不可压湍流反应流直接模拟和RANS反应模型检验

用谱方法对三维不可压槽道湍流反应流动进行了直接数值模拟,得到了温度和质量分数耦合的瞬态数据库.结果显示温度与质量分数脉动在近壁区都有条带结构.推导了雷诺平均方法中湍流二阶矩反应模型中所求关联量的精确输运方程,发现耗散项是化学反应率系数-质量分数关联量封闭的关键,耗散项需要考虑化学反应影响.基于数据库的统计结果,对关联量模型方程中各项进行了先验研究,发现产生项和耗散项的贡献最大,扩散项和反应项的贡献较小,化学反应对各项大小和分布形状有明显影响.在算例中,直接模拟统计得到的化学反应率系数-质量分数关联和用代数二阶矩模型的模拟值很接近,说明ASOM模型具有一定的合理性.      

军用飞机效费综合特性的可视拓扑映射评估

根据SOM网络原理,采用Voronoi向量改进了SOM网络算法,提高了其收敛速度和映射精度,实现了可视拓扑映射图。应用改进算法构建了军用飞机效费综合特性可视拓扑映射图评估模型,并对现代几种军用飞机效费综合特性进行了可视化综合评估。可视拓扑映射图可以直观地反映不同型号飞机的效费综合特性、参数相关特征、参数变化趋势,而且能对飞机效费综合特性相似性预测,从而为军用飞机效费综合特性分析提供了一种新的有效方法。     

A continual model of soil organic matter transformations for predicting soil forming dynamics inside higher plant CELSS

A continual model of humification and mineralization of soil organic matter (SOM) formed under the conditions of a Lunar base from biological waste materials is proposed. The model parameters corresponding to the conditions of several Earths climatic regions are estimated. The time necessary for the formation of organic matter in the soil based on regolith and higher plant residues has been evaluated. Soil formation under tropical conditions are shown to be the most appropriate for Lunar base CELSS due to high matter turnover rate, relatively short formation time, minimum deposited mass, and satisfactory predictability of expected soil parameters.     

基于SOM网络的军事供应链绩效评估

根据平衡记分卡原理确定了影响军事供应链绩效的6个关键因素,继而建立了具有聚类功能的自组织映射SOM(Self-Organization Feature Map)网络模型.模型以调研得到的各个因素优劣评分组成的向量为输入向量,经过SOM网络把24个样本向量分为了优、良、中和一般4类,建立了评估标准.最后进行了评估应用,与...     

基于距离代价函数和信息熵的发动机性能参数估计研究

研究发动机部件性能参数变化规律,对于减少维修次数和推动视情维修具有重要意义。针对测量参数个数少于待估性能参数的情况,给出了一种通过构建代价函数和优化算法的参数估计方法。原代价函数只考虑当前点参数,缺少与前面点参数的联系,因此结合自组织神经网络,构造了包含以前与当前点参数的距离代价函数。并提出了一种快速的参数估计方法。由于准确的部件性能参数很难获取,并且参数趋势估计不同于单纯的点估计问题,以对应的测量参数为基础,利用信息熵方法评定部件性能参数估计效果。进一步得到距离代价函数对应的参数信息熵为0.6805,优于原代价函数的估计结果。最后通过实例验证了参数估计方法的有效性。      

Spatial understanding and temporal correlation for a mobile robot

In this article we discuss a network model, which simulates functionallysome of the features intrinsic to human navigation and the merits ofincorporating such features on a behavior-based robot. Specifically thepaper deals with implementing a memory based reasoning strategy duringreal-time navigation of a mobile robot. For the purpose ofimplementation, memory has been identified with an ability to cognizethe local environment or scenario, classify such scenarios in terms ofpreviously learned primitives or landmarks, remember and recollect suchprimitives at later instants and correlate over time similar experiencesof scenarios. Such memory based reasoning enhances the robot'snavigation capabilities through intelligent decisions due to spatialunderstanding, scene recollection abilities by remembrance and detectinglocal minimum traps through place recognition. A double layeredspatio-temporal classification scheme consisting of a fuzzy rule-basedspatial classifier and a temporal classifier based on self-organizingmap and ART networks are adopted for this purpose. The classifiernetwork reduces the robot's experience of its environment consisting ofa stream of sensor patterns into weight vectors that signify aparticular landmark. An extension of the network architecture is alsointroduced to cognize the presence of dynamic obstacles amidststationary ones.