基于TRIZ理论的叶片仿生设计与有限元力学分析

改善风力机叶片气动性能,提高叶片刚度、稳定性,已成为大型风力机叶片设计迫切需要解决的问题。生物体独特的外部形状、功能、结构、材料的完美统一,高超的环境适应能力,也为风力机仿生设计提供了不竭灵感。仿生过程是一个分析综合创新的过程,运用TRIZ产品进化理论对风力机叶片技术所处发展阶段进行研究,有助于更清楚地了解风力机叶片的发展趋势和创新的必要性,使研究工作更具系统性和规律性。应用TRIZ产品进化理论,对风力机叶片技术的相关专利数据进行统计并绘制曲线图,通过与标准曲线的区段比较找出风力机叶片所处的发展阶段和接下来的发展趋势与对策。将鱼鳍作为仿生对象进行建模与力学分析,得到仿生模型的力学指标。     

A simple linear time certifying LBFS-based algorithm for recognizing trivially perfect graphs and their complements

We introduce a simple, linear time algorithm for recognizing trivially perfect (TP) graphs. It improves upon the algorithm of Yan et al. [J.-H. Yan, J.-J. Chen, G.J. Chang, Quasi-threshold graphs, Discrete Appl. Math. 69 (3) (1996) 247–255] in that it is certifying, producing a P₄ or a C₄ when the graph is not TP. In addition, our algorithm can be easily modified to recognize the complement of TP graphs (co-TP) in linear time as well. It is based on lexicographic BFS, and in particular the technique of partition refinement, which has been used in the recognition of many other graph classes [D.G. Corneil, Lexicographic breadth first search—a survey, in: WG 2004, in: Lecture Notes in Comput. Sci., vol. 3353, Springer, 2004, pp. 1–19].     

多工作模式产品配色意象的灰色评价方法

针对产品开发过程中的色彩规划问题,考虑多工作模式产品的配色特征,构建一种多工作模式产品的配色意象评价模型.基于灰色关联分析法建立产品方案色彩与意象之间的关联模型,运用灰色聚类法判断产品配色方案的意象值;将产品各工作模式下的配色意象同时作为评价属性并赋予相应的权值,进行综合评价.文中方法兼顾了多工作模式产品色彩面积的可变性和消费者主观意象的不确定性,将多工作模式产品的配色意象评价方法置于灵活、直观的框架中.最后以工程机械产品为应用实例,证明该方法较单属性评价方法更为贴近消费者的主观意象.     

Pattern Classification With Class Probability Output Network

The output of a classifier is usually determined by the value of a discriminant function and a decision is made based on this output which does not necessarily represent the posterior probability for the soft decision of classification. In this context, it is desirable that the output of a classifier be calibrated in such a way to give the meaning of the posterior probability of class membership. This paper presents a new method of postprocessing for the probabilistic scaling of classifier's output. For this purpose, the output of a classifier is analyzed and the distribution of the output is described by the beta distribution parameters. For more accurate approximation of class output distribution, the beta distribution parameters as well as the kernel parameters describing the discriminant function are adjusted in such a way to improve the uniformity of beta cumulative distribution function (CDF) values for the given class output samples. As a result, the classifier with the proposed scaling method referred to as the class probability output network (CPON) can provide accurate posterior probabilities for the soft decision of classification. To show the effectiveness of the proposed method, the simulation for pattern classification using the support vector machine (SVM) classifiers is performed for the University of California at Irvine (UCI) data sets. The simulation results using the SVM classifiers with the proposed CPON demonstrated a statistically meaningful performance improvement over the SVM and SVM-related classifiers, and also other probabilistic scaling methods.     

Application of maximum entropy principle for reliability-based design optimization

The maximum entropy principle (MEP) is used to generate a natural probability distribution among the many possible that have the same moment conditions. The MEP can accommodate higher order moment information and therefore facilitate a higher quality PDF model. The performance of the MEP for PDF estimation is studied by using more than four moments. For the case with four moments, the results are compared with those by the Pearson system. It is observed that as accommodating higher order moment, the estimated PDF converges to the original one. A sensitivity analysis formulation of the failure probability based on the MEP is derived for reliability-based design optimization (RBDO) and the accuracy is compared with that by finite difference method (FDM). Two RBDO examples including a realistic three-dimensional wing design are solved by using the derived sensitivity formula and the MEP-based moment method. The results are compared with other methods such as TR-SQP, FAMM + Pearson system, FFMM + Pearson system in terms of accuracy and efficiency. It is also shown that an improvement in the accuracy by including more moment terms can increase numerical efficiency of optimization for the three-dimensional wing design. The moment method equipped with the MEP is found flexible and well adoptable for reliability analysis and design.     

土壤有机碳储量研究进展

如何有效进行土壤有机碳储量估算,世界各同都做了有益地探索和研究.本文通过对比分析目前国内外土壤有机碳相关研究成果,系统总结了土壤有机碳的研究背景、研究方法、评价指标及储量等主要成果,并指出了我国在土壤有机碳储量研究方面存在的若干问题.最后提出目前需要深入的几个研究方向,包括采用大比例尺地形图,进一步提高不同海拔地块土壤碳储量估算精度,加强土壤有机碳与气候相互作用机理分析,综合分析土地利用/覆盖变化对土壤有机碳的影响,并寻求不同时空条件下土壤有机碳估算方法.     

基准物最好具有较大摩尔质量的两种求证方法

对基准物“最好具有较大当量”更改为“最好具有较大摩尔质量”是否完全等效及当前所提出的两种求证方法进行了论证、比较。指出两法得到相同结论实属巧合之例;另举例说明在比较基准物摩尔质量大小以说明称量误差大小时,只有选用完全一致的比较标准才能使基准物“最好具有较大当量”或“最好具有较大摩尔质量”的两提法完全等效,并适用于任何情况。     

基于PWM占空比优化的PMSM预测直接转矩控制

针对PMSM传统直接转矩控制存在开关频率不规则、开关噪声的频率范围太宽和死区补偿算法复杂等问题,本文提出了一种基于优化脉宽调制(PWM)和死区补偿的PMSM预测直接转矩控制(DTC)方法。该方法首先在已知零电压矢量的基础上,根据预测转矩和磁通误差来选择两个其他有效电压矢量,与此同时,也考虑反电动势和磁通-转矩耦合器;接着,利用零电压矢量和两个其他有效电压矢量预测每个采样周期的转矩和磁通变化量,其中,三个电压矢量的开关周期由转矩和磁通误差以及在上一步中计算出的预测转矩和磁通变化共同决定;然后,采用死区补偿算法和改进的PWM来减小死区效应,以提高预测效果;最后,通过仿真和实验验证了所提方法的有效性和优越性,研究结果表明,所提方法在转矩控制和磁通控制效果要明显优于其他方法,且极大降低了开关损耗。     

InAs基范德华异质结界面电荷转移特性第一性原理计算的研究进展

由低维InAs材料和其他二维层状材料堆叠而成的垂直范德华异质结构在纳米电子、光电子和量子信息等新兴领域中应用广泛。探索跨结界面的电荷转移机制对于全面理解该类器件的非凡特性至关重要。第一性原理计算在揭示界面电荷转移特性与各种能量稳定型InAs基范德华异质结的电、光、磁等原理物理特性和器件性能变化之间的内在关系方面发挥着不可比拟的作用。文中梳理、总结和探讨了近年来InAs基范德华异质结间界面电荷转移特性的理论研究工作与潜在的功能应用,提出在理论方法和计算精度方面大力发展第一性原理计算的几个途径,为更好地开展InAs基范德华异质结的基础科学研究和应用器件设计提供可借鉴的量化研究基础。     

InPBi禁带下红外光致发光效率的Bi组分依赖研究

稀Bi半导体InPBi的光致发光（Photoluminescence, PL）主要来自缺陷能级跃迁过程,具有红外长波长、大线宽和高辐射强度等特点,因而引发广泛兴趣。针对InPBi的红外发光效率问题,本文研究了不同Bi组分InPBi的激发功率依赖红外PL光谱演化规律。实验发现,随着Bi组分增大,PL线型发生显著变化,导致发光波长总体红移;同时激发功率依赖的PL积分强度演化分析表明,发光效率随Bi组分先增大然后下降,在0.5%组分时发光效率达到峰值。发光效率增大一方面归因于Bi捕获空穴降低非辐射复合,另一方面来自Bi的表面活性剂效应;而高Bi组分引入过多缺陷从而抑制了Bi的优势,导致发光效率下降。这些结果或有助于理解InPBi的红外发射性能,表明InPBi具有红外光电子应用前景。