42 resultados para Newton, Willliam


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Density gradient ultracentrifugation (DGU) has emerged as a promising tool to prepare chirality enriched nanotube samples. Here, we assess the performance of different surfactants for DGU. Bile salts (e.g., sodium cholate (SC), sodium deoxycholate (SDC), and sodium taurodeoxycholate (TDC)) are more effective in individualizing Single Wall Carbon Nanotubes (SWNTs) compared to linear chain surfactants (e.g., sodium dodecylbenzene sulfonate (SDBS) and sodium dodecylsulfate (SDS)) and better suited for DGU. Using SC, a narrower diameter distribution (0.69-0.81 nm) is achieved through a single DGU step on CoMoCAT tubes, when compared to SDC and TDC (0.69-0.89 nm). No selectivity is obtained using SDBS. due to its ineffectiveness in debundling. We assign the reduce selectivity of dihydroxy bile salts (S DC and TDC) in comparison with trihydroxy SC to the formation of secondary micelles. This is determined by the number and position of hydroxyl ( OH) groups on the a-side of the steroid backbone. We also enrich CoMoCAT SWNT in the 0.84-0.92 nm range using the Pluronic F98 triblock copolymer. Mixtures of bile salts (SC) and linear chain surfactants (SOS) are used to enrich metallic and semiconducting laser-ablation grown SWNTs. We demonstrate enrichment of a single chirality, (6,5), combining diameter and metallic versus semiconductillg separation on CoMoCAT samples.

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A three-dimensional MHD solver is described in the paper. The solver simulates reacting flows with nonequilibrium between translational-rotational, vibrational and electron translational modes. The conservation equations are discretized with implicit time marching and the second-order modified Steger-Warming scheme, and the resulted linear system is solved iteratively with Newton-Krylov-Schwarz method that is implemented by PETS,: package. The results of convergence tests arc plotted, which show good scalability and convergence around twice faster when compared with the DPLR method. Then five test runs are conducted simulating the experiments done at the NASA Ames MHD channel, and the calculated pressures, temperatures, electrical conductivity, back EMF, load factors and flow accelerations are shown to agree with the experimental data. Our computation shows that the electrical conductivity distribution is not uniform in the powered section of the MHD channel, and that it is important to include Joule heating in order to calculate the correct conductivity and the MHD acceleration.

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对超音速冷靶的形成机理进行了系统介绍,并利用热力学、流体力学、Newton力学对超音速靶的形成过程和性质参数进行简要推导,并根据推导结果编写程序计算了气体靶的各种参数及其与冷靶喷嘴各种参数的关系,得到了不同实验条件下超音速靶的性质参数,与实验测得的数据吻合很好.最后,依据理论计算和实验结果的验证发现:降低靶气体的初始温度、初始气压及提高抽速,可以有效地减小气体靶的横向动量分散,有利于提高粒子与原子分子碰撞实验中反冲离子动量测量精度.实际中,在综合考虑实验中气体的初始气压的同时,还需要降低靶气体的初始温度,提高气体的抽速.

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We investigate the generalized second law of thermodynamics (GSL) in generalized theories of gravity. We examine the total entropy evolution with time including the horizon entropy, the non-equilibrium entropy production, and the entropy of all matter, field and energy components. We derive a universal condition to protect the generalized second law and study its validity in different gravity theories. In Einstein gravity (even in the phantom-dominated universe with a Schwarzschild black hole), Lovelock gravity and braneworld gravity, we show that the condition to keep the GSL can always be satisfied. In f ( R) gravity and scalar-tensor gravity, the condition to protect the GSL can also hold because the temperature should be positive, gravity is always attractive and the effective Newton constant should be an approximate constant satisfying the experimental bounds.

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协议识别是进行有效的网络管理与控制的重要条件,由于新的P2P软件(以Skype,Emule,BitComet,迅雷为代表)开始使用加密协议和协议伪装等技术手段来防止被网管探测、识别、封堵,传统的根据协议特征码来识别的方式已经难以识别这些软件产生的流量。基于流量特征的P2P协议识别的方法是目前研究的主要方向,将机器学习的理论与模型运用到协议识别领域是发展的一个趋势。通过对传输层数据包(包括TCP和UDP数据包)进行分析,并结合P2P系统所表现出来的流量特征,来识别某个网络流是否属于P2P。这类方法包括:TCP/UDP端口识别技术、网络直径分析技术、节点角色分析技术、协议对分析技术和地址端口对分析技术等,但是其准确性和识别率不如特征码识别。本文就基于半监督聚类的模型运用到识别具体P2P应用的可能性进行了分析与实验,提出了一种基于Newton-Raphson方法学习特征权值矩阵的训练的办法,在依据P2P应用特征选取连接特征的基础上进一步提高系统识别准确率和召回率。在本文的实验环境下,针对具体的BitComet和Emule应用的识别器的识别率和召回率均达到了85%左右,在加密协议的识别上取得了不错的效果。如何优化系统的识别准确率和召回率,提高系统效率是本文重点研究并试图解决的问题,主要包括以下三个方面的成果:一、实验并分析了基于半监督学习的聚类模型在加密P2P应用识别上的效果,同时总结了一套分析P2P协议特征的办法。二、将Newton-Raphson方法引入到连接特征的选取上,将特征权值矩阵用于距离的计算,进一步提高了训练和识别的效果。三、基于KD-Tree的识别器的实现使得整个在线识别过程能在内核的协议层高效实现,有效的控制了系统的计算复杂度。

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Quantitative structure-retention relationship(QSRR) was studied for amines to gas-liquid chromatography on three stationary phases of different polarities with the topological indices A(m) (A(m1), A(m2), A(m3)) and gravitational index GI. The algorithm of "Leaps and Bounds" was performed for selection of the variables. And the multi-regression and the quasi-Newton neural networks were employed for the calculation with better results.

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The extended gravitational index G(Q) and quantum-chemical descriptors were calculated for the relationship analysis of aminoquinolines. An evolutionary algorithm was described for variable selection and building QSAR models. And the quasi-newton neural networks were employed with better results.

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随着人们对能源需求的不断增加,深海海洋油气开发已引起了人们越来越大的兴趣,随之而来的是对海洋构筑物的设计和防护提出了更高的要求。由于在传统的阴极保护工程设计中,大多采用实际测量或经验估计的方法来掌握电位分布规律,很难真实的反映构筑物的实际状态,为了确保安全,往往采用较大的安全系数,不但会造成金属材料的浪费,而且还会在构筑物的局部造成保护不足或过保护。 本文研究了边界元方法(BEM)利用数值仿真技术对阴极保护状态下的海洋构筑物的保护状态进行模拟,从而获得阴极保护状态下的金属材料的电位分布。采用常数单元对于二维问题进行了研究,推导出了边界积分方程的离散化形式,并结合阴极保护环境下的阳极和阴极的极化曲线作为边界条件,建立了线性方程组。采用Newton-Raphson 迭代法和分段拟线性化的方法对边界条件做了线性化处理,应用FORTRAN语言开发出阴极保护的边界元仿真求解程序CPBEM,并利用该程序选择合适的算例进行了验证,结果表明该程序是有效和可行的。 通过管线钢在不同温度海泥埋片的腐蚀失重实验,证明了如果有充足的氧的供给的情况下,温度每增加10oC,腐蚀速度便增加一倍。阴极保护系统数值仿真的精确度最主要的影响因素就是阴极和阳极的极化曲线。而金属材料的极化曲线往往受到多种环境因素的影响,本文系统的讨论了在海泥介质中两种管线钢的腐蚀行为,对管线钢极化行为产生影响的各种环境因素,以及这些因素与金属的腐蚀速度之间的关系。首次将灰关联分析的手段运用到海泥介质的腐蚀,研究了环境因素对于ERW,SML两种管线钢在海泥中的腐蚀速率的影响。

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A numerical analysis of galvanic corrosion of hot-dip galvanized steel immersed in seawater was presented. The analysis was based on the boundary element methods (BEMs) coupled with Newton-Raphson iterative technique to treat the nonlinear boundary conditions, which were determined by the experimental polarization curves. Results showed that galvanic current density concentrates on the boundary of steel substrate and zinc coating, and the sacrificial protection of zinc coating to steel substrate results in overprotection of steel cathode. Not only oxygen reduction but also hydrogen reduction could occur as cathode reactions, which probably led up to the adsorption and absorption of hydrogen atoms. Flat galvanized steel tensile sample shows a brittle behavior similar to hydrogen embrittlement according to the SSRT (show strain rate test) in seawater.

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受磁场对载流导线有力的作用和牛顿第三定律的启发 ,希望制造一种新型的直流电动机。然而失败了。在找寻失败原因的实验中发现了如下物理现象 :以电磁相互作用的两个物体 ,在发生相互作用时 ,作用在两物体等效作用点上的二力虽然大小相等方向相反 ,但是该二力可以不在一条直线上。

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介绍了ZMP的概念,比较常见的几种ZMP建模方法,提出将高效牛顿-欧拉算法(RENA)与ZMP的概念相结合的迭代ZMP建模方法,并利用该方法完成轮式仿人机器人的ZMP建模.通过模型分析,得出该轮式仿人机器人的ZMP简化计算公式.最后得出此类轮式仿人机器人的稳定性判据及稳定度的定义.

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本文介绍的仿人机器人具有差动腰部机构,它除了受自身的动力学影响以外,还受到手臂和车体运动以及外力、外力矩等对腰部机构关节力矩的影响。笔者利用高效牛顿-欧拉算法完成了仿人机器人的整体建模;在不考虑各关节间耦合运动的情况下,对整体动力学模型进行适当简化,得到了腰部机构的动力学模型。简化后的动力学模型既反映了机器人车体、腰部及双臂的动力学关系,又大大地减小了计算量,易于实现基于动力学的控制算法。基于动力学模型,给出了腰部机构PD伺服轨迹跟踪控制算法,并结合计算力矩方法用于补偿腰部机构两关节受到的力矩扰动。仿真分析表明,该控制方法可以明显提高腰部机构的位置跟踪精度,并提高仿人机器人的整体作业精度。

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利用高效迭代牛顿-欧拉方法对一个21自由度的轮式移动仿人机器人进行了整体动力学建模,该模型虽然维数较高,但消除了分块建模中需要对模块之间相互作用力进行建模的难点问题,并且由于机器人双臂的对称结构,当合理规划双臂运动时,动力学模型将得到部分简化。本文还对某关节运动时在各个关节所产生的力或力矩进行了仿真分析。解析及仿真结果表明,合理规划上臂各关节的协调运动,将极大地削弱车体及腰部各关节所受的力或力矩扰动,为基于动力学的机器人运动控制以及稳定性分析提供理论依据。

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本文设计了一种新颖的微力感知传感器及其标定方法,以获得亚μN(micro Newton)的可靠的、高精度力反馈信息。可靠的、高精度的微力感知和控制在提高微装配的效率上具有重要的作用。目前微装配中还没有可靠的亚μN分辨率的传感器。本文以PVDF(polyvinylidene fluoride)为基本材料,建立出PVDF传感器所受的微力与输出电压之间的关系模型,开发出相应的信号处理电路,并对PVDF传感器的上述模型进行了标定。实验结果表明本文开发的PVDF传感器具有亚μN的分辨率,同时验证了本文建立的PVDF传感器模型的正确性,并证明了信号处理电路以及标定方法是有效的。本文设计的微力传感器为微装配和微操作中微接触力的反馈控制提供了可靠的解决方法,并将促进微装配和微操作的自动化加工技术水平,实现微型装备的可靠、高产量的批量制造。

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对于图像抖动产生偏移,提出了一种基于各向异性非线性扩散以及抖动估计的抖动消除算法。这种各向异性非线性扩散的模型由两项组成,即扩散项以及强制项。基本思想就是对于边界点以及图像内部的点分别进行处理。利用Newton-Raphson算法最小化抖动误差,估计出抖动偏移量。实验结果表明本文的抖动消除技术比其他方法的消除性能好,恢复效果接近于理想图像且性能稳定。