潜艇均衡系统自流注水调节阀稳态噪声试验研究

本文模拟建立了潜艇均衡系统自流注水试验系统,对不同假海压力、不同系统流量、不同出口背压及串联2台调节阀时自流注水稳定过程振动噪声进行研究。结果表明:潜艇均衡注水振动噪声随着假海深度的增大而增大;空气噪声随流量调节阀开度的增大而增大,在流量调节阀开度为60°-70°之间,振动加速度及水动力噪声产生峰值;在出口背压为0-0.5 MPa之间时,振动噪声值均大于无背压状态,峰值为0.2 MPa;串联2台流量调节阀可大幅降低自流注水振动噪声。     

鱼雷发动机三组元比例控制器数值模拟

利用计算流体力学软件Pumplinx模拟鱼雷发动机中三组元比例控制器的内部流场,分析计算中不同压差情况下对比例控制器性能的影响,以及叶片与定子间间隙大小对于比例控制器性能的影响,同时对不同叶片数目下性能进行对比。计算结果表明:由于比例控制器为被动旋转马达结构,其转速和流量均随时间呈周期性脉动变化,随着工作压差增大,转速脉动幅度基本保持不变,而流量和扭矩脉动幅值增加;随着间隙增大,泄漏量增大,但流量、扭矩、转速脉动幅值大幅降低,出口流量较为平稳;叶片数目增多后比例控制器转速降低、排量降低。由计算结果推断出目前比例控制器的最优叶片数目为4。本文可为进一步研究比例控制器精度问题提供参考。     

浅谈FAS双中心建设及设备维护

重点分析了西安局集团公司由2K数调主系统组网更新改造为FAS双中心网络的建设方法,并根据日常维护经验,列举了调度台通道故障处理、FASB简易故障判断及计表倒换试验、FASA和FASB系统与MSC之间的业务故障处理等.     

基于灰色—小波神经网络的有效泊位预测

针对停车场有效停车泊位的变化特征,提出了基于灰色—小波神经网络的组合模型.先通过灰色单因素预测模型对有效停车泊位时间序列进行修正处理,再基于分步式小波神经网络模型对修正预测值进行运算,并通过马克科夫链预测模型得到更精确的预测区间,并利用实际案例分析,对模型的预测精度、稳定性、拟合度和训练时间进行了评价.研究表明,灰色—小波神经网络预测模型可降低初始数据波动性的干扰,与传统神经网络相比,预测结果误差波动性降低了10%~19%,稳定性提高了27%~33%,拟合度提高了10%~15%,精确度明显提高.     

Continuum theory for pedestrian traffic flow: Local route choice modelling and its implications

This contribution puts forward a novel multi-class continuum model that captures some of the key dynamic features of pedestrian flows. It considers route choice behaviour on both the strategic (pre-trip) and tactical (en-route) level. To achieve this, we put forward a class-specific equilibrium direction relation of the pedestrians, which is governed by two parts: one part describing the global route choice, which is pre-determined based on the expectations of the pedestrians, and one part describing the local route choice, which is a density-gradient dependent term that reflects local adaptations based on prevailing flow conditions.Including the local route choice term in the multi-class model causes first of all dispersion of the flow: pedestrians will move away from high density areas in order to reduce their overall walking costs. Second of all, for the crossing flow and bi-directional flow cases, local route choice causes well known self-organised patterns to emerge (i.e. diagonal stripes and bi-directional lanes). We study under which demand conditions self-organisation occurs and fails, as well as what the impact is of the choices of the different model parameters. In particular, the differences in the weights reflecting the impact of the own and the other classes appear to have a very strong impact on the self-organisation process.     

水下容器开启过程流场特性仿真研究

水下容器开启过程中,海水快速灌入容器内,对载体的平衡产生较大的影响.采用Mixture多相流计算模型求解气液两相流场,网格更新方法采用域动分层法,对不同开启角度进行数值计算.结果表明:开启角度越小,容器底部压力和容器内部进水量波动越大,且峰值越大,随着开启角度的增大,两者波动范围有所减缓,研究成果可为水下容器总体设计、系统使用流程优化提供理论支撑.     

舰船开孔流动噪声控制措施研究

基于计算流体软件,采用大涡模拟方法计算了给定来流速度条件下表面开孔的非定常流场,分析了流场的非定常流频谱特性,采用边界元方法模拟了噪声源特征,对各种流动噪声控制措施进行了对比分析.计算结果表明,开孔形式的改变会直接影响流噪声的水平,设计结果可以为舰船流水孔的降噪设计提供参考.     

融合式空间塔式算子和HIK-SVM的交通标志识别研究

在交通标志识别问题上,提出了一种基于融合式的空间塔式算子和直方图交叉核支持向量机(HIK-SVM)的分类方法.在该方法中,通过提取图像的灰度塔式词袋直方图(Gray-PHOW)特征、颜色塔式词袋直方图(Color-PHOW)特征和塔式边缘方向梯度直方图(PHOG)特征来对交通标志的外观、颜色和轮廓信息进行描述.通过提取空间塔式直方图特征,能很好地对图像各种特征的空间分布状况进行描述.提取到图像的外观、颜色、轮廓和特征的空间分布信息后,对其进行融合,最后得到的融合式的空间塔式特征具有很强的鲁棒性.将该融合式特征送入HIK-SVM进行训练和分类,取得了极其高的识别效果.     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.