Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。     

Process monitoring method based on correlation variable classification and vine copula

Chemical processes are becoming increasingly complicated, leading to an increase in process variables and more complex relationships among them. The vine copula has a significant advantage in portraying the dependence of high-dimensional variables. However, as the dimensions increase, the vine copula model incurs a high computational load; such pressure greatly reduces model efficiency. Relationships among variables in the industrial process are complex. Different variables may be strongly or weakly associated or even independent. This paper proposes a process monitoring method based on correlation variable classification and vine copula. The weighted correlation measure is first used to divide variables into a correlated subspace and weakly correlated subspace. Then, two vine structures, C-vine and D-vine, are applied to the correlated and weakly correlated subspaces, respectively. This method takes advantage of C-vine for correlated variables and the flexibility of D-vine for weakly correlated variables. Finally, comprehensive statistics are established based on different subspaces. Monitoring results of the numerical system and the Tennessee Eastman process demonstrate the effectiveness and validity of the proposed method.     

Mechanism of methanol decomposition on the Pd/WC(0001) surface unveiled by first-principles calculations

In this study, the decomposition of methanol into the CO and H species on the Pd/tungsten carbide (WC)(0001) surface is systematically investigated using periodic density functional theory (DFT) calculations. The possible reaction pathways and intermediates are determined. The results reveal that saturated molecules, i.e., methanol and formaldehyde, adsorb weakly on the Pd/ WC(0001) surface. Both CO and H prefer three-fold sites, with adsorption energies of −1.51 and −2.67 eV, respectively. On the other hand, CH₃O stably binds at three-fold and bridge sites, with an adsorption energy of −2.58 eV. However, most of the other intermediates tend to adsorb to the surface with the carbon and oxygen atoms in their sp³ and hydroxyl-like configurations, respectively. Hence, the C atom of CH₂OH preferentially attaches to the top sites, CHOH and CH₂O adsorb at the bridge sites, while COH and CHO occupy the three-fold sites. The DFT calculations indicate that the rupture of the initial C–H bond promotes the decomposition of CH₃OH and CH₂OH, whereas in the case of CHOH, O–H bond scission is favored over the C–H bond rupture. Thus, the most probable methanol decomposition pathway on the Pd/WC(0001) surface is CH₃OH → CH₂OH → trans-CHOH → CHO → CO. The present study demonstrates that the synergistic effect of WC (as carrier) and Pd (as catalyst) alters the CH₃OH decomposition pathway and reduces the noble metal utilization.     

新一代IP QoS的实现

文章介绍了新一代IP骨干网上的IP QoS实现技术，论述了集成业务(IntServ)与差分业务(DiffServ)解决方案的特点，详细介绍了相关的队列管理与排队机制。并结合多协议标签交换（MPLS)技术的最新发展，阐述了综合多协议标签交换流量工程与DiffServ技术体系端到端IP QoS的实现。     

Fast Positive Feedback Between the Adrenocortical Stress Response and a Brain Mechanism Involved in Aggressive Behavior.

Aggressive behavior induces an adrenocortical stress response, and sudden stressors often precipitate violent behavior. Experiments in rats revealed a fast, mutual, positive feedback between the adrenocortical stress response and a brain mechanism controlling aggression. Stimulation of the aggressive area in the hypothalamus rapidly activated the adrenocortical response, even in the absence of an opponent and fighting. Hypothalamic aggression, in turn, was rapidly facilitated by a corticosterone injection in rats in which the natural adrenocortical stress response was prevented by adrenalectomy. The rapidity of both effects points to a fast, mutual, positive feedback of the controlling mechanisms within the time frame of a single conflict. Such a mutual facilitation may contribute to the precipitation and escalation of violent behavior under stressful conditions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

径向水平井弯曲转向机构影响因素仿真研究

针对径向水平井钻进中钻杆弯曲转向前进运动困难的问题,通过建立弯曲转向机构仿真有限元模型,对其主要影响因素:滑道轨迹曲率、间隙、工作压力、滚轮形状与位置和钻杆壁厚等用ANSYS软件进行仿真研究。研究表明:影响截面变形的主要因素是滑道曲率的改变和滑道摩擦因数,钻井失败时钻杆所受阻力的增大不是因为升高工作压力导致截面变形过大与滑道干涉所致,钻杆经校直段,钻头中轴线与校直中心线存在一定的角度,即钻杆的前进轨迹就会偏离理论值,或与地层干涉,或可能再次发生弯曲变形;另一主要原因是转向器滑道工作恶化。增加钻杆壁厚,降低工作压力和滑道摩擦因数,设计合理弯曲转向机构是解决问题的关键。     

泌阳凹陷复杂断块群油气分布控制因素

泌阳凹陷北部斜坡复杂断块群油田以断鼻、断块及断层+岩性油气藏为主,垂向含油层系多,平面上叠合连片,油气主要富集在鼻状构造主体部位的断鼻断块内。通过对研究区油气控制因素的分析,指出继承性的鼻状构造控制了油气聚集方向和富集程度,油气藏含油范围和油气藏高度则主要受断层封闭性和封闭程度的控制,油气分布规律受伸展构造所伴生的各种断块群构造型式的控制。     

A Study on Turbo—rotor Multi—fault Diagnosis Based on a Neural Network

The multi-fault phenomena are common in the turbo-rotor system of a liquid rocket engine.As it has many excellent qualities,the neural network might be used to solve the problems of multi-fault diagnasis of a turbo-rotor system.First,the feature expression of a common turbo-rotor fault was studied in order to build up the standard fault pattern and satisfy the need of neural network studying and diagnosing.Then.the turbo-rotor fault identification and diagnosis problems were investigated by using a BP(back-propaga-tion)neural network.According to the BP neural network problems,the parallel BP neural network method of multi-fault diagnosis and classification was presented and investigated.The results indicated that the parallel Bp neural network method could solve the turbo-rotor multi-fault diagnosis problems.     

江苏复杂小断块油藏老井侧钻实践与认识

利用停关、低效井实施老井侧钻,其条件包括油藏、井身及技术经济等3个方面。侧钻效益的好坏与油藏类型、侧钻目标有着很大关系,侧钻断块油层、挖掘构造高部位剩余油成功率高,边底水、高渗透油藏侧钻效果好。实践表明,老井侧钻是提高江苏复杂小断块油藏开发效果,降低投资、提高效益的一项重要手段。