模腔注射模拟显式算法中对流项作用的评估

为研究Navier-Stokes方程中对流项对粘性流注射模拟结果的影响,在基于矢量化显式算法模拟软件中加入对流作用项.应用修正后的软件模拟两个典型的注射填充过程的算例,并与相应的实验比较.对模拟和实验结果的比较表明,对流项对粘性流注射填充过程和的其中的自由表面形状的模拟结果影响可以忽略.     

注射成形填充模拟的修正算法

为提高注射成形过程数值模拟结果的准确性,采用类似迎风法的概念,通过对平流方程作为填充状态控制方程而导致模拟失真原因的分析,提出了相应的数值修正算法.该方法在高效显式数值模拟算法和有限元软件基础上,通过对模型内流体速度场的系统性操作,削弱空气流动速度场对喂料填充的不真实影响,使得填充状态的输送更基于流动前沿面后部的流场作用,并对⊥型和L型模腔进行了数值仿真.结果表明:该方法能有效抑制填充流的失真现象,实现了在流动过程中流向发生大角度变化模腔的正确填充过程.      

显式有限元法在车辆耐撞性研究中的应用

基于连续介质理论，通过建立车辆碰撞的控制方程，在此基础上得到与控制方程和边界条件等效的“弱积分”形式。通过空间和时间的显式离散，得到了车辆碰撞的有限元方程。采用动力显式积分方法，使位移计算显式化，避免了由材料、几何、边界高度非线性因素引起的计算收敛问题，并讨论了薄板单元的Courant稳定性条件。提出了“端部吸能结构纵向压缩变形、纵向吸能”的耐冲击结构设计的思路，并对算例进行了数值模拟。结果表明，该设计方法可以实现车辆结构自身被动安全保护的目的，显式有限元数值模拟方法是车辆耐撞性研究的有效方法之一，但是需要进行部分撞击试验，进一步修正模型后提高其分析精度。     

双向蚁群算法在无人驾驶车辆路径规划中的应用

针对传统蚁群算法在无人驾驶车辆路径规划中收敛速度慢、易陷入局部最优等问题,提出一种全局路径规划的双向蚁群算法。通过双向搜索策略改进蚁群算法,设计相遇机制求解更多可行路径,提高算法全局搜索能力;引入奖惩因子分别扩大和减小双向搜索后的较优路径和较差路径对信息素浓度的影响,加快求解最优路径的速度;最后在Matlab中模拟无人驾驶车环境,随机生成不同地图面积和障碍物出现率的车辆仿真栅格地图,比对传统蚁群算法和双向蚁群算法的实验效果。结果表明:双向蚁群算法的迭代次数和求解时间明显减少,在加快收敛速度、提高全局搜索能力以及避免局部最优方面有较大改进。     

车辆-轨道耦合动力学钢轨模型求解方法

应用车辆-轨道非线性耦合动力学模型,分析了采用解析方法的模态叠加法、有限元法的模态叠加法和有限元法的直接积分法求解车辆-轨道耦合动力学钢轨模型的计算精度与计算效率.选取Bernoulli-Euler梁或Rayleigh-Timoshenko梁模拟钢轨,采用不同类型单元离散钢轨模型,并利用显式积分方法求解车辆-轨道耦合动...     

微注射成形实验与数值模拟

为研究注射料的流动性和模腔形状的复制能力,加工了含有微流道的模具,在微注射系统上进行了微注射实验.应用基于矢量化显式算法的程序,在不同壁面边界条件下,对微注射实验进行了模拟.结果表明:在注射料温度220 ℃、模具温度40 ℃、注射流量为20 mm3/s、注射时间1 s、保压时间10 s的注射工艺条件下,聚丙烯能较好的复制长5 mm,宽1.5 mm和厚0.8 mm的微流道形状.采用滑移边界条件的微注射模拟结果与实验结果一致,说明微注射中存在边界滑移速度.     

求解Flow Shop排序问题的模拟进化法

为Ｆｌｏｗ Ｓｈｏｐ排序问题的求解构造了一类模拟进化寻优方法－基于启发式规则的有序遗传算法，并对不同规模的实例进行了计算机模拟。研究结果表明算法对求解Ｆｌｏｗ Ｓｈｏｐ排序问题所具有的全局搜索优势。     

NARMA模型预测控制滚动优化的两组协调法

针对ＮＡＲＭＡ模型，提出了预测控制滚动优化的两级协调法。该算法由三层构成，上、中两层是两个协调器，第三层是局部决策单元，该算法避免了在子问题的求解中使用效率较低的规划方法，提高了线计算的效率，领导具结果该算法的有效性。     

动态显式有限元法在冷冲压加工模拟中的应用

介绍了动态显式有限元法的原理、特点和应用，并用动态显式有限元法对机车车辆的转向架交叉杆冷冲压加工过程进行计算机模拟分析．模拟分析的结果说明了动态显式有限元法在模拟像冲压加工这种大变形过程中的优越性．     

多层结构船舶机舱火灾烟气充填数值计算

应用大涡模拟技术，建立了多层结构船舶机舱火灾的过滤平衡方程组与Smagorinsky亚格子模型。采用二阶有限差分法对空间变量进行离散，采用显式二阶预估校中法对流动变量进行离散，采用显式二阶Runge-Kutta法对时间变量进行离散，分别求解了速度场、温度场、烟气浓度与烟气层高度，比较了多层结构与单层结构船舶机舱火灾烟气...     

A New Explicit Algorithm for Bi-Phasic Mixture Flow in MIM

Metal injection moulding (MIM) is a new technology to manufacture small intricate parts in large quantity. Numerical simulation plays an important role in its development. To predict the specific segregation effect in MIM injection, mixture theory is adopted to model the injection flow by a bi-phasic model. This model conducts to the solution of two-coupled Stokes equations. It is an extremely computational consuming solution in the scope of the traditional algorithms, which induce a serious challenge to cost-effectivity of the MIM simulation. Referred to some methods proposed by Lewis in mono-phasic simulation and the implicit algorithms in MIM simulation, a new explicit algorithm is proposed and realized to perform efficiently this type of bi-phasic flow. Numerically this algorithm is devised to perform the simulation in a fully uncoupled manner except for a global solution of the pressure field in each time step. The physical coupling is taken into account in a sequential pattern by fractional steps. This special algorithm does not need any iteration, so it is straightforward and robust, suitable for MIM simulation and other sorts of simulations for multi-phasic flow.     

Computer Simulation of Mould Filling and Solidification of Castings

InfoructionThCcastingProcsscoInbinOsacomplex,dynandcPrOblemoffluldflowtalhCattransferinorthetoProduCethehighqualitycastings,thefoundryengineesshOuldknOWthCsesfluldflowandheaIransferMmenaPr6viouslyUoftwtaty,theSe~naaretDOdifficulttousethetheOrodcalanalysiswithOutcowtonalteWes'ThedeSignOfthecastingsystem(suchasgatinndeq)usedhaydepeAnunonextwthanonengineeringbo.MnysuccesshodeSigDSarendybasedontalanderrorInrecenW'theinCrodsingN[i]forwtraridPrOtOtyPincashngs~tomakacastingrightatthefu…     

局部阴影光伏发电系统中基于改进PSO的MPPT控制

光伏发电系统在局部阴影条件下,传统的最大功率点跟踪算法（maximum power point tracking,MPPT）容易陷入局部寻优,无法跟踪到全局最大功率点. 针对这一问题,本文提出了一种基于自适应学习因子粒子群算法的最大功率跟踪方法. 该方法在普通粒子群算法的基础上不断改变学习因子和权重系数,以提高算法收敛的速度和精度. 将其应用于局部阴影条件下的光伏发电系统最大功率点跟踪中,并在RT-LAB实时仿真平台中以两个接受不同光照强度的光伏阵列为例进行实时仿真验证. 仿真结果表明,两峰情况下本文所提出的自适应学习因子粒子群算法能够在0.298 s左右跟踪到全局最大功率点,普通粒子群算法需要约0.615 s,而扰动观察法陷入了局部最大功率点,本文所提算法能够有效提高系统的收敛速度和精度并且适用于多峰情况. 最后设置仿真算例验证本算法适用于光照突变的情况.      

广义Gauss模型及其模拟退火算法

研究了求解优化问题全局解的随机神经网络方法，将Gauss模型拓展为广义Gauss模型，使之能求解一般优化问题的全局解。进而引入全局性较好的模拟退火算法的思想，提出了广义Gauss模型的模拟退火算法。通过算例比较了几种计算智能算法的全局性。广义Gauss模型的模拟退火运行全局性最好，但它付出了时间的代价；广义Gauss模型兼顾了计算效率和全局性；广义Hopfield网络的全局性最不理想。     

Fault reconfiguration of shipboard power system based on triple quantum differential evolution algorithm

Fault reconfiguration of shipboard power system is viewed as a typical nonlinear and multi-objective combinatorial optimization problem. A comprehensive reconfiguration model is presented in this paper, in which the restored loads, switch frequency and generator efficiency are taken into account. In this model, analytic hierarchy process(AHP) is proposed to determine the coefficients of these objective functions. Meanwhile, a quantum differential evolution algorithm with triple quantum bit code is proposed. This algorithm aiming at the characteristics of shipboard power system is different from the normal quantum bit representation. The individual polymorphic expression is realized, and the convergence performance can be further enhanced in combination with the global parallel search capacity of differential evolution algorithm and the superposition properties of quantum theory. The local optimum can be avoided by dynamic rotation gate. The validity of algorithm and model is verified by the simulation examples.     

Bi-phasic Simulation of Metal Injection Moulding： Constitutive Determinations

IntroductionMetalinjectionmolding (MIM )isexpectedtobeveryefficienttoproducesmalland 3Dcomplicatedpartsinlargeseries .Thistechnologycombinesthewell knownpolymerinjectionmouldingandpowdermetallurgytechnology .AnMIM processincludesfourmainstages[1,2 ] :them…     

Phase Behaviors in Bi-phase Simulation of Powder Segregation in Metal Injection Molding

Powder segregation induced by mold filling is an important phenomenon that affects the final quality of metal injection molding （MIM）. The prediction of segregation in MIM requires a bi-phase flow model to describe distinctly the flows of metallic powder and polymer binder. Viscous behaviors for the flows of each phase should hence be determined. The coefficient of interaction between the flows of two phases should also be evaluated. However, only viscosity of the mixed feedstock is measurable by capillary tests. Wall sticking is supposed in the traditional model for capillary tests, while the wall slip is important to be taken into account in MIM injection. Objective of the present paper is to introduce the slip effect in bi-phase simulation, and search the suitable way to determine the viscous behaviors for each phase with the consideration of wall slip in capillary tests. Analytical and numerical methods were proposed to realize such a specific purpose. The proposed method is based on the mass conservation between the capillary flows in mono-phase model for the mixed feedstock and in bi-phase model for the flows of two phases. Examples of the bi-phase simulation in MIM were realized with the software developed by research team. The results show evident segregation, which is valuable for improving the mould designs.     

An Iterative Algorithm for Computed Tomography Image Reconstruction from Limited-Angle Projections

In application of tomography imaging, limited-angle problem is a quite practical and important issue.In this paper, an iterative reprojection-reconstruction(IRR) algorithm using a modified Papoulis-Gerchberg(PG)iterative scheme is developed for reconstruction from limited-angle projections which contain noise. The proposed algorithm has two iterative update processes, one is the extrapolation of unknown data, and the other is the modification of the known noisy observation data. And the algorithm introduces scaling factors to control the two processes, respectively. The convergence of the algorithm is guaranteed, and the method of choosing the scaling factors is given with energy constraints. The simulation result demonstrates our conclusions and indicates that the algorithm proposed in this paper can obviously improve the reconstruction quality.     

公交线网优化的算法研究

为缩短居民乘车出行时间以及减少公交运营投入,在公交线网优化过程中通常采用具有全局最优的遗传算法。针对基本遗传算法自身的一些缺点,提出了一种改进的遗传算法。该算法在公共交通路线优选过程中运用减少搜索空间、加入最佳保留策略和修正策略的方法,对基本遗传算法中的选择、交叉、变异算子及中止条件进行改进。改进遗传算法能够在保证种群多样性的同时加快收敛速度,较好地避免了基本遗传算法前期容易早熟和后期进化缓慢等现象。实例仿真计算表明,该算法具有比基本遗传算法更高的效率,是优化公交线网的一个有效途径。