模腔注射填充的全矢量显式算法

为满足注射成形模拟工业应用的实际需要，基于已有的模拟注填充显式算法，提出并实现了一种新的全矢量化显式算法，对于各类注射填充的模拟问题，此算法避免了压力场的全局求解，矩阵操作仅在单元一级进行，通过反馈修正，各时间增量步满足不可压缩条件，由于避免了所有的全局耦合求解，计算代价与节点的自由度近似成正比，可实现填充模拟过程的高效运算，容易实现并行计算，通过新算法的填充模拟结果与MINI单元的三维模拟结果比较，证实了该算法的有效性。     

MODULATION OF A δ－AND C－FIBER EVOKED RESPONSES OF NOCICEPTIVE NEURONS IN THE SUPERFICIAL AND THE DEEPER DORSAL HORN OF THE ME

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Calculation of Temperature Field During Laser Transformation Hardening of Cylindrical Bodies

IntroductionLaserTransformationhardeningtechniquehasbeensuccessfullyusedinindustryformanyyears.AlotsoftheoreticalworkshasbeendoneforheatflowduringthelasertfansformationhardeningofflatworkPieces["].Cyindricalbodiesarewidelyusedinindustrysuchaslocomotivecrankshaft,steelrollervalyeseat,enginecyinder.IftheschcesoftheseworkPiecesaretreatedbylasertheirwearresistancewiIIimProvealot.UptillnowmanyexPerimentalworkshasbeendoneforlasertransformationhardeningofcyindricalbodies,butfewtheoreticalworkshav…     

THE NEURONS DOUBLE-LABELLED BY SEROTONIN AND GLUTAMATE-IMMUNOREACTIVITY IN

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EFFECTS OF NITRIC OXIDE SYNTHESIS INHIBITION WITH OR WITHOUT NITRIC OXIDE IN

ＦＦＥＣＴＳＯＦＮＩＴＲＩＣＯＸＩＤＥＳＹＮＴＨＥＳＩＳＩＮＨＩＢＩＴＩＯＮＷＩＴＨＯＲＷＩＴＨＯＵＴＮＩＴＲＩＣＯＸＩＤＥＩＮＨＡＬＡＴＩＯＮＯＮＲＥＳＰＯＮＳＥＳＴＯＳＹＳＴＥＭＩＣＣＯＣＡＩＮＥＡＤＭＩＮＩＳＴＲＡＴＩＯＮＩＮＲＡＴＳ．Ｅ．Ｈｅ...     

Switch Panel wear loading – a parametric study regarding governing train operational factors

The acting forces and resulting material degradation at the running surfaces of wheels and rail are determined by vehicle, track, interface and operational characteristics. To effectively manage the experienced wear, plastic deformation and crack development at wheels and rail, the interaction between vehicle and track demands a system approach both in maintenance and in design. This requires insight into the impact of train operational parameters on rail- and wheel degradation, in particular at switches and crossings due to the complex dynamic behaviour of a railway vehicle at a turnout. A parametric study was carried out by means of vehicle-track simulations within the VAMPIRE® multibody simulation software, performing a sensitivity analysis regarding operational factors and their impact on expected switch panel wear loading. Additionally, theoretical concepts were cross-checked with operational practices by means of a case study in response to a dramatic change in lateral rail wear development at specific switches in Dutch track. Data from train operation, track maintenance and track inspection were analysed, providing further insight into the operational dependencies. From the simulations performed in this study, it was found that switch rail lateral wear loading at the diverging route of a 1:9 type turnout is significantly influenced by the level of wheel–rail friction and to a lesser extent by the direction of travel (facing or trailing). The influence of other investigated parameters, being vehicle speed, traction, gauge widening and track layout is found to be small. Findings from the case study further confirm the simulation outcome. This research clearly demonstrates the contribution flange lubrication can have in preventing abnormal lateral wear at locations where the wheel–rail interface is heavily loaded.     

Design and development of automotive blind spot detection radar system based on ROI pre-processing scheme

In the conventional 2D-FFT based target detection method, all range-Doppler cells are computed by FFT (Fast Fourier Transform) and scanned by CA-CFAR (Cell-Averaging Constant False Alarm Rate) detection. This results in high computational complexity and long processing time. In this paper, we developed an automotive 24 GHz BSD (Blind Spot Detection) FMCW (Frequency Modulated Continuous Wave) radar with a low complexity target detection architecture based on a ROI (Region Of Interest) pre-processing scheme. In the real BSD zone, because the number of cars to be detected is limited, the designed method only extracts their velocities corresponding to the range ROIs in which real targets exist. Moreover, the presence probability of vehicles with the same range-bin but different velocities is very low. Thus, in the designed method, some Doppler ROIs cells with a high magnitude are only applied for CA-CFAR detection. This architecture can dramatically reduce the amount of data to be processed compared to that of the conventional 2D FFT based method, resulting in enhanced processing time. We developed a 24 GHz FMCW radar system composed a transceiver, antennas, and signal processing module. The designed algorithm was implemented in a tiny micro-processor of the signal processing module. By implementing our proposed algorithm in the developed 24 GHz FMCW radar system in an anechoic chamber and a real road, we verified that the range and velocity of a car occupying the BSD zone were detected. Compared to that of the conventional method, the reduction ratio of the total processing time was measured to be 52.4 %.     

Calibration efficiency improvement of rule-based energy management system for a plug-in hybrid electric vehicle

This paper presents a calibration method of a rule-based energy management strategy designed for a plug-in hybrid electric vehicle, which aims to find the optimal set of control parameters to compromise within the conflicting calibration requirements (e.g. emissions and economy). A comprehensive evaluating indicator covering emissions and economy performance is constructed by the method of radar chart. Moreover, a radial basis functions (RBFs) neural network model is proposed to establish a precise model within the control parameters and the comprehensive evaluation indicator. The best set of control parameters under offline calibration is gained by the multi-island genetic algorithm. Finally, the offline calibration results are compared with the experimental results using a chassis dynamometer. The comparison results validate the effectiveness of the proposed offline calibrating approach, which is based on the radar chart method and the RBF neural network model on vehicle performance improvement and calibrating efficiency.     

Performance decay of stern bearing based on lubrication numerical model and state parameters北大核心CSCD

[目的]为了实现对船舶艉轴承润滑状态的监测和评估,提出一种结合润滑性能衰变模型和支持向量机(SVM)算法的艉轴承润滑性能评估方法。[方法]针对船舶艉轴承润滑状态难以监测和识别的问题,建立轴承润滑衰变数值模型,并运用实验数据对该模型进行验证,研究载荷、粗糙度和半径间隙对润滑状态衰变机理的影响。基于SVM算法,构建润滑状态分类器,通过网格搜索算法优化超参数,利用不同润滑状态的数据集进行训练,最后实现对艉轴承润滑状态的评估。[结果]结果显示,随着外部载荷、粗糙度和半径间隙的增大,轴承润滑状态恶化的临界速度增大,动压润滑工作范围减小,混合润滑工作范围增大;由仿真数据集对润滑状态识别模型的验证表明,所提的润滑状态识别方法准确率达96.88%。[结论]所提方法能监测轴承的润滑性能特征,有效识别轴承的润滑状态。