基于负载敏感回路的起竖液压系统仿真

介绍负载敏感技术在发射车起竖液压系统中的应用,通过AMESim搭建负载敏感泵、平衡阀、多路阀以及多级液压缸等核心元件的仿真模型并进行系统仿真,提出采用多联多路阀控制多级液压缸的匹配组合方式,以适应起竖及回收过程中多级液压缸的面积比变化,解决了大面积比回收时回油路过度节流、系统憋压的问题.     

精细注水配套工艺技术优化研究

本文通过对注水配套工艺的优化研究,有效提高奈曼油田分注率和配注合格率,提高精细注水开发效果。     

An SOFC anode model using TPB-based kinetics

Fundamental studies focusing on the electrode kinetics are essential in understanding the fuel cell operation and optimizing the electrode designs. In this study, we determined the triple-phase boundary (TPB)-based kinetics of hydrogen electrochemical oxidation using nickel patterned electrode experimental data and the Butler-Volmer formalism of the oxidation process. The same kinetics are then incorporated in a cermet electrode electrochemical model to estimate the effective TPB density of the nickel/yittrium-stabilized zirconia cermet anode. The kinetics are found to be of the same order of magnitude as previously determined by the microstructure reconstruction of cermet anode. Simulation results further revealed that the effective TPB density is several orders of magnitude lower than the typically reported physical densities of the cermet anode that possibly suggests that only a minor fraction of the physical TPB is actually required or available to produce the cell current at given cell voltage. The effect of various operating conditions on the anode activation overpotential is also investigated and discussed in this study.     

西溪南村民宿外部空间设计的模式语言提取

利用传统村落中的自然人文资源来开发产品是民宿行业的主流趋势之一,根据对西溪南村民宿的调研走访,对其外部空间的现状以及问题进行分析,借鉴亚历山大的《建筑模式语言》一书,将西溪南村中民宿外部空间的设计手法用模式语言的方式进行研究和总结,并提取出其民宿中构建庭院、花园、露台、停车位的模式语言。     

Three-dimensional Entity Resolution with JedAI

Entity Resolution (ER) is the task of detecting different entity profiles that describe the same real-world objects. To facilitate its execution, we have developed JedAI, an open-source system that puts together a series of state-of-the-art ER techniques that have been proposed and examined independently, targeting parts of the ER end-to-end pipeline. This is a unique approach, as no other ER tool brings together so many established techniques. Instead, most ER tools merely convey a few techniques, those primarily developed by their creators. In addition to democratizing ER techniques, JedAI goes beyond the other ER tools by offering a series of unique characteristics: (i) It allows for building and benchmarking millions of ER pipelines. (ii) It is the only ER system that applies seamlessly to any combination of structured and/or semi-structured data. (iii) It constitutes the only ER system that runs seamlessly both on stand-alone computers and clusters of computers — through the parallel implementation of all algorithms in Apache Spark. (iv) It supports two different end-to-end workflows for carrying out batch ER (i.e., budget-agnostic), a schema-agnostic one based on blocks, and a schema-based one relying on similarity joins. (v) It adapts both end-to-end workflows to budget-aware (i.e., progressive) ER. We present in detail all features of JedAI, stressing the core characteristics that enhance its usability, and boost its versatility and effectiveness. We also compare it to the state-of-the-art in the field, qualitatively and quantitatively, demonstrating its state-of-the-art performance over a variety of large-scale datasets from different domains.The central repository of the JedAI’s code base is here: https://github.com/scify/JedAIToolkit .A video demonstrating the JedAI’s Web application is available here: https://www.youtube.com/watch?v=OJY1DUrUAe8.     

Optimization of energy exchange inmicrogrid networks: a coalition formationapproach

In this paper, we elaborate a new strategy based on cooperative game theory models to encourage and manage the interactions in a MicroGrid network. The proposed strategy optimizes the cooperation and the energy exchange in a distributed μGrid network. The strategy consists of a two stage algorithm: Coalition formation algorithm which was specifically created to approximate the optimal set of coalitions that return considerable savings. And the Matching game to manage the energy exchange inside each coalition. The performance of our strategy was verified through simulations. These latter show that the losses can be considerably decreased by the use of the proposed strategy: the rate of the loss reduction can reach up to 20% if the two stages are applied on the network. Moreover, the strategy proved to have a fast convergence which makes it operational for real implemented networks.     

A neural network-based shape control system for cold rolling operations

In cold steel rolling, strip shape is crucial to product quality. For modern rolling mills, there are a number of different ways to control the strip shape, including adjusting the side depression, bending the work rolls and axial shifting the middle roll. However, these controls are not independent and hence, must be used with great care. This paper introduces a new method for strip shape control. It takes two steps: the first step is to use an Artificial Neural Network (ANN) to recognize the strip shape pattern. The second step is to apply one or a combination of several controls accordingly. This process may take several iterative steps. The new method is validated on an 8000 KN HC mill. The results demonstrated the new method could reduce the strip shape error step by step.     

Local convergence of the fuzzy c-Means algorithms

Much understanding has recently been gained concerning global convergence properties of the fuzzy c-Means (FCM) family of clustering algorithms. These global convergence properties, which hold for all iteration sequences, guarantee that every FCM iteration sequence converges, at least along a subsequence, to a stationary point of an FCM objective function. In this paper we prove a local convergence property, that is, a property pertaining to iteration sequences started near a solution. Specifically, a simple result is proved which shows that whenever an FCM algorithm is started sufficiently near a minimizer of the corresponding objective function, then the iteration sequence must converge to that particular minimizer. The result guarantees that once captured by the local neighborhood of a minimizer, the succeeding iterate sequence will not escape—thus, infinite oscillation of such a sequence cannot occur. The rate of convergence of the sequence to such a point is also discussed.