准确反演。     

火焰喷雾热解合成ZrO2纳米颗粒的大涡–群平衡Monte Carlo(LES-PBMC)模拟

本文基于OpenFoam平台开发的非线性大涡模拟–部分搅拌反应器(NLES-PaSR)模型,对FSP湍流喷雾燃烧火焰进行LES模拟,并首次发展了高效的多维群平衡蒙特卡洛(PBMC)方法,对FSP过程中ZrO2纳米颗粒的时空演化过程进行描述。结果表明,FSP是一个剧烈的强湍流燃烧过程,在周围稳燃火焰的影响下,其火焰温度具有两个峰值,且三种动力学事件的发生速率均在第一个温度峰值(HAB=0.012 m)达到最大。随着颗粒在火焰中的迁移及停留时间的增加,颗粒粒径逐渐增大。三种动力学事件之间的相互竞争关系以及颗粒在流场中的迁移行为,共同影响着火焰中颗粒尺寸、形态的演变。     

颗粒链在振动条件下的行为研究

采用实验方法研究打结颗粒链在外部激振下解结过程与激振源以及颗粒链长度的关系.实验结果表明颗粒链结解开所需的时间与振动频率有关,颗粒链解结存在截止频率和最佳振动频率;颗粒链解结时间与链长之间呈非线性关系.同时采用Monte Carlo时步模拟的方法,对珠链解结的动力学模型进行仿真.     

梯度场中荧光关联谱测量的Monte Carlo模拟

荧光关联谱（FCS）利用少量分子的荧光涨落获得分子运动和反应信息,是一种探测活细胞内生物过程的有力工具。本文利用Monte Carlo方法模拟激光梯度场下瑞利粒子的布郎运动,分析梯度场对FCS测量得到的扩散时间、粒子数等参数的影响,模拟与初步实验结果定性吻合。文中还讨论了Monte Carlo模拟预测的一些实验现象。     

重力场中理想气体密度分布的 Monte Carlo 模拟

利用Monte Carlo 方法模拟了重力场中理想气体的密度分布,直观展现了重力场中气体分子位置的改变和分布特点,讨论了分子质量和系统温度对气体密度分布曲线以及重力势能零点处密度n0的影响.模拟结果与玻耳兹曼分布律完全吻合.另外,模拟结果表明玻耳兹曼分布律不仅对纯的理想气体成立,而且对混合理想气体中各成分气体也成立.     

颗粒粒径分布测量反演算法的改进

综合奇异值截断法、奇异值修正法、Tikhonov正则化思想及Chahine迭代算法,提出一种改进的病态问题求解算法来测量颗粒系的粒径分布。结合Backus-Gilbert折中准则与奇异值最小原则确定了奇异截断值,采用L曲线法确定了最优正则化参数,并利用联合迭代反演法(SIRT)实现解的非负约束。模拟及实验结果表明,该算法对单、双峰分布的测量误差均小于3%,其抗噪性能、测量准确性、时效性及粒径测量范围相较其他反演算法都有明显优势。     

粒径对激光驱动颗粒溅射动力学特征的影响

激光脉冲辐照材料靶面产生的等离子体的演化过程会对靶面施加一脉冲式冲击压.当被辐照的靶材为离散颗粒堆积物时,激光冲击压在靶面能够驱动颗粒发生溅射现象.本文选用中值直径分别为84, 109, 184,234μm且具有窄粒径分布的干燥石英砂堆积形成离散颗粒靶,并采用波长为1064 nm的Nd:YAG纳秒激光脉冲与其相互作用产生的冲击压驱动石英颗粒发生溅射,同时通过高速摄像机记录溅射过程,研究了粒径对激光驱动颗粒溅射动力学特征的影响.通过分析高速影像发现,激光驱动的颗粒溅射在时间尺度上可以分为两个特征明显的过程,即持续百微秒垂直于靶面方向的快速早期溅射过程和持续几十毫秒扇形颗粒帘结构的慢速后期溅射过程.前者对应的颗粒出射动能呈现出了随粒径的增加而增大的趋势,后者对应的沿径向扩张的帘底直径D随时间t的演化规律遵循点源模型的描述:D(t)=αt~β,系数α的拟合值随粒径的增加而减小,幂指数β的拟合值却呈现出了随粒径增加而增大的趋势.通过细致考虑粒径依赖的颗粒在气流中的冲量耦合效率,以及粒径依赖的激光与颗粒靶相互作用产生的等离子体特征,对以上实验观察给予了合理的解释.本研究加深了人们对激光驱动颗粒溅...     

不同粒径街道灰尘中Zn的分布特征

在宿州市城区采集23个街尘样品,利用X射线荧光光谱法(XRF)测定了4个粒径区间(250-500、150-250、75-150μm和＜75μm)街尘中的Zn含量,并利用单因子指数法评价了宿州市街尘Zn污染状况.结果发现:宿州市街尘Zn含量在各粒径区间存在明显差异,其中以＜75μm和75-150μm粒径段的含量最高,说明...     

Analysis of Particle Size Distribution by Particle Tracking

Particle tracking is performed using a combination of dark field or fluorescence video microscopy with automatic image analysis. The optical detection together with the image analysis software allows for the time resolved localization of individual particles with diameters between 100 and 1000 nm. Observation of their Brownian motion over a set of time intervals leads to the determination of their mean square displacements under the given room temperature and viscosity. Hereby, the radii of a set of particles visible within a given optical frame are derived simultaneously. Rapid data analysis leads to reliable particle size histograms. The applicability of this method is demonstrated on polystyrene latices and PMMA nanospheres with radii between 51 nm and 202 nm.     

Monte Carlo Simulations of Reflected Spectra Derived from Tissue Phantom with Double-Peak Particle Size Distribution

We made a tissue phantom with double-peak particle size distribution, which has polystyrene particles of cell nuclear size and mitochondrial size, and measured the spectrum from the tissue phantom using a single optical fiber. In this paper we investigate the characterization method for the tissue phantom with double-peak particle size distribution by comparing the measured spectra with the calculated ones using the Monte Carlo (MC) method. It is first shown that the Mie phase function characterizes better than the Henyey-Greenstein (H-G) phase function in MC calculation. Next, we compare the measurement spectra with those obtained by modeling as single-peak, conventional modeling for particle size distribution, and for double-peak particle size distribution. The single-peak modeling is found to cause considerable error for the tissue phantom with double-peak particle size distribution, which seems to simulate a biological tissue. We suggest that if one simulates the particle size distribution of a biological tissue by conventional modeling, the accuracy of estimation will be lower.     

Particle Size Distribution Retrieval from Elastic Light Scattering Measurements by a Modified Regularization Method

Retrieval of polymeric emulsions Particle Size Distribution (PSD) from Elastic Light Scattering (ELS) measurements requires the solution of an ill conditioned inverse problem. In this paper we compare the performance of classical regularization methods such as Truncated Singular Value Decomposition and Tikhonov's, to a regularization technique due to Pike that includes positivity constraints on the PSD. We also propose a new method that combines Tikhonov's approach with Pike's method. Simulated ELS measurements for two polymeric materials were generated under different experimental noise assumptions. Uncertainties on the polymer refractive index value were also considered. The PSD estimations obtained show that the implementation of the proposed more sophisticated algorithm is convenient for this very ill‐conditioned problem.     

Measurements on Particle Size Distribution and Concentration by Transmission Fluctuation Spectrometry with Temporal Correlation

Transmission fluctuation spectrometry with temporal correlation (TFS‐TC) is a new method for particle analysis. When a narrow light beam irradiates on a particle dispersion flow, the variation of the number of particles in the small measuring zone will cause the transmitted light to fluctuate, which includes the complete information on both particle size distribution (PSD) and particle concentration. The method may be used for real‐time, inline/online applications due to its simplicity of measuring principle and experimental setup. Until recently, the theory has been limited to low particle concentrations. In this work, an experimental study of the TFS‐TC measurement is presented for a very wide range of the particle concentrations. By introducing an empirical correction including the high concentration effects and considering the effect from rheological conditions in the inversion algorithm, the particle size distribution and particle concentration are reconstructed, resulting in the coverage of a broad range of particle size and concentration.     

DCC Size Effects on Pion Spectrum Distribution

The effects of two kinds of coherent lengths, the wave packet length of the emitter and the radius of the coherent source, on pion spectrum distribution are studied. It is shown that both coherent lengths can cause abundant pions at low momentum. Observing abundant pions at low momentum may be taken as a signal of DCC effects.     

Calculation of Particle Size Distributions from Ultrasonic Measurements: A Mineral Slurry Case Study

Ultrasonic transmission measurements have been used extensively to determine the particle size of solids in slurries. This case study examines the application of mathematical inversion techniques to the determination of the particle size distribution of a mineral slurry from data collected at a minerals processing plant. A new mathematical inversion technique, based on an extension of modified Chahine iteration combined with the principle of maximum entropy has been developed. Four algorithms were constructed and used to calculate particle size distributions from synthetic and raw plant data. These incorporated modified Chahine iteration and its extension, together with two different approaches to applying a density measurement constraint on the particle size distribution. In general the algorithms performed well with regression errors below 3 %. The correlation coefficients and slopes for this technique were 0.86 and 1.35 for the weight fraction of particles less than 75 microns when compared with the laser diffraction analysis. A better match was obtained for the plant data by using the new inversion technique, into which the principle of maximum entropy has been incorporated whereas this was not the case with the synthetic data, illustrating the need to match the inversion technique to the problem.     

非独立模式算法下粒径分布反演及分类的研究

在光全散射法颗粒粒径测量中,提出一种非独立模式算法下粒径分布反演及分类的方法。对被测颗粒系分别按照不同的粒径分布函数同时进行反演,并依据反演误差大小判断被测颗粒系符合哪种分布函数。仿真实验结果表明,在非独立模式下,完全可以利用已知的不同分布函数的反演误差作为分类依据,从而更准确地确定被测颗粒系的粒径分布。采用的遗传反演算法能够在3个可见光波长下得到较准确的粒径分布,反演结果稳定可靠,最大限度地减少了多个波长的使用,从而对光源有更大的选择余地。对透射消光测量结果加入5%随机噪声时,单峰分布颗粒系的反演误差小于5%,多峰分布颗粒系的反演误差小于10%。整个算法运行时间小于2 s。该方法具有原理简单,计算速度快等优点,能够满足颗粒粒径在线测量的要求。     

A Comparative Study of Various Size Distribution

One of the major product specifications of a crystalline material is the crystal size distribution (CSD). In order to monitor and control the CSD in an industrial crystallization process, on‐line sensors are required. Over the years, a number of techniques to measure the CSD have been established. In this paper, three instruments operated in an on‐line fashion and an off‐line method are compared. The instruments were the OPUS, a HELOS/VARIO (both manufactured by Sympatec) and a Malvern 2600c (manufactured by Malvern). They were implemented on an 1100‐l evaporative draft tube baffle (DTB) crystallizer producing ammonium sulfate crystals from aqueous solution. Samples from this crystallizer were also analyzed offline by wet sieving. The results show reasonably good agreement between the different on‐line techniques and the wet sieving technique concerning the shape of the distribution. However, there is a discrepancy regarding the absolute values, which can be explained by the fact that the techniques used are based on different measuring principles.     

Particle Size Distribution of Nanospheres by Monte Carlo Fitting of Small Angle X‐Ray Scattering Curves

A method for recovering the size distribution of spherical particles from small angle scattering data by using a Monte Carlo interference function fitting algorithm is presented. The method is based on the direct simulation of the small angle scattering data upon the assumption of non‐interacting hard sphere ensembles (“dilute” solution approximation). The algorithm for retrieving the particle size distribution does not require any additional parameters apart from the input of the scattering data. The fitting strategy necessarily implies positive particle size distributions, while preserving the advantage of the indirect transformation method for data desmearing. Furthermore, the present approach does not use any regularisation procedures of the best fit solution and favours smooth particle size distributions. The Monte Carlo procedure has been tested against several simulated cases with various types of mono‐ and bi‐modal size distributions and different noise levels. In the special case of non‐interacting spheres, the Monte Carlo fitting algorithm had the same retrieving ability as the well assessed indirect transformation, structure interference and maximum entropy methods. Finally, the algorithm was applied to retrieve the distribution of spherical nanopowders produced by gas‐to‐particle conversion both as free powder and as reinforcing second‐phase agent in polymer nanocomposites.