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Improvement of moving particle semi‐implicit method for simulation of progressive water waves 下载免费PDF全文
Precise simulation of the propagation of surface water waves, especially when involving breaking wave, takes a significant place in computational fluid dynamics. Because of the strong nonlinear properties, the treatment of large surface deformation of free surface flow has always been a challenging work in the development of numerical models. In this paper, the moving particle semi‐implicit (MPS) method, an entirely Lagrangian method, is modified to simulate wave motion in a 2‐D numerical wave flume preferably. In terms of consecutive pressure distribution, a new and simple free surface detection criterion is proposed to enhance the free surface recognition in the MPS method. In addition, a revised gradient model is deduced to diminish the effect of nonuniform particle distribution and then to reduce the numerical wave attenuation occurring in the original MPS model. The applicability and stability of the improved MPS method are firstly demonstrated by the calculation of hydrostatic problem. It is revealed that these modifications are effective to suppress the pressure oscillation, weaken the local particle clustering, and boost the stability of numerical algorithm. It is then applied to investigate the propagation of progressive waves on a flat bed and the wave breaking on a mild slope. Comparisons with the analytical solutions and experimental results indicate that the improved MPS model can give better results about the profiles and heights of surface waves in contrast with the previous MPS models. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
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Eleni G. Farmaki Constantinos E. Efstathiou 《International journal of environmental analytical chemistry》2013,93(2):85-105
Artificial Neural Networks (ANNs) have seen an explosion of interest over the last two decades and have been successfully applied in all fields of chemistry and particularly in analytical chemistry. Inspired from biological systems and originated from the perceptron, i.e. a program unit that learns concepts, ANNs are capable of gradual learning over time and modelling extremely complex functions. In addition to the traditional multivariate chemometric techniques, ANNs are often applied for prediction, clustering, classification, modelling of a property, process control, procedural optimisation and/or regression of the obtained data. This paper aims at presenting the most common network architectures such as Multi-layer Perceptrons (MLPs), Radial Basis Function (RBF) and Kohonen's self-organisations maps (SOM). Moreover, back-propagation (BP), the most widespread algorithm used today and its modifications, such as quick-propagation (QP) and Delta-bar-Delta, are also discussed. All architectures correlate input variables to output variables through non-linear, weighted, parameterised functions, called neurons. In addition, various training algorithms have been developed in order to minimise the prediction error made by the network. The applications of ANNs in water analysis and water quality assessment are also reviewed. Most of the ANNs works are focused on modelling and parameters prediction. In the case of water quality assessment, extended predictive models are constructed and optimised, while variables correlation and significance is usually estimated in the framework of the predictive or classifier models. On the contrary, ANNs models are not frequently used for clustering/classification purposes, although they seem to be an effective tool. ANNs proved to be a powerful, yet often complementary, tool for water quality assessment, prediction and classification. 相似文献
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该文在免疫遗传算法(IGA)的基础上,提出一种改进免疫遗传算法(iIGA)用于近红外光谱波长变量的选择。该算法舍去了原算法中固定抗体相似度阈值的思想,取而代之的是抗体相似度阈值自适应,同时引入精英保留策略和贪心算法思想,使得算法朝着正确的方向进行局部性探优。将该算法在玉米的淀粉和蛋白质含量数据集上进行实验测试,建立偏最小二乘(PLS)分析模型,并与IGA、遗传算法(GA)以及全谱方法进行了对比。结果表明,在玉米淀粉含量的预测上,iIGA相较于原IGA算法,预测集均方根误差(RMSEP)从0.312 0降至0.298 0,预测集预测精度提升4.5%;在玉米蛋白质含量的预测上,RMSEP从0.124 4降至0.110 3,预测集预测精度提升11.3%。分别对预测淀粉和蛋白质模型的RMSEP值进行显著性检验,F值分别为165.22和182.05,P值分别为9.5 × 10-23和4.5 × 10-24,P值均小于0.05,因此,iIGA能显著提升模型预测精度。 相似文献
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并行测试以减少测试时间和降低测试成本的强大优势,已成为当前自动测试系统发展的方向。针对并行自动测试过程中,测试任务调度复杂,难以优化的问题,以PSO算法为基础,通过对问题空间编码的重新定义,并运用交叉、变异算子给出了新的粒子位置的更新公式,提出了一种改进后的DPSO算法。依据并行测试完成时间极限定理,给出了并行测试任务调度的目标函数与约束条件。以某雷达电子装备并行测试系统中三块电路板并行测试为例,对改进的DPSO算法进行了仿真验证,得到了最优调度测试序列。结果表明:与遗传算法相比,改进后的DPSO算法迭代次数更少,寻优性能更好,适用于工程应用。 相似文献
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针对氧乐果合成过程中温度控制具有参数时变、时滞后、非线性的特点,提出了一种基于改进粒子群算法的支持向量回归的建模方法。对于支持向量回归模型,3个参数(ε,C,γ)的选取很大程度上决定了其拟合的精度和泛化能力的好坏,采用改进的粒子群算法对参数(ε,C,γ)进行同时寻优,建立了改进的氧乐果合成过程PSO-SVR回归模型,该模型具有很好的学习能力和推广能力。实验结果表明,模型较好地体现了系统的动态特性,可用于氧乐果合成过程的模型预估控制,提高系统的控制品质。 相似文献
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针对现有的变结构滑模控制切换面单一性会导致系统状态在原点处收敛缓慢的缺陷,对自主式水下机器人(AUVs)变结构滑模控制设计了折线型的切换面,并且进一步改进实现了速度控制和定点定速控制。改进的切换面由斜率不同的自线段构成,并在拐点处通过S型函数光滑过渡。将切换面的斜率减小到0时,则可以实现速度控制,同时为了消除速度控制的稳态误差,引进了采用能智积分方法的积分项。最后在某AUV上进行仿真实验,结果证实了应用折线型切换面可以减少控制系统的上升时间,提高反应速度;速度控制的稳态误差接近0,并很好地实现定点定速的控制效果。该方法可以有效用于AUVs的控制。 相似文献
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In a capillary discharge experiment for the neon-like argon lasing, we have proposed an experimental scheme to verify that the multi-spike of X-ray diode (XRD) signal is a multi-pulse laser or is a reflection of the laser pulse in the XRD.The ceramic capillary has an inner diameter of 3mm and a length of 200mm.At the gas pressure of 28Pa and discharge current of 27kA, stable lasing has been realized.The experimental results prove that the multi-spike of XRD signal is a reflection of the electromagnetic signal produced by the laser pulse in the XRD.The improved electrocircuit scheme of the XRD to minimize the reflection phenomena is also found. 相似文献