基于VR技术的智能变电站运行仿真培训系统

为了更加真实、直观地呈现智能变电站的运行整体结构,构建基于VR技术的智能变电站运行仿真培训系统。该系统通过5个模块协同完成智能变电站运行仿真培训,结合实际变电站的设备情况,采用二维纹理映射方法完成变电站设备仿真建模;系统利用虚拟现实交互模块呈现培训场景,参与培训人员能够通过人机交互设备,实现场景漫游和相关培训内容操作。测试结果表明:该系统能够较好地模拟出智能变电站的实际运行情况,参与培训的人员可以身临其境地完成整个变电站的巡视,更真实、直观地呈现智能变电站的整体状态。     

基于CiteSpace的资源型产业研究知识图谱分析

资源型产业发展为推进国家经济增长和工业化进程提供了重要保障。为深入了解资源型产业的研究情况，以CNKI数据库为数据源，搜集2000—2020年关于资源型产业的核心及以上期刊论文，利用CiteSpace软件从发文作者与研究机构分布、关键词共现网络和时区图谱等方面，绘制知识图谱，进行可视化分析。研究发现：资源型产业领域的研究成果愈加丰富，但研究群体间联系合作较少，且现有的合作研究主要集中在所处地域资源富集和具有学科优势的研究机构及学者；资源型产业领域的研究热点可概括为产业发展、资源型城市、产业集群、产业结构、产业链和产业集聚等方面；针对资源型产业领域未来可从资源型产业相关理论研究、创新发展模式和可持续发展等方面深入展开。     

Design of frameworks for self-adaptive service-oriented applications: A systematic analysis

Self-adaptive service-oriented Applications (Self-Apps) must be able to understand themselves or the environment in which they are executed, and propose solutions to meet changing conditions. The development of these applications is not a trivial task, since it encompasses issues from different research areas. Despite the importance of frameworks for Self-Apps, there is a lack of comprehensive analysis of how the design of such applications is performed, and regarding the standardization of concepts and coverage of minimum requirements for Self-Apps. The main contribution of this article is to present this comprehensive analysis, providing the state of the art for this subject. This analysis was built through a Systematic Mapping Study, based on a total of 65 studies, from which we identify the main attributes for Quality of Service (QoS), search strategies, and service management strategies employed in the design of frameworks for Self-Apps. The main aspects of requirements involved in the design of Self-Apps were pointed out to stakeholders. For example, these applications must implement a method for evaluation of QoS based on metrics. We also put forward the S-Frame, a modular solution that brings together the main features for the design of Self-Apps, and describe the main challenges concerning these applications.     

Revealing Nanomechanical Domains and Their Transient Behavior in Mixed-Halide Perovskite Films

Halide perovskites are a versatile class of semiconductors employed for high performance emerging optoelectronic devices, including flexoelectric systems, yet the influence of their ionic nature on their mechanical behavior is still to be understood. Here, a combination of atomic-force, optical, and compositional X-ray microscopy techniques is employed to shed light on the mechanical properties of halide perovskite films at the nanoscale. Mechanical domains within and between morphological grains, enclosed by mechanical boundaries of higher Young's Modulus (YM) than the bulk parent material, are revealed. These mechanical boundaries are associated with the presence of bromide-rich clusters as visualized by nano-X-ray fluorescence mapping. Stiffer regions are specifically selectively modified upon light soaking the sample, resulting in an overall homogenization of the mechanical properties toward the bulk YM. This behavior is attributed to light-induced ion migration processes that homogenize the local chemical distribution, which is accompanied by photobrightening of the photoluminescence within the same region. This work highlights critical links between mechanical, chemical, and optoelectronic characteristics in this family of perovskites, and demonstrates the potential of combinational imaging studies to understand and design halide perovskite films for emerging applications such as photoflexoelectricity.     

Shape optimization of bi-directional flow passage components based on a genetic algorithm and computational fluid dynamics

The inlet/outlet is an important part of a water conveyance system in a pumped storage power station (PSPS). Its hydraulic characteristics are directly related to the operation and economic benefit of the PSPS. Frequent changes between inflow and outflow operations pose significant challenges in the design of the inlet/outlet diffusion segment shape. In this study, an effective optimization method, including three-dimensional parametric modelling, computational fluid dynamics and a genetic algorithm, is introduced and coupled to the design of the diffusion segment shape. The hydraulic characteristics of bi-directional flow, including the head loss, velocity uneven distribution and uneven discharge distribution, are selected as the objective function in the optimization method. Using this method, the recommended shape of the inlet/outlet is studied and its hydraulic characteristics are discussed. The results indicate that the optimized inlet/outlet has better performance.     

Value stream mapping approach and analytical network process to identify and prioritize production system’s Mudas (case study: natural fibre clothing manufacturing company)

The current research has been done to identify and prioritize the Mudas of the production line of a natural fibre clothing manufacturing company; in this way, value stream mapping has been used to identify the Mudas, then analytical hierarchy method has been used to screen the Mudas. In the first step, necessary information to design value stream of production process has been obtained by observation, measurement and interview; afterward, according to the obtained information and by forming a focus group, Mudas in the production line have been identified and prioritized according to seven categories of Mudas. In order to prioritizing the Mudas by the usage of analytical hierarchy method, the Super Decision software has been applied. Then, according to the obtained priorities, suggested map of the future value system has been drawn and some suggestions have been presented to eliminate Mudas and move towards the lean manufacturing.     

GEOPHYSICAL CHARACTERIZATION OF THE SANGU GAS FIELD,OFFSHORE, BANGLADESH: CONSTRAINTS ON RESERVOIRS

The only produced offshore gas field in Bangladesh, known as the Sangu field, is located in the Hatiya Trough in the east of the Bay of Bengal, and has estimated total reserves of about 1055 BCF GIIP. The early shut-down of the field in October 2013 may have resulted in significant volumes of recoverable gas being left in the subsurface over a depth range of 1893 m to 3640 m. In this paper, seismic and well log data were analyzed and interpreted in order to investigate the structure and stratigraphy of the Sangu field, together with the lithology, extent and petrophysical properties of the reservoir. The general lithostratigraphy at Sangu has some similarity to that of the Surma Basin of the Bengal Foredeep. Reservoir rocks consist of Miocene and Pliocene deltaic sandstones and deep-water clastics. The source rock is the Miocene Bhuban Shale which is mature for gas generation in the Hatiya Trough. Three Neogene seismic stratigraphic megasequences were recognised at Sangu and are interpreted to have been deposited respectively in fluvial, delta front and shelf slope or marginal marine settings. Based on an analysis of wireline logs from wells Sangu-1 and Sangu-5 and on seismic-to-well ties, a series of reservoir units referred to (from the base up) as the T1 (E, D, C, A&B), Supra-T1, T2 and T3 have been identified. Petrophysical analyses showed that the average total porosity of these reservoir units is >13%, the permeability is in general less than10 mD, and the gas saturation ranges from 24% to 80%. Mapping of the reservoirs shows that the structure at Sangu is an asymmetric anticline with a NNW-SSE axial trend. Amplitude data have allowed the delineation of two other potential reservoir zones in the field at depths of 2900-3000 m and 3550-3750 m. The study will contribute to future offshore gas exploration and development in the Bay of Bengal region based on the geological and geophysical characteristics of the reservoirs delineated.     

面向数据流结构的指令映射优化方法

在高性能计算领域,数据流是一类重要的计算结构,也在很多实际场景表现出很好的性能和适用性。在数据流计算模式中,程序是以数据流图来表示的,数据流计算中一个关键的问题是如何将数据流图映射到多个执行单元上。通过分析现有数据流结构的指令映射方法及其不足,提出了基于数据流结构的新型指令映射优化方法。主要是根据多地址共享数据包的特性对指令映射方法进行优化,延迟多地址共享数据路由包的拆分,减少网络拥堵。     

Adaptive neural network command filtered backstepping control of pure‐feedback systems in presence of full state constraints

An adaptive neural network (NN) command filtered backstepping control is proposed for the pure‐feedback system subjected to time‐varying output/stated constraints. By introducing a one‐to‐one nonlinear mapping, the obstacle caused by full stated constraints is conquered. The adaptive control law is constructed by command filtered backstepping technology and radial basis function NNs, where only one learning parameter needs to be updated online. The stability analysis via nonlinear small‐gain theorem shows that all the signals in closed‐loop system are semiglobal uniformly ultimately bounded. The simulation examples demonstrate the effectiveness of the proposed control scheme.