Numerical study on PEMFC’s geometrical parameters under different humidifying conditions

Steady-state and three-dimensional simulations were carried out to study the influences of geometrical parameters on the performance of PEMFC under different hydrating conditions. Flow fields, species transport, transport of water in polymer membrane and movement of liquid water in cathode and anode porous layers were determined, in order to accomplish a complete estimation of ohmic and concentration losses of PEMFC power. The geometrical parameters were thickness of the polymer membrane, cathode catalyst layer as well as gas channel to rib width ratio. Every simulation was made under different relative humidities of inlet flows (50 and 100%) for every change of characteristic length. Results show that the influence of the geometrical parameters on ohmic and concentration losses is of considerable importance. The performance of PEMFC is seriously affected under dehydrating conditions. However, such performance may be considerably improved by using suitable geometrical parameters. Cathode and anode liquid saturation may not only affect the transport of species, but also the polymer electrolyte water content. These results show the importance of simultaneously calculating both the water absorption and desorption through the polymer electrolyte and the liquid saturation in the cathode and anode porous mediums to obtain an actual view of ohmic and concentration losses of the PEMFC performance.     

A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.     

胶凝砂砾石坝材料特性研究及工程应用

本文阐述了胶凝砂砾石坝的起源和发展情况。根据福建街面水电站下游围堰的施工要求，即施工期作为挡水堰，运行期作为量水堰，设计了围堰坝体的断面，对堰体的应力、稳定和渗流进行了分析，提出了材料的性能参数要求，并探讨了胶凝砂砾石材料的渗透溶蚀性能。研究结果表明，采用当地天然砂砾石，掺入水泥和粉煤灰各40kg/m3，其180d龄期抗压强度等级可达到C7.5，并满足围堰的力学、稳定、防渗和抗溶蚀要求，缩短了工期，降低了造价。     

可追溯的绿色安全猪肉生产系统研究

现在，养猪生产者滥用激素、微量元素和违禁药物饲养生猪，而消费者却无法识别这种猪肉，严重地威胁着消费者的食品卫生安全。为此，应用射频识别技术，采用综合软件管理，以一维条形码实行三网合一查验的方式来建立猪肉生产卫生安全跟踪系统，是保障消费者食品卫生安全的理想方法。     

基于隐性故障模型和风险理论的关键线路辨识

在大规模电网中，由简单故障触发的电力系统连锁故障常常会引起大停电的灾难性后果。为了研究复杂电网连锁故障的传播机理，同时找出对连锁故障产生重要影响的关键线路，文中基于模拟连锁故障的隐性故障模型和风险理论，提出了复杂电力系统的线路故障风险评估方法，并辨识出了对系统大停电产生重要影响的一系列关键线路。模型考虑了线路过负荷保护、隐性故障、控制策略及系统运行等参数，对IEEE 118节点系统仿真结果表明，在重负荷状态运行下只对辨识出的少量关键线路加以改善，就可以使系统停电概率大幅减小，特别是大停电概率;在临界状态运行下改善少量关键线路，则可以使系统脱离临界状态，避免大停电发生。     

X射线三轴晶衍射法测量半绝缘GaAs单晶的化学配比

采用X射线三轴晶衍射法,根据As间隙原子对作为过量As在GaAs单晶材料中存在的主要形式的模型,可以无损、高精度测量半绝缘GaAs单晶的化学配比.并探讨了引起晶格变化的原因及其与熔体组分的关系,对于制备高质量GaAs单晶及其光电器件具有重要的意义.     

桥梁颤振气动导数识别的迭代法

本文提出一种利用自由振动响应通过年顿－拉夫逊迭代同时识别出桥梁全部8个颤振气动导的方法。此法具有对迭代初值要求不高，识别结果稳定的特点，并具有一定的抗噪声干扰能力。数字仿真与实物试验结果表明本文方法有效，可行。     

Approximate channel identification via δ‐signed correlation

A method of approximate channel identification is proposed that is based on a simplification of the correlation estimator. Despite the numerical simplification (no multiplications or additions are required, only comparisons and an accumulator), the performance of the proposed estimator is not significantly worse than that of the standard correlation estimator. A free (user selectable) parameter moves ‘smoothly’ from a situation with small sum‐squared channel estimation error but hard‐to‐identify channel peaks, to one with a larger sum‐squared estimation error but easy‐to‐identify channel peaks. The proposed estimator is shown to be biased and its behaviour is analysed in a number of situations. Applications of the proposed estimator to sparsity detection, symbol timing recovery and to the initialization of blind equalizers are suggested. Copyright © 2002 John Wiley & Sons, Ltd.     

构造性神经网络在测井岩性识别中的应用

测井岩性识别是石油勘探中十分重要的基础工作,准确的岩性识别结果可以为勘探和开发提供可靠的依据。人工神经网络方法可对复杂的高维数据进行非线性映射,在模式识别领域得到越来越广泛的应用。针对传统的BP神经网络算法存在收敛速度慢、隐层数以及隐层节点数难以确定等缺点,研究了一种构造性神经网络学习算法---级联算法（Cascade Correlation Algorithm,简称CC算法）及其在石油工程中的应用。采用该算法对甘肃镇原-泾川地区进行岩性识别研究,通过与BP神经网络的识别结果进行比较,体现出构造性神经网络的优越性。