Hydraulic Optimization of a Double-channel Pump's Impeller Based on Multi-objective Genetic Algorithm

Computational fluid dynamics（CFD） can give a lot of potentially very useful information for hydraulic optimization design of pumps, however, it cannot directly state what kind of modification should be made to improve such hydrodynamic performance. In this paper, a more convenient and effective approach is proposed by combined using of CFD, multi-objective genetic algorithm（MOGA） and artificial neural networks（ANN） for a double-channel pump＇s impeller, with maximum head and efficiency set as optimization objectives, four key geometrical parameters including inlet diameter, outlet diameter, exit width and midline wrap angle chosen as optimization parameters. Firstly, a multi-fidelity fitness assignment system in which fitness of impellers serving as training and comparison samples for ANN is evaluated by CFD, meanwhile fitness of impellers generated by MOGA is evaluated by ANN, is established and dramatically reduces the computational expense. Then, a modified MOGA optimization process, in which selection is performed independently in two sub-populations according to two optimization objectives, crossover and mutation is performed afterword in the merged population, is developed to ensure the global optimal solution to be found. Finally, Pareto optimal frontier is found after 500 steps of iterations, and two optimal design schemes are chosen according to the design requirements. The preliminary and optimal design schemes are compared, and the comparing results show that hydraulic performances of both pumps 1 and 2 are improved, with the head and efficiency of pump 1 increased by 5.7% and 5.2%, respectively in the design working conditions, meanwhile shaft power decreased in all working conditions, the head and efficiency of pump 2 increased by 11.7% and 5.9%, respectively while shaft power increased by 5.5%. Inner flow field analyses also show that the backflow phenomenon significantly diminishes at the entrance of the optimal impellers 1 and 2, both the area of vortex and intensity of vortex decreases in the whole flow channel. This paper provides a promising tool to solve the hydraulic optimization problem of pumps＇ impellers.

A Study of the Double Object Construction

Thestudyofthedoubleobjectconstructionhasbeenoneofthetopicsintheliteratureofgenerativegrammar.Themajorquestionsare:1)theCaseproblemsofthetwoobjects;2)therelationbetweenthedoubleobjectconstructionandthedativeconstruction.InGB,Caseisassignedtoanominalun...

基于Double DQN的双模式多目标信号配时方法

近年来深度强化学习作为一种高效可靠的机器学习方法被广泛应用在交通信号控制领域。目前,现有交通信号配时方法通常忽略了特殊车辆(例如救护车、消防车等)的优先通行;此外,基于传统深度强化学习的信号配时方法优化目标较为单一,导致其在复杂交通场景中性能不佳。针对上述问题,基于Double DQN提出一种融合特殊车辆优先通行的双模式多目标信号配时方法(Dual-mode Multi-objective signal timing method based on Double DQN,DMDD),以提高不同交通场景下路口的通行效率。该方法首先基于路口的饱和状态选择信号控制模式,特殊车辆在紧急控制模式下被赋予更高的通行权重,有利于其更快通过路口;接着针对等待时长、队列长度和CO 2排放量3个指标分别设计神经网络进行奖励计算;最后利用Double DQN进行最优信号相位的选择,通过灵活切换信号相位以提升通行效率。基于SUMO的实验结果表明,DMDD与对比方法相比能有效缩短路口处特殊车辆的等待时长、队列长度和CO 2排放量,特殊车辆能够更快通过路口,有效地提高了通行效率。

Language Transfer Evidence in the Acquisition of Double Object Construction by Chinese EFL Learners

Based on the theory of language transfer in second language acquisition, this study explored the dynamic acquisition of English double object construction by Chinese EFL learners through comparative analysis. Altogether 120 subjects participated in this experiment and were required to take the proofreading exercise in limited time. The experimental results showed that Chinese EFL learners at different levels of proficiency acquired the core subclass of double object construction better than peripheral ones;meanwhile, learners at higher levels of proficiency outperformed those at lower levels, especially in the peripheral types. Relevant theoretical interpretations were given thereafter to the above research findings, with the hope to shed some light on the learning of double object construction by Chinese EFL learners.

“对象性活动”:马克思辩证法的本体论基础——对《1844年经济学哲学手稿》中辩证法思想的理解

《1844年经济学哲学手稿》是马克思辩证法理论的真正开端。在手稿中,马克思对非批判的运动以及非批判的形式进行了双重的批判,从而确定了辩证法的本体论基础——“对象性活动”。“对象性活动”内蕴了辩证法理论的三个基本原则,即建立在感性基础上的现实性原则、以主体性为基础的活动性原则、以对象性为基础的历史性原则。辩证法的三原则是建构“合理形态”的辩证法的前提,是批判性、革命性的本质展现,是现实性和力量性的地基。

Double balloon enteroscopy to retrieve an accidentally swallowed dental reamer deep in the jejunum

Accidentally swallowed foreign objects are not uncommon but difficult to manage without complications. We describe the case of a 68 year old man who accidentally a swallowed sharp-pointed dental reamer that had reached deep in his jejunum. Double balloon enteroscopic retrieval was performed with polypectomy snare but the reamer was entangled in the wire loop of the snare and penetrated the jejunal wall. After releasing the reamer by pushing and pulling the snare for approximately 30 min, the reamer was retrieved with biopsy forceps. This is the first report of double balloon enteroscopic removal of a dental reamer. Furthermore, this is a novel case with regard to decision making in situations when sharp objects are swallowed.

平遥话“复合式动量双宾”结构研究——从“双及物”到“致使”的创新演变

文章观察到在晋语平遥方言中动量成分可以出现在由“V给”构成的双宾结构中,形成非常有特色的“复合式动量双宾”结构,如“踢给兀家一脚”“冻给狗日一晚间”“跌给你一跤”等。平遥话中的“复合动量双宾式”不仅丰富了汉语双及物和致使范畴的表现形式,也展示了“V给”结构经由“双及物”到“致使”的独特发展路径。文章论证了平遥话中的“动量双宾式”既可以表达“给予”义,又可以表达“致使”义。其中,“踢给兀家一脚”类“动量双宾式”是把动作隐喻为转移物的“双及物结构”;而“冻给狗日一晚间”“跌给你一跤”类“动量双宾式”是可以表达“使令”及“允让”情景的致使结构。给予义“动量双宾式”中的“给”表示“给予义”,允准“准动量”;而致使义“动量双宾式”中的“给”表示“蒙受义”,允准“真动量”。伴随着“给”及“动量成分”的性质变化,“动量双宾式”展示出“给”字结构经由双及物结构向致使演变的独特类型。

An Improved Double r-iteration IOD Method for GEO UCTs Based on SBSS System

The purpose of initial orbit determination,especially in the case of angles-only data for observation,is to obtain an initial estimate that is close enough to the true orbit to enable subsequent precision orbit determination processing to be successful.However,the classical angles-only initial orbit determination methods cannot deal with the observation data whose Earth-central angle is larger than 360°.In this paper,an improved double r-iteration initial orbit determination method to deal with the above case is presented to monitor geosynchronous Earth orbit objects for a spacebased surveillance system.Simulation results indicate that the improved double r-iteration method is feasible,and the accuracy of the obtained initial orbit meets the requirements of re-acquiring the object.

Estimation of Winds at Different Isobaric Levels Based on the Observed Winds at 850 hPa Level Using Double Fourier Series

A technique based on the double Fourier series is developed to estimate the winds at different isobaric levels forthe limited area domain, 35°E to 140°E and 30°S to 40°N, using the observed winds at 850 hPa lcvcl for the month ofJune. For this purpose the wind field at a level under consideration is taken in the ratio form with that of 850 hPa level and the coefficients of the double Fouricr series are computed. These coefficients are subsequently used to computethe winds which are compared with the actual winds. The results of the double Fourier series technique are comparedwith those of the polynomial surface fitting method developed by Bavadekar and Khaladkar (1 992). The technique isalso applied for the daily wind data of 11. June, 1979 and the validation of the technique is tested for a few radiosondestations of india. The computed winds for these radiosonde stations arc quite close to observed winds.

基于双帧融合的野外运动小目标检测网络

由于野外监控传感系统中背景干扰较多、小目标像素点较少以及缺乏相关公开数据集等因素,在野外复杂环境中检测运动小目标仍然是国防军事应用中一个具有挑战性的问题。针对这一问题,提出一种基于YOLOv5改进的双帧融合目标检测网络(YOLO-DFNet)。首先,提出双帧融合模块用来处理骨干网络输出的相邻帧特征,通过计算通道及时间维度的注意力和空间注意力,提取运动特征;其次,在颈部网络与检测头之间设计一个时间梯形融合网络,关注不同大小感受野上的运动目标,改善大位移小目标的检测效果。在野外运动小目标数据集FMSOD上的实验结果表明:YOLO-DFNet在不同IoU上的平均精度比YOLOv5算法提高3.9个百分点,同时也优于TPH-YOLOv5、YOLOv7等其他目标检测网络。

Dynamic Self-Adaptive Double Population Particle Swarm Optimization Algorithm Based on Lorenz Equation

In order to improve some shortcomings of the standard particle swarm optimization algorithm, such as premature convergence and slow local search speed, a double population particle swarm optimization algorithm based on Lorenz equation and dynamic self-adaptive strategy is proposed. Chaotic sequences produced by Lorenz equation are used to tune the acceleration coefficients for the balance between exploration and exploitation, the dynamic self-adaptive inertia weight factor is used to accelerate the converging speed, and the double population purposes to enhance convergence accuracy. The experiment was carried out with four multi-objective test functions compared with two classical multi-objective algorithms, non-dominated sorting genetic algorithm and multi-objective particle swarm optimization algorithm. The results show that the proposed algorithm has excellent performance with faster convergence rate and strong ability to jump out of local optimum, could use to solve many optimization problems.

大直径双浮动端面密封结构多目标优化设计

针对缺乏直径大于600 mm浮动端面密封环结构参数选取标准的问题,建立了密封橡胶O形圈二维轴对称非线性接触模型;结合试验设计、有限元计算、响应面模型、多目标优化算法与优劣解距离决策方法,以密封环最大变形量和端面比压为目标,开展了不同结构双浮动端面密封优化设计研究;分析了密封环结构参数对其端面比压与变形量的影响规律。结果表明:密封环锥面最小半径R_(min)与锥面角 β 越大,密封端面比压越大;R_(min)与 β 越大,安装间隙A越小,密封环变形量越大。影响端面比压的主因素为R_(min)与 β,影响变形量的主因素为R_(min)。浮动环最优结构参数为:R_(min)=381 mm,β=23°,A=18 mm,相应的密封环端面比压为0.49 MPa,最大变形量为12.11 μm。经过静压和运转密封性能测试试验,设计的双浮动端面密封无泄漏,表明优化设计方法有效可行。

基于双层代理模型的无人机气动隐身综合设计

基于双层代理模型方法展开飞翼布局无人机气动隐身综合设计方法研究。DSM模型集成了插值型代理模型和回归型代理模型的优点,在同样样本的条件下,具有更高的预测精度。文中分别以Navier-Stokes方程数值求解方法和稀疏矩阵方法分析无人机气动、隐身特性,并构造了两种分析方法的DSM模型,验证了DSM模型特性。文章最后基于自适应代理模型优化设计策略,结合多目标遗传算法将DSM模型用于无人机气动隐身综合设计,使其在满足一定约束的前提下最小化全机阻力和头向雷达反射截面,取得了令人满意的设计结果,验证了文中方法的实用性。

基于多目标优化的菱形车双横臂悬架运动学分析

运用多体动力学有限转动张量和空间解析几何方法,建立了双横臂悬架关键点的约束方程,导出了轮胎滑移和倾角随车轮跳动的变化规律。结合多目标遗传算法,以悬架横臂长度和初始位置为参数,对双横臂悬架跳动过程中的轮胎滑移和倾角的变化进行了优化。求解出了工程许可范围内的双横臂悬架轮胎滑移和外倾角变化关系及其悬架导向杆系参数。

电动汽车减速器啸叫噪声的双目标优化

为降低电动汽车减速器的啸叫噪声,采用齿形修形和齿向修形相结合的齿面修形法,并提出了一种齿轮传递误差和齿面接触应力双目标函数优化模型,对修形参数进行优化。结果表明:采用优化后修形参数进行修形后,电动汽车双级减速器的高速和低速齿轮副的传递误差最大变化量分别降至0.15和0.48μm;最大齿面接触应力分别为700和980MPa,达到了降低传递误差和改善齿面接触应力的预期目标。最后,将减速器安装在整车上进行齿轮优化修形前后的噪声声压级对比测试,结果表明:经齿面优化修形后,驾驶员右耳处噪声声压级峰值降低了7.3d B,啸叫噪声得到了有效控制。

自适应双阈值的运动目标检测算法

针对噪声、不同的天气状况和光照强度等环境变化对运动目标检测的影响,提出了一种自适应双阈值运动掩膜算法.为提高复杂环境条件下运动目标检测的识别率,该算法首先利用多帧平均法初始化背景,采用函数链接型神经网络算法动态更新高低两个阈值,自动适应光照变化.根据运动掩膜算法判定前景和背景区域动态更新背景后,采用自适应双阈值背景差法分割得到前景目标区域,并结合数学形态学方法,消除阴影,准确识别出前景目标.实验结果验证了该算法对运动目标检测的高准确性和良好的鲁棒性.

采用多目标纵横交叉算法的电力系统动态环境经济调度

针对带非线性约束的电力系统动态环境经济调度问题,提出一种多目标纵横交叉算法。对动态调度中燃料费用和污染排放两个相互约束、冲突的目标同时进行优化。求解过程中,结合非约束支配策略,提出一种双交叉机制,增强粒子穿越非可行区域的能力,使得生成的帕累托最优解落在可行区域内。通过边缘探索,增强算法的全局搜索能力。同时,采用外部存档集合储存非劣解,并通过拥挤度对比,保持非劣解的多样性。最后,采用模糊决策理论获得最优折中解。对10机电力系统的仿真结果验证了所提方法的有效性与优越性。

最优控制理论在拱坝动力优化中的应用

在拱坝的动力优化中，应用传统的以体积为目标函数的数学模型，有一定的局限性．本文用最优控制理论建立双目标模型与能量模型对拱坝进行动力优化分析，两模型综合考虑拱坝的安全性、经济性和稳定性．并以小湾拱坝的计算结果验证两模型的合理性与可行性．

基于双种群算法的模拟移动床多目标操作优化

以有限元法求解模拟移动床的稳态TMB模型和动态SMB模型,提出基于Pareto非劣解集的多目标双种群遗传粒子群算法;利用动态SMB模型仿真模拟移动床色谱吸附分离过程,以分离纯度和性能指标分别作为约束条件和目标函数进行多目标操作优化设计。仿真结果表明,SMB模型较之TMB模型更真实可靠,双种群遗传粒子群算法也较单一种群的遗传算法或粒子群算法具有更好的收敛性和鲁棒性,能有效地对模拟移动床操作条件进行优化,提高其分离性能和经济效益。

一种自适应的双门限场面运动目标检测方法

为了有效解决在复杂环境下机场场面运动目标的精确检测问题,提出了一种自适应的双门限场面运动目标检测方法。首先采用混合高斯背景模型的方法来提取背景图像,然后使用两个门限值对差分图像进行前景目标分割,低门限阈值用于粗分割以检测出较明显的运动目标,在粗分割的基础上再用高门限阈值进行细分割以去除噪声目标和伪目标,最终得到场面运动目标的准确检测和分割结果。在复杂条件下的场景进行的实验,验证了该方法具有良好的噪声抑制能力和对慢目标良好的鲁棒性,同时能有效地分割出前景目标。