氨燃料固体氧化物燃料电池低温化性能分析

在氨燃料固体氧化物燃料电池(solid oxide fuel cell,SOFC)低温化发展趋势下,降低工作温度将会提高电池寿命,但随之带来的化学及电化学反应速率降低和电解质欧姆损失增加等问题,这会直接影响电池的输出性能。该文基于COMSOL仿真平台,构建SOFC的多物理模型仿真模型,对SOFC内部化学及电化学反应、质量传递、能量传递和温度场分布进行耦合求解,着重量化分析工作温度和电解质厚度参数对氨燃料SOFC输出性能的敏感性影响。结果表明:降低工作温度至700℃可以显著降低电池内部热应力,尤其入口和出口侧降幅达14.37%。增加阳极厚度和氨气浓度导致功率密度下降48.76%。采用10μm电解质厚度和氧化钆参杂氧化铈(gadolinia-doped ceria,GDC)材料可以提高电池平均功率密度至785.87 W/m^(2),增幅达77.25%。因此,降低温度可以有效降低电池内部的热应力及分布差异,可提高电池的寿命,但阳极氨气平均浓度增加56.57%,镍基氮化作用随之增强可能会对电池稳定性造成不利影响,可采用减小电解质厚度和换用电解质材料两种方法对电池的输出性能进行提升。

Application of support vector machine in trip chaining pattern recognition and analysis of explanatory variable effects

In order to improve the accuracy of travel demand forecast and considering the distribution of travel behaviors within time dimension, a trip chaining pattern recognition model was established based on activity purposes by applying three methods： the support vector machine （SVM） model, the radial basis function neural network （RBFNN） model and the multinomial logit （MNL） model. The effect of explanatory factors on trip chaining behaviors and their contribution to model performace were investigated by sensitivity analysis. Results show that the SVM model has a better performance than the RBFNN model and the MNL model due to its higher overall and partial accuracy, indicating its recognition advantage under a smai sample size scenario. It is also proved that the SVM model is capable of estimating the effect of multi-category factors on trip chaining behaviors more accurately. The different contribution of explanatory, factors to trip chaining pattern recognition reflects the importance of refining trip chaining patterns ad exploring factors that are specific to each pattern. It is shown that the SVM technology in travel demand forecast modeling and analysis of explanatory variable effects is practical.

Parametric analysis on buffeting performance of a long-span high-speed railway suspension bridge

The buffeting performance of kilometer-level high-speed railway suspension bridges has a great impact on the smooth operation of high-speed trains.To investigate the buffeting performance of the structure significantly different from traditional suspension bridges,the first long-span high-speed railway suspension bridge,Wufengshan Yangtze River Bridge(WYRB),is taken as a numerical example to demonstrate the effects of structural parameters and wind field parameters on the buffeting responses.Based on the design information,the spatial finite element model(FEM)of WYRB is established before testing its accuracy.The fluctuating wind fields are simulated via both classical and stochastic wave based spectral representation method(SRM).Finite element method is further taken to analyze the parametric sensitivity on wind induced buffeting responses in time domain.The results show that the vertical displacement is more sensitive to the changing dead load than the lateral and torsional ones.The larger stiffness of the main girder and the lower sag-to-span ratio are both helpful to reduce the buffeting responses.Wind spectrum and coherence function are key influencing factors to the responses so setting proper wind field parameters are essential in the wind-resistant design stage.The analytical results can provide references for wind resistance analysis and selection of structural and fluctuating wind field parameters for similar long-span high-speed railway suspension bridges.

Synthesis and property of temperature and pH sensitive xanthan–MA/PNIPAAm hydrogels

A novel class of xanthan-maleic anhydride (Xan-MA)/poly(N-isopropylacrylamide) hybrid hydrogels was designed and synthesized by solution polymerization. The xanthan-based precursor (Xan-MA) was prepared by substituting the hydroxyl groups in Xan by MA. This Xan-MA precursor was then polymerized with a known temperature sensitive precursor (N-isopropylacrylamide, NIPAAm) to form hybrid hydrogels with a series range of composition ratio of Xan-MA to NIPAAm precursors. These smart hydrogels were characterized by Fourier transform infrared spectroscopy for structural determination, differential scanning calorimertry for thermal property. And maximum swelling ratio, swelling kinetics and temperature response kinetics were studied. The data obtained clearly show that these smart hydrogels are responsive to the external changes of temperature as well as pH value. The magnitudes of smart and hydrogel properties of these hybrid hydrogels depend on the feed composition ratio of the two precursors. With the increase of the content of Xan-MA the maximum swelling ratio, reswelling ratio and thermo-sensitivities increase, and the feed composition ratio of Xan-MA/NIPAAm increases the maximum swelling ratio augment from 13.88 to 23.21. From XMN0, XMN1, XMN3 to XMN5, the lower critical solution temperatures (LCSTs) are 33.02, 36.15, 40.28 and 41.92 ℃, respectively. By changing the composition ratio of these two precursors, the LCST of the hybrid hydrogels could also be adjusted to be or near the body temperature for the potential applications in bioengineering and biotechnology fields.

Influences of the Suspension Parameters on the Vehicle Suspension Performance for a Terrain Vehicle

This paper describes an effective methodology for evaluation of the suspension parameters intended to be used for a terrain vehicle. The objective of this approach is to make quick analyses of the sensitivity of the vehicle suspension parameters. For the purpose of developing such a methodology, a mathematical modeling of a quarter vehicles suspension system is developed. Sensitive analysis of the suspension parameters is performed by employing the standard deviation of the vehicle body acceleration, dynamic tire load, and suspension travel. Sensitivity analysis results have shown that the spring stiffness, damping coefficient, tire stiffness and sprung mass have substantial influence on the ride comfort and road holding, while un-sprung mass on the other side has much lower impact in performance of the vehicle suspension system.