油酸钾浓度及玄武岩纤维取向对天然橡胶/玄武岩纤维复合材料性能的影响

通过油酸钾溶液对玄武岩纤维进行表面改性处理,研究了不同浓度的油酸钾溶液对玄武岩纤维表面处理及玄武岩纤维取向对天然橡胶(NR)/玄武岩纤维(BF)复合材料综合性能的影响。结果表明,随着油酸浓度的增大,复合材料的拉伸强度、撕裂强度及断裂伸长率均表现为先增大后减小,且在油酸钾溶液的质量分数为7%时取得最大值,拉伸强度提高了15.6%,撕裂强度提高了12.1%;BF经定向排列后,复合材料的Payne效应减弱,采用径向取向制备的复合材料,其拉伸强度提高了2.3%,断裂伸长率降低了17.8%,但磨耗增加了8.3%。扫描电镜缝隙表明,7%浓度的油酸钾可以均匀地包覆在BF表面,纤维在橡胶中分散性较好。

腹腔镜前列腺癌根治术后切缘阳性的相关影响因素分析

目的:探究影响腹腔镜前列腺癌根治术(laparoscopic radical prostatectomy,LRP)后切缘阳性(positive surgical margin,PSM)的相关因素。方法:回顾性分析2016年1月至2017年12月177例于北京大学第一医院行LRP患者的临床资料,将患者分为术后PSM和切缘阴性组,分析各组不同的年龄、前列腺体积、穿刺前血清前列腺特异性抗原(prostate-specific antigen,PSA)值、穿刺阳性针数及其百分比、穿刺及术后病理的Gleason评分和术后病理T分期对术后切缘的影响。结果:177例患者中,患者术后PSM的阳性率为32.2%(57/177)。患者年龄、前列腺体积、穿刺前血清PSA值、穿刺及术后病理的Gleason评分与术后PSM之间无显著相关性(P>0.05)。穿刺阳性针数及其百分比、术后病理不同T分期的术后PSM与切缘阴性进行比较,差异具有统计学意义(P<0.05)。多因素Logistic回归模型分析显示,术后病理T分期是PSM的独立危险因素(OR为1.616,95%CI为1.062～2.459,P<0.05)。结论:LRP后PSM与前列腺穿刺阳性针数及其百分比、术后病理T分期之间具有相关性,且术后病理T分期是其独立危险因素。

Role of the Nocturnal Low-level Jet in the Formation of the Morning Precipitation Peak over the Dabie Mountains

The diurnal variation of precipitation over the Dabie Mountains(DBM) in eastern China during the 2013 mei-yu season is investigated with forecasts of a regional convection-permitting model. Simulated precipitation is verified against surface rain-gauge observations. The observed morning precipitation peak on the windward(relative to the prevailing synoptic-scale wind) side of the DBM is reproduced with good spatial and temporal accuracy. The interaction between the DBM and a nocturnal boundary layer low-level jet(BLJ) due to the inertial oscillation mechanism is shown to be responsible for this precipitation peak. The BLJ is aligned with the lower-level southwesterly synoptic-scale flow that carries abundant moisture.The BLJ core is established at around 0200 LST upwind of the mountains. It moves towards the DBM and reaches maximum intensity at about 70 km ahead of the mountains. When the BLJ impinges upon the windward side of the DBM in the early morning, mechanical lifting of moist air leads to condensation and subsequent precipitation.

Assimilating Surface Observations in a Four-Dimensional Variational Doppler Radar Data Assimilation System to Improve the Analysis and Forecast of a Squall Line Case

This paper examines how assimilating surface observations can improve the analysis and forecast ability of a four- dimensional Variational Doppler Radar Analysis System （VDRAS）. Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational （4DVAR） data assimilation system. A squall-line case observed during a field campaign is selected to investigate the performance of the technique. A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions. The surface-based cold pool, divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation. Three experiments--assimilating radar data only, assimilating radar data with surface data blended in a mesoscale background, and assimilating both radar and surface observations with a 4DVAR cost function--are conducted to examine the impact of the surface data assimilation. Independent surface and wind profiler observations are used for verification. The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations. It is also shown that the additional surface data can help improve the analysis and forecast at low levels. Surface and low-level features of the squall line-- including the surface warm inflow, cold pool, gust front, and low-level wind--are much closer to the observations after assimilating the surface data in VDRAS.

Optimal capacity planning of combined renewable energy source-pumped storage and seawater desalination systems

As water scarcity is becoming a growing threat to human development, finding effective solutions has become an urgent need. To make better use of water resources, seawater desalination and storage systems using renewable energy sources(RES) are designed and implemented around the world. In this paper, an optimal capacity planning method for RES-pumped storage-seawater desalination(RES-PS-D) system is introduced. The configuration of the RES-PS-D system is clarified first, after which a cost-benefit analysis is performed using all cost and benefit components. A function for determining maximum economic benefits of the RES-PS-D system is then established, and the constraints are proposed based on various limitations. The mixed-integer linear programming algorithm is applied to solve the optimal function. A case study is introduced to validate the feasibility and effectiveness of the method. The conclusion shows that the strategy is suitable for solving the configuration optimization problem, and finally both merits and defects of the method are discussed.

Slight Co-doping tuned magnetic and electric properties on cubic BaFeO_(3) single crystal

The single crystal of cubic perovskite BaFeO3 shows multiple magnetic transitions and external stimulus sensitive magnetism.In this paper,a 5%-Co-doped BaFeO_(3)(i.e.BaFe_(0.95)Co_(0.05)O_(3))single crystal was grown by combining floating zone methods with high-pressure techniques.Such a slight Co doping has little effect on crystal structure,but significantly changes the magnetism from the parent antiferromagnetic ground state to a ferromagnetic one with the Curie temperature TC≈120 K.Compared with the parent BaFeO3 at the induced ferromagnetic state,the saturated magnetic moment of the doped BaFe_(0.95)Co_(0.05)O_(3) increases by about 10%and reaches 3.64μB/f.u.Resistivity and specific heat measurements show that the ferromagnetic ordering favors metallic-like electrical transport behavior for BaFe_(0.95)Co_(0.05)O_(3).The present work indicates that Co-doping is an effective method to tune the magnetic and electric properties for the cubic perovskite phase of BaFeO_(3).

A Distributed Self-Consistent Control Method for Electric Vehicles to Coordinate Low-Carbon Transportation and Energy

Dear Editor,In this letter, a distributed self-consistent control method to coordinate low-carbon transportation and energy is proposed to address the efficient utilization of regional transportation energy and renewable energy. Specifically, taking into account the coordinated development of transportation, power grids, and renewable energy, transportation energy self-consistent, including instant self-consistent rate and power self-consistent rate。

Multi-objective Optimization of Integrated Energy Systems Considering Ladder-type Carbon Emission Trading and Refined Load Demand Response

In this paper,a novel multi-objective optimization model of integrated energy systems(IESs)is proposed based on the ladder-type carbon emission trading mechanism and refined load demand response strategies.First,the carbon emission trading mechanism is introduced into the optimal scheduling of IESs,and a ladder-type carbon emission cost calculation model based on rewards and penalties is established to strictly control the carbon emissions of the system.Then,according to different response characteristics of electric load and heating load,a refined load demand response model is built based on the price elasticity matrix and substitutability of energy supply mode.On these basis,a multi-objective optimization model of IESs is established,which aims to minimize the total operating cost and the renewable energy source(RES)curtailment.Finally,based on typical case studies,the simulation results show that the proposed model can effectively improve the economic benefits of IESs and the utilization efficiency of RESs.

Robust Optimal Operation of Active Distribution Network Based on Minimum Confidence Interval of Distributed Energy Beta Distribution

With the gradual increase of distributed energy penetration,the traditional optimization model of distribution network can no longer guarantee the stable and efficient operation of the distribution network.In order to deal with the inevitable uncertainty of distributed energy,a new robust optimal operation method is proposed for active distribution network(ADN)based on the minimum confidence interval of distributed energy Beta distribution in this paper.First,an ADN model is established with second-order cone to include the energy storage device,capacitor bank,static var compensator,on-load tap changer,wind turbine and photovoltaic.Then,the historical data of related distributed energy are analyzed and described by the probability density function,and the minimum confidence interval is obtained by interval searching.Furthermore,via taking this minimum confidence interval as the uncertain interval,a less conservative two-stage robust optimization model is established and solved for ADN.The simulation results for the IEEE33-bus distribution network have verified that the proposed method can realize a more stable and efficient operation of the distribution network compared with the traditional robust optimization method.

Analysis of Pressure Forcings for the Vertical Turbulent Fluxes in the Convective Boundary Layer at Gray Zone Resolutions

At kilometer and sub-kilometer resolutions,known as the numerical gray zone for boundary layer turbulence,the atmospheric boundary layer turbulence becomes partially resolved and partially subgrid-scale(SGS) in a numerical model,thus requiring scale-adaptive turbulence schemes.Such schemes are often built by modifying the existing parameterizations,either the planetary boundary layer(PBL) schemes or the large-eddy simulation(LES) closures,to produce the right SGS turbulent fluxes at gray zone resolutions.However,the underlying forcings responsible for the changes in the vertical turbulent fluxes are largely ignored in these approaches.This study follows the original approach of Wyngaard(2004) and analyzes the turbulent buoyancy and momentum flux budgets,to gain a better understanding of the variations of flux forcings at gray zone resolutions.The investigation focuses on the pressure covariance term,which is one of the most dominant terms in the budget equations.By using the coarse-grained LES of a dry convective boundary layer(CBL) case as reference,two widely-used pressure covariance models are evaluated and optimized across the gray zone resolution range.The optimized linear model is further evaluated a priori against another dry CBL case with a different bulk stability,and a shallow-cumulus-topped boundary layer case.The model applies well to both cases,and notably shows good performance for the cloud layer.Based on the analysis of the flux forcings and the optimized pressure model,a scale-adaptive turbulence model for the gray zone is derived from the steady-state flux budgets.