多孔管孔出流速度和流量影响因素数值仿真及试验

本文通过控制变量法进行工况设计,对多孔管进行数值模拟和试验对比,分别研究多孔管管径、管长、孔径、孔间距、水压五个变量对多孔管孔出流速及流量的影响。使用ANSYS软件中的DesignModeler模块进行几何建模,ICEM中的O-Block技术进行流体计算域网格划分,Fluent软件进行求解。研究发现,多孔管管内径和管长的增加均使孔出流速和出流量减小,管长度的增加会影响孔出流沿程的均匀性;孔径的增大使孔出流速明显减小,且影响孔出流沿程的均匀分布,出流量受孔径的影响较复杂,在孔径不超过2.5mm时可以认为出流量与孔径的平方成正比;孔间距的增大对孔出流速和沿程均匀分布基本无影响,而与出流量成正比。最后将数值模拟结果和试验进行对比,发现试验数据所反映的多孔管出流量与管内径、管长、孔径和孔间距的关系与数值模拟基本吻合,而试验中管的出流量普遍比数值模拟小。     

Biofuel futures in road transport – A modeling analysis for Sweden

First and second generation biofuels are among few low-carbon alternatives for road transport that currently are commercially available or in an early commercialization phase. They are thus potential options for meeting climate targets in the medium term. For the case of Sweden, we investigate cost-efficient use of biofuels in road transport under system-wide CO₂ reduction targets to 2050, and the effects of implementation of targets for an almost fossil-free road transport sector to 2030. We apply the bottom-up, optimization MARKAL_Sweden model, which covers the entire Swedish energy system including the transport sector. For CO₂ reductions of 80% to 2050 in the Swedish energy system as a whole, the results of the main scenario show an annual growth rate for road transport biofuels of about 6% from 2010 to 2050, with biofuels accounting for 78% of road transport final energy use in 2050. The preferred biofuel choices are methanol and biomethane. When introducing additional fossil fuel phase-out policies in road transport (−80% to 2030), a doubling of the growth rate to 2030 is required and system CO₂ abatement costs increases by 6% for the main scenario. Results imply that second generation biofuels, along with energy-efficient vehicle technologies such as plug-in hybrids, can be an important part of optimized system solutions meeting stringent medium-term climate targets.     

预应力混凝土槽形梁静力行为研究

为了解槽形梁静力行为,进行了一片预制预应力混凝土槽形梁的模型试验,分别考虑跨中最大弯矩及梁端最大剪力两种荷载工况对试验模型进行加载,测试了试验模型的控制断面的应力、变形.并采用非线性有限元分析方法对槽形梁的力学特性进行了研究.试验和研究得到了如下结论:该槽形梁的剪力滞效应较为突出,具有明显的开口薄壁杆件特征,底板的空间板效应明显,在设计荷载作用下结构处于线弹性状态,具有一定的安全储备.     

《大学生创业基础》示范课程建设实践与探索

大学生创业教育已成为目前各高校面临的新课题.文章结合广西交通职业技术学院教学实践,以《大学生创业基础》示范课程的建设为突破口,提出了创业教育示范课程建设的思路与设想,探讨了专业教育与创业教育相匹配的方法,并评述了该示范课程建设的效果.     

Model-based predictive control for bicycling in urban intersections

In this paper, a model predictive control approach for improving the efficiency of bicycling as part of intermodal transportation systems is proposed. Considering a dedicated bicycle lanes infrastructure, the focus in this paper is to optimize the dynamic interaction between bicycles and vehicles at the multimodal urban traffic intersections. In the proposed approach, a dynamic model for the flows, queues, and number of both vehicles and bicycles is explicitly incorporated in the controller. For obtaining a good trade-off between the total time spent by the cyclists and by the drivers, a Pareto analysis is proposed to adjust the objective function of the MPC controller. Simulation results for a two-intersections urban traffic network are presented and the controller is analyzed considering different methods of including in the MPC controller the inflow demands of both vehicles and bicycles.     

南京河西有轨电车路基设计特点

现代有轨电车作为新兴的城市轨道交通,与地铁、轻轨、高速铁路的设计有着众多方面的显著差别,在现有路基设计理论的基础上结合南京河西地区有轨电车的工程实践情况,研究阐明本项目沉降控制标准的确定依据、地基处理方案的主要影响因素、路基结构的设计参数,为制定有轨电车合理的设计标准提供参考。     

一种基于改进的减缩模型修正方法

提出一种改进的模型修正方法,该方法采用多目标优化技术使得结构的减缩模型与实测结果相吻合。即首先建立一个多目标优化模型,其中包括一个关于单元修正系数的隐式非线性特征方程组,然后通过遗传算法来求解该多目标优化问题,来同时实现模型修正和损伤检测。文中通过对一个悬臂梁的数值仿真,表明本文所提出的方法的有效性,即在较大的测量噪声的情况下,同时具有模型修正和损伤检测两种功能,且较改进前的基于迭代的方法具有更好的噪声鲁棒性。     

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988–1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.