Fiber–fiber interactions in carbon mat thermoplastics

Carbon mat thermoplastics (CMT) consisting of 12.7 mm long, chopped carbon fibers in a polypropylene matrix were manufactured using the wetlay technique at fiber volume fractions (FVF) from 10% to 25%, and tests simulating the compression molding process were conducted. The packing stress of the CMT followed a power law relation with FVF. A single fiber pull-out fixture was used to measure the frictional and hydrodynamic lubrication coefficients at fiber–fiber touch points, and results were fit with an existing relation for glass mat thermoplastics. In isothermal squeeze flow the load–displacement behavior for the 10% FVF CMT was similar in shape to that for a fluid with a yield stress. However, for FVFs of 15–25%, the load–displacement curves showed a load spike at the beginning of the flow, then followed the curve for a fluid with a yield stress. The spike was attributed to fiber breakage that increased with increasing FVF of the sample.     

折线链节点标注技术

针对传统多边形位置关系计算比较烦琐,以及简单多边形的理论难以拓展到一般多边形的问题,提出标注节点状态的方法.通过定义11种位置来描述折线链上每个节点的状态,再采用"线段端点与线段"和"线段端点与邻折线"的标注方法来实现任意折线链的标注,同时利用两线段分割预处理使相交仅发生在端点处,从而使算法更高效;然后给出折线链基本位置关系的节点特征,并且探讨了三维顶点的标注方法.该方法的标注原理简单、方法实用,算法空间和时间复杂度分别为O(n)和O(n2).实验结果表明,该方法对任意形状的折线链都能实现稳定标注;通过搜索节点状态特征可以求解折线链间的相互关系,还可以实现一般折线链的碰撞检测、相交区域计算以及多边形简单化分解等.     

Influential facilities placement over moving objects

Distributed and Parallel Databases - In this paper we propose and study the problem of k-Collective influential facility placement over moving object. Specifically, given a set of candidate...     

直齿圆柱齿轮差速器运动学与动力学分析仿真

关于电动车操纵稳定性优化问题,设计了某型微电动车用新型直齿圆柱齿轮差速器。为准确把握直齿差速器的功能特点及工作动载荷情况,在参考锥齿差速器研究方法和成果的基础上,根据直齿差速器的运动特性和转矩特性。为提高性能,采用虚拟样机技术,在PRO/E中建立了直齿差速器三维装配模型,利用无缝接口Mech/pro将模型导入ADAMS中建立虚拟样机模型,在虚拟环境中进行了直线和转弯两种工况下的差速器运动学和动力学仿真,得到了齿轮转速特性曲线和啮合力仿真曲线。通过转速曲线验证了差速功能,并将齿轮啮合力仿真结果与理论数值对比,验证了仿真模型的有效性。啮合力仿真曲线可作为差速器齿轮优化设计的依据,并为动态优化及疲劳寿命预测提供指导。     

利用零序电流倍增特征的不接地系统故障选线

针对中性点不接地系统单相接地故障选线困难的问题,通过母线故障相接地故障转移与中性点接入小电阻的方式来增强故障信息从而选出故障线路。建立了故障转移阶段、并联电阻投入前后各个阶段的零序网络模型,分析了健全线路和故障线路各自的零序电流幅值的变化特征。在中性点小电阻投入、母线开关分闸前后各馈线零序电流幅值变化明显,健全线路零序电流在母线开关分闸后显著减小而故障线路零序电流增大。利用故障线路与健全线路的零序电流变化特征构建了不接地系统故障选线判据。大量的仿真计算验证了该方法对于不接地系统单相接地故障良好的适应性,有助于进一步提高故障选线准确率。     

生物质直燃发电大气污染物超低排放技术路线分析

总结了生物质燃料与煤的元素含量的差异,分析了生物质锅炉积灰、结渣、腐蚀的机理,梳理了生物质锅炉的烟气特点,并对选择性非催化还原脱硝技术、选择性催化还原脱硝技术、湿法脱硫技术在生物质电厂应用的局限性进行了讨论和总结。结果表明:固态高分子脱硝和催化剂脱硝脱硫均需特殊催化剂或脱硝剂,属于专利产品,运行成本高;氧化脱硝技术属于氧化吸收反应,产生易溶于水的硝酸盐,部分地区禁止采用该技术;陶瓷催化滤管一体化脱除技术运行维护简单,锅炉过氧燃烧可提高燃烧效率,延长空气预热器使用寿命,而且没有脱硫废水、烟囱防腐、白色烟羽等相关问题,适用于生物质锅炉硫、尘、硝超低排放。     

An intelligent negotiator agent design for bilateral contracts of electrical energy

In this paper, an intelligent agent (using the Fuzzy SARSA learning approach) is proposed to negotiate for bilateral contracts (BC) of electrical energy in Block Forward Markets (BFM or similar market environments). In the BFM energy markets, the buyers (or loads) and the sellers (or generators) submit their bids and offers on a daily basis. The loads and generators could employ intelligent software agents to trade energy in BC markets on their behalves. Since each agent attempts to choose the best bid/offer in the market, conflict of interests might happen. In this work, the trading of energy in BC markets is modeled and solved using Game Theory and Reinforcement Learning (RL) approaches. The Stackelberg equation concept is used for the match making among load and generator agents. Then to overcome the negotiation limited time problems (it is assumed that a limited time is given to each generator–load pairs to negotiate and make an agreement), a Fuzzy SARSA Learning (FSL) method is used. The fuzzy feature of FSL helps the agent cope with continuous characteristics of the environment and also prevents it from the curse of dimensionality. The performance of the FSL (compared to other well-known traditional negotiation techniques, such as time-dependent and imitative techniques) is illustrated through simulation studies. The case study simulation results show that the FSL based agent could achieve more profits compared to the agents using other reviewed techniques in the BC energy market.     

Approximate inference for dynamic Bayesian networks: sliding window approach

Dynamic Bayesian networks (DBNs) are probabilistic graphical models that have become a ubiquitous tool for compactly describing statistical relationships among a group of stochastic processes. A suite of elaborately designed inference algorithms makes it possible for intelligent systems to use a DBN to make inferences in uncertain conditions. Unfortunately, exact inference or even approximation in a DBN has been proved to be NP-hard and is generally computationally prohibitive. In this paper, we investigate a sliding window framework for approximate inference in DBNs to reduce the computational burden. By introducing a sliding window that moves forward as time progresses, inference at any time is restricted to a quite narrow region of the network. The main contributions to the sliding window framework include an exploration of its foundations, explication of how it operates, and the proposal of two strategies for adaptive window size selection. To make this framework available as an inference engine, the interface algorithm widely used in exact inference is then integrated with the framework for approximate inference in DBNs. After analyzing its computational complexity, further empirical work is presented to demonstrate the validity of the proposed algorithms.     

Transformation of hardening to softening behaviors induced by Sb substitution in CuO-doped KNN-based piezoceramics

Pb-free piezoceramics of K_0.5Na_0.5Nb_1-xSb_xO₃ + 1 mol% CuO are synthesized via a solid-state reaction. Furthermore, the transformation of hardening to softening behaviors induced by Sb substitution is exhibited and the corresponding microscopic mechanism is proposed. The CuO-doped K_0.5Na_0.5NbO₃ ceramic without adding Sb exhibits extremely hardening characteristics (i.e., ultrahigh Q_m of ∼2426, low tanδ of 0.32%, and pinched ferroelectric hysteresis loop) due to the formation of defect combinations (${({\text{Cu}}_{\text{Nb}}^{\text{'''}}-{\text{V}}_{\text{o}}^{••})}^{\text{'}}$ and ${({\text{V}}_{\text{o}}^{••}-{\text{Cu}}_{\text{Nb}}^{\text{'''}}-{\text{V}}_{\text{o}}^{••})}^{•}$). Whereas, the addition of Sb dramatically reduces the levels of defect combinations, leading to obviously softening properties (d₃₃ > 210 pC N⁻¹, k_p > 40%, low Q_m, and normal single P-E hysteresis loop). Our results indicate that the decrease of defect combinations with Sb addition should be responsible for the hardening-softening transformation of piezoelectricity and ferroelectricity in CuO-doped K_0.5Na_0.5Nb_1-xSb_xO₃ piezoceramics.     

分数跳-扩散下外汇期权定价

用保险精算方法,在股票价格服从分数跳-扩散过程,且无风险利率、波动率和期望收益率为时间的非随机函数,给出了外汇期权定价公式.