基于物理模型的烟雾模拟

在分析研究流体物理特性算法基础上,提出一种新的烟雾模拟实现方法。该方法基于物理模型的求解简化方程模拟烟雾的动态变化过程。模型中采用了非粘性欧拉方程,通常它比其他用粘性Navier-Stoke方程建模的更适合用来对气体进行建模并且减少计算量。实验验证该模型还可以正确处理烟雾与移动的物体之间的相互作用。     

考虑电网阻抗耦合的模块化多电平换流器交直流侧阻抗通用计算方法

以模块化多电平换流器(modular multilevel converter,MMC)为技术路线的柔性直流输电技术在风电接入、电网异步互联等领域迅速发展。MMC的阻抗建模是分析柔性直流输电系统振荡起源的重要依据。文中分析MMC在交、直流侧激励下的谐波传递机制,建立一种适用于交、直流侧阻抗计算的通用方法。对一次系统频域建模关联了MMC所连接的交、直流侧网络阻抗,并考虑包含解耦双同步参考坐标系锁相环及负序内环控制在内的全部控制模块。通过求解线性方程组对MMC阻抗进行计算,并在PSCAD/EMTDC环境中对双端背靠背MMC系统在多种工况下1～5kHz频段内进行扫频,验证该方法的准确性,并详细分析网络阻抗耦合、控制链路延时、功率等级、负序内环和外环控制等因素对MMC阻抗的影响。     

Reconstructing design parameters of a rectangular resonator via peak signal-to-noise ratio and global optimization algorithms

This article proposes an approach for reconstructing physical parameters of a sample in a rectangular resonator during microwave radiation, knowing a priori, its electric field distribution. The inverse problem was solved using two global optimization algorithms and the peak signal-to-noise ratio (PSNR) criterion. First, the Self-regulated Fretwidth Harmony Search algorithm (SFHS) identified suitable resonant frequencies for a given configuration. Next, the unified Particle Swarm Optimization (UPSO) optimized said configuration. Together, they became a maximization strategy of the PSNR through a dual optimization process. Results showed the ability of the approach for estimating the height of each sample block and the resonating frequency of the cavity. This process takes longer to finish as a higher PSNR is demanded (mainly due to the aforementioned dual optimization). Even so, it allows for more similar electric field distributions between both, the direct and inverse problems.     

EDA9033A在分布式风机性能测试系统中的应用

针对以单片机为核心的风机性能测试系统存在稳定性差、抗干扰能力差、精度低等问题,开发了以PLC为核心、采用互感式采集模块EDA9033A采集风机电参数的分布式风机性能测试系统,给出了该风机性能测试系统的结构,详细介绍了EDA9033A的硬件及软件设计。实际应用表明,EDA9033A采集的风机电参数结果稳定、快速、准确。     

Discrete particle swarm optimization based on estimation of distribution for terminal assignment problems

Terminal assignment problem (TEAP) is to determine minimum cost links to form a network by connecting a given set of terminals to a given collection of concentrators. This paper presents a novel discrete particle swarm optimization (PSO) based on estimation of distribution (EDA), named DPSO-EDA, for TEAP. EDAs sample new solutions from a probability model which characterizes the distribution of promising solutions in the search space at each generation. The DPSO-EDA incorporates the global statistical information collected from personal best solutions of all particles into the PSO, and therefore each particle has comprehensive learning and search ability. In the DPSO-EDA, a modified constraint handling method based on Hopfield neural network (HNN) is also introduced to fit nicely into the framework of the PSO and thus utilize the merit of the PSO. The DPSO-EDA adopts the asynchronous updating scheme. Further, the DPSO-EDA is applied to a problem directly related to TEAP, the task assignment problem (TAAP), in order to show that the DPSO-EDA can be generalized to other related combinatorial optimization problems. Simulation results on several problem instances show that the DPSO-EDA is better than previous methods.     

Further results of recursive evaluation for compound distribution with the severity distribution of mixed type

Yang et al. [J.P. Yang, S.H. Cheng, Q. Wu, Recursive equations for compound distribution with the severity distribution of the mixed type, Science in China Series A 48 (2005) 594-609] investigated a recursive procedure for a kind of compound distributions with the number of claims belonging to (a,b)-family and the severity distribution of the mixed type. In this paper, we extend their results by assuming that the claim number belongs to a larger class. As applications, the excess-of-loss reinsurance treaty is discussed and concrete examples are considered in some detail.     

A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure

This paper addresses the food distribution decision from a wholesaler's perspective, as the wholesalers are often faced with thorny issues such as when, where, how to deliver products at the lowest costs to best satisfy the retailers’ changing needs. This research relies on a distribution problem encountered at Northern Grocery Company in Beijing as an example to develop a two-stage solution procedure and subsequent computer-enabled programs for identifying efficient vehicle routing alternatives. The solution process, which integrates heuristic search algorithms and an integer programming model, can be applied to a wide range of distribution problems with specified route durations and a circular transportation network structure as exemplified by City of Beijing.     

A DSS for integrated distribution of empty and full containers

A DSS integrating empty and full containers transshipment operations is presented, addressing the typically unbalanced export/import containers trading problem. The problem is modeled as a network, where nodes represent customers, leasing companies, harbors and warehouses, while arcs represent transportation routes. The underlying mathematical model operates in stages, first prioritizing and adjusting full containers demands considering available empty containers supplies, and then statically optimizing costs. Transportation routes are registered and dynamically controlled, cyclically, for a given time horizon. The DSS is flexible, allowing several parameters to be configured. Experimental examples using randomly generated parameters were conducted to evaluate the effectiveness of the system.