Empowering wave energy with control technology: Possibilities and pitfalls

With an increasing focus on climate action and energy security, an appropriate mix of renewable energy technologies is imperative. Despite having considerable global potential, wave energy has still not reached a state of maturity or economic competitiveness to have made an impact. Challenges include the high capital and operational costs associated with deployment in the harsh ocean environment, so it is imperative that the full energy harnessing capacity of wave energy devices, and arrays of devices in farms, is realised. To this end, control technology has an important role to play in maximising power capture, while ensuring that physical system constraints are respected, and control actions do not adversely affect device lifetime. Within the gamut of control technology, a variety of tools can be brought to bear on the wave energy control problem, including various control strategies (optimal, robust, nonlinear, etc.), data-based model identification, estimation, and forecasting. However, the wave energy problem displays a number of unique features which challenge the traditional application of these techniques, while also presenting a number of control ‘paradoxes’. This review articulates the important control-related characteristics of the wave energy control problem, provides a survey of currently applied control and control-related techniques, and gives some perspectives on the outstanding challenges and future possibilities. The emerging area of control co-design, which is especially relevant to the relatively immature area of wave energy system design, is also covered.     

混合遗传蚁群算法优化BP神经网络预测空气质量

为了进一步提高空气质量指数预测精度,提出一种混合遗传蚁群算法优化BP神经网络的方式对空气质量指数进行预测.首先初始化蚁群算法的信息素分布,对不满足适应度条件的进行遗传算法的交叉、变异操作,进而计算蚁群的状态转移概率和信息素浓度,当适应度值满足条件要求时,将寻优结果作为BP神经网络的最优权值和阈值,来改善单一BP神经网络的不足.最后通过运用西安市的空气质量指数日历史数据进行验证,实验表明,本文所提模型的各个评价指标相对其他对比模型误差更小,在预测精度方面具有更高的说服力,因此能够有效地预测空气质量指数.     

BP神经网络结合变量选择方法在牛奶蛋白质含量检测中的应用北大核心CSCD

牛奶中的蛋白质含量会影响牛奶的品质,利用高光谱图像的光谱特征信息研究对牛奶蛋白质含量预测的可行性。本文提出一种基于竞争性自适应重加权算法(competitive adaptive reweighted sampling, CARS)和连续投影算法(successive projections algorithm, SPA)结合多层前馈神经网络(back propagation, BP)的预测建模方法,实验以含有不同浓度蛋白质的牛奶为对象,利用可见光/近红外高光谱成像系统共采集到5种牛奶共计250组高光谱数据,通过实验对比选择采用标准化方法对获取到的吸收光谱预处理,然后采用CARS结合SPA筛选特征波长,得到18个特征波长,建立CARS-SPA-BP模型,经过试验,CARS-SPA-BP模型的训练集决定系数和测试集决定系数R;和R;分别达到0.971和0.968,训练集均方根误差(root mean square error of calibration,RMSEC)和测试集均方根误差(root mean square error of prediction,RMSEP)达到了0.033和0.034。研究发现,采用CARS结合SPA筛选的牛奶特征波长建立的多层前馈神经网络模型,其模型预测结果与全波长建模相比并没有明显降低,因此将CARS结合SPA用于波长筛选并且结合BP神经网络基本可以完成对牛奶蛋白质含量的预测。为验证CARS-SPA-BP模型的预测能力,在相同数据环境下,使用较为传统的偏最小二乘回归(partial least squares regression, PLSR)进行建模,实验结果表明,CARS-SPA-BP相较于PLSR,R;和RMSEP均有明显提升。研究表明,CARS-SPA-BP可充分利用牛奶光谱特征信息实现较高精度的牛奶蛋白质含量检测。     

Wave propagation in functionally graded nanocomposites reinforced with carbon nanotubes based on second-order shear deformation theory

In the present article, as a first endeavor, the wave propagation in functionally graded nanocomposites reinforced with carbon nanotubes is investigated on the basis of second-order shear deformation theory. Four different types of functionally graded nanocomposites are presented. An analytical method is used to find the circular frequencies and phase velocities. To show the accuracy of the present methodology, our results for the free vibration are compared with the results of functionally graded plates available in the literature. The influences of different parameters are also investigated on the circular frequencies and phase velocities.     

Fatigue Crack Growth and Fracture of 30 wt% B4C/6061Al Composites

This paper focuses on studying the fatigue crack growth (FCG) characteristics and fracture behaviours of 30 wt% B₄C/6061Al composites fabricated by using powder metallurgy and hot extrusion method. Compact tension (CT) specimens having incisions parallel to the extrusion direction (T‐D) and perpendicular to the extrusion direction (E‐D) were investigated through FCG tests. Results show that, at low/medium stress‐intensity factor range levels (ΔK ≤ 9), crack propagation rate in E‐D specimens is lower than that in T‐D specimens because the elongated B₄C particles parallel to the extrusion direction in E‐D specimens can deflect the crack. The scanning electron microscope micrographs of the fractured surface illustrate that crack mainly propagates in the matrix alloy at the initial stage of its propagation and propagates more remarkably near the particle‐matrix interface with the increase of ΔK value. B₄C particles are also found to be easy to fracture during the rapid crack propagation. Based on fracture analyses, considering the impacts of factors like crack deviation, plastic zone size at the crack tip, and crack driving force, a 2‐D crack propagation model was developed to study the fatigue crack propagation mechanism in the 30 wt% B₄C/6061Al composite.     

硬脂酸粉尘爆炸过程中火焰传播试验及数值模拟

采用试验和数值模拟相结合的方法研究了硬脂酸粉尘火焰在上端开口的圆柱形垂直燃烧管道的传播过程。试验利用高速摄影系统和红外热成像仪记录了火焰的传播过程和温度分布情况,结果表明:火焰传播速度和火焰温度均呈现先增大后减小的趋势。采用Fluent软件计算得到的模拟结果与试验值吻合较好,模拟结果揭示了硬脂酸粉尘爆炸过程中气流速度的变化情况,分析结果表明:在同一时刻,气流速度高于粉尘火焰传播速度,是造成粉尘二次扬尘,进而产生持续爆炸的重要因素之一。     

Automatic text classification using BPLion-neural network and semantic word processing

Text mining has become a major research topic in which text classification is the important task for finding the relevant information from the new document. Accordingly, this paper presents a semantic word processing technique for text categorization that utilizes semantic keywords, instead of using independent features of the keywords in the documents. Hence, the dimensionality of the search space can be reduced. Here, the Back Propagation Lion algorithm (BP Lion algorithm) is also proposed to overcome the problem in updating the neuron weight. The proposed text classification methodology is experimented over two data sets, namely, 20 Newsgroup and Reuter. The performance of the proposed BPLion is analysed, in terms of sensitivity, specificity, and accuracy, and compared with the performance of the existing works. The result shows that the proposed BPLion algorithm and semantic processing methodology classifies the documents with less training time and more classification accuracy of 90.9%.     

Region-based surveillance video retrieval with effective object representation

Retrieving the most relevant video frames that contain the object specified in a given query (query-by-region) remains a challenging task. Two common challenges of region-based retrieval approaches are to accurately extract or segment object(s) and select a proper matching strategy. This paper addresses these problems by proposing a retrieval approach that uses a new region-based matching technique equipped with an effective object representation method. In the first stage, the proposed approach selects the most informative instances of each object that appeared in the video by utilizing an adapted clustering algorithm over the extracted features. In the retrieval stage, the new matching technique returns the most relevant sequences of video by mapping a given region with those identified representative instances of objects based on their similarity scores. The proposed approach is evaluated on standard datasets and the results demonstrate a 31% improvement in the retrieval performance compared to other state-of-the-art methods.     

Effects of microstructure on fatigue crack propagation behavior in a bi-modal TC11 titanium alloy fabricated via laser additive manufacturing

In this study, the crack propagation behaviors in the equiaxed and equiaxed-columnar grain regions of a heat-treated laser additive manufacturing (LAM) TC11 alloy with a special bi-modal microstructure are investigated. The results indicate that the alloy presents a special bi-modal microstructure that comprises a fork-like primary α (α_p) phase surrounded by a secondary α colony (α_s) in the β phase matrix after the heat treatment is completed. The samples demonstrate a fast crack growth rate with larger da/dN values through the equiaxed grain sample versus across the equiaxed-columnar grain sample at low ΔK values (<13.8). The differences that are observed between the crack propagation behaviors (in the crack initiation stage) of the samples can be mostly attributed to the different size and morphology of the α_p lamellae and α_s colony within the grains in the equiaxed and columnar grain regions rather than the grain boundaries. The cracks prefer to grow along the α/β boundary with a smooth propagation route and a fast propagation rate in the equiaxed grain region, where the α_p and α clusters have a large size. However, in the columnar grain region, small and randomly distributed α_p lamellae generate a zigzag-shaped propagation path with a reduction in the da/dN value. Additionally, the change in the size of the α_p lamellae in the equiaxed grains (heat affected bands, HAB) is also observed to influence the propagation behavior of the crack during the crack initiation stage.     

变阻障碍物对管道内瓦斯爆炸的影响

为探究障碍物阻塞比变化率对瓦斯爆炸的影响,分别建立平均阻塞比为0.6、 0.3的受限空间物理模型,基于Charlette湍流燃烧模型,利用Fluent软件对阻塞比变化率依次为0、 0.05、 0.10、 0.15的障碍物条件下的爆炸火焰、湍流转捩、压力波耦合过程进行大涡模拟(LES)。研究结果表明：火焰经过障碍物会产生回流卷吸效应。在平均阻塞比为0.6的工况组A中,当阻塞比变化率为0.10、 0.15时,火焰锋面更加尖锐,火焰传播速度峰值更高,平均传播速度更高,到达超压所需时间更短,超压峰值更大。在平均阻塞比为0.3的工况组B中,各工况平均传播速度相同,随着阻塞比变化率的增大,到达超压所需时间更长,超压峰值更大。