烯烃催化裂解反应动力学的研究

根据脉冲微反条件下C5～C8烯烃裂解产物分布,建立烯烃裂解反应网络,通过参数估计方法确定反应网络动力学常数、反应活化能和指前因子.结果表明,随着碳数的增加,C5～C8烯烃单分子裂解反应速率加快.反应温度600℃时C5～C8正构烯烃裂解生成丙烯,其反应速率常数的比值为1:8.18:38.48:27.98,最快生成丙烯的是1-庚烯.反应温度相同,1-烯烃的主要裂解反应速率是碳数相同的2-甲基-2-烯烃的1.1～1.6倍.C5烯烃裂解为单、双分子裂化并存的反应体系,但双分子裂解反应速率远大于单分子裂解,双分子反应占优势.     

CPU与GPU并行计算的火焰模拟

采用基于粒子插值的SPH方法对火焰流体进行模拟,用GPU加速粒子状态地计算,同时用CPU并行地计算粒子邻接关系并控制粒子产生速率。在SPH模型中,较为高效地加入了漩涡场的计算,增加了粒子运动的细节。在粒子渲染过程中,采用了色度场、有向点扩散和颜色锐化技术,由离散的粒子空间分布得到了较为理想的连续火焰图像。由于该方法属于流体模拟的拉格朗日法,所以火焰具有物理真实性,又由于采用GPU为主CPU为辅的计算架构,使得模拟达到了实时。     

复杂产品开发项目调度问题的模糊优化算法

对具有不确定时间参数的复杂产品开发项目调度问题,提出一种有效的模糊优化调度算法-基于预测的模糊BoP项目调度算法.首先,用模糊数表示不确定的时间参数,并构造相应的模糊数运算方法,对适合于确定性调度问题的BoP算法进行扩展,使其能处理模糊性时间参数.其次,修正了BoP算法中子项目调度方法,提高了算法的调度性能,降低了计算复杂度.大量的数值仿真实验表明,与基于启发式规则的调度算法相比,模糊BoP算法更适合于具有不确定时间参数的复杂产品开发项目调度问题.     

基于嵌入式的悬架与转向集成控制器研究

为了改善车辆的操纵稳定性和行驶平顺性,提高汽车底盘控制的集成度,本文对底盘部分的半主动悬架SASS (Semi Active Suspension System)和电动动力转向EPS (Electric Power Steering)系统进行了集成控制研究.设计并试制出基于嵌入式系统ARM S3C44BOX的SASS和EPS集成控制器,并进行了台架试验,结果表明研制的集成控制器效果良好,可用于汽车底盘集成控制系统的开发研究.     

Research on the Mechanical Properties of Magnetorheological Damping and the Performance of Microprobe Test Process

Journal of Electronic Testing - In order to control the stable and controllable loading of the wafer level microprobe test bench, the magnetorheological (MR) damper used in the existing research...     

Finite element implementation of a thermo-damage-viscoelastic constitutive model for hydroxyl-terminated polybutadiene composite propellant

A thermo-damage-viscoelastic model for hydroxyl-terminated polybutadiene (HTPB) composite propellant with consideration for the effect of temperature was implemented in ABAQUS. The damage evolution law of the model has the same form as the crack growth equation for viscoelastic materials, and only a single damage variable \(S\) is considered. The HTPB propellant was considered as an isotropic material, and the deviatoric and volumetric strain-stress relations are decoupled and described by the bulk and shear relaxation moduli, respectively. The stress update equations were expressed by the principal stresses \(\sigma_{ii}^{R}\) and the rotation tensor \(M\), the Jacobian matrix in the global coordinate system \(J_{ijkl}\) was obtained according to the fourth-order tensor transformation rules. Two models having complex stress states were used to verify the accuracy of the constitutive model. The test results showed good agreement with the strain responses of characteristic points measured by a contactless optical deformation test system, which illustrates that the thermo-damage-viscoelastic model perform well at describing the mechanical properties of an HTPB propellant.     

Epitaxial growth and thermal-conductivity limit of single-crystalline Bi2Se3/In2Se3 superlattices on mica

Nano Research - Thermal transport in superlattices is governed by various phonon-scattering processes. For extracting the phonon-scattering contribution of hetero-interfaces in chalcogenide...     

全固态裸露式Ag／AgCl参比电极的研制及应用

该文报道了一种树脂接界全固态裸露式Ag／Agcl参比电极,勿需电镀氯化,制备工艺简单,性能稳定,是对电解型Ag／AgCl参比电极的一大改进。可代替饱和甘汞电极作为通用型参比电极,同时可减少汞对环境所造成的二次污染,在温度大于75℃时仍能保持良好性能,突破了甘汞电极的局限。     

Multi-agent and driving behavior based rear-end collision alarm modeling and simulating

Distance-between-vehicle-measurement is the only factor in traditional car rear-end alarm system. To address the above problem, this paper proposes an alarming model based on multi-agent systems (MAS) and driving behavior. It consists of four different types of agents that can either work alone or collaborate through a communications protocol on the basis of the extended KQML. The rear-end alarming algorithm applies the Bayes decision theory to calculate the probability of collision and prevent its occurrence real-time. The learning algorithm of driving behavior based on ensemble artificial neural network (ANN) and the decision procedure based on Bayes’ theory are also described in this paper. Both autonomy and reliability are enhanced in the proposed system. The effectiveness and robustness of the model have been confirmed by the simulated experiments.