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311.
准确预报船体运动响应对于砰击等波浪载荷的计算以及合理结构设计具有重要意义。船舶在大幅波浪中的运动呈明显的非线性,而现阶段耐波性预报多采用线性切片方法。三维水动力分析软件 WASIM基于时域势流理论,采用 Rankine面元法预报船舶在波浪中的运动响应,并考虑了多种非线性因素。本文以标模 DTMB5512为对象,采用 WASIM预报其在不同航速下的耐波性,并与基于线性切片理论的计算结果和模型试验结果进行对比。结果表明:利用 WASIM计算得到的船体运动响应比其他方法更接近试验值,合理体现了船舶在风浪中的实际耐波性能。因此,利用 WASIM能够较好地评估船舶在波浪中的非线性耐波特性。 相似文献
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ABSTRACTThe purpose of maritime accident prediction is to reasonably forecast an accident occurring in the future. In determining the level of maritime traffic management safety, it is important to analyze development trends of existing traffic conditions. Common prediction methods for maritime accidents include regression analysis, grey system models (GM) and exponential smoothing. In this study, a brief introduction is provided that discusses the aforementioned prediction models, including the associated methods and characteristics of each analysis, which form the basis for an attempt to apply a residual error correction model designed to optimize the grey system model. Based on the results, in which the model is verified using two different types of maritime accident data (linear smooth type and random-fluctuation type, respectively), the prediction accuracy and the applicability were validated. A discussion is then presented on how to apply the Markov model as a way to optimize the grey system model. This method, which proved to be correct in terms of prediction accuracy and applicability, is explored through empirical analysis. Although the accuracy of the residual error correction model is usually higher than the accuracy of the original GM (1,1), the effect of the Markov correction model is not always superior to the original GM (1,1). In addition, the accuracy of the former model depends on the characteristics of the original data, the status partition and the determination method for the status transition matrix. 相似文献
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Traffic flow prediction is an essential part of intelligent transportation systems (ITS). Most of the previous traffic flow prediction work treated traffic flow as a time series process only, ignoring the spatial relationship from the upstream flows or the correlation with other traffic attributes like speed and density. In this paper, we utilize a linear conditional Gaussian (LCG) Bayesian network (BN) model to consider both spatial and temporal dimensions of traffic as well as speed information for short‐term traffic flow prediction. The LCG BN allows both continuous and discrete variables, which enables the consideration of categorical variables in traffic flow prediction. A microscopic traffic simulation dataset is used to test the performance of the proposed model compared to other popular approaches under different predicting time intervals. In addition, the authors investigate the importance of spatial data and speed data in flow prediction by comparing models with different levels of information. The results indicate that the prediction accuracy will increase significantly when both spatial data and speed data are included. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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This paper proposes a novel short/medium-term prediction method for aviation emissions distribution in en route airspace. An en route traffic demand model characterizing both the dynamics and the fluctuation of the actual traffic demand is developed, based on which the variation and the uncertainty of the short/medium-term traffic growth are predicted. Building on the demand forecast the Boeing Fuel Flow Method 2 is applied to estimate the fuel consumption and the resulting aviation emissions in the en route airspace. Based on the traffic demand prediction and the en route emissions estimation, an aviation emissions prediction model is built, which can be used to forecast the generation of en route emissions with uncertainty limits. The developed method is applied to a real data set from Hefei Area Control Center for the en route emission prediction in the next 5 years, with time granularities of both months and years. To validate the uncertainty limits associated with the emission prediction, this paper also presents the prediction results based on future traffic demand derived from the regression model widely adopted by FAA and Eurocontrol. The analysis of the case study shows that the proposed method can characterize well the dynamics and the fluctuation of the en route emissions, thereby providing satisfactory prediction results with appropriate uncertainty limits. The prediction results show a gradual growth at an average annual rate of 7.74%, and the monthly prediction results reveal distinct fluctuation patterns in the growth. 相似文献
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超大型全冷式液化气船(VLGC)是国际上公认的设计及建造技术难度最大的船型之一,VLGC波浪载荷是船舶设计计算分析的重要载荷,准确的评估波浪载荷对船舶强度的设计非常重要。论文从DNV先进的水动力计算软件HydroD对VLGC船满载和压载工况下的波浪载荷进行了计算,得到了VLGC船相应工况下的运动响应和短期预报、长期预报值,并把计算出的波浪载荷传递到全船结构有限元结构模型中,加载分析得到了VLGC船的应力分布,对相应地方做了适当改进和加强,并对典型节点进行疲劳强度分析,得到了典型节点的疲劳寿命。对VLGC船整个波浪载荷传递到有限元模型的这一套流程做了分析和研究,也为进一步应用水动力方法计算其它船型的结构强度和疲劳寿命打下了良好的基础。 相似文献
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公交客流量具有动态性,受多种因素的影响,不能或无法用精确的数学模型进行预测。通过对公交客流量预测的Elman和BP神经网络的建立、学习和训练。并以前三年的公交客流量、国内生产总值、工业总产值、城市人口数作为两种神经网络的输入神经元,第四年的公交客流量作为输出神经元,同时以合肥市公交客流量为例进行分析,结果表明:所建的Elman模型比EBP模型的预测精度高,效果好。 相似文献
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道路交通安全评价技术 总被引:1,自引:1,他引:0
交通安全评价能对交通系统中固有的或潜在的危险进行预测或评估,进而为采取措施改善交通安全现状提供依据。基于交通安全评价方法、事故预测模型和道路安全审计三个方面,有关道路交通安全评价方法和技术的优缺点及运用范围的介绍,可为相关研究提供一定参考。 相似文献