2-D IMAGE-BASED VOLUMETRIC MODELING FOR PARTICLE OF RANDOM SHAPE

In this paper, an approach to predicting randomly-shaped particle volume based on its two- Dimensional （2-D） digital image is explored. Conversion of gray-scale image of the particles to its binary counterpart is first performed using backlighting technique. The silhouette of particle is thus obtained, and consequently, informative features such as particle area, centroid and shape-related descriptors are collected. Several dimensionless parameters are defined, and used as regressor variables in a multiple linear regression model to predict particle volume. Regressor coefficients are found by fitting to a randomly selected sample of 501 panicles ranging in size from 4.75mm to 25ram. The model testing experiment is conducted against a different aggregate sample of the similar statistical properties, the errors of the model-predicted volume of the batch is within ±2%.

Effect of Quadrat Shape on Spatial Point Pattern Performance of Haloxylon ammodendron

In this study, we investigated the natural growth of Haloxylon ammodendron forest in Moso Bay, southwest of Gurbantunggut Desert. Random sample analysis was used to analyze the spatial point pattern performance of Haloxylon ammodendron population. ArcGIS software was used to summarize and analyze the spatial point pattern response of Haloxylon ammodendron population. The results showed that: 1) There were significant differences in the performance of point pattern analysis among different random quadrants. The paired t-test for variance mean ratio showed that the P values were 0.048, 0.004 and 0.301 respectively, indicating that the influence of quadrat shape on the performance of point pattern analysis was significant under the condition of the same optimal quadrat area. 2) The comparative analysis of square shapes shows that circular square is the best, square and regular hexagonal square are the second, and there is no significant difference between square and regular hexagonal square. 3) The number of samples plays a decisive role in spatial point pattern analysis. Insufficient sample size will lead to unstable results. With the increase of the number of samples to more than 120, the V value and P value curves will eventually stabilize. That is, stable spatial point pattern analysis results are closely related to the increase of the number of samples in random sample square analysis.

Wave Pressure Acting on V-Shaped Floating Breakwater in Random Seas

Wave pressure on the wet surface of a V-shaped floating breakwater in random seas is investigated. Considering the diffraction effect, the unit velocity potential caused by the single regular waves around the breakwater is solved using the finite-depth Green function and boundary element method, in which the Green function is solved by integral method. The Response-Amplitude Operator(RAO) of wave pressure is acquired according to the Longuet-Higgins' wave model and the linear Bernoulli equation. Furthermore, the wave pressure's response spectrum is calculated according to the wave spectrum by discretizing the frequency domain. The wave pressure's characteristic value corresponding to certain cumulative probability is determined according to the Rayleigh distribution of wave heights. The numerical results and field test results are compared, which indicates that the wave pressure calculated in random seas agrees with that of field measurements. It is found that the bigger angle between legs will cause the bigger pressure response, while the increase in leg length does not influence the pressure significantly. The pressure at the side of head sea is larger than that of back waves. When the incident wave angle changes from 0? to 90?, the pressure at the side of back waves decreases clearly, while at the side of head sea, the situation is more complicated and there seems no obvious tendency. The concentration of wave energy around low frequency(long wavelength) will induce bigger wave pressure, and more attention should be paid to this situation for the structure safety.

基于波前整形和自适应光学的水下可见光通信系统

为了解决水下可见光通信中复杂的水下湍流、散射环境对光束造成的畸变而导致信号传输失败的问题,使用随机相位屏方法模拟了水下湍流信道,在发射端对光束进行波前整形实现远距离聚焦,接收端使用自适应相位恢复算法对接收端光斑进行恢复。在1.2 m水下实验平台使用比特功率加载技术发射离散多音信号(discrete multi-tone, DMT)信号测量接收光功率与数据传输速率的对应关系,基于此,预测了100 m湍流环境下可见光信号的传输速率,与经过波前整形以及自适应相位恢复后的结果对比得到,所提出的方法可以使得水下可见光系统的传输速率得到极大提升。

基于随机森林算法的山东省区域臭氧污染事件中气象条件和排放贡献影响研究

山东省作为我国东部的工业大省,近年在经济快速发展的同时也面临着严重的臭氧(O_(3))污染;在不利气象条件的影响下,发生过多次影响范围大、持续时间长的O_(3)污染事件.因此,如何基于地面观测数据剥离气象条件及排放的影响,成为O_(3)污染防控政策评估和政策制定中的重要问题.为此,本研究基于2020−2022年山东省地面国控监测站点O_(3)浓度逐时观测数据及对应气象数据,运用随机森林模型对气象条件和排放的贡献进行了剥离;基于沙普利加和模型,定量分析了各气象因子对O_(3)污染的影响;此外,研究中定义了区域O_(3)污染事件,并对事件期间气象条件及排放的影响进行了深入的对比分析.结果表明:2020−2022年山东省3个亚区域O_(3)前体物排放影响呈逐年上升趋势,年变化速率分别为3.3%(鲁西)、7.8%(鲁中)和4.4%(鲁东),2020年和2021年气象条件有利于高浓度O_(3)的消减,导致O_(3)年均浓度下降2.27~8.26μg/m^(3),属于“天帮忙”;而2022年气象条件相对不利,气象条件贡献了O_(3)年均浓度的5.16~10.69μg/m^(3).排放对O_(3)浓度的相对贡献在24个O_(3)区域污染期间与非污染期间较为一致,不利的气象条件是O_(3)污染形成的主要诱因.在各气象因子中,温度和相对湿度是影响O_(3)浓度最主要的气象因素,其中温度的影响最为显著,对O_(3)小时浓度的贡献为33.36~89.61μg/m^(3).研究显示,2020−2022年山东省O_(3)前体物排放贡献的年际变化差异不显著,不利气象条件则是造成O_(3)污染的重要因素,后续应更加重视在高温低湿条件下的O_(3)污染防控工作.

扩展目标多特征估计自适应渐进滤波器

针对具有不规则形状的扩展目标跟踪(Extended Target Tracking,ETT)问题,本文提出了一种基于随机超曲面模型的自适应渐进贝叶斯滤波器(Random Hypersurface Model-Adaptive Progressive Bayesian Filter,RHMAPBF).首先,对扩展目标连续状态先验概率密度的局部累积分布进行随机采样,再最小化连续概率密度和狄拉克混合概率密度的局部累积分布之间的修正克莱默冯米塞斯距离得到粒子的最优位置,以自适应地变步长进而渐进更新将粒子迁移到扩展目标后验的密集区域求得更加准确的后验概率密度近似;其次,利用随机超曲面描述任意星凸形扩展目标的量测源分布,提出了星凸形不规则形状扩展目标跟踪自适应渐进滤波器,有效实现了不规则形状扩展目标多特征概率密度信息的递归.最后通过不同噪声水平以及复杂随机环境的扩展目标(Extended Target,ET)和群目标(Group Target,GT)的跟踪仿真实验验证本文方法的有效性.

基于随机超曲面模型的机动星凸形扩展目标跟踪

针对具有强机动性的扩展目标跟踪问题,不仅需要估计目标的运动状态,还要准确识别目标机动过程中的形状变化。由于目标机动和模型的复杂所导致的高维非线性问题,提出了一种基于随机超曲面模型的扩展目标方向自适应跟踪算法。通过使用输入估计检测器对目标机动进行判断,再利用目标机动的大小修正形状参数的先验,其次基于先验信息更新量测,并结合无迹卡尔曼滤波算法,实现对机动扩展目标的状态跟踪和形状识别。利用均方根误差和quasi-Jaccard距离分别对目标质心位置的跟踪质量和形状的跟踪性能进行评价。仿真实验结果证明了该算法的有效性。

随机森林算法在超声缺陷识别中的应用研究

超声波检测是一种常见的钢材缺陷检测方法,通过机器学习算法建立分类模型能够实现有效的缺陷识别。神经网络是目前最常采用的一种算法,但存在模型结构复杂且需要大量训练数据的问题。对此,提出一种基于随机森林的超声缺陷识别方法,能够实现对缺陷类型的智能、准确识别,以解决模型结构复杂和训练数据需求大的问题。首先对方体试件中的不同形状、尺寸和深度的缺陷进行超声检测实验,基于实验数据利用随机森林算法建立超声缺陷识别模型;进而对模型的缺陷识别效果进行分析,并与支持向量机、K-近邻分类算法、AdaBoosting算法和卷积神经网络比对分析缺陷识别效果;然后利用验证试件进行缺陷识别验证实验,以进一步验证所建立缺陷识别模型的有效性。结果表明,所提缺陷识别方法相比其他算法具有最高的准确率,验证实验中缺陷分类准确率达到94.6%。

某型航空导叶作动筒振动性能仿真分析

针对航空导叶作动筒在复杂工况下的损坏问题,为在设计阶段预测产品可能出现的损坏,获取导叶作动筒标准载荷下的易损位置,利用有限元仿真建模方法建立了该型作动筒的模态分析、谐响应分析、随机振动分析与疲劳分析仿真模型。通过对数正弦扫频试验验证了模态分析仿真模型的准确性,获得了振型、固有频率与功率谱载荷下的应力响应等信息。考虑作动筒活塞的轴向伺服工作影响,在标准功率谱上叠加伺服工作正弦载荷模拟了该工况。建立随机振动情况下的疲劳寿命分析仿真模型,活塞与活塞密封圈的疲劳寿命结果在可接受范围内,为该航空作动筒结构优化设计提供了依据。

基于随机森林预测的矩形消力井体型

泄水建筑物出口无法正对河道,地形条件难以满足传统底流消能的池长要求时,增加池深与池宽形成矩形消力井是一种可行的选择。基于水工模型试验数据,通过随机森林算法底板动水压强预测模型,研究入射水流动能变化条件下的矩形消力井体型。研究结果表明:预测模型可以得到矩形消力井几何边界重要程度,从大到小依次为井深、井长、井宽;进而给出了不同傅汝德数入射水流适宜井宽条件下,底板动水压强能够满足消能要求的井深、井长组合关系;在分析入射水流动能(傅汝德数)所对应的多组消能水体容积基础上,得出了满足消能效果的最小消能水体容积和边界取值。

Analyses of egg size,otolith shape,and growth revealed two components of small yellow croaker in Haizhou Bay spawning stock

The geographical variations in life history characteristics of small yellow croaker Larimichthys polyactis, caused by experienced different environmental conditions, have been observed in China seas. Previous studies based on spatial distribution, migration route, and body morphometrics suggested a complex stock structure. In this study, to clarify the source of a spawning stock, we investigated the reproduction strategy and inter-structure of the Haizhou Bay (HZB) spawning stock in the middle Yellow Sea from both egg survey and adult otolith increment analysis. Egg and adult samples were collected from three surveys during spawning season in 2013. Distinct spatial and temporal variations were detected in egg distribution and size, and otolith shape analysis of adult fishes revealed two morphotypes with different increment growth using random forest cluster. The results indicate the existence of two components within the same spawning stock in HZB from different wintering grounds, and accordingly special protection should be required for this stock given the significance to maintain connectivity between adjacent subpopulations.

多轴随机振动下制动器防尘罩失效分析与优化

针对某型商用车制动器防尘罩提前失效的问题,采用基于实测载荷谱的数值仿真与试验验证相结合的方法,准确识别了失效原因,并提出寿命提升的优化改进方案。首先,分析防尘罩失效部位断口的微观形貌,确定失效机理;其次,结合防尘罩结构的模态分析与基于实测道路载荷谱的随机振动应力响应分析,识别结构失效原因;然后,考虑随机载荷多轴耦合特性,通过分析失效主导载荷,制定单轴高加速试验载荷谱,通过加速试验验证仿真分析结果的准确性;最后,通过形状优化给出防尘罩的寿命提升方案,并采用数值仿真进行了验证。结果表明:基于实测载荷谱的数值仿真与主导载荷下的高加速试验对防尘罩结构的失效分析吻合度良好,并与耐久试验结果一致,形状优化后的防尘罩寿命提升显著。该方法可为实际工况下多轴随机振动载荷作用的结构失效分析与优化提供参考依据。

基于车桥接触点响应的桥梁振型与损伤识别研究

以过桥车辆为桥梁动态特性的信息载体对桥梁进行监测,避免了利用动载试验测量桥梁模态参数而存在的成本高、操作复杂等缺陷。基于车辆与桥梁之间的耦合作用,结合中心差分方法得到车辆与桥梁的接触点加速度,利用变分模态分解与希尔伯特变换获得桥梁的各阶分量响应,并重构振型。以某一简支梁桥为例,研究车速、路面粗糙度、随机交通等参数对振型识别的影响,利用重构的一阶振型结合曲率模态法对桥梁的损伤定位进行了探索。结果表明:路面粗糙度对振型识别不利,通过加入一辆伴随车辆激励桥梁能较为精确地识别出A级粗糙度下桥梁的前三阶振型。由于随机交通的存在,量测车采集到的加速度信号中包含交通流中车辆的频率信息,但重构的振型仍可以满足工程精度。当量测车的行驶速度较低时,信号数据中包含的桥梁模态信息丰富,重构的一阶振型具有较高的分辨率,结合曲率模态法可以准确地定位桥梁的损伤。

Mechanisms of Cup-Shaped Vesicle Formation Using Amphiphilic Diblock Copolymer

A cup shape is a dynamic morphology of cells and organelles. With the aim of elucidating the formation of the biotic cup-shaped morphology, this study investigated cup-shaped vesicles consisting of an amphiphilic diblock copolymer from the aspect of synthetic polymer chemistry. Cup-shaped vesicles were obtained by the polymerization-induced self-assembly of poly(methacrylic acid)-block-poly(n-butyl methacrylate-random-methacrylic acid), PMAA-b-P(BMA-r-MAA), in an aqueous methanol solution using the photo nitroxide-mediated controlled/living radical polymerization technique. Field emission scanning electron microscopic observations demonstrated that the cup-shaped vesicles were suddenly formed during the late stage of the polymerization due to the extension of the hydrophobic P(BMA-r-MAA) block chain. During the early stage, the polymerization produced spherical vesicles rather than a cup shape. As the hydrophobic block chain was extended by the polymerization progress, the spherical vesicles reduced the size and were accompanied by the generation of small particles that were attached to the vesicles. The vesicles continued to reduce the size due to further extension of the hydrophobic chain;however, they suddenly grew into cup-shaped vesicles. This growth was accounted for by a change in the critical packing shape of the copolymer due to the hydrophobic chain extension. These findings are helpful for a better understanding of the biotic cup-shaped vesicle formation.

S形空间曲线顶管开挖引起的地表沉降计算——以宁波市潘桥变电站迁建工程为例

为研究S形空间曲线顶管隧道施工引起的地表沉降规律,基于Mindlin弹性力学解和随机介质理论,构建S形空间曲线顶管施工引起的地表沉降计算模型,获得顶管施工各参数和空间曲线段施工地层损失引起的沉降规律,并与宁波市潘桥变电站顶管隧道工程地表沉降实测值进行对比验证。研究结果表明:1)考虑顶管施工引起的附加荷载、水平与竖向超挖间隙等因素所构建的S形空间曲线顶管施工引起的地表沉降计算方法,理论计算值与实测值吻合较好,能够对地表沉降进行较为准确的预测;2)空间曲线顶管施工引起的地表沉降槽不以顶管中心轴线对称,在顶管机头无超挖刀参与掘进的情况下,最大沉降值向弯道外侧偏移,且顶管机平面转弯产生的超挖间隙对沉降槽偏移影响最大;3)在S形空间曲线顶进时,地层损失是造成地表沉降的主要原因,应严格控制注浆参数,理论注浆量应包括环形空隙与超挖间隙注浆量体积之和。

QFP焊点形态模拟及随机振动疲劳寿命预测

针对电子设备中翼型焊点的振动可靠性问题,介绍了电子设备元器件焊点在随机振动载荷下的仿真分析的通用方法。通过Surface Evolver软件得到了某机载电子设备元器件焊点的形态预测模型,然后结合Hypermesh将模型导入到ABAQUS有限元软件中完成有限元模型搭建;在有限元软件中,对模型加载随机振动载荷,采用Steinberg模型,结合Manson高周疲劳经验公式及Palmgren-Miner线性疲劳损伤累计准则;得到了焊点随机振动载荷下的可靠性寿命,研究成果对电子设备元器件焊点的失效分析具有实用价值。

Local Radial Basis Function Methods: Comparison, Improvements, and Implementation

Radial Basis Function methods for scattered data interpolation and for the numerical solution of PDEs were originally implemented in a global manner. Subsequently, it was realized that the methods could be implemented more efficiently in a local manner and that the local approaches could match or even surpass the accuracy of the global implementations. In this work, three localization approaches are compared: a local RBF method, a partition of unity method, and a recently introduced modified partition of unity method. A simple shape parameter selection method is introduced and the application of artificial viscosity to stabilize each of the local methods when approximating time-dependent PDEs is reviewed. Additionally, a new type of quasi-random center is introduced which may be better choices than other quasi-random points that are commonly used with RBF methods. All the results within the manuscript are reproducible as they are included as examples in the freely available Python Radial Basis Function Toolbox.

任意形状工作面沉陷预计计算方法

为弥补现有任意形状工作面沉陷预计计算方法存在的不足,更加准确地预计煤炭开采引起的地表移动和变形,基于概率积分法理论,将工作面按照角点划分为若干梯形,再利用变步长Simpson二重积分法在各梯形区域按预计公式进行积分计算,最后将各梯形单元产生的影响进行叠加处理,实现了任意形状工作面的沉陷预计计算。另外,通过研究拐点偏移距对工作面位置的影响,探讨了任意形状工作面实际计算边界角点坐标的解算方法。在此基础上设计、开发了开采沉陷预计程序,实现了地表移动变形预计、预计结果分析及可视化输出。以某矿区实际开采工作面为例,对计算方法及预计程序进行了验证。结果表明:程序设计合理,预计结果准确可靠,符合实际情况,能够满足大范围沉陷预计的需要,可为"三下"采煤、土地复垦规划提供必要的技术支持。

加速混合遗传算法在搜索边坡最危险滑动面中的应用

基于简化Janbu条分法,提出一种加速混合遗传算法,在无需对边坡最危险滑动面的几何形状进行假设的前提下,自由搜索最危险任意形状滑动面,并计算其对应的最小安全系数。该方法是通过把无约束优化的Powell算法作为一个与遗传算法的选择、交叉和变异平行的算子,嵌入到改进的实数编码遗传算法中而得到的,它同时具有两种方法的优点:(1)有较强的自适应能力,使得收敛速度加快;(2)还有可能搜索到最优化问题的全局最优解。首先通过一算例验证加速混合遗传算法的准确性,然后应用于一工程实例。与现场勘察结果对照表明,加速混合遗传算法搜索到的最危险滑动面与实际情况吻合得很好,优于简单遗传算法。

堆石料碾压试验的颗粒流模拟新方法

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