GO/PI复合纳米纤维的制备及其过滤性能研究

为制备高过滤效率、低过滤阻力的空气过滤材料,将氧化石墨烯纳米颗粒(GO)掺杂到聚酰亚胺(PI)纺丝溶液中,制备氧化石墨烯/聚酰亚胺(GO/PI)复合纳米纤维过滤材料。通过观察其形貌、过滤性能来确定最优纺丝工艺参数。结果表明:当PI质量分数为30%,GO质量分数为1%,纺丝电压为25 kV,接收距离为20 cm时,复合纳米薄膜的纤维形貌较好,过滤性能优良。与PI纯组分纳米纤维过滤材料相比,GO/PI复合纳米纤维过滤材料的过滤性能更好,制得GO/PI复合纳米纤维膜的平均孔径为1.8μm,过滤效率为99.68%,过滤阻力仅为85.35 Pa。     

中国天然气市场可持续发展分析

承接2016年回暖之势,2017年中国天然气市场迎来爆发式增长,全年天然气消费量达2 335×10~8 m~3、年消费增量达353×10~8 m~3。为此,有必要剖析推动中国天然气市场爆发式增长的主要因素并预测其未来发展的可持续性。研究结果表明:(1)2017年爆发式增长主要受益于宏观经济形势好转、大气污染防治措施深入实施、化工等大宗产品价格回升、华东地区天然气发电负荷增加、管道天然气供应价格相对较低、LNG汽车市场整体呈现回暖态势等因素;(2)经济发展形势、"煤改气"的推进、政策实施方向、油气价格趋势等外部因素将能继续支持天然气市场的快速增长;(3)但天然气产业的自身条件、资源和基础设施条件将对市场发展造成制约。结论认为:(1)2020年之前我国天然气市场需求量仍会保持快速增长的趋势,但难以维持每年300×10~8 m~3的增长规模;(2)工业燃料和发电是天然气市场发展的主要方向;(3)环渤海等地区是未来天然气需求量增长的主要区域。为了保持我国天然气市场的发展态势,提出如下建议:(1)千方百计扩大天然气供应规模,在认真做好国产非常规天然气资源开发的同时,积极落实进口天然气资源;(2)毫不松懈地建设基础设施,管道要超前建设,LNG接收站要加大力度建设,地下储气库等调峰设施要鼓励建设;(3)科学合理地理顺天然气价格,居民价格与非居民价格并轨首当其冲,确立价格是平衡供需关系的杠杆作用,减少行政干涉。     

深水油区多油田组合开发及产量接替优化

对由多个油田组成的海外深水开发项目区块，高效开发的关键是针对不同油田的特点，统筹规划不同油田投产次序和产量接替的组合方式，实现有效开发时间内的整个开发项目的最大收益。文中基于深水油田特点及开发要求，通过3个方面的研究来实现深水油区不同油田组合的储量动用及产量接替优化。一是建立深水油田储量分级评价标准，并利用数学综合评价方法确定不同油田的储量等级；二是通过分析深水油田产量运行主控因素，建立不同等级储量的关键开发指标预测模型，可作为不同油田组合开发下产量运行计算的基础；三是建立满足不同限制条件、开发效益最大的数学模型，并利用过程控制理论进行计算，优化得到不同储量等级油田的组合方式和逐次动用程序。将本文方法应用在XF深水油区的开发部署中，基于油田实际数据，进行了不同条件下、多个油田储量动用及产量接替方式的计算，优化结果符合实际开发需求，提高了深水油田开发决策的科学性。     

闪蒸纺纳微米纤维非织造技术的研究进展

为拓展纳微米纤维的制备方法,拓宽防护服面料的来源,对闪蒸法制备纳微米纤维非织造布及其用于防护服的研究进展进行综述。介绍了闪蒸纺丝所用原料的种类及目前存在的问题,对纺丝工艺、纺丝过程及产品进行阐述;总结了闪蒸纺丝技术国内外研究现状及趋势,分析了闪蒸非织造布的特点和应用;讨论了闪蒸非织造布防护服的分类以及目前使用中存在的问题;最后提出闪蒸纺丝技术是目前发展前景良好的纳微米纤维非织造布制备技术,闪蒸非织造布可作为一种理想的防护服面料,发展该技术对提高我国非织造行业技术水平,保护人民生命健康具有重要意义。     

Influence and comparison of emerging techniques of yarn manufacturing on physical–mechanical properties of polyester-/cotton-blended yarns and their woven fabrics

Abstract

In this study, the physical–mechanical properties of ring spun, ring compact, rotor and air-vortex yarns were investigated. The study was carried with yarn having linear densities of 24.4 tex and 36.7 tex, which were then converted to woven fabrics. The ring spun yarns have higher values of strength but also with higher strength irregularities. Extra-ordinarily low hairiness was observed in air-vortex yarns due to its unique yarn formation technique. The deviation rate (DR) of yarns have correlation with the mass spectrogram of respective yarns obtained from USTER Tester 5. Rotor and air-vortex yarns exhibited higher coefficient of friction. The woven fabrics made from ring spun yarns exhibited higher tensile and tear strength with higher elongation at break. The fabrics made from air-vortex yarns have very good pilling grade due to less protruding fibres on their surface and good structural integrity.     

提升超深层超高压气藏动态储量评价可靠性的新方法——物质平衡实用化分析方法

超深层大气田一般都具有高压超高压、基质致密、裂缝发育等特点,其动态储量评价结果具有较强的不确定性。为了准确评价该类型气藏的动态储量,首先基于高压超高压气藏物质平衡方程,深入分析了岩石有效压缩系数与岩石累积有效压缩系数的相关关系,优选出适合于高压超高压气藏动态储量评价的物质平衡分析方法 ;然后,基于非线性回归法确定了动态储量评价的起算条件,针对未达到起算条件的情形建立了半对数典型曲线拟合法,并采用该方法计算了3个超高压气田(藏)的动态储量,进而验证其可靠性。研究结果表明:(1)高压超高压气藏物质平衡方程中的气藏累积有效压缩系数是影响该类气藏动态储量评价结果的关键参数,该参数是原始地层压力和当前平均地层压力的函数,而其数值难以通过岩心实验测得;(2)针对高压超高压气藏,推荐采用不需要压缩系数的非线性回归法进行动态储量评价;(3)采用非线性回归法计算动态储量的起算点(无量纲视地层压力与累计产气量关系曲线偏离直线的起点)无法通过理论计算得到,基于图解法的统计结果得到不同无量纲线性系数(ωD)情形下起算点对应的无量纲视地层压力衰竭程度介于0.06～0.38,基于实例气藏数据统计得到的起算点也在此范围内;(4)未达到起算条件时可采用半对数典型曲线拟合法估算动态储量,动态储量与视地质储量的比值(G/G_(app))是ωD的函数,ωD越大,(G/G_(app))越小;(5)处于试采阶段的高压超高压气藏,应尽可能延长试采时间,以提高动态储量评价的可靠性;对处于开发中后期的高压超高压气藏,则应以动态储量为基础制订气藏综合治理措施,进而不断改善气藏的开发效果。     

自旋对角接触球轴承弹流润滑与油膜刚度的影响

根据角接触球轴承自旋运动特征，同时考虑弹流润滑效应，建立角接触球轴承考虑自旋运动的弹流润滑模型；采用多重网格法求解弹性变形，利用有限差分法迭代求解雷诺方程，得到较为精确的数值解；分析不同赫兹接触压力、滚道表面粗糙度下自旋对角接触球轴承弹流润滑和油膜刚度的影响。结果表明：考虑自旋时随着Hertz接触压力、自旋角速度增大，油膜厚度减小，油膜压力增大，油膜承压区域呈细长状，并向接触中心靠近；随着滚道表面粗糙度幅值增大，油膜压力和膜厚均出现了波动，且考虑自旋运动时，轴承油膜厚度明显减小，油膜局部压力峰值更大；随着卷吸速度、润滑油黏度增大，油膜刚度减小，而考虑自旋运动时油膜刚度值更大；随着自旋角速度增大，油膜刚度逐渐增大。     

天然橡胶期货市场回顾及后市展望

2019年天然橡胶期货市场起起落落,沪胶价格继续低位震荡。2020年天然橡胶供大于求的局面仍不会发生根本性改变,由极端天气引发的天然橡胶市场行情变动可能会减小,汽车行业可能会在政策支持下再次振兴,尤其重型卡车市场会成为亮点,轮胎企业继续寻求扩大出口。2020年上半年,天然橡胶期货市场可能还会受到2019年异常天气和病害等的余波作用,胶价会达到一个相对的高点,价格底部抬升,但很难出现持续性上涨的市场行情。2020年下半年,随着天然橡胶产量的季节性增长,胶价可能会再次回落。     

Machine learning methods for short‐term bid forecasting in the renewable energy market: A case study in Italy

In liberalized markets, there usually exists a day‐ahead session where energy is sold and acquired for the following production day. Owing to the high uncertainty of its production, renewable energy (wind in particular) can significantly influence the network imbalance of the following day. In this work, we consider the problem of predicting the sum of the bid volumes for wind energy of all the producers inside the day‐ahead energy market. This is a valuable tool to be used by an energy provider in order to determine the imbalance of a market zone and, thus, properly size its bids. In particular, we focus on the estimation of the possible relationship between the meteorological forecasts and the wind power offered on the market by the companies for a market zone. We propose a machine learning model which is used to compute a 1‐day‐ahead forecast. The input‐output mapping is obtained by support vector regression. The input feature vector is defined by a suitable feature extraction technique since the meteorological forecasts are given on a lattice of thousands of geographical points. The computational experiments are performed considering the Italian market as a case study (years 2012‐2016). The results show that the proposed feature extraction technique, selecting only some geographical zones, manages to reduce the error attained using all the features. Moreover, classical statistical methods are shown to be outperformed by machine learning models. The analysis reveals also some weaknesses of the model, which may be due to other nonmeteorological factors at play.     

Binary whale optimization algorithm: a new metaheuristic approach for profit-based unit commitment problems in competitive electricity markets

This article presents a metaheuristic approach, the binary whale optimization algorithm (BWOA), to solve complex, constrained, non-convex, binary-nature profit-based unit commitment (PBUC) optimization problems of a price-taking generation company (GenCo) in the electricity market. To simulate the binary-nature PBUC problem, the continuous, real-value whale position/location is mapped into binary search space through various transfer functions. This article introduces three variants of BWOA using tangential hyperbolic, inverse tangent (arctan) and sigmoidal transfer functions. The effectiveness of the BWOA approaches is examined in test systems with different market mechanisms, i.e. an energy-only market, and energy and reserve market participation with different reserve payment methods. The simulation results are presented, discussed and compared with other existing approaches. The convergence characteristics, solution quality and consistency of the results across different BWOA variants are discussed. The superiority and statistical significance of the proposed approaches with respect to existing approaches is also presented.