Combined imbibition system with black nanosheet and low-salinity water for improving oil recovery in tight sandstone reservoirs

Nanomaterials and low-salinity water(LSW)are two popular enhanced oil recovery(EOR)methods that have been widely studied in recent years.The former is used for in-depth conformance improvement and the latter for microscopic oil displacement(by altering the potential and contact angle).However,there are few literature on combining them to achieve synergistic effects,especially for tight sandstone res-ervoirs.Based on the reservoir conditions of the Jimusar Oilfield,this study investigated the oil recovery mechanism of the combined imbibition system,which was composed of black nanosheet(BN)and LSW.Its performances including decreasing interfacial tension,emulsification,and wettability alterations were evaluated.The imbibition differences between the single system of BN and LSW and the combined BN-LsW imbibition system were then compared.Results showed that the combined imbibition system had a better emulsification effect on the crude oil and could also alter the wettability of the core surface.Moreover,the combined system could increase both the imbibition rate and the ultimate oil recovery.The nuclear magnetic T2 spectrum also indicated that the addition of black nanosheets could divert more fluid into small pores and thus improve the microscopic sweep efficiency.

Improvements of marine clay slurries using chemicale-physical combined method(CPCM)

In this paper, the effectiveness, applicability and validity of chemicalephysical combined methods（CPCMs） for treatment of marine clay （MC） slurries were evaluated. The method CPCM1 combineschemical stabilization and vacuum preloading （VP）, while CPCM2 is similar to CPCM1 but includes boththe application of surcharge and use of geo-bags to provide confinement during surcharge preloading.The key advantage of CPCM2 using geo-bags is that the surcharge can be immediately applied on thechemically stabilized slurries. Two types of geo-bags were investigated under simulated land filling anddyke conditions, respectively. The test results show that the shear strength （cu） of treated slurry byCPCM2 is generally much higher than that by CPCM1. Besides, the use of CPCM2 can significantly reducethe treatment time due to the short drainage paths created by geo-bags. Overall, CPCM2 allows fasterconsolidation and higher preloading that help to achieve higher mechanical properties of the stabilizedslurry. There are consistent relationships between cU and water content of slurries treated by CPCM2.Several important observations were also made based on comparisons of experimental data. 2015 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting byElsevier B.V. All rights reserved.

Comparisons of Three Recurrent Selection Methods in the Improvement of Maize Populations

The maize population Csyn 4 was improved for three cycles with three recurrent selection methods MS1, MS1-HS, and MHSRRS in northern China. A total of 40 NC Ⅱ testcrosses were made by four testers with Csyn 4 and 10 improved populations, which were evaluated in four environments in the cropping season of 2005. Analysis of variance indicated a significant progress （P〈 0.05） in yield and other chief agronomic traits in the improved populations and testcrosses, demonstrating that the three recurrent selection methods were effective for increasing grain yield of testcrosses and improvement of general combining ability in maize population. The average grain yield increase of population Csyn 4 in MS1, MS1-HS, and MHSRRS recurrent selections was 266.7 kg ha^-1 （5.3%）, 288.0 kg ha^-1 （5.7%）, and 231.3 kg ha^-1 （4.6%） per cycle, while the grain yield of S 1 progeny of population for Csyn 4 was increased by 420.0 kg ha^-1 （10.9%）, 376.0 kg ha^-1 （9.8%）, and 414.7 kg ha^-1 （10.8%） per cycle in MS1, MS1-HS, and MHSRRS recurrent selections, respectively. Linear responses （b） in the MS1, MS1-HS, and MHSRRS recurrent selections were the same as the realized responses of the selection （G） for grain yield increase of Csyn 4 and S1 progeny of the populations. The grain yield of testcrosses increased by 3.3-5.2% on average per cycle. The value of heterosis did not display any differences amongst the different cycles of selections. The GCA for yield component traits of population Csyn 4 was improved significantly by means of three selection methods, whereas the GCA for plant height, ear height, days to silking, and days to pollen did not show significant increase in the recurrent selections. GCA for the number of tassel branches were decreased in the selections, while GCA for the number of plant leaves were increased, but the difference was not significant.

Improving cancer therapy by combining cell biological, physical, and molecular targeting strategies

Successful cancer therapy depends on selective killing of tumor cells while sparing normal cells. Selectivity can be achieved through treatment strategies that target tumor cells. A recent report from the Li laboratory （1） describes an elegant strategy to selectively kill tumor cells by combining several targeting strategies based on cell biological, physical, and molecular （genetic） properties of tumor and normal cells that enhances tumor cell killing in vitro and in an in vivo tumor xenograft model. The idea of using a multiplex targeting approach is reminiscent of strategies in which several antibiotics are used to treat bacterial infections while minimizing the chance that rare antibiotic-resistant mutants will arise within a population.

Region coverage control for multiple stratospheric airships with combined self-/event-triggered mechanism

The region coverage control problem of multiple stratospheric airships system is firstly addressed in this paper.Towards it,we propose a two-layer control framework with the artificial potential field(APF)-based region coverage control law and the adaptive tracking control law.The APF-based region coverage control law ensures the coverage task is achieved until every single stratospheric airship ends up performing station keeping where near the respective global minimum point,in which an innovative solution to the local minimum problem is put forward.The adaptive tracking control law is designed to realize motion control using tracking the desired velocity and angular velocity given by coverage control law,with the consideration of several practical control problems as unknown individual differences and external disturbances.To save resources,the combined self-/event-triggered mechanism designed therein significantly reduces the times of state information transmission and control law calculation.The effectiveness of the proposed control framework is verified through simulations.

Prediction of a maximum pull-out load of anchor bolts using an optimal combination model

The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.

煤矿井下掘进机器人路径规划方法研究

针对煤矿非全断面巷道条件下掘进机器人移机难度大、效率低下等问题,分析了煤矿井下非结构化环境特征及掘进机器人运动特性,提出了基于深度强化学习的掘进机器人机身路径规划方法。利用深度相机将巷道环境实时重建,在虚拟环境中建立掘进机器人与巷道环境的碰撞检测模型,并使用层次包围盒法进行虚拟环境碰撞检测,形成巷道边界受限下的避障策略。考虑到掘进机器人形体大小且路径规划过程目标单一,在传统SAC算法的基础上引入后见经验回放技术,提出HER-SAC算法,该算法通过环境初始目标得到的轨迹扩展目标子集,以增加训练样本、提高训练速度。在此基础上,基于奖惩机制建立智能体,根据掘进机器人运动特性定义其状态空间与动作空间,在同一场景下分别使用3种算法对智能体进行训练,综合平均奖励值、最高奖励值、达到最高奖励值的步数以及鲁棒性4项性能指标进行对比分析。为进一步验证所提方法的可靠性,采用虚实结合的方式,通过调整目标位置设置2种实验场景进行掘进机器人的路径规划,并将传统SAC算法和HER-SAC算法的路径结果进行对比。结果表明:相较于PPO算法和SAC算法,HER-SAC算法收敛速度更快、综合性能达到最优;在2种实验场景下,HER-SAC算法相比传统SAC算法规划出的路径更加平滑、路径长度更短、路径终点与目标位置的误差在3.53 cm以内,能够有效地完成移机路径规划任务。该方法为煤矿掘进机器人的自主移机控制奠定了理论基础,为煤矿掘进设备自动化提供了新方法。

基于VMD-改进最优加权法的短期负荷变权组合预测策略

为提升短期电力负荷预测精度,提出了一种变权组合预测策略。首先,为了降低负荷数据的不平稳度,使用变分模态分解(variational mode decomposition,VMD)将负荷数据分解成了高频、低频、残差3种特征模态分量。其次,充分计及负荷数据的时序特点,参考指数加权法原理设计自适应误差重要性量化函数,并结合组合模型在时间窗口内的历史负荷数据的均方预测误差设计改进最优加权法的目标函数和约束条件,以完成子模型的准确变权。最后,针对波动较强的高频分量选定极端梯度提升(XGBoost)和卷积神经网络-长短期记忆(CNN-LSTM)模型并使用改进最优加权法进行组合预测、低频分量使用多元线性回归(MLR)模型预测、残差分量使用LSTM模型预测,叠加各模态分量的预测结果,实现了短期负荷数据的准确预测。实验结果表明,使用策略组合模型的平均绝对百分比误差为4.18%。与使用传统组合策略的组合模型相比,平均绝对百分比预测误差平均降低了0.87%。

基于云模型的水光互补清洁能源基地容量配置方案优选

为优选水光互补清洁能源基地容量配置方案,从安全性、环保性、经济性、技术性4个方面选取14个指标构建了综合评价指标体系,采用改进云模型方法对容量配置方案进行评价。改进云模型方法以基于层次分析法改进的云模型求解主观权重,以熵权法求解客观权重,组合赋权得到指标权重,再利用条件云发生器计算各指标的隶属度,最后根据级别特征值法计算容量方案等级评分,确定最优方案。将该方法应用于我国西南某清洁能源基地水光互补系统容量配置方案的优选,优选结果与集对分析法优选结果和实际选择方案均相符,证明了该方法的有效性与适用性。

基于改进金豺算法的短期负荷预测

针对电力负荷序列波动性和预测精度不高的问题,提出一种基于变分模态分解、排列熵和改进金豺算法优化双向长短期记忆网络的预测模型。首先,利用变分模态分解重构原始负荷序列,再采用排列熵理论对分解后的子序列进行熵值重组;然后,利用改进金豺算法对双向长短期记忆网络的参数进行优化,并对每个子序列建立预测模型;最后,组合各模型结果得到最终预测值。实验结果表明,本文模型预测精度更高,与真实值拟合度更好。

改进雷达图法在高校宿舍火灾风险评估中的应用

由于高校宿舍人员高度密集,一旦发生火灾其极易造成严重后果,因此高校宿舍火灾问题亟待重视。为合理评估该风险,首先,借助文献从人、物、环境、管理四方面建立评价指标体系及评价量表;其次,运用合作博弈法将主观赋权结果和客观赋权结果相结合以对评价指标进行组合赋权;随后,将指标权重集转换成各指标轴夹角并计算各指标取值;最后,将经火灾风险雷达图平均周长与同面积圆周长之比为短板系数进行修正的雷达图平均面积作为评价特征量建立高校宿舍火灾风险评价方法。该方法可避免人为赋权的主观性且能以图形形式直观显示出风险管控环节中的薄弱环节。最后以某一实例验证了该评价方法的有效可行性,可为高校宿舍火灾风险评价提供新的思路。

建设中华民族现代文明:习近平文化思想形成的逻辑理路与实践指向

文化自信理念奠定了习近平文化思想的理论前提,是建设中华民族现代文明的信心之源与力量之本;文化强国建设是锻造中华民族现代文明的历练之路与淬炼之炉;“两个结合”揭示了习近平文化思想的创新源泉;建设中华民族现代文明标注了习近平文化思想的伟大使命。习近平文化思想形成的逻辑理路与实践指向浓缩了新时代宣传思想文化建设发展史,谱写了马克思主义文化理论的时代新篇。

顾及环境敏感特征的铁路线路方案优选方法研究

为合理地解决环境敏感区铁路线路方案综合优选问题,研究顾及环境敏感特征的铁路线路方案优选方法 .首先,基于文献调研和环境敏感区特征探析,分析总结影响线路方案的因素,构建涵盖4大方面18项指标的顾及环境敏感特征的铁路线路方案优选指标体系.其次,在专家经验主观赋权和工程信息客观赋权的基础上,运用灰色关联分析理论进行组合赋权.然后,结合改进优劣解距离法(Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS)确定各线路方案的相对贴近度,进而实现线路方案优选.最后,以新建铁路西宁至成都线合作至郎木寺段线路方案选择为例进行优选方法验证.研究结果表明:该区段线路的4个备选方案的相对贴近度依次为0.527 9,0.523 6,0.508 7,0.522 7,方案一的相对贴近度最大为最优方案,基于本方法的优选结果与实际专家论证结果一致;与传统TOPSIS比较,基于改进TOPSIS的运算结果避免了计算结果受单方面优势指标影响的弊端,在运算过程中将线路方案涉及的极端优劣指标进行综合权衡考量,得到的运算结果更贴近实际情况.研究成果可为未来环境敏感区线路方案优选问题提供一种新的优选思路.

地铁运营中断下应急接驳公交调度方案研究

【目的】针对传统应急调度模式单一、疏运效率低的特征,研究了多种调度模式组合应急公交调度方法。【方法】考虑应急停车场派车能力、车辆运力、车辆救援时间特性,构建以应急公交车辆疏运成本最小和乘客平均延误最小为目标的多目标组合调度优化模型。根据该模型的特点提出使用快速非支配排序遗传算法(NSGA-Ⅱ)求解,为提高种群的多样性和算法的性能对该算法进行了相应的改进,最终得到Pareto分布优化解集,并采用隶属函数从中选取出最优折衷解。最后,以南昌轨道交通1号线作为算例,对应急公交组合调度方案和单一调度方案分别进行求解。【结果】结果表明:文章提出的组合调度方案相比传统单一调度方案的乘客平均延误时间降低了20.48%,疏运成本降低了16.96%,改进后的NSGA-Ⅱ算法相比较标准的NSGA-Ⅱ算法进行求解时,乘客平均延误时间降低了6.72%,疏运成本降低了3.59%。【结论】通过灵敏度分析发现:在确定滞留乘客疏运需求的情况下,滞留乘客的平均延误时间和车队规模呈负相关,应急公交的疏运成本和车队规模成正相关。

基于改进云模型的隧道爆破效果综合评价研究

针对隧道爆破效果综合评价的不确定性问题,提出基于改进云模型与组合赋权的评价方法。结合现场工程经验与相关研究,选择平均线性超挖量、平均线性欠挖量、炮孔利用率、周边孔半孔痕率、大块率以及炸药单耗为评价指标,结合序关系分析(G1)法与基于指标相关性(CRITIC)法对各指标赋权,借助改进云模型对爆破效果数值及等级区间进行同向化处理,从而构建爆破效果综合评价模型。以某隧道为实例进行验证,模型分析结果表明在当前的爆破设计方案和生产水平下该隧道爆破效果的综合评价等级为“较好”,指明了影响爆破效果的主要因素,为进一步优化爆破设计参数提供了方向。

基于三重扰动和线性组合的批量矩阵乘法可验证计算方案

随着云计算、物联网技术的发展,可验证计算作为一种新兴的计算技术得到了广泛的应用。可验证计算在为用户带来便利的同时也存在着安全挑战:数据隐私性、结果可验证性和高效性。目前,矩阵乘法可验证计算方案基本采用稀疏矩阵相乘的加密方法来保护数据的隐私性。分析稀疏矩阵加密算法后,发现存在两个挑战:一是行或列公因子泄露原始矩阵行或列数据,二是零元素泄露原始矩阵零元素统计信息。同时,现有方案对云服务器计算结果的验证效率也不理想。针对数据隐私保护挑战,设计的批量矩阵乘法可验证计算方案利用三重扰动加密算法在不增加加解密计算复杂度的同时达到更强的隐私保护效果,其中,通过构造特殊的上或下三角稀疏矩阵加入双重扰动(乘法扰动和加法扰动)来保护行或列数据,通过构造特殊的加法稀疏矩阵加入单重扰动(加法扰动)来保护零元素信息。针对云服务器计算结果验证效率挑战,所提方案利用矩阵线性组合技术实现计算结果的批量验证,验证效率提高了约50倍,并随着矩阵数量的增多而提升。性能分析表明,所提方案基本没有增加客户端加解密开销,并提高了结果验证效率。

改进型三斜叶-Rushton组合桨槽内流场特性的粒子图像测速技术

通过粒子图像测速技术(PIV)对装配三斜叶-Rushton组合桨搅拌槽内流场进行了实验研究,在甘油-水溶液中研究了该组合桨在不同转速N、离底距C_(1)以及桨叶间距C_(2)时的槽内流场变化情况。研究结果表明:当转速N=100 r·min^(-1)时,上桨叶区的混合效果有所改善,桨叶间速度分布相对均匀;当离底距C_(1)=0.3H时,上桨叶区低速区域最小,搅拌槽内的混合效果达到最佳;当桨间距C_(2)=0.25H时,上桨叶区的低速区得到改善,混合效果有所提升,两桨叶间速度分布趋于平稳有利于混合和传质。

基于改进相关系数和IGOWLA算子的三角模糊数组合预测模型

随着经济系统复杂程度日益提高,用三角模糊数能更好地反映不确定信息.为保证预测结果的内部整体性,提出将三角模糊数序列的3个界点值转化为等价信息的面积中心、中界值、重心并构建新的序列.随后以预测精度为诱导因子,构建诱导广义有序加权对数平均(IGOWLA)算子,在此基础上选取改进后的Pearson相关系数作为最优准则,构建多目标组合预测模型,并引入偏好系数将模型进一步转化为单目标规划模型,通过实例分析证明了组合预测模型的有效性.结果表明:该组合预测模型可以在保证内部整体性的基础上有效地提高预测精度.

基于k-sums分段聚类的动态组合学习光伏短期功率预测

目前单一模型预测精度存在难以随着功率波动保持最优的问题,为提高并网系统运行的稳定性和电网的节能调度,文中提出了一种基于k-sums分层聚类的动态学习组合光伏短期功率预测方法。利用k-sums算法经过分段聚类,将天气类型分为晴天A 1、多云A 2、阴雨天B。通过TCN(Temporal Convolutional Network)提取数据的时序特征,并结合GRU(Gate Recurrent Unit)建立融合提取时序特征模块的改进GRU结构,以达到对时序特征敏感的效果。将改进GRU结构与SVM(Support Vector Machine)动态组合,使用Elastic Net算法输出最佳权重值叠加得到最终预测值。文中采用江苏某地区的光伏发电功率数据及对应的气象数据对所提方法进行验证,结果表明动态组合学习模型的MAE(Mean Absolute Error)为1.888,RMSE(Root Mean Squared Error)为2.403。

规模化屋顶光伏接入配电网的建设决策

围绕规模化屋顶光伏的选优建设问题,提出一种规模化屋顶光伏建设方案的综合评价方法。基于屋顶光伏建设的相关方分析,从供电影响侧、环保侧、经济侧、市场侧角度构建一套适用于屋顶光伏建设决策的综合评价指标体系,供电影响侧考虑并网运行质量与匹配度,环保侧体现绿色低碳效益,经济侧关注投资建设效益,市场侧反映应用参与度与接受度;采用层次分析-G1结合赋权法、改进的基于指标相关性的指标权重确定法分别求解指标主、客观权重,并通过改进的最小偏差组合赋权模型确定指标综合权重,采用优劣解距离法完成方案的评价与决策。算例仿真结果验证了所提方法的有效性。