Review of the phase change material (PCM) usage for solar domestic water heating systems (SDWHS)

The shortage in energy resources combined with the climb in greenhouse emissions is the main incentive beyond the deployment of solar energy resource in various applications. One of the most successful applications is the utilization of solar energy in the domestic water heating systems (DWHS) because 70% of the consumed energy in the residential segment is utilized for space heating and appliances in cold climates 1 . However, the full deployment of solar energy in domestic water heating is only possible when an energy storage system with acceptable price is available. Recently a new tendency for deploying phase change materials (PCMs) as an energy storage system is introduced in several solar DWHS. These systems are known as integrated PCM in solar DWHS and offer several advantages including high storage capacity, low storage volume, and isothermal operation during the charging and discharging phases. The present study reviews various techniques utilized for integrating the PCM in solar water heating systems and the utilized methods for enhancing the heat transfer characteristics of the PCM through the usage of extended surfaces and high conductive additives. Copyright © 2017 John Wiley & Sons, Ltd.     

初始制动时预测湿式制动器热对流特性的积分方法

湿式制动器对重型车辆安全具有关键影响，以湿式制动器摩擦副间隙的冷却液压油（Automotive transmission fluid，ATF）为研究对象，考虑车辆初始制动阶段流体的黏性摩擦和层流流动特征，利用积分方法建立了摩擦副流体的非稳态能量方程，并获得了能同时满足轴向和径向边界条件的三维温度和热流密度显式解析表达式，通过简化动量方程和多项式分布假设也获得了径向速度和压力的理论解，与以往试验对比表明，压力和温度解析解与试验结果具有较好的一致性，理论模型有望推广用于液黏离合器等其他HVD装置的ATF速度场、温度场和热流密度场的理论预测。     

Quantitative assessments of performance and robustness of maintenance policies for stochastically deteriorating production systems

Over the last few decades, many efforts have been invested in improving the economic performances of maintenance policies for stochastically deteriorating production systems. However, with the development of complex production systems, maintenance managers are interested not only in cost saving, but also in how to trustworthily plan and allocate the required maintenance budget. In this context, the robustness of maintenance policies which is related to the maintenance cost variability from a renewal cycle to another plays a pivotal role. This research deals with a quantitative approach to jointly assess the economic performance and robustness of some representatives of two most well-known classes of maintenance policies: time-based and condition-based maintenance. To this end, we first propose a new cost criterion which combines the long-run expected cost rate and standard deviation of maintenance cost per renewal cycle. Then, we develop and compare the associated mathematical cost models of the considered maintenance policies on the basis of the Gamma degradation process and the theory of stochastic renewal processes. The comparison results under different situations of maintenance costs and system characteristics show that the optimal configuration of maintenance policies gives the best compromise between the performance and robustness, and is mostly affected by the system downtime. Under this aspect, the condition-based maintenance remains more profitable than the time-based maintenance. Still, maintenance managers could implement condition-based maintenance policies that efficiently control the downtime to maximise the maintenance effectiveness of production systems from both performance and robustness viewpoints.     

光伏系统用于漏电流测量的霍尔闭环传感器设计

基于闭环磁通门技术的传感器广泛应用在测量大电流中的小剩余电流以及噪声共模电流。这类传感器的精度以及对大电流的隔离能力使之成为漏电流检测的最优方案,但通常缺点是成本昂贵且体积庞大。本文介绍了一种新型小尺寸且利用霍尔闭环技术对太阳能系统中的漏电流进行测量的传感器:新一代的LDSR产品。     

Comprehensive reliability evaluation of multistate complex electromechanical systems based on similarity of cloud models

High reliability and security have become the hallmarks of complex electromechanical systems. Owing to the difficulties in fault data collection, ambiguity and uncertainty have been inevitably associated with complex electromechanical systems. Thus, the ability to perform reliability evaluation using scarce fault data is of immense significance to these machines and is the focus of this study. A similarity based cloud model is proposed to evaluate the running state of complex electromechanical systems. By combining objective and subjective factors, the reliability of complex electromechanical systems is evaluated by calculating the similarity between the cloud models of actual and standardised states. Next, the inverter of an offshore wind turbine is used to verify the accuracy and effectiveness of the proposed approach. The cloud model based framework for reliability evaluation inherits the preponderance of the uncertainty problem, overcomes the drawbacks of the current reliability approaches, and provides a theoretical basis, as well as a practical approach for the maintenance and repair of complex electromechanical systems with missing fault data. Additionally, it also provides a new methodology for solving the uncertainty problems caused by paucity of data.     

Pseudospectral method for assessing stability robustness for linear time-periodic delayed dynamical systems

The article presents a pseudospectral approach to assess the stability robustness of linear time-periodic delay systems, where periodic functions potentially present discontinuities and the delays may also periodically vary in time. The considered systems are subject to linear real-valued time-periodic uncertainties affecting the coefficient matrices, and the presented method is able to fully exploit structure and potential interdependencies among the uncertainties. The assessment of robustness relies on the computation of the pseudospectral radius of the monodromy operator, namely, the largest Floquet multiplier that the system can attain within a given range of perturbations. Instrumental to the adopted novel approach, a solver for the computation of Floquet multipliers is introduced, which results into the solution of a generalized eigenvalue problem which is linear w.r.t. (samples of) the original system matrices. We provide numerical simulations for popular applications modeled by time-periodic delay systems, such as the inverted pendulum subject to an act-and-wait controller, a single-degree-of-freedom milling model and a turning operation with spindle speed variation.     

准周期量子动力系统的数值求解

本文提出了研究准周期量子动力系统的计算方法.传统计算方法通常使用大的周期系统来近似计算准周期系统,这会产生丢番图逼近误差.我们的方法将准周期系统在高维周期结构中表示和计算,这样不仅可以避免丢番图逼近误差,而且可以将周期系统的高效算法,比如快速Fourier变换直接运用到新的算法中.我们将算法用于计算具有准周期势的线性薛定谔方程和准周期初值的非线性薛定谔方程.数值结果表明了算法的可靠性和高效性,并可以用于研究包含Anderson局域化、非线性光子准晶在内的准周期量子行为.     

PUL-Mediated Plant Cell Wall Polysaccharide Utilization in the Gut Bacteroidetes

Plant cell wall polysaccharides (PCWP) are abundantly present in the food of humans and feed of livestock. Mammalians by themselves cannot degrade PCWP but rather depend on microbes resident in the gut intestine for deconstruction. The dominant Bacteroidetes in the gut microbial community are such bacteria with PCWP-degrading ability. The polysaccharide utilization systems (PUL) responsible for PCWP degradation and utilization are a prominent feature of Bacteroidetes. In recent years, there have been tremendous efforts in elucidating how PULs assist Bacteroidetes to assimilate carbon and acquire energy from PCWP. Here, we will review the PUL-mediated plant cell wall polysaccharides utilization in the gut Bacteroidetes focusing on cellulose, xylan, mannan, and pectin utilization and discuss how the mechanisms can be exploited to modulate the gut microbiota.     

Adaptive robust control-based energy management of hybrid PV-Battery systems with improved transient performance

Energy management of hybrid photovoltaic (PV)-battery systems still serve as a challenging task owing to their complex and nonlinear characteristics, multicomponent structures, and the extensive range of environmental factors disturbing their nominal performance. The hybrid energy system developed in this study encompasses PV arrays, a battery component, one boost converter, and one bidirectional boost converter. In this paper, we propose a novel adaptive robust control framework for the optimal energy management of the PV-battery systems under many operating conditions and subject to unmodelled dynamics. An improved exponential-like adaptive integral sliding mode (EISM) control coupled to neural network approximator is introduced using a multi-rate convergence tweaking mechanism for the sliding surface to improve the transient performance of the closed-loop system. Furthermore, the entire dynamics of the hybrid energy system is considered unknown, unlike the previous studies that only assumed the parametric uncertainties. The global asymptotic stability of the system is guaranteed, and the effectiveness of this novel framework is compared to benchmark studies.