Development of mobile miniature natural gas liquefiers

With increasing consumption of natural gas (NG), small NG reservoirs, such as coalbed methane and oil field associated gas, have recently drawn significant attention. Owing to their special characteristics (e.g., scattered distribution and small output), small-scale NG liquefiers are highly required. Similarly, the mixed refrigerant cycle (MRC) is suitable for small-scale liquefaction systems due to its moderate complexity and power consumption. In consideration of the above, this paper reviews the development of mobile miniature NG liquefiers in Technical Institute of Physics and Chemistry (TIPC), China. To effectively liquefy the scattered NG and overcome the drawbacks of existing technologies, three main improvements, i.e., low-pressure MRC process driven by oil-lubricated screw compressor, compact cold box with the new designed heat exchangers, and standardized equipment manufacturing and integrated process technology have been made. The development pattern of “rapid cluster application and flexible liquefaction center” has been eventually proposed. The small-scale NG liquefier developed by TIPC has reached a minimum liquefaction power consumption of about 0.35 kW·h/Nm³. It is suitable to exploit small remote gas reserves which can also be used in boil-off gas reliquefaction and distributed peak-shaving of pipe networks.     

Pattern search algorithms for nonlinear inversion of high-frequency Rayleigh-wave dispersion curves

Inversion of Rayleigh wave dispersion curves is challenging for most local-search methods due to its high nonlinearity and to its multimodality. In this paper, we implemented and tested a Rayleigh wave dispersion curve inversion scheme based on GPS Positive Basis 2N, a commonly used pattern search algorithm. Incorporating complete poll and complete search strategies based on GPS Positive Basis 2N into the inverse procedure greatly enhances the performance of pattern search algorithms because the two steps can effectively locate the promising areas in the solution space containing the global minima and significantly reduce the computation cost, respectively.The proposed inverse procedure was applied to nonlinear inversion of fundamental-mode Rayleigh wave dispersion curves for a near-surface shear (S)-wave velocity profile. The calculation efficiency and stability of the inversion scheme are tested on three synthetic models and a real example from a roadbed survey in Henan, China. Effects of the number of data points, the reduction of the frequency range of the considered dispersion curve, errors in P-wave velocities and density, the initial S-wave velocity profile as well as the number of layers and their thicknesses on inversion results are also investigated in the present study to further evaluate the performance of the proposed approach.Results demonstrate that pattern search algorithms applied to nonlinear inversion of high-frequency surface wave data should be considered good not only in terms of accuracy but also in terms of the computation effort due to their global and deterministic search process.     

随机通胀下基于终止风险的DB养老金计划的保费估值

针对随机通胀以及终止风险对DB养老金计划的养老金支付问题的影响,提出了在随机通胀的条件下养老金福利担保公司(Pension Benefit Guaranty Corporation,PBGC)为基于提前终止和遇险终止风险的DB养老金计划提供担保的保费估值问题;由于DB养老金计划可能发生两类终止而导致养老基金赤字和计划发起人公司破产而未能按照承诺支付养老金,就会产生支付缺口,此时,引入PBGC将缺口的养老金支付给养老金计划受益人.PBGC的引入能够充分保障受益人的利益,大大降低了受益人承担的风险.忽略通货膨胀会使结果有误差,因此,在随机通胀的基础上构建了基于两类终止风险的DB养老金计划的保费估值模型.最后,对模型进行了数值模拟.结果表明,通货膨胀的加入使得保费有所增加,虽然这一结果给计划发起人增加了负担,需要支付更多的保费给PBGC,但却降低了PBGC所承担的风险.该模型引入了随机通胀,使得研究的结果更符合实际.     

基于话题检测的自适应增量K-means算法

根据话题检测任务的定义和特点,本文分析了传统的增量聚类算法和K-means算法的优缺点,提出了基于话题检测的自适应增量K-means算法,设计了话题检测实验,实验结果证明了该算法提高了话题检测性能,具有良好的应用前景。     

Logistic视频字幕增强模型

目的：为提高复杂背景下的视频字幕在OCR中的识别率,需要对提取的视频字幕进行有效地字幕增强。该文首次将Logistic模型应用到视频字幕增强中,提出了基于Logistic模型的融合多帧信息的视频字幕增强方法。方法：对字幕进行检测与跟踪,将出现在连续多帧中的同一字幕片段进行对齐;通过分析字幕片段在多帧中信息,提出字幕背景在时域上的变化特征、背景和字幕文本的固有特征,并将三个特征进行量化与融合,构建适用于字幕增强的Logistic模型,实现对视频字幕的增强。结果：对含阴影或描边效果的特殊复杂背景字幕、普通复杂背景字幕、单一背景字幕分别进行实验,增强后的字幕在OCR软件中的识别正确率分别为81.76%、97.13%、98.19%,与对比方法比较均有一定的提高。结论：实验结果表明,该文方法既可以降低字幕背景的复杂度,又可以提高字幕背景与文本的对比度,从而可以对复杂背景和单一背景下的视频字幕进行有效地增强。     

月表环境无线电波传播分段预测模型

针对经典无线电波传播模型不适用于月球特殊的传播环境问题,提出一种月表环境下电波传播损耗分段预测模型。该模型首先建立包含自由空间段、月面反射段和月球绕射段的理想分段预测模型,并给出不同区间内传播损耗预测算法,然后考虑传播路径剖面上多重障碍物导致的额外损耗,以及其对分段区间参数的修正方法。将其应用于美国国家航天局提供的月表实际场景,仿真结果表明该模型预测结果与“阿波罗”登月工程获得的实测数据非常吻合,可用于辅助月表无线通信系统的参数设计和性能评估。     

汉语概念复合块的自动分析

为解决句法分析任务中的块边界识别和块内结构分析问题,该文基于概念复合块描述体系进行了块分析探索。通过概念复合块与以往的基本块和功能块描述体系的对比分析,深入挖掘了概念复合块自动分析的主要难点所在,提出了一种基于“移进-归约”模型的汉语概念复合块自动分析方法。在从清华句法树库TCT中自动提取的概念复合块标注库上,多层次、多角度对概念复合块自动分析性能进行了纵向与横向评估,初步实验结果证明了该分析方法对简单概念复合块分析的有效性,为后续进行更复杂的概念复合块的句法语义分析研究打下了很好的基础。     

吐哈盆地台北凹陷水西沟群有利勘探区带预测

以台北凹陷水西沟群2套主力层段三工河组上段(J1s上)和西山窑组一段(J2x1)为研究对象,研究沉积体系、储层特征和关键成藏时期的古构造,明确有利储集相带,分析主要储集空间类型与储层分布规律.结果表明:浅水辫状河三角洲前缘的水下分流河道砂体是有利储集体;粒内溶蚀孔、基质晶间微孔和微缝是主要储集空间;关键成藏期以来的持续古构造高部位和断裂发育部位更利于发生溶蚀作用,是有利储层分布区,预测台北凹陷4个有利勘探区带,是下一步勘探方向.     

搜索引擎日志中“N+V+N”和“V+N+N”型短语功能类别识别

采用支持向量机(SVM)方法实现搜索引擎日志中"N+V+N"、"V+N+N"型短语功能类别识别。通过选取不同特征,构建多特征模板,实现对"N+V+N"、"V+N+N"型短语中名词短语、动词短语、主谓短语三种功能短语的自动识别,并且针对不同词性标注集对实验结果是否有影响进行了实验。实验结果显示,SVM在搜索引擎日志短语识别中有很高的识别率。     

可重构制造系统的多Agent模型

论文在介绍可重构制造系统重构方法的基础上,给出了可重构制造系统多Agent模型的结构,并详细描述了基于该模型的可重构车间加工系统的重构算法,最后对重构算法进行仿真验证了该算法的可行性。