自适应SA-PSO优化的威布尔混合分布参数估计方法及应用

针对采用传统参数估计方法得到的模型拟合误差较大的问题，建立多重威布尔混合分布参数估计的非线性最小二乘模型，并提出基于模拟退火（SA）思想的自适应粒子群（PSO）算法进行求解。在PSO算法优化过程中，采用自适应方法调整惯性权重和加速因子，加快其收敛速度；引入模拟退火机制，根据Metropolis准则确定最优粒子的取舍，改善其全局搜索能力。将该方法应用到某型柴油机喷油器失效分布的参数估计中，并与图解法、基于Levenberg-Marquardt的非线性最小二乘法、标准PSO算法、自适应PSO算法求解的结果进行比较，分析所提方法的优化性能及精度。结果表明，该方法能够有效提高多重威布尔混合分布模型参数估计的精度和效率。     

随车起重机伸缩臂截面多目标优化

为了提高某火箭炮弹药装填车随车起重机伸缩臂的结构刚度,减轻结构质量,建立了随车起重机伸缩臂参数化模型,并对伸缩臂在水平受载状态下进行仿真分析。以伸缩臂截面尺寸参数为设计变量,借助最优拉丁超立方试验设计建立样本空间,构造响应面多项式函数近似模型。在此基础上,利用NSGA-Ⅱ型遗传算法对伸缩臂自身重量、挠度进行多目标优化。优化结果表明:伸缩臂质量减轻了24.5%,减重效果明显。文中所采用的将参数化建模、有限元分析和数值寻优相结合的优化方法,可为起重机伸缩臂截面优化提供一定的参考。     

Investigating hydrogen evolution reaction properties of a new honeycomb 2D AlC

The hydrogen due to its high mass energy density is a new renewable, economically viable and clean resource. The most eco-friendly and economical approaches for the generation of hydrogen through hydrogen evolution is electrochemical water splitting. The two-dimensional (2D) nanomaterials have been recently found as potential candidates as non-noble metal catalyst for hydrogen evolution. In this work, we have systematically studied the structural and electronic properties of the newly predicted hexagonal-aluminium carbide monolayer (h-AlC ML) under the framework of dispersion-corrected density functional theory (DFT) calculations. The calculated electronic total density of states (TDOS) of h-AlC ML predict its metallic nature in contrast to other polar honeycomb 2D materials which are either semiconducting or semimetallic. The metallic behavior of h-AlC monolayer which motivates us to investigate its HER activity results due to the presence of delocalized charge density near Fermi level. Thus, we have investigated the HER activity of h-AlC ML by calculating hydrogen (H) adsorption energy (ΔE_H) and Gibbs free energy (ΔG_H) at three different sites of the 3 × 3 and 4 × 4 supercells of h-AlC ML; top of carbon atom (E_H-C), top of aluminium atom (E_H-Al) and hollow site (E_H-Hollow). Our results show that the hollow site is most catalytically active site in both supercells of h-AlC ML. We believe that our results will inspire experimentalists to fabricate this new 2D material for achieving the desired range of HER activity.     

基于高斯混合隐马尔科夫模型与人工神经网络的紧急换道行为预测方法

为了有效降低因驾驶员紧急换道行为而诱发的交通事故，提高道路交通事故链阻断效率，提出一种基于高斯混合隐马尔科夫模型（GMM-HMM）和人工神经网络（ANN）的紧急换道行为预测方法。首先利用GMM-HMM对车辆行驶状态以及驾驶行为连续观察序列进行换道意图辨识，采用ANN预测下一时段的驾驶行为，再预测换道过程中的横向加速度变化率，从而判断紧急换道的危险程度。驾驶员在环仿真实验及实车实验结果表明，该方法预测避险成功率达92.83%，实验避险成功率达90.32%。该方法能有效地对紧急换道行为进行提前警告与干预。     

传统村落码头空间改造的适宜性评价研究

综合运用Yaahp软件分析、层次分析法、Delphi法、文献解析与问卷调研等方法,对功能改造活动的调研数据建立判断矩阵,选取22个指标并计算推演指标权重,建立传统村落码头的功能改造的适宜性评价模型,并提出相应的量化评价方法,推导出传统村落码头空间功能改造适应性的七个关键要素。为传统村落的文化传承与功能提升提供决策依据。     

Composite mixed matrix membranes incorporating microporous carbon molecular sieve as filler in polyethersulfone for CO2/CH4 separation

Membrane technology has been considered a key factor for sustainable growth in high-efficiency gas separation. Current mixed matrix membranes (MMMs) technology is rising, but these membranes in the dense structure are having difficulties in operating at high pressures and scale up for commercialization. The purpose of this research is to synthesize composite MMMs (CMMMs) consisting of polyethersulfone (PES), carbon molecular sieve (CMS 1–5 wt %), and Novatex 2471 nonwoven fabric (support layer). The membranes' physical, chemical, and thermal properties were evaluated by different analytical equipment. The morphology of both PES and PES-CMS composite membranes had a porous and asymmetric structure, in which CMS was uniformly distributed in the polymer matrix. The thermal properties showed that the membranes were stable up to 350 °C with a single glass transition temperature. The functional groups in the membrane were confirmed by spectral analysis. The gas performance results showed that carbon dioxide permeance increased with increased CMS concentration and methane permeance decreased due to the hindering effect of CMS under similar operating conditions. The highest selectivity achieved was 12.774 using CMMM of 5 wt % of CMS at 10 bar, which on average was 137.80%, improved selectivity compared to pure PES membrane. The support layer was able to withstand high operating pressures and showed the ability to scale up. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48476.     

Mixed convection flow of a Maxwell nanofluid with Hall and ion‐slip impacts employing the spectral relaxation method

This article investigates the Hall and ion‐slip impacts on the mixed convection flow of a Maxwell nanofluid over an expanding surface in a permeable medium. The impacts of Brownian movement and thermophoresis parameters, Soret, Dufour, viscous dissipation, chemical reaction, and suction parameters, are, moreover, considered. Using the similitude changes, the partial differential equations with regard to the momentum, energy, and concentration equations are transformed to an arrangement of nonlinear ordinary differential equations, which are handled numerically utilizing a spectral relaxation method (SRM). The impacts of noteworthy physical parameters on the velocities, thermal, and concentration distributions are investigated graphically. Moreover, the numerical values of skin‐friction coefficients, local Nusselt number, and Sherwood number for different values of the mixed convection parameter $\left(\gamma \right),$ Deborah number $\left(\lambda \right),$ Hall parameter $({\beta }_{\mathrm{H}}),$ ion‐slip parameter $({\beta }_{\mathrm{i}}),$ Dufour number (Du), and Soret number $\left(\mathit{Sr}\right)$ are computed and tabulated. It is discovered that ascent in Deborah number reduces both the stream and transverse velocity profiles, while the inverse pattern is seen with augmentation in the mixed convection parameter. In addition, inverse patterns of the stream and transverse velocity profiles are seen with expansion in magnetic, Hall, and ion‐slip parameters. Besides this, the temperature and concentration disseminations decline with augmentation in Dufour number and chemical reaction parameters, respectively. It is likewise seen that both the skin‐friction coefficients lessen with expansion in Deborah number, and they ascend with upgrade in blended convection and ion‐slip parameters, while the opposite condition is noticed with augmentation in Hall parameter. Furthermore, the reverse trends of local Nusselt and Sherwood numbers are discovered with expansion in the Dufour and Soret numbers.     

基于VMD瞬时能量与GA- RBF的滚动轴承故障诊断

针对滚动轴承早期故障的有效识别,提出了一种基于VMD瞬时能量与GA优化的RBF神经网络的滚动轴承故障诊断方法,可以有效对滚动故障做出诊断。首先,VMD将滚动轴承振动信号进行分解成合适数目的本证模态函数;其次,计算本证模态函数分量的瞬时能量并组成特征向量;最后,将特征向量输入到GA优化的RBF神经网络实现轴承故障识别。通过滚动轴承故障诊断实验对该方法进行验证。结果表明,该方法识别滚动轴承故障的准确率为96.43%,较默认参数的RBF神经网络和EEMD瞬时能量与GA-RBF神经网络有明显的提高,证明了所提方法的可行性。     

An iterative approach for the discrete‐time dynamic control of Markov jump linear systems with partial information

The , and mixed dynamic output feedback control of Markov jump linear systems in a partial observation context is studied through an iterative approach. By partial information, we mean that neither the state variable x(k) nor the Markov chain θ(k) are available to the controller. Instead, we assume that the controller relies only on an output y(k) and a measured variable coming from a detector that provides the only information of the Markov chain θ(k). To solve the problem, we resort to an iterative method that starts with a state‐feedback controller and solves at each iteration a linear matrix inequality optimization problem. It is shown that this iterative algorithm yields to a nonincreasing sequence of upper bound costs so that it converges to a minimum value. The effectiveness of the iterative procedure is illustrated by means of two examples in which the conservatism between the upper bounds and actual costs is significantly reduced.